Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range
By
Muhammad Rafiq
Department of Microbiology Quaid-i-Azam University Islamabad, Pakistan 2016
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range
A thesis
Submitted in the Partial Fulfillment of the
Requirements for the Degree of DOCTOR OF PHILOSOPHY
IN
MICROBIOLOGY
By
Muhammad Rafiq
Department of Microbiology Quaid-i-Azam University Islamabad, Pakistan 2016
DECLARATION
The material contained in this thesis is my original work and I have not presented any part of this thesis/work elsewhere for any other degree.
Muhammad Rafiq
DEDICATED
TO
My Ammi and Abbu
CERTIFICATE
This thesis, submitted by Mr. Muhammad Rafiq is accepted in its present form by the Department of Microbiology, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad as satisfying the thesis requirement for the degree of Doctor of Philosophy (PhD) in Microbiology.
Internal Examiner: ______(Dr. Fariha Hasan)
External Examiner: ______
External Examiner: ______
Chairperson: ______
Dated:
CONTENTS
S. No. Title Page No.
1. List of Abbreviations i
2. List of Tables ii
3. List of Figures iv
4. Acknowledgements vi
5. Summary viii
6. Chapter 1: Introduction 1
7. Chapter 2: Review of Literature 20
8. Chapter 3: Bacterial Diversity 89
9. Chapter 4: Fungal Diversity 182
10. Chapter 5: Metagenomic study 289
a. Abstract 289
b. Introduction 290
c. Methodology 297
d. Results 301
e. Discussion 323
f. References 335
11. Conclusions 345
12. Appendices 347
List of Abbreviations
ATP Adenosine-5’-triphosphate A Adenosine BLAST Basic Local Alignment Search Tool BLASTN BLAST search using a nucleotide query BLASTX BLAST search using a translated nucleotide query bp Base pairs C Cytosine °C Degree celsius DGGE Denaturing Gradient Gel Electrophoresis DNA Deoxyribonucleic acid dNTP Deoxynucleoside triphosphate e.g. Exempli gratia, for example et al. et alii/alia, and others Fe Iron Fig. Figure G Guanine i.e. id est, that is Ion Torrent PGM Ion Torrent Personal Genome Machine KEGG Kyoto Encyclopedia of Genes and Genomes KO KEGG Orthology MEGAN 4 MEtaGenome ANalyzer MG-RAST Metagenomic Rapid Annotations using Subsystems Technology M5NR Database M5 non-redundant database NaCl Sodium Chloride NCBI National Center for Biotechnology Information NGS Next Generation Sequencing OTU Operational Taxonomic Unit PCA Principal Component Analysis PCR Polymerase Chain Reaction pH Power of Hydrogen RDP Ribosomal Database Project rRNA Ribosomal ribonucleic acid SOLiD Sequencing by Oligonucleotide Ligation and Detection SSU RNA small subunit RNA T Thymine
i
List of Tables
No. Title Page No. 1 List of psychrophilic microbes with their habitats 3 3.1.1 Concentration of different metals in samples 98 3.1.2 Concentration of amino acids in samples 99 3.1.3 Cation and Anion concentrations in samples 99 3.1.4 Total viable cells (CFU/ml) and physiochemical conditions of the glacial 100 samples 3.1.5 16S rDNA sequence based identification and characteristics of selected 101 isolates from the Tirich Mir glacier 3.1.6 Salt tolerance profile of the study isolates 104 3.1.7 Temperature profile of all isolates from Tirich Mir glaciers 106 3.1.8 Effect of temperature on pigment production of the isolates from Tirich 107 Mir glacier 3.1.9 Antibacterial and antifungal activity of potent bacterial isolates of Tirich 114 Mir Glacier 3.2.1 Morphological and microscopic charactarization of study isolates 138 3.2.2 Comparative study of bacteria isolates resistant to different antibiotics 144 3.2.3 Antibiotic resistance and production of antimicrobial compounds in 146 Gram negative bacteria isolated from Siachen Glacier 3.2.4 Antibiotic resistance, mutliple antibiotic resistant (MAR) index and 148 antimicrobial activity of Gram positive bacterial isolates 3.2.5 Tolerance of Gram negative and Gram positive bacteria to varying 151 concentrations of metal ions 4.1.1 Total viable count (CFU/mL or g) of fungal isolates at 15°C and 4°C 188 4.1.2 Colony morphology and microscopic characteristics of fungal isolates on 189 SDA 4.1.3 The resemblance directory of the fungal isolates with respective 194 homologous strains 4.1.4 Temperature, pH and the salt tolerance range of the fungal isolates 195 4.1.5 Antibacterial and antifungal activity of the fungal isolates by point 197 inoculation method 4.1.6 Production of various extracellular enzymes by fungal isolates 198 4.2.1 Total viable count (CFU/g or mL) of fungal isolates at 15°C and 4°C. 214 4.2.2 Similarity of the fungal isolates to their corresponding homologous 216 species and accession No. 4.2.3 Physiological analysis of the fungal isolates on different temperature, pH 217 and salt concentrations 4.2.4 Antimicrobial activity of the fungal isolates against the clinically 219 isolated bacterial and fungal strains 4.2.5 Screening of the fungal isolates for the extracellular enzymes production 220 (qualitatively). 4.3.1 Total viable count (CFU/mL or g) of fungal isolates at 15°C and 4°C 235 4.3.2 The resemblance index of strains with respective homology of the fungal 236 isolates 4.3.3 Growth responses of the fungal isolates to temperature, pH and the salt 238 4.3.4 Antibacterial and antifungal activity of the fungal isolates by point 239 inoculation 4.3.5 Production of various extracellular enzymes by fungal isolates 240 4.4.1 Total viable count (CFU/mL or g) of Tirich Mir fungal isolates at 15°C 252 and 4°C 4.4.2 Resemblance directory of the isolates with homologous strains 254 ii
4.4.3 Physiological parameters analysis of the fungal isolates on different 255 temperature, pH media and NaCl concentrations 4.4.4 Antibacterial and antifungal activity of the Tirich Mir fungal strains 257 against different bacterial and fungal strains 4.4.5 Production of various extracellular enzymes (qualitatively) by fungal 258 isolates 4.5.1 Morphological characteristics of Alternaria isolates 283 4.5.2 Percentage similarity of Alternaria isolates 285 4.5.3 Physiological analysis of the Alternaria isolates on different 286 temperature, pH and salt concentrations 4.5.4 Antibacterial and antifungal activity of the Alternaria isolates against 287 ATCC cultures 4.5.5 Production of various extracellular enzymes by Alternaria isolates 288 5.1 Sequence break down of the sequences obtained from Illumina for 303 functional categories. 5.2 Alpha diversity (Specie richness) of the study sample 306
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List of Figure
No. Page Title No. 1 Climate map of the world. 21 2 North and South poles of the world 22 3 Locations of Permafrost land across the world 23 4 Hindu Kush, Karakoram and Himalaya (HKKH) region, considered as the 25 ‘Third Pole’ of the world. 5 Structure of Valley glacier, demonstrate its different parts 27 6 Various physiological adaptations in psychrophilic Bacteria 33 7 Adaptation mechanisms in psychrophilic fungi to survive the harsh 34 environment of low temperature 3.1.1 Location of the sampling site (A), photograph of the glacier from where 94 samples were collected (B) 3.1.2 Distribution of phylogenetic groups (%) of the culturable isolates of the 109 study isolates from Tirich Mir glacier 3.1.3 Evolutionary relationships of taxa of Proteobacteria group. 110 3.1.4 Evolutionary relationships of taxa of Firmicutes group. 111 3.1.5 Evolutionary relationships of taxa of Actinobacteria group 112 3.1.6 Evolutionary relationships of taxa of Bacteroidetes group 112 3.1.7 Metal tolerance of Tirich Mir low- temperature isolates 115 3.1.8 Metal tolerance of Tirich Mir high- temperature isolates. 116 3.2.1 Molecular Phylogenetic analysis of HTS (15°C) by Maximum Likelihood 142 method 3.2.2 Molecular Phylogenetic analysis of low temperature isolates (LTS) by 143 Maximum Likelihood method 3.3.1 Molecular phylogenetic analysis of HTP6 (Alcaligenes faecalis) by 168 Maximum Likelihood method. 3.3.2 Antibiotic sensitivity profile of Alcaligenes faecalis HTP6, showing 169 variable zones of inhibition against different antibiotics. 3.3.3 Zone of inhibition (mm) of Alcaligenes faecalis HTP6 against tested 170 ATCC cultures and clinically isolated bacterial strains 3.3.4 Optimization of isolate for biomass production with different parameters, 171 these parameters 3.3.5 Optimization of parameters for the maximum production of antimicrobial 172 compounds 3.3.6 The effect of incubation time on the antimicrobial compounds activity 173 showed best inhibition at 96 hours of incubation 3.3.7 Zone of inhibition (mm) of crude extract of Alcaligenes faecalis HTP6 174 against the test bacterial and fungal strains. Best inhibition was found against A. fumigatus followed by S. aureus 3.3.8 The tolerance of Alcaligenes faecalis HTP6 to different metal ions(ppm) 174 showed best tolerance against Fe++.and least against Hg++ 3.3.9 FTIR analysis of the antimicrobial metabolite produced by Alcaligenes 175 faecalis HTP6 showing the presence of various functional groups 3.3.10 Multiple bands of the antimicrobial crude extract under (a) UV 365 nm 176 and (b) 254 nm. The arrows showed metabolites of different molecular weight, probably having antimicrobial activity. 4.1.1 Molecular Phylogenetic analysis of the Batura fungal isolates by 201 Maximum Likelihood method 4.2.1 Phylogenetic tree of the fungal isolates prepared by Maximum Likelihood 215
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analysis of ITS1 and ITS4 sequences 4.3.1 Phylogenetic analysis of the Siachen isolates using Maximum Likely hood 237 4.4.1 Molecular Phylogenetic analysis by Maximum Likelihood method 253 4.5.1 Phylogenetic relationships of Alternaria taxa isolated from Tirich Mir 282 Glacier 5.1 Distribution of sequences of all 4 samples into functional categories 305 5.2 Rare faction curve showing specie richness of the study samples 306 5.3 Domain distribution of all the samples, all samples indicates the absolute 307 abundance of domain bacteria. 5.4 Taxonomic abundance in Passu sediment (PS) sample and Siachen 309 sediment (SS) sample. 5.5 Taxonomic abundance in Tirich Mir sediment (T-05) sample and Tirich 310 Mir muddy surface ice (T-08) sample 5.6 community distribution and Bacterial distribution of Passu Sediment PS in 312 Krona Chart 5.7 Community distribution and Bacterial distribution of Siachen Sediment SS 313 in Krona Chart 5.8 Community distribution and Bacterial distribution of Tirich Mir Sediment 314 T-05 sample in Krona Chart 5.9 Community distribution and bacterial distribution of Tirich Mir muddy 315 surface ice T-08 in Krona Chart. 5.10a Taxonomic rank abundance plots for the metagenomic samples PS and SS 316 5.10b Taxonomic rank abundance plots for the metagenomic samples T-05 and 317 T-08. 5.11 Functional hits distribution of sample genomes by COG distribution. 318 KEGG Orthology Hits 5.12 KEGG orthology functional hits of the study samples 319 5.13 Distribution of functional gene by subsystem technologies 321 5.14 Heat map of the functional subsystem categories of the study sample 322
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Acknowledgements
Praise to ALMIGHTY ALLAH, whose blessings enabled me to achieve my goals. Tremendous praise for the Holy Prophet Hazrat Muhammad (Peace Be upon Him), who is forever a torch of guidance for the knowledge seekers and humanity as a whole.
I have great reverence and admiration for my research supervisor, Dr. Fariha Hasan, Department of Microbiology, Quaid-i-Azam University, Islamabad, Pakistan, for her scholastic guidance, continuous encouragement, sincere criticism and moral support throughout the study. Her guidance helped me in all the time of research and writing of this thesis, with her patience and immense knowledge.
I do not find enough words to express my heartfelt gratitude for Prof. Dr. Alexandre Magno Anesio, Professor in Biogeochemistry, School of Geographical Sciences University of Bristol, UK. He supervised me during my studies in University of Bristol during IRSIP. This experience would not have been as valuable without the guidance, support and inspiration provided by him. I am impressed by his scientific thinking and politeness.
I am also thankful to Chris Bellas and Marie Sabacka, Postdoctoral Research Associates at Bristol Glaciology Center, for their care and immense help during my entire stay at University of Bristol.
I would also like to thank Higher Education Commission, Pakistan, for providing me grant under the Project “International Research Support Initiative Program (IRSIP)” and Indigenous Scholarships.
I am extremely grateful to the entire faculty at the Department of Microbiology, Quaid-i-Azam University, Islamabad. I feel thankful to the non-teaching staff, Shabbir Sahib, Shafaqat sahib, Sharjeel, Tanveer and Shahid Department of Microbiology, QAU, Islamabad, for their kind assistance. Many thanks to Dr. Simmon Cobb, Senior Teaching Laboratory Technician and Mr. James Williams, the Analytical Research Technician in LOWTEX for their help during my stay in University of Bristol.
I extend my great depth of loving thanks to all my friends and lab mates (seniors and juniors) especially Abdul Haleem, Sahib Zada, Arshad, Abdul Haq, Ghufran,
vi
Matiullah, Wasim, Waqas, Hameed Wazir, Wasim Hukam, Manzoor, Umair, Akhtar Nadhman, Saad, Shahid, Barkat, Faiz, Ayesha, Shama, Afshan Hina, Maliha, Nazia Anum for their help and care throughout my study.
I would like to thank my class fellows Irfan, Imran, Abdul Rehman and Zia Ullah for their help and support.
A special thanks to a cluster of people always with me during ups and down during research period. These special people are Shaukat, Rabia, Noor Hassan, Hayat, Mohsin, Ibrar and Faisal.
I would also like to thank Pervaiz, Shaukat, his cousin and two anonymous school teachers of upper Tirich (Chitral) who assisted me in sample collection.
A non-payable debt to my loving Ammi, Abbu, brothers and sisters for bearing all the ups and downs of my research, motivating me for higher studies, sharing my burden and making sure that I sailed through smoothly. Completion of this work would not have been possible without the unconditional support and encouragement of my loving family members. I would like to acknowledge my uncles Yousaf, Jauhar Ali, cousin Shafiq and all other family members for their support.
Finally, I express my gratitude and apology to all those who provided me the opportunity to achieve my endeavors but I missed to mention them personally.
Muhammad Rafiq
vii
Summary
Mountain ranges of Hindu Kush, Karakoram and Himalaya (HKKH) are the largest mountains of the world. They contain all fourteen tallest peaks of the world above 8000 m in elevation. They also harbor thousands of small and large glaciers. Due to heavy glacial ice mass, it is also termed as third pole of the world. Microbiologically, no single report is available to describe the diversity of these psychrophilic important niches. The present study aims to unveil the culturable and unculturable microbial diversity of the HKKH glaciers; Tirich Mir glacier (Hindu Kush), Batura and Passu (Karakoram) and Siachen (Himalayan Karakoram) and thus, adding to our understanding of the bacterial and fungal diversity of these psychrophilic niches. In current study we collected glacial ice, sediment and melt water samples from four different glaciers. Isolation of bacteria and fungi was carried out from these samples on the basis of distinct colony morphology. The cultured isolates were identified by 16S rRNA gene sequencing and were further characterized on various physiological parameters (such as temperatures, pH, salts and metal concentration) as well as screened out for antimicrobial metabolites and extracellular enzyme production. Four samples were also subjected for determination of uncultured diversity by metagenomic approach. Illumina sequencing technologies were used for sequencing of the samples and analyzed through MG-RAST (Metagenomic Rapid Annotation Subsystem Technologies) an online data base.
From Tirich Mir glacier sample, total 43 bacterial and 54 fungal isolates were selected on the basis of morphology. For bacterial 16S rDNA sequence analysis revealed that the most abundant group was Proteobacteria (53%), followed by Firmicutes (23%), Actinobacteria (15%) and Bacteroidetes (9%). Most of the isolates (74%) showed tolerance up to 10% of NaCl concentration, while the highest tolerance was up to 36% NaCl. Most of the isolates were able to grow between 4 and 37°C. Most of the bacterial isolates of Tirich Mir glacier were resistant to different toxic metals like Cd+2, Cr+3, Hg+2, Fe+3, Ar+3 and Ni+2 but highest resistant was observed against Fe+3, and least against Hg+2. Many isolates showed antimicrobial activity against ATCC and clinically isolated Gram positive and Gram negative bacteria and fungi. Similarly, 54 fungi were also isolated from same samples. After morphological and molecular (18S rRNA sequencing) analysis, Penicillium and Alterneria were found dominant isolated genera followed by Cladosporium, Didymella, Phoma, Coprinopsis, Epicoccum, Ulocladium, Ascochyta, Aspergillus, Comoclathris, Davidiella, Geomyces, Irpex, Pseudogymnoascus, Scopulariopsis and Tomicus. These fungal isolates showed remarkable abilities to grow on different pH (2-11), temperatures (4- 37°C) and NaCl concentrations (2-18%). Ulocladium sp. showed activity against both ATCC bacterial and fungal strains. These fungal isolates were also able to produce various extracellular enzymes (amylase, cellulase, deoxyribonuclease and lipase). Bacterial and fungal diversity of previously unexplored Siachen glacier, was studied. A total 50 bacterial and seventeen fungal isolates have been isolated from all the samples. For bacterial isolates 16S rRNA gene sequences shown that genus viii
Pseudomonas was isolated as a most dominated genus. Most of the isolated bacteria were moderate halophiles, while some were extreme halophiles and grew up to 6.12 M NaCl. Among the all bacteria, Gram positive bacteria (94.11%) were more resistant to iron while least against mercury as compared to Gram negative (78.79%). More than 2/3 of the isolates showed antimicrobial activity against multidrug resistant and ATCC bacterial and fungal strains. Moreover, the isolated seventeen fungal isolates identified by analysis of 18S rRNA ITS1-ITS4 region. The most frequently isolated fungal genus was Leotiomycetes. All isolates were found to tolerate NaCl concentration up to 10-20%, pH 1-13 while some isolates showed viability at 45°C. All isolates were showed good antimicrobial activity against Gram (+) bacteria. Most of the fungal isolates were good producers of cellulase, lipase and protease. In the present research work, a bacterial species, HTP6 was isolated from sediment sample, collected from Passu glacier. The isolate HTP6 was Gram negative, non-pigmented rod and was identified as Alcaligenes faecalis HTP6 on the basis of 16S rRNA gene sequence analysis. The strain showed resistance to clindamycin, cefotaxime and sulfamethoxazole/trimethoprim. Maximum growth and inhibitory activity of Alcaligenes faecalis HTP6 was observed against selected ATCC strains [Staphylococcus aureus (ATCC 25923) and Pseudomonas aeruginosa (ATCC 27853)] and various clinical isolates (S. aureus, E. faecalis, Candida albicans and Aspergillus fumigatus) at pH 7 and 30°C, when LB (Luria Bertani) and LB1 (medium supplemented by FeSO4) broth media were used. The crude extract showed good storage and thermal stability at 55°C, and pH stability at 7 along with brine shrimp lethality up to 30%, however, there was no DNA binding and haemolytic activity observed.
Batura and Passu glaciers have been investigated for the presence of psychrotrophic fungi. A total of 60 fungal isolates were isolated from sediments, ice and water samples. Fungal isolates were identified morphologically and microscopically and confirmed by 18S rRNA gene sequencing. Most of the fungal isolates belonged to the genus Penicillium, followed by Cladosporium, Geomyces, Cordyceps, Mrakia, Cadophora, Tetracladium, Eupenicillium, Trametes, Mortierella, Scopulariopsis, Beauveria, Candida, Pseudogymnoascus, Pseudeurotium, Fontanospora, Trichoderma, Antrodia, Sporobolomyces, Phoma and Beauveria. Majority of the isolates were able to grow at pH from 1 to 13, 2-26% salt concentration and between 4 and 37°C, whereas, some fungal isolates were able to grow at 45°C as well. The majority of fungal isolates shown best activity against Staphylococcus sp. Sporobolomyces ruberrimus was found to produce five different enzymes (amylase, cellulase, deoxyribonuclease, phosphatase and protease).
For the metagenomic studies, four samples were selected and processed. The results revealed that these samples are rich in diversity and members of all three domains of life were found in great number. The most abundant group was bacteria in all samples constituting more than 90% in all samples (Some samples constitute about 97 – 98% of bacteria). Insight into the domain bacteria revealed that the most abundant groups ix
were Proteobacteria, Actinobacteria, Cyanobacteria, Firmcutes, Bacteroidetes, Chloroflexi in all samples. The combination of autotrophic and heterotrophic was observed. Beside these other radiorsistant deinococcus was also observed. The Eukaya domain was dominated by heterotrophic fungal group Ascomycota. The number of Ascomycota was much higher than the relative eukaryotes groups. Some important primary producers of Eukaya domain were present. The major group was Algae which have a basic role in the cycling of important compounds. Members of the domain Archaea was also found in large number. These psychrophilic archaea belonged to Crenarchaeota, Euryarchaeota, Korarchaeota and Nanoarchaeota. Besides, a large number of sequences were detected belonging to psychrophilic Viruses and some sequences were unspecified.
The functional hierarchy revealed that these frozen zones were metabolically very active. The annotations in M5NR database showed that the majority of the sequences belong to metabolism. In metabolism the most abundant subsystem hits were responsible for carbohydrates, protein and cell components. The other important groups were stress response proteins, cell wall and capsular, secondary metabolites and many other which help the microbes of these harsh environments to live and thrive there.
Results indicated that these glaciers are microbiologically and functionally more active. The microbe living in these glaciers have great potential of producing industrially important compounds. The glaciers of HKKH range are wide spread in many countries and provide drinking and agriculture water to billions of people. There is a need to further investigate the deep microbial diversity, role of viruses in geochemical and biochemical processes. Investigations of the role of microbe on climate change may bring some facts of global warming and possible solutions to the problem.
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Chapter 1 Background
Background
The extreme environment and complete absence of visible biological life forms in some Antarctic desert regions, made the scientists conclude that microbial life does not exist in Antarctic soils. Now it is known that abundant microbial life exists in most “extreme” habitats such as Antarctic desert soils or any other extreme environment (Cowan et al., 2010). Extremophiles are structurally adapted at the molecular level to tolerate and adapt under these harsh conditions (Gomes and Steiner, 2004).
The term extremophile was first coined by MacElroy in 1974 (MacElroy, 1974). ‘Extreme environment’ is a general term, where environments considered extreme for one type of living entities may be vital for the existence of another type of organism. Extremophiles live and thrive under circumstances that would normally be lethal for most of the other organisms and many cannot survive in the normal man made global environments. Some of the most wide spread extreme environments are high (55 to 121°C) or low (–40 to 20°C) temperatures, high concentration of salt (2–5 M NaCl), high acidity (pH < 4), high alkalinity (pH > 8) (Madigan and Marrs, 1997; Rothschild and Manicinelli, 2001). The organisms which not only survive and grow but also thrive in such harsh conditions are called extremophiles. Many extremophiles have the ability to tolerate harsh environmental conditions like increased concentration of metals (Metalophiles), low availability of nutrients (Oligothrophs), low water availability (Xerophiles), high radiation (Radioresistant), high pressure level (Barophiles/Piezophiles) and less oxygen tension (Anaerobes) (Gomes and Steiner, 2004), poisonous materials or unfamiliar environments such as life in rocks (Endoliths, Epiliths) (Madigan and Marrs, 1997; Rothschild and Manicinelli, 2001). Some environments are collection of more than one harsh conditions, thus the organisms living there, faces many challenges for their survival, such environments include high temperature niches along with high pH, low pH, low nutrients availability, similarly, deep ocean with high pressure also harbors low temperature, no light, low nutrient availability. Such organisms living in environments with a combination of extreme conditions are termed as “polyextremophiles”. Members of all the 3 domains are found in each extreme environment but the major group of
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 1 Chapter 1 Background extremophiles belongs to domain Archaea, followed by bacteria and eukaryotes (Madigan and Marrs, 1997; Rothschild and Manicinelli, 2001).
One of the most abundant environments on Earth, is low temperature environment, which includes polar region, high mountains of Europe, glaciers, 95% part of the oceans, upper part of atmosphere, manmade refrigerators and freezers, surfaces of plant and animal life in cold environments, where temperatures seldom go beyond 5°C (Gomes and Steiner, 2004; Cavicchioli et al., 2002; Deming, 2002; Margesin et al., 2002; Feller and Gerday, 200; Georlette et al., 2004).
The organisms that grows at temperature below 20°C are called Psychrophilic (cold- loving) while some organisms grow optimally at higher temperature but can tolerate low temperature are called psychrotolerant (cold-adapted) (Gomes and Steiner, 2004). Although, this terminology is still widely used, in the last few years the terms eurypsychrophiles (from Greek euros=broad) and stenopsychrophiles (from Greek stenos=narrow) have been suggested as more appropriate to describe the range of temperature that an organism can tolerate (Margesin and Miteva, 2011).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 2 Chapter 1 Background
Table 1. List of psychrophilic microbes with their habitats
Psychrophilic habitats Major Country/locatio Microbes isolated Source of isolation References Subzone Zone n Deinococcus, Vibrio, Arthrobacter, (-17) Snow, lakewater, sediment, (Carpenter et al. Pseudomonas , Methanogenium spp. ice 2000) (Amundsen-Scott South Pole (Cavicchioli and Amundsen– Station) Thomas 2000) Scott Station methanogenic Archaea Ace Lake, Antarctica: Franzmann et United state Methanococcoides burtonii sp. nov. al., 1992, 1997 and Methanogenium frigidum sp. nov. Princess Dominant green sulfur bacterium Ace Lake Ng et al., 2010 South pole Elizabeth Land (Antarctic Spore and non-spore forming bacteria, Ice sheets (Vostok station) Abyzov et al., Polar a) yeast and fungi 1999 regions (-82 - - Alpha and beta-proteobacteria and Ice 3590 m below (Vostok station) Priscu et at., Russia 12°C) Actinobacteria 1999 Gram negative bacteria Accretion ice (Vostok station) Karl et al.1999
Bacillus, Nocardioides, Spile dome Christner et al. Spile coast Sphingomonas 2000
South Shetland Auto- and heterotrophic bacteria King George Island islands Princess Colwellia, Shewanella, Marinobacter, Sea ice cores sample Vestfold Hills Bowman et al., Elizabeth Land Planococcus, and 1997
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 3 Chapter 1 Background
novel phylogenetic lineages adjacent to Colwellia and Alteromonas, Pseudoalteromonas, Psychrobacter, Halomonas, Pseudomonas, Hyphomonas, Sphingomonas, Arthrobacter, Planococcus, and Halobacillus Acinetobacter, Bosea, Taylor dome Christner et al. Bradyrhizobium, Methylobacterium, 2000 Sphingomonas Victoria Land Alphaproteobacteria, Lakes of McMurdo Dry Valleys Stingl et al., Betaproteobacteria, Bacteroidetes and 2008 Actinobacteria Bacteria and Eukarya Lake Vida, McMurdo Dry Valleys Mosier et al., 2007 S. frigidimarina and P. cryohalolentis Glacial ice samples of an Antarctic Laura Garcia- South Shetland and Shewanella oneidensis glacier in Mount Pond, Deception Descalzo et al., Islands Island 2012 Firmicutes, proteobacteria, Antarctic ice core samples Segawa et al., Mizuho plateau Bacteroidetes, Actinobacteria, 1 Mizuho Base 2010 b Cyanobacteria and Deinococci. 2 Yamato Mountains Serratia, Enterobacter, Klebsiella and Stream, lake and glacier Canada's Dancer et al., Yersinia High Arctic 1997
Actinobacteria, Proteobacteria, Canadian high Steven et al., Canada Firmicutes, Cytophaga - Flavobacteria Arctic permafrost 2007a, b. - Bacteroides, Planctomyces and Gemmatimonadetes; Euryarchaeota and Crenarchaeota.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 4 Chapter 1 Background
Bacteroidetes, Proteobacteria and Ice shelves in the Canadian High Bottos et al., Actinobacteria and Euryarchaeota Arctic 2008 Cyanobacteria, especially High Arctic lakes, streams and ice (Bonilla et al., representatives of Oscillatoriales, 2005; Jungblut Nostocales and Chroococales et al., 2010; Tang et al., 1997). Crenarchaeota and Euryarchaeota High Arctic lakes, (Galand et al., 2008a; Pouliot et al., 2009). Aerobic chemoheterotrophs and ice layers of a high Arctic glacier Skidmore et al., anaerobic nitrate reducers, sulfate (John Evans Glacier) 2000 reducers, and methanogens Acidobacterium, Actinobacteria, Glacier in the McMurdo Dry Valley Christner et al., Cyanobacteria, Cytophagales, 2003a Gemmimonas, Planctomycetes, Proteobacteria, and Verrucomicrobia Bacteroidetes (predominantly John Evans Glacier Cheng and Flavobacterium),Betaproteobacteria Foght, 2007 (particularly Comamonadaceae), Actinobacteria were detected Biomineralizing microorganisms Canadian high Arctic soil sample Steven et al., 2007a,b Proteobacteria, Actinobacteria, Antarctic iceberg Yanagihara et Firmicutes, Cyanobacteria and Ongul Island al., 2011 Bacteroidetes Norway 4500 sequences were obtained from 52 soil samples from foreland of Schutte et al., each sample by 454 pyrosequencing. Midre Love´n glacier 2010
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 5 Chapter 1 Background
Ascomycetous and Basidiomycetous Kongsfjorden Cimerman et al., yeasts 2003 Viruses and bacteria Midre Lovénbreen and Austre Anesio et al., Brøggerbreen glaciers 2007 Hymenobacter Red snow in (Queen Maud Land Fujii et al., Antarctica ) 2010 psychrophilic yeast Leucosporidium Tvillingvatnet, Norway Lee et al., 2010 sp. Methylobacterium, Brevundimonas, Coastal Dronning Maud Antony et al., Paenibacillus, Bacillus and Land, East Antarctica. 2012 Micrococcus Alphaproteobacteria, Snow cover at Spitzberg. Svalbard, Amato et al., Betaproteobacteria and Norway, arctic ocean 2007a Gammaproteobacteria, Firmicutes and Actinobacteria. Iceland (Proteobacteria, and Cytophaga- 3,043-m-deep Greenland glacier ice Miteva and Flavobacteria-Bacteroides) core Brenchley, 2005 Arthrobacter, Microbacterium, Paenibacillus, Sphingomonas Proteobacteria, CFB group. High Miteva, et al., Greenland G+C gram positive (Arthrobacter- Deep Greenland Glacier Ice Core 2004 Micrococcus,Microbacteriaceae; Acti nomycetes), low G+C Sporosarcina Paenibacillus Exiguobacterium and Aerococcus. )
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 6 Chapter 1 Background
Betaproteobacteria and glacial snow and ice sample of Segawa et al., Gammaproteobacteria Gulkana Glacier (Alaska) 2011
Proteobacteria, Bacteroidetes, surface ice and snow sample of Choudhari et al., United States Firmicutes, Actinobacteria, Byron Glacier in Alaska 2013 (Alaska) Cyanobacteria, Acidobacteria, Verrucomicrobia, and Planctomycetes. Majority of unculturable species. More than 30 archaeal species Uncultarable Archaea frigid marine surface waters of DeLong et al.,
Antarctica 1994 Pseudoalteromonas haloplanktis Dumont d'Urville, Terre Adélie Medigue et al., Chile TAC125 Antarctica 2005 Micrococcaceae, Microbacteriaceae, altitude of 20,000 m along a west to Griffin, 2008 Continental US Staphylococcus and Brevibacterium east Atmospheric sample
Non Aureobacterium, Bacillus, Ice core of Christner et al. Polar America Brevibacterium, Cellulomonas, Nevado Sajama 2000 Zone Frankia sp. str. AVN175, Friedmanniella, Microbacterium, Bovilia Micrococcus, Mycobacteria, Norcardia, Norcardioides, Planococcus and Staphylococcus.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 7 Chapter 1 Background
Proteobacteria, Firmicutes, East Rongbuk, Laohugou and Zhang et al., Actinobacteria and Bacteroidetes. Hailuogou glaciers on the Tibetan 2010 b Brevundimonas, Flavobacterium, Plateau Hymenobacter, Bacillus, China Polaromonas, Rhodoferax and Streptomyces, Hylemonella, Delftia, Zoogloea, Blastococcus and Rhodococcus Actinobacteria, Firmicutes, East Rongbuk Glacier, Mt. Zhang etal., Proteobacteria and Deinococcus- Qomolangma 2010 a Thermus, Proteobacteria, Actinobacteria, Snow of East Rongbuk glacier, Mt. Liu et al., 2006b Firmicutes, CFB, Cyanobacteria, Everest Eukaryotic chloroplast, and TM7 Asia candidate phylum Proteobacteria, Cytophaga– Two moraine lakes and two glacial Liu et al., 2006a Flavobacteria–Bacteroides, meltwaters Actinobacteria, Planctomycetes, Tibetan plateau Verrucomicrobia, Fibrobacteres and Eukaryotic chroloplast Proteobacteria, Actinobacteria and snow of the four glaciers Guoqu, Liu et al., 2009 Bacteroidetes Zadang, East Rongbuk and Palong No. 4 (Tibetan Plateau)
Acinetobacter, Arthrobacter, Guliya ice Christner et al. Aureobacterium, Bacillus, Cap 2000 Cellulomonas, Clavibacter, Flavobacterium, Microbacterium, Micromonospora, Paenibacillus,
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 8 Chapter 1 Background
Propioniferax, Staphylococcus, Stenotrophomonas Proteobacteria, Acidobacteria, Cold springs, Qinghai-Tibetan Li et al., 2012 Deinococci, Sphingobacteria, Plateau Flavobacteria, Nitrospirae, Actinobacteria,Gemmatimonadetes, and unclassified-bacteria; and the archaeal clones Crenarchaeota and Thaumarchaeota. Cryobacterium psychrophilum, Mountain snow from the Tateyama Segawa et al., Japan Variovorax paradoxus and Mountains, Toyama Prefecture, 2005 Janthinobacterium lividum. Japan. Bacteroidetes dominated high altitude lakes in the Mount Sommaruga Nepal Everest region and Casamayor, 2009 Bacillus simplex and Staphylococcus Stratosphere air sample at an Wainwright et pasteuri) and a single fungus, altitude of 41 km al., Engyodontium album 2004 Actinobacteria, Firmicutes and Soil samples in the vicinity of Shivaji et al., India Proteobacteria, Acidobacteria, Pindari glacier 2010 Bacteroidetes, Gemmatimonadetes and Planctomycetes, Chlamydiae, Chlorobi, Chloroflexi, Dictyoglomi, Fibrobacteres, Nitrospirae, Verrucomicrobia, Australia
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 9 Chapter 1 Background
gamma and beta proteobacteria and Sediments and melt water (Haut Cytophaga-Flavobacteria-Bacteroides Glacier d'Arolla HGA) Montross 2007 (CFB) and large community of Switzerland unculturable bacteria Proteobacteria, Actinobacteria, Soil sample of Swiss glacier Lazzaro et al., Firmicutes forefields 2012 (Damma and Tsanfleuron), Actinobacteria, Bacteroidetes, Atmospheric water samples from Amato Proteobacteria,Firmicutes, clouds at the Puy de Dôme et al., 2005, Ascomycota and Basidiomycota 2007b Proteobacteria, Bacteroidetes, Cloud water from the puy de Dôme Vaïtilingom et Firmicutes and Actinobacteria, and summit in France al., 2012 France Basidiomycetous and Ascomycetous yeasts) Europe Actinobacteria, proteobacteria, Cloud droplets (Puy de Dome) Amato et al., Bacteroidetes, Firmicutes, ascomycota 2005 and basidiomycota Psychrophilic Stubai Glacier Zhang et al., bacterium Sphingomonas glacialis sp. 2010 nov., Betaproteobacteria and Actinobacteria Piburger See; Seefelder Wildsee; Ho¨rtnagl et al., Obernberger See; Gossenköllesee; 2010 Rotfelssee; and Schwarzsee ob Austria Sölden. Bacteria, Yeast and Hyphomycetes Stubaier glacier Margesin et al., 2002; Pedobacter cryoconitis sp. nov. Stubai Glacier Margesin et al., 2003 Members of Betaproteobacteria , Gossenko¨llesee in the Tyrolean Alfreider et al.,
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 10 Chapter 1 Background
Alphaproteobacteria and CFB Alps Austria (Alpine lakes) 1996 Dominated by Fluorescent Hebridean cloud and rain water Ahern et al., Scotland pseudomonads sample 2007 Proteobacteria and Bacteroidetes, (Snow and ice sample) western Lutz et al., 2015 Archaea and algae glacier Snaefellsjökull, northern glacier Drangajökull, central glacier Hofsjökull, Laugafell in the Central Iceland Highlands, southern glaciers Vatnajökull, Eyafjallajökull, Mýrdalsjökull, Solheimajökull and western glaciers Snaefellsjökull and Langjökull
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in Hindu Kush Karakoram Himalaya (HKKH), Pakistan 11 Chapter 1 Background
Cold temperature have many adverse effects on the cell, including deleterious effect on cell integrity, water availability, solute uptake, membrane flexibility, activity of enzymes and other biochemical processes (Rodrigues and Tiedje, 2008; Piette, et al., 2011b). Therefore, a microbe without proper tools and accessories cannot tolerate cold conditions (Rodrigues and Tiedje, 2008). As such, psychrophiles have evolved mechanisms to successfully counteract additional stress factors associated with cold environments, such as desiccation, radiation, excessive UV, high or low pH, high osmotic pressure and low nutrient availability (Morgan-Kiss et al., 2006; Tehei and Zaccai, 2005).
Psychrophilic microbes developed different adaptive strategies to cope with such harsh conditions and produce enzymes and proteins which are metabolically active at such low temperature. Psychrophiles also modify their structural proteins and building blocks which protect and maintain structure of the cell from adverse effect of low temperature (Cavicchioli et al., 2002; Deming, 2002; Margesin et al., 2002; Feller and Gerday, 200; Georlette et al., 2004). Psychrophilic proteins, in comparison to mesophilic proteins, have low bonding interactions like ionic, hydrophobic and hydrogen bonds and high charge cluster on cell surface (Cavicchioli et al., 2002; Deming, 2002; Margesin et al., 2002; Feller and Gerday, 200; Georlette et al., 2004). These changes made proteins flexible to work properly in such low temperature environment. Furthermore, the unsaturated fatty acids are present in membranes which maintain the fluidity and transportation in frozen environments. Psychrophiles also synthesize a number of cold shock and antifreeze proteins. These proteins make the environment suitable inside the cell for the maintenance and stabilization of enzyme activity even at freezing temperature (Carpenter et al., 2000; Georlette et al., 2004; Rivkina et al., 2000). The microbes capable of some special modifications in phenotypic and genotypic characteristics to adapt low temperature environments bring about abundant life form in all psychriphilic habitats, include polar, non polar and deep ocean (Deming and Baross, 2001; Deming and Huston, 2000; Staley et al., 2001; Price, 2000; Thomas and Dieckmann, 2002)
One of the coldest biome reported yet is Tundra. Including Tundra there are other regions include Antarctic, Arctic and alpine regions considered free of any life form, but in summer increase in temperature heavily support the microbial growth and
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 12 Chapter 1 Background cycling of carbon and other elements are carried out. The food web and element cycling in the cryosphere are due to many different type life forms, these may include bacteria, fungi, viruses, protozoa and algae (Anesio and Laybourn-Parry, 2012)..
Microbial biogeography is defined as the science that documents the spatial distribution of prokaryotic taxa in the environment on a local, regional and continental scale (Ramette and Tiedje, 2007). Several factors have great influence on outline and shape of the distribution of microbes in the nature. In the distribution and colonization of psychrophilic microbes, combinations of many factors play a key role. The most important factors for dissemination are climatic factors like storms and wind flows, distribution through a vector like insects, plant seeds, dust, oceanic currents and birds (Glöckner et al., 2012). Microorganisms transfer via any of the mentioned method and colonized in new niches. The organisms, having tools for the survival has the ability to live and thrive there. Thus, different dispersal methods, ability of colonization, survival potential of the cells, these characteristics are under the influence of different factors which shape the diversity patterns. (Fierer, 2008).
Glacial ice is accumulated as a result of snowfall on the polar region, arctic line and high altitude mountains of Europe, America and Asia (HKKH). These glacial masses internalized different materials like particulate substances of biological and inorganic origin. Very little is known about the total diversity of cold habitats and the correlations of climate changes with diversity of all three domains. The studies showed that cold habitats have members of all three domains of life. The most abundant groups including; bacteria, fungi, archaea, parasites and viruses as well (Abyzov et al., 1982, 1998; Abyzov 1993; Dancer et al., 1997; Castello et al., 1999; Willerslev et al., 1999). Not only all the three domains are found in cryosphere, there is also very active and diverse viral populations are present with many novel groups. These viruses may infect the prokaryotes and eukaryote hosts. The genetic studies reveled that many genes are found which help in the maintenance of long term relation with the hosts (Bellas et al., 2015).
The ecosystem of glacial and ice sheets are thoughts to be helping in the cycling of carbon. The glacial ecosystems contain both oxygenic (surface) and anoxic (deep areas) regions which possess many mechanisms for the metabolism of organic Carbon and other elements (Stibal et al., 2012a).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 13 Chapter 1 Background
The rRNA gene analysis show that major groups of organisms present have similar proportion throughout the cold habitat of polar, non-polar, deep sea and high altitude glaciers (Bai et al., 2006; Xiang et al., 2009; Shen et al., 2012). The major groups; Actinobacteria, Proteobacteria, Cytophaga-Flavobacteria and ascomycota are spread over all cold habitats (Christner et al., 2008b). Rodrigues et al. (2009) isolated high number of Psychrobacter and Exiguobacterium from Antarctica and Siberian permafrost.
To determine the number and type of microbes in cryosphere environment is important for better understanding of microbial quantification and biogeochemical processes in the active biological system. But the quantification is very difficult due to low number of cells and presence of interfering mineral elements (Stibal et al., 2015).
The area of psychrophilic research since last decade has been focused on the microbial diversity of ice, permafrost, sediments and glacier melt water of polar regions and alpine glaciers (Skidmore et al., 2005; Xiang et al., 2005; Liu et al., 2006a; Zhang et al., 2006; Nemergut et al., 2007; Zhang et al., 2008; Gangwar et al., 2009; Liu et al., 2009a, b). A total of 90% of the glacial microbial flora consists of bacteria. The abundance of fungi and archaea is relatively very low (Margesin and Miteva, 2011). Some studies on glaciers of different parts of the world, e.g. Alaska (Segawa et al., 2010a), Tibet (Zhang et al., 2010b), China (Bai et al., 2006; Xiang et al., 2009; Shen et al., 2012), Canada (Cheng and Foght, 2007) and New Zealand (Foght et al., 2004) revealed that the most abundant bacterial group reported was Proteobacteria, constituting up to 65% of the total isolates, of which Beta- proteobacteria are the dominant class. Proteobacteria is followed by Bacteroidetes, Actinobacteria, Gemmatimonadates, Chloroflexi, Acidobacteria and Firmicutes. The Korean Polar and Alpine Microbial Collection (PAMC) composed of about 1500 identified strains also support these findings (Lee et al., 2012). On the basis of 16S ribosomal RNA sequence analysis, most of the isolates were reported to belong to non- spore former Gram positive bacteria including; Actinobacteria, Firmicutes and proteobacteria and bacteroidetes from Gram negative bacteria. Apart from these, a number of photosynthetic cyanobacteria, chloflexi, were also identified. These organisms were consistent with colored and viscous colonies which may help in the protection of cells in harsh environment.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 14 Chapter 1 Background
Similarly, psychrophilic and psychrotrophic fungi have widely been studied for their presence in several cold environments in Arctic and Antarctica regions (Azmi and Seppelt, 1997; Babjeva and Reshetova, 1998; Selbmann et al., 2005; Tosi et al., 2002; Onofri et al., 2004; Vishniac, 2006). Fungi are an important component of the soil act both as decomposer and symbiont and play a role in the biogeochemical processes. But very little is known about the fungal diversity by culturing method. New technologies are very helpful in determining the fungal communities by next generation sequencing (Liu et al., 2015).
Furthermore, fungi have been investigated in different cold environments, including; permafrost (Broady and Weinstein, 1998; Golubev, 1998), cold water (Dmitriev, 1997; Botha and Wolfaardt, 2000), glacial ice (Ma et al., 1999), snow and below snow-covered tundra (Schadt et al., 2003) and off shore polar waters (Broady and Weinstein, 1998), glaciers, ice sheets and shelves, freshwater ice, sea ice and icebergs (Bridge, 2010; Tojo and Newsham, 2012).
The studies related to fungal diversity and characterization in non-polar regions such as Hindukush-Karakoram-Himalaya (HKKH) glaciers are very scarce. The HKKH glaciers have not so properly been investigated for presence of psychrophilic and psychrotrophic life (especially microorganisms). Five species of aquatic hyphomycetes belonging to the genus Lemonniera and aquatic hyphomycete, Tetracladium nainitalense, as a root endophyte, have been isolated from Kumaun Himalaya, India (Sati et al., 2009; Sati et al., 2014b). Anupama et al. (2011) reported the psychrophilic and halotolerant Thelebolus microsporus from the Pangong Lake Himalayan region.
Singh and Palni (2011) have collected 35 species belonging to 7 families of rust fungi from herbaceous and shrubby hosts in central Himalayan region. Moreover, 25 psychrophilic yeasts were isolated from the Roop Kund Lake soil of Himalayas, India (Shivaji et al., 2008). Three anti-fungal, Trichodermal species, T. harzianum, T. konengii and T. viride have been isolated from forest of Indian Himalayan Region (Ghildiyal and Pandey, 2008). Wang et al. (2015) studied glaciers of Qinghai-Tibet Plateau for the presence cold-adapted fungi and isolated 1428 fungi, of which, 150 species were identified and Phomasclerotioides and Pseudogymnoascus pannorum were the most dominant species. Hirose et al. (2009) have isolated 24 fungal species
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 15 Chapter 1 Background and carried out their comparison studies on cotton strips at three different altitudes on the Tibetan Plateau and assessed the environmental variables influencing them.
Glaciers are very diverse in microbial community and biomass of different geography (Carpenter, et al., 2000; . Christner, et al., 2000; Liu, et al., 2009a, b; Miteva,et al., 2004; Skidmore, et al., 2005; Zhang, et al., 2007; Zhang, et al., 2009). The microbial diversity are based on many factors include climate and environmental conditions, which may be geographic location (Battin, et al., 2001; Kikuchi, 1994; Mueller, et al., 2004; Takeuchi and Koshima, 2004) wind direction and speed, light intensity, freeze thaw cycles, nutrient availability (Christner, et al., 2003; Liu, et al., 2009a; Takeuchi, et al., 2006; Zhang, et al., 2007; Zhang, et al., 2009).
Comparisons of geographically distinct glaciers worldwide have shown a great variation in microbial biomass and community structure (Carpenter, et al., 2000; Christner, et al., 2000; Liu, et al., 2009a; Miteva, et al., 2004; Skidmore, et al., 2005; Zhang, et al., 2007; Zhang, et al., 2009). The variability is largely controlled by climatic and environmental factors, including geographic location (Battin, et al., 2001; Kikuchi, 1994; Mueller and Pollard, 2004; Takeuchi and Koshima, 2004), wind direction, wind speed, light intensity, and availability of nutrients and liquid water (Bhatia, et al., 2006; Carpenter, et al., 2000; Hill, et al., 2003; Kohshima, 1994; Mueller and Pollard, 2004; Takeuchi and Koshima, 2004). There is some limited evidence of biogeographic effects on the distribution of microorganisms in the geographically different glaciers (Christner, et al., 2003; Liu, et al., 2009a; Takeuchi, et al., 2006; Zhang, et al., 2007; Zhang, et al., 2009). However, main factors driving the dynamics of microbial community in glacial systems remain unclear (Xiang et al., 2009).
Only 1% of the world microbes are cultured and 99%of the microbes are still uncultured because of lack of availability of proper natural environmental conditions. These tools include the collection of information of DNA, RNA and protein sequences. These techniques are used to find out both the alpha, beta and gamma diversity (Fierer, 2008). Alpha diversity is the diversity within a locations, beta diversity comprises the differences between two habitats, while the gamma diversity explain the diversity of continents (Zinger et al., 2012).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 16 Chapter 1 Background
Metagenomics is the most supreme and powerful technique which revolutionized the microbial ecology by detection of the diversity of an ecosystem through culture independent methods. The library construction of DNA sequences without culturing is used for the detection of microbial communities in a given sample. Metagenomics is also used for the detection of important gene annotation and protein prediction to detect already available genes and predict new genes and new functions (Rho et al., 2010; Torsvik et al., 2002; Riesenfeld et al., 2004). The most advance set of metagenomics is discovery of next generation sequencing technologies (Hoff et al., 2009; Stewart et al., 2009). Next generation sequencing is used for detection of microbial diversity of many environments including soil, human gut, ocean water, glacial ice etc. As a result of these techniques, taxonomic and functional diversity of different environments are evaluated. For the assessment of functional dynamics of different environments, metatranscriptomics and metaproteomic discipline came into being (Simon and Daniel, 2010; Richter et al., 2008; Wilmes et al., 2015).
The detection of any specific protein’s function and its connection to specific microbe is difficult, but recently some advance techniques are helpful in the detection of and connection of taxa and protein function (Chistoserdovai, 2010).
The knowledge gained from studying ecology of extreme environment may be supportive in understanding our knowledge and clue for life on extraterrestrial environments and evolution of life on Earth. The discovery of ice on other planets provoked the thoughts to use glaciers as model for simulation studies of extraterrestrial life (Thomas and Dieckmann, 2002; Tung et al., 2005).
Cold habitats provide the world largest habitat on the Earth’s surface. According to Margesin and Miteva (2011) cold environments are classified into two groups. The first category is Aquatic cold environment which include; atmosphere and clouds, snow, cryoconite holes, glaciers, polar and Alpine lakes, deep sea and sea ice, while the second category is terrestrial cold environments including; cold soils and permafrost. The chief portion of low temperature environment constitutes the deep sea (~ 71% of the total Earth’s surface) of which about 90% of the deep sea or ocean is below 5°C, followed by snow (35%), permafrost (24%), sea ice (13%) and glaciers (10%). Other cold environments include cold water lakes, cold soil, caves and manmade fridge and freezers (Margesin and Miteva, 2011).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 17 Chapter 1 Background
In Pakistan, there are more than 5000 small and large glaciers. Pakistan is home of three great mountain ranges; Hindu Kush, Karakoram and Himalaya. These mountain ranges are situated in northern area of Pakistan i.e. Gilgit Baltistan to Chitral. These mountain ranges harbor world’s 2nd largest glacier outside polar region, Siachen glacier, which is about 76 Km in length along the disputed area between Pakistan and India. Biafo (67 km), Baltoro (63 km) and Batura (57 km) are the third, fifth and seventh longest glaciers, outside the polar region. In Pakistan, glaciers are spread over an area of about 16933 square km. Other than the polar region, Hindu Kush, Karakoram and Himalaya represent the largest glaciated mass (Bajracharya and Shrestha, 2011). Therefore, it is also termed as third pole of the Earth. HKKH spread over an area of more than 4.3 million square Km in Afghanistan, Bangladesh, Bhutan, China, India, Myanmar, Nepal and Pakistan. These mountain ranges contain all 14 peaks of the world, above 8,000 meters in height (Bajracharya and Shrestha, 2011) and there are 108 peaks more than 6000 m (Abbas, 2013; SUPARCO Pak 2014).
The glaciers are huge basins of drinking water resources and their regular melting nourishes about 60 small and large rivers in the country. These glaciers store water which is very crucial for the economy (agriculture, industrial and domestic use) of Pakistan (Pak Geographic 2015). Any depletion in the glaciers will adversely affect agriculture, drinking water supply, hydroelectric power and ecological habitats. This impact will lead to adversely affect the economy of Pakistan. This retretion in glaciers and global climate change also caused floods in the country (Abbas, 2013; SUPARCO Pak 2014).
The microbes in the extreme environment are always of great interest for scientists to look for the industrially important products like, enzymes, antibiotics and other pharmaceutical, etc. The new approaches opens a gateway to explore such communities for human and nature’s benefits (Lewin et al., 2013; Cavicchioli et al. 2002; Deming, 2002; Margesin et al., 2002; Feller and Gerday, 2003;Georlette et al., 2004).
The cold habitats Greenland and Antarctica is extensively studied for psychrophilic microbial ecology so far by many research teams (Dancer et al., 1997; Castello et al., 1999; Willerslev et al., 1999), alpine and eastern Himalaya (China) (Yao et al., 2006; Zhang et al., 2003; Yao et al., 2006). The glaciers of eastern Himalaya were studied
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 18 Chapter 1 Background for the bacterial diversity which showed that these glaciers are rich habitats of bacteria and also a number of novel strains were reported (Reddy et al., 2000; Chaturvedi et al., 2005; Mayilraj et al., 2005; Reddy et al., 2008; Kishore et al., 2010; Reddy et al., 2010) while there is not a single study available on the bacterial or fungal diversity of the glaciers of HKKH, Pakistan.
The present study aims to unveil the culturable microbial diversity of the HKKH glaciers; Tirich Mir glacier (Hindu Kush), Batura and Passu (Karakoram) and Siachen (Himalayan Karakoram) and thus, adding to our understanding of the bacterial and fungal diversity of these psychrophilic niches. This investigation provides a comparative study of diversity of polar and non-polar regions as psychrophilic habitats and the quantitative and qualitative ecological variances and life style of these newly explored habitats of microorganisms. The findings will also help to screen out some new isolates from such extreme environments with potential of producing industrially important metabolites including; cold active enzymes and antibiotics
.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 19 Aims and objectives Aims and Objectives Aim of the present research is to study the microbial diversity of various glaciers of Pakistan through culture dependent and independent techniques and study some of their unique characteristics. Isolation and identification of bacteria and fungi from sediment, ice and water samples collected from Batura, Siachen, Passu and Tirich Mir glaciers of HKKH, Pakistan. Determination of optimum temperature and pH required for growth of all the isolates, both bacteria and fungi. Screening of all the fungal and bacterial isolates for the production of industrially important enzymes Screening of all the fungal and bacterial isolates for their ability to show antifungal and antibacterial activity. To study the tolerance of all the bacterial and fungal isolates to varying salt concentrations Resistance of all the bacterial and fungal isolates to different metal ions. Study of microbial diversity (fungal, bacterial, archaeal) and functional diversity in glacial samples through metagenomics using next generation sequencing and bioinformatics tools. Percent distribution and taxonomic distribution into various phyla among four glaciers and phylogenetic analysis (culturable/ non-culturable). To find out the functional potential of the glacial samples from HKKH glaciers. A general survey of prospecting of novel industrially important metabolites using metagenomics
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 2 Review of Literature
Review of Literature
Cold Habitats around the world
Approximately, 80-85% regions of planet earth’s temperature is ˂ 5°C including oceans, the polar regions including Antarctica, the Arctic environments, mountains (Alps, Himalayas and other rocky mountains), the mesosphere and stratosphere (Rodrigues and Tiedje, 2008; Casanueva et al., 2010; Margesin and Miteva, 2011). Most of these low temperature environments consist of the deep sea (around 71% earth is occupied by oceans having temperature from -1 to 4°C), then followed by the snow (35% of total surface of land), permafrost (about 24% of Earth’s surface), ice of sea (13% of the Earth surface) and glaciers (constitute about 10% of total land surface of land, ~-5°C) as well as some other cold environments including cold deserts, lakes, caves and soils particularly subsoils (Singh et al., 2006; Margesin and Miteva, 2011). This marks low temperature biosphere as the most widespread ‘extreme’ diverse and widely distributed habitat on Earth, constituting low temperature adapted microorganisms that are facing diverse stress conditions (Piette et al., 2011a,b). Microbes evolved several adoptive mechanisms (Rodrigues and Tiedje, 2008) to respond to stress conditions such as desiccation, radiation, low nutrient concentration, high osmotic pressure, and extreme pH (Morgan-Kiss et al., 2006). Cold environments are less explored that prompt the scientist’s interest due to the probability of new species (Lee et al., 2012).
Cold habitats around the world are categorized as:
- Polar (Antarctica and Arctic regions): glaciers, ice sheets, permafrost, cold deserts. - Non- Polar (European alpine, Asian; HKKH): glaciers, ocean deep, high mountains Other low temperature habitats include: sea ice, subterranean ecosystems like caves, cold water lakes, elevated atmosphere, clouds, snow, man-made (Freezer/Refrigerator), the surfaces of animals and plants living in cold areas, where temperatures does not exceed 5°C.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 20 Chapter 2 Review of Literature
Fig 1. Climate map of the world.
(http://www.mapsofindia.com/worldmap/climate.html)
Polar (Antarctica and Arctic regions)
Antarctic and Arctic regions constitute permanently cold regions. Both Antarctic and Arctic regions contain various glaciers, ice sheets, permafrost and cold deserts.
Antarctica: Approximately, 99% of the Antarctica land is ice (Fox et al., 1994) and is demarcated as the driest and coldest region of planet Earth (Ovstedal and Smith, 2001; Onofri, 1999). Continent Antarctica is located at South Pole of Earth, which is entirely covered by thousand meters of thick sheets holding about 90% fresh water of planet. (British Antarctic Survey). Antarctica get a very low level of precipitation in the form of annual snowfall that results in extreme dry interior of the continent that makes it a desert. It is distinguished into 3 different zones including; the Continental Antarctica, the Sub-antarctica and the Maritime Antarctica (Peck et al., 2006). McMurdo Dry Valleys situated at Southern Victoria Land are ‘extreme’ terrestrial environments because of coldest and driest conditions, low nutrient availability and high UV irradiation (Onofri et al., 2007a; Finster et al., 2007). King George Island is
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 21 Chapter 2 Review of Literature located in South Shetland archipelago, Antarctica, and has an average temperature of 2°C (min -20°C, max 10°C).
Fig 2. North and South poles of the world, picture adopted from (http://2.bp.blogspot.com/-88HQ IqeVuU I/TkeVaz0E00I/AAAAAAAAAmk/_ hcEmXMlfu4/s1600/ poli_67425700.jpg)
Arctic: According to Bliss and Matveyeva (1992) biologist agree on the description as Arctic are lands i.e. outside the boundary of climate required by trees. Arctic is situated at the top of biosphere in the North Pole. The average summer temperature is more than 50 degree Fahrenheit while at winter temperature is -30 degrees Fahrenheit (http://polardiscovery.whoi.edu/arctic/index.html). It consists of the fully ice-covered Arctic Ocean, Spitsbergen, Greenland and the northern parts of Russia, Alaska, Norway and Canada. Its boundary is defined by either the treeline on the northern limit, where the average temperature in July was ~10°C (50°F), or the imaginary line of latitude “the Arctic Circle” located at 66 degrees 33min north, where the sun never sets in the summer (June 21st). The Greenland are ice-covered and the Alaska have lush tundra (http://polardiscovery.whoi.edu/arctic/geography.html). The Arctic region at 80-85°N comprise of the Ellesmere Island, Franz Joseph Land, Novaya Zemlya, New Siberian Islands and Svalbard. The Arctic is divided into five bioclimatic subzones (A-E), with A being the coldest subzone at northern side and the most extreme south part is subzone E being the warmest (Walker et al., 2005). As latitude increases, organisms face harsher conditions due to decreased air and soil temperatures (Billings, 1992).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 22 Chapter 2 Review of Literature
Permafrost is the frozen soils that store large quantities of organic carbon within high altitudes including Arctic and sub-Arctic regions comprising 24% of land in Northern Hemisphere. Induction of environmental changes due to increase in climatic temperature can potentially speed up the microbial breakdown of organic carbon and eventually the release of greenhouse gases to the environment (CO2 and CH4). Recent evidence reveals a gradual and prolonged greenhouse gas emission from the frozen carbon fool to the atmosphere, which will resulted the increased rate of climate change in the near future (Schuur et al., 2008; Schuur et al., 2015). The melting of permafrost results in erosion, landslides, ground subsidence, lakes desertion and leads to the alteration in flora composition at high altitudes.
Fig 3. The figure demonstrate different locations of Permafrost land across the world. (https://www.wunderground.com/resources/climate/melting_permafrost.asp)
Cold Deserts are porous soil with a large amount of salt and slit, having large amount of snowfall in winter and high rainfall up to 26cm occurring mainly in autumn (area dependent), with an average winter temperature of -2 to 4ºC and summer 21-26º. Permafrost are found in Antarctic, Atacama (Peru and Chile Coasts), Greenland, Northren (Gobi) and Westren (Takla Makan) China, Russia (Turkestan), South- western Africa (Namib), Iranian (Pakistan, Iran and Afghanistan), Great Basin (Nevada, Utah, Idaho, Western United states and Oregon) and North America (Nearctic area) (https://wildtracks.wordpress.com/world-ecosystems/desert- ecosystems/cold-desert-ecosystem/).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 23 Chapter 2 Review of Literature
Non-Polar regions
Non- polar regions are those which constitute mostly the high altitude regions like the European alpine and the Asian (Hindu Kush, Karakoram, Himalaya). Non- polar regions also include the cold seas and deep oceans.
The European Alps: The Alps are the largest mountain range of Europe that is situated in eight European Alpine countries. The total width and length of European Alps mountain range are about 200 km and 800 km, respectively, that extends from about 44-48°N and 316.5°E (Casty et al., 2005). The highest peaks of Alps Mountain are approximately 4400-4800 m with an average elevation of ∼2500 m. The mean temperature in January on the valley floors range from -5°C to 4°C to as high as 8°C in the Mediterranean mountains bordering, whereas in summer the temperatures ranges between 15°C to 24°C. The variability of European Alps’ climate is influenced by the North the enormous Eurasian land mass, the Atlantic environment and the Mediterranean Sea (Beniston and Jungo, 2002; Auer et al., 2005; Begert et al., 2005).
Hindu Kush-Karakoram-Himalayas (HKKH): Pakistan is located in South Asia that covers 796,095 km2 (307,374 sq m) area. It is the 36th biggest country in the world that harbours the world’s famous mountain ranges like Himalayas, Karakoram and Hindu Kush in its north. HKKH glaciers make biggest glaciated mass outside polar region, therefore also called ‘The Third Pole’. It comprised the highest mountains of the world including fourteen peaks all of them are ˃8000 m and ten major rivers ensue from it (http://www.icimod.org/?q=3487). Because of their great height, the HKKH exhibit heavy glaciation, and the Karakorams serve as a watershed for the basins of many rivers. HKKH glaciers provide drinking water for more than 1.4 billion people (Khan et al., 2014), provide agriculture water for 60,000 km2 area and also provide water for ~ 9 countries. Hindu Kush-Karakoram-Himalayas host more than 20,000 glaciers of which 5,000 are in the Karakoram (Inman, 2010), and more than 12,000 are in the Himalayas that cover about 60,000 km area (Kaab et al., 2012).
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Fig 4.Hindu Kush, Karakoram and Himalaya (HKKH) region, considered as the ‘Third Pole’ of the world. Adopted from (http://www.tpe.ac.cn/)
Pakistan has one of the world’s largest glaciers reserves in the HKKH ranges. The important glaciers in HKKH includes; Siachen glacier, Batura glacier, Baltoro glacier, Passu glacier, Biafo glacier, Tirich Mir glacier, and many others. Tirich Mir glacier spreads over an area from Pakistan to Afghanistan, located in Hindu Kush range and its highest peak is Tirich Mir. Batura glacier is located in Karakoram range and is the 7th largest glacier in the world and is 57 km in length. Batura Glacier is one of the biggest glaciers present outside the polar region and is located in the north of Passu 7,500 m above sea level. Passu glacier is situated in Karakoram Range; it’s the 5th longest glacier which is 60 km in length. The Passu glacier has many links with Batura glacier and with many other important glaciers of the region. Siachen is long valley glacier of 74 km, situated in the eastern Karakoram region. This is the world’s largest second glacier in non-polar regions and largest in Karakoram regions (Upadhyay, 2009). The global atmospheric changes significantly impact the peaks. Since 1850s, Himalayan regions are in state of retreat (Mayewski, and Jeschke, 1979) at the mid of 1970s in these areas the average temperature increased by 1ºC (Hasnain 2000). Trends in recession of Himalayan region glaciers are expected to continue this century, which is retreating faster than any glacier of the world (Ageta, 1992; Nakawo, 1997; Hasnain, 1999; Naito et., al, 2000; Vohra)
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Due of topographical and climatic factors, the irregular rate of recession rate and the volume change have been for Himalayan arc glaciers (Kotlia et al., 2008). According to WWF report in 2005 the glaciers of Himalaya are being retreating at rate around 10-15 meters i.e. (33-49 ft) annually. Siachen glacier has been classified in the category of actively receding glaciers worldwide (Hasnain, 2005). According to Taylor (2006), global warming scientists have recently reported that the glaciers are shrinking, so the growth of glaciers is suggested in Himalayan ranges. Researchers suggested that ice sheets are formed because the frequent winter snow is fails to melt in cooler summers (Taylor, 2006). Likewise, Raina and Sangewar (2007) reported that the rapid advancement may occur of about 700 m or the front snout of Siachen glacier from 1862 to 1909, whereas the faster retreat neutralized the rapid increase since 1929 and 1958 AD. Since then there had been very low or practically no retreat along its snout front and less expectation of any further drastic retreat, except if a devastating atmospheric alteration held (Raina and Sangewar, 2007). The Himalayan arc glaciers either advancing, retreating or in ‘stationary mode’, the known fact is the last glacial period ended almost 8,000 years ago but the after effects are not over yet. The common geologic evidence of ice ages are found at the glaciers like glacial moraines, deposition of till or tillites, carved-out landscape because of moving ice, drumlins, rock grinding and glacial erratics, valley cutting scouring and scratching etc.
Deep Sea Environment is characterized by the presence of low temperature (< 4°C) or high temperature (> 400°C in hydrothermal vents), absence of sunlight, low nutrient availability and high hydrostatic pressure (Nagano and Nagahama, 2010). Such conditions make the deep sea an extreme environment. The deep sea normally relates to oceans larger than 200 m depth. Due to coldness, darkness and stability of the deep-sea bottom, it was presumed that majority of the life forms may be present in a suspended state in this largest world’s refrigerator.
Glacier is a body of ice, formed by packing and accumulation of snow that did not melt, and moves by its own weight force. A glacier can only form in that places where all the snow which falls in the winter does not melts in summer that becomes grains of ice (firn). As snowfall is accumulating each year, the firn weight squeezes most of the air and become a solid glacier ice. There were still small air bubbles but the pore
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 26 Chapter 2 Review of Literature space was no longer connected to each other. Firn air bubbles containing small sample of earth was buried and converted to ice. These atmospheric samples are significant tools for researchers to decipher the past climates on biosphere. Glaciers flow under the force of gravity deposits and transport a huge amount of sediments. Glaciers produce a distinctive landscape different from stream landscape.
The retreat, advancement and growth of glacier depend on the balance between the subtraction and addition of glacial ice known as “glacial ice budget”. The annual budget for the amount of snow is `accumulation of glacier without melting, minus melts glacier`. And ablation is a term used for `glacier part where snow from previous year melts and ice is breaking off by melting, which results in glacier ice loss. The ablation zone is a part of glacier where ice is lost by all these processes. Diagram shows basic parts (Fig 5) of alpine vally glacier in cross-section with the length of the glacier.
Fig 5. Structure of Valley glacier, demonstrate its different parts. Adopted from (http://www.physicalgeography.net/fundamentals/10af.html)
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Glaciers are categorized into two types; Alpine glaciers are confined to mountains and Continental glaciers, which is confined to Greenland and Antarctica.
Almost all glaciers produce landforms due to eroding of rocks and deposition of sediments. Alpine regions include the valley glacier which extends down for some distance beyond the area of valley where glacier begins. Cirque glacier (Alpine glacier part) confined to amphitheatre shaped or bowl shaped depression on the side of mountain. Ice cap glaciers a type of Alpine glacier covers the mountain areas, except the high peaks that extends down various valleys. A piedmont glacier is formed where various valley glaciers combine on plain and flat area next to mountain ranges.
Alpine glacier located near the equator and also farther from equator line. Near to equator are high mountains of Africa, South America, North America, Asia and Europe. Farther from the equator includes the Alps (Europe), the Rocky Mountains (North America), and the Himalaya region Mountains (Asia). The Sierra Nevada high mountains in California having a few Alpine glaciers left from the most extensive glaciations.
Glaciers deposit a variety of sediments that vary in their sedimentary structure including sedimentary bedding and different sedimentary texture, including sorting and grain size. These variations depends on glacial sediments deposition, either directly from ice glacier, by wind that blow off the glacier, streams that carry melt water from glacier, redistribute fine sediments and lakes formed by glacier.
Main storage of glacier is in the form of glacier and also debris that locked inside the glacier which transport as moraine. The outputs are mainly the calfing and melt water of the ice. The retreat or advance form of glacier is referring to regime of glacier. (http://thebritishgeographer.weebly.com/the-physical-characteristics-of-extreme- environments.html).
Extremophiles
Since past few decades, biologists have realized the existence of life wherever there is trace amount of water and in dry areas inhabited by fungal spores (Ball and Stillinger, 1999). Microorganisms, like fungi (Eukarya), bacteria and archaea have been
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 28 Chapter 2 Review of Literature identified from harsh atmospheres with several barriers for life’s maintenance. Such organisms are categorized as extremophiles that can grow and survive in extreme environments (Cavicchioli, 2002). The term ‘extremophile’ was introduced by MacElroy (1974). The meaning of ‘extreme’ milieu is anthropogenic, whereas such environments are from the organism’s prospect are normal growth habitats (Horikoshi and Bull, 2011; Zhang et al., 2013a). The cryosphere comprising, ice caps, permafrost, ice sheets and glaciers are thought to be dynamic because of ocean circulation, continuous precipitation and hydrology (Giddings and Newman, 2015). Extreme environmental conditions include; extreme temperature, pressure, salinity, pH, nutrients, water availability or radiation. Extremophiles can be classified as polyextremophiles, acidophiles (Baker-Austin and Dopson, 2007), alkaliphiles (Gundala et al., 2013), endoliths (Pedersen, 1997), hypoliths, halophiles (DasSharma and Arora, 2001), piezophiles, hyperthermophiles (Stetter, 1996), psychrophiles and psychrotrophs (Rodrigues and Tiedje, 2008). Mostly, extremophiles belong to the Archaea domain. However, extremophiles have also been identified and characterized from the eubacterial and eukaryotic kingdoms (van-den-Burg, 2003).
Glaciers as ecosystem
Glacier surface ecosystems were once considered nutrient deprived and that they behave only as a life-entrapping medium, collecting and preserving deposited microorganisms, derived through atmospheric precipitation (Butinar et al., 2007), but now we know that they are actually the sites of biological production (Bagshaw et al., 2013). Chemoorganotrophic microbes in polar environments decompose the organic matter. Some of them include the psychrophilic/psychrotolerant microorganisms which decompose organic matter in the permaprost soil of Canada, Europe, Siberia, Alaska, Patagonia and inhabit the peat bogs (Hoovera and Pikutab, 2010)
It is now understood that areas on glaciers if accompanied with some chemical and physical conditions makes a favourable environment for the diverse communities of micro and macrobiota (Hodson et al. 2008; Anesio and Laybourn-Parry, 2012). Meltwater washed out from glacier surfaces contain bioavailable carbon, which possibly stimulate production in downstream ecosystems (Lawson et al., 2014).
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Glaciers of Antarctica include many ecological active habitats. These habitats include cryoconite holes, subglacial lake and water and glacial melt water. The dark dust deposit (cryoconite) in significant quantities accelerates the melting and cause reduction of albedo from the surface of ice. The cryoconite holes are formed when ice melts, a hole formed filled with water and dust particles sinks down into it (Anesio et al. 2010). The debris is fine-grained and aeolian transported or abrasive material resulting from medial residues or rock slides. Bagshaw et al., (2010) stated that the size of cryoconite holes is smaller in comparison to cryolakes. Cryonite holes are slightly warmer than surroundings remain for many years (Fountain et al., 2004) therefore they have a vast number of different microbes including cyanobacteria, tardigrades and rotifers (Christner et al., 2003). At shallow depths (<1 m) solar heating of the sediment melts the surrounding ice, so water is often present in these habitats, an ice cover of 3-20 cm sealed beneath, even when temperature of air is below 0°C (Gribbon, 1979; Fountain et al., 2004). Cryolakes are the largest reservoirs of liquid water in the typically frozen supraglacial environment (Fountain et al., 2004). The organic carbon and nutrient stored can affect downstream ecosystems when organic compounds and nutrients are flushed from the glacier surface by periodic high melt rates (Bagshaw et al., 2010), eventually supporting enhanced biological activity in glacier forefields, lakes and streams (Foreman et al., 2004; Hood et al., 2015). The genesis of organic carbon on glacier surfaces has gained much attention since last decade (Anesio and Laybourn-Parry, 2012). New autochthonous organic carbon accumulates when production is greater than respiration.
When the solar radiation falls on the surface of ablating glacier, the glacier becomes liquid water which is vital for biological activities and is covered by source of nitrogen and carbon source in the form of debris particles of varying degree (Franzetti et al. 2013; Anesio et al. 2009; Kennedy, 1993). When the upper surface of glacier is melts gradually during the summer season, which turns the snow line to retreat upward and further ablate the exposed ice. The zone of ablation is a rigid ice sponge enriched with minerals, organic wind borne debris and saturated with waters which support the life. However, the microorganisms growing there still have to face with low pH, High UV radiations, low Nutrients and freez-thaw cycles (Edwards et al. 2014).
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Studying the microbial abundance and spatiotemporal variability in glacier ice and its control is important to estimate the carbon stocks, microbial growth and activity and flow in glacial environments. The significance of such research is future extrapolations to predict the response of microbial community to anthropogenic influence and climate change in the cryosphere (Stibal et al., 2012b).
The mountain glaciers whose area of ablation is laminated by debris are demarcated as Debris-covered glaciers (DCGs) (Benn and Evans, 2010). These glaciers are predominantly found on the peaks of Andes (South America), Karakorum, Himalayan and Tien Shan (Asia), Alps, Alaska and New Zealand (Smiraglia et al., 2000; Diolaiuti et al., 2003; Mihalcea et al., 2008; Benn and Evans, 2010). Buried ice ablation reduces by the rate as well as magnitude of thick supraglacial debris (Østrem, 1959; Nakawo and Rana, 1999), whereas the surface of debris can be heated by solar radiation (Brock et al., 2010). The debris covering the higher portion of debris covered glaciers is dominated by rock substrate. That is mainly comprised of clasts with a diameter of few millimetres to meters, which falls from the surrounding mountains on the surface of glacier. This debris are differ from wind-blown particles which formed cryconite (Laybourn-Parry et al., 2012). Debris is then shifted to down valley on some glacier which can take centuries (Pelfini et al., 2007).
The surface of glacier is laminated by the layer of debris and thickness of the debris layer increases towards the glacier terminus. The long transportation over the surface of glacier leads the alteration of debris and weathering, additionally it’s not only inhabited by microbial community but also by plants as well as animals (Pelfini et al., 2007, 2012; Caccianiga et al., 2011; Gobbi et al., 2011). The ecological communities present over the surface of debris are possibly structured according to chronosequence along with the communities at terminus is increasing (Gobbi et al., 2011).
Challenges for the Microorganisms
Permanent exposure of microorganisms to cold has necessitated the adaptations to viscosity of aqueous environment and low temperature (D'Amico et al., 2006). These challenges have led to the adaptation with a variety of harsh condition; membrane fluidity, protein function, reduced enzyme activity, altered transport of nutrients, genetic expression, intracellular ice formation and waste products (Cavicchioli et al.,
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2000; D'Amico et al., 2006). To survive in these harsh conditions the psychrophilic microorganisms have developed various mechanisms to fight for their growth and reproduction.
These challenges include:
• Protein cold-denaturation • Reduced enzyme activity • Low temperatures • Decreased membrane fluidity • Inappropriate protein folding • Low liquid water availability • Decreased rates of transcription • Freeze thaw cycles • Low nutrient availability • Lowered solute uptake rate • Intracellular crystalline ice formation • Translation and cell division
Physical and physiological adaptations in a psychrophilic prokaryotes
As microorganisms are in thermal equilibrium with their surroundings, it is convincing to accept that psychrophiles are structurally and functionally adapted to some extent to the requirement of low temperature (Casanueva et al., 2010). Low temperature extremophiles from marine environment facing a constant low temperature, while terrestrial are in continuous stress of desiccation, UV radiation, low level of nutrients, pH and temperature (Piette et al., 2011b). However, these microbes evolved several adaptive mechanisms (Rodrigues and Tiedje, 2008) to respond to such stress conditions (Morgan-Kiss et al., 2006).
Cell membranes
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Cell membranes control cellular haemostasis via regulating membrane transport. In psychrophiles the changes in lipid composition due to reducing temperature is well reported (Chattopadhyay, 2006). Commonly, a decrease in growth temperature increases unsaturation, increase in methyl branching while decreases fatty acid chain length. Such changes reducing the shift of crystalline to the gel phase characteristics commonly known as membrane fluidity (Casanueva et al., 2010). The modulation of membrane fluidity is the significant adaptation strategy followed at low temperature (Najjar et al., 2007; Mykytczuk et al., 2010). Fatty acid composition in the membrane- lipid like saturation, structure, length of fatty acid chains are thought to be associated with the fluidity of membrane (Kim and Lee, 2015). Polyunsaturated fatty acid (PUFA) is one of the factors, that decrease the melting point of the membrane lipid and is considered an important factor to increase fluidity of membrane (Chintalapati et al., 2004; Velly et al., 2015). All such changes are essential for membrane structure, permeability, fluidity and all processes associated with membrane (Berdanier and Chow, 2000; Gill and Valivety, 1997).
Fig 6. Various physiological adaptations in psychrophilic Bacteria adopted from De Maayer et al. 2015 )
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Fig 7. Adaptation mechanisms in psychrophilic fungi to survive the harsh environment of low temperature
Compatible solutes, ice nucleation and antifreeze proteins; as a freeze protection
Osmotic tension, freezing and desiccation are common phenomenon in psychrophiles (Brewer, 1999; Pascual et al., 2002). In these organisms one of the general means of protection against such stress conditions is the compatible solutes accumulation particularly trehalose, sorbitol, glycerol, glycine, betaine and mannitol (Casanueva et al., 2010). The freezing temperature for the aqueous phase of cytoplasm reduces and the macromolecules in cytoplasm mainly the enzyme stabilized due to the presence of such extremely soluble poly-hydroxylated substances (Welsh, 2000; Borges et al., 2002).
Glycerol and mannitol are most important compatible solutes, providing cryoprotection during desiccation or freezing condition (Brown, 1978; Feofilova et
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 34 Chapter 2 Review of Literature al., 1994). The turgor pressure may also be maintained due to these substances against low external water potential (Cooke and Whipps, 1993; Grant, 2004).
Polyols (acyclic sugar alcohols) are the principal soluble carbohydrates that help in low temperature adaptation (Lewis and Smith, 1967) and in fungi mycelium may constitute up to 20% of the dry weight (Rast and Pfyffer, 1989). Polyols mainly help in coenzyme regulation, osmoregulation (Jennings, 1984) as well as protection against freeze damage by lowering the freezing point of intracellular fluid (Nash, 1966).
Trehalose is another compatible solute widely found in found in low temperature extremophiles particularly in fungi. In fungi this disaccharide commonly found in both asexual and reproductive phases of fungi (Thevelein, 1984). Trehalose plays a significant rule to increase resistance in fungi under extreme and stressful conditions (D’Amore et al., 1991; Gadd et al., 1987; Hottiger et al., 1987, Lewis et al., 1995).
For controlling the lethal effects of cytoplasmic freezing, there are also additional specific mechanism like antifreeze proteins and ice nucleating proteins (Kawahara, 2002). Ice binding and antifreeze proteins prevent the formation of ice crystal and growth of recrystallization by binding to ice (Venketesh and Dayananda, 2008). Ice binding proteins have been identified from numerous low temperature microorganism (Raymond et al., 2008: Lee et al., 2010) and antifreeze proteins have been well categorized (Venketesh and Dayananda, 2008). Ice-nucleating proteins prevent supercooling of water by inducing ice crystallization at temperature closer to melting point (Kawahara, 2002) and they might be involved in survival at colder temperatures (Wu et al., 2009). These proteins are intensely concerned with cryopreservation of cellular material by producing a depression of freezing point near 2°C (Kawahara, 2002).
Cold-shock responses
An unexpected fall of temperature prompt a “cold shock response” in diverse microorganism where large number of genes either down regulated or up regulated (Jones and Inouye, 1994). However, cold shock is particularly triggered by specific stress and fast cooling (Al-Fageeh and Smales, 2006). A family of Cold shock proteins (Csps) consist of extremely small conserved proteins that attach through
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 35 Chapter 2 Review of Literature nucleic acid binding motif or cold shock domains (CSD) to single stranded nucleic acid (Horn et al., 2007). These protein responses are also involved in certain cold RNA helicase that work along with other CSps in translation and replication (El- Sharoud and Graumann, 2007). Besides these, various other genes comprising those encoding proteins are involved in sugar transportation, metabolism, proteins associated with flagellar operon and most fascinatingly genes involved in heat shock proteins are upregulated (Phadtare and Inouye, 2004). These responses are well studied in E. coli (Thieringer et al., 1998), however numerous current genomic (Phadtare and Inouye, 2004, Methe et al., 2005) and proteomic studies (Goodchild et al., 2004, Goodchild et al., 2005) have added significantly increased the understanding of mechanism. The cold shock responses in psychrophiles vary from responses in mesophiles various genes in mesophiles associated with cold response is constitutive in psychrophiles and might be designated as cold acclimation response (D’Amico et al., 2006). A huge number of homologues proteins of CSPs have been discovered and identified as well as cold acclimation proteins.
Enzymes and Proteins
At very low temperatures, one of most apparent disadvantage is probably the low rates of catalysis. In psychrophilic microorganisms the proliferation and survival at extreme low temperature is extensively supported by cold-active enzymes (Kuddus et al., 2011; Cairns et al., 1995; Weinstein et al., 2000; Fenice et al., 1998; Fenice et al., 1997). According to Arrhenius law, at 0oC the rate of reaction should be 10-60 times less than the rate of reaction at 30oC (Casanueva et al., 2010). However, it should not appear to be an important hindrance to the physiology of microorganisms and it is obvious that enzymes from psychrophilic sources are adapted to work efficiently at low temperatures. The Catalytic efficiency is well characterized as the ratio (kcat/KM)
(Keff). When the Keff values of low adopted enzymes in comparison with mesophilic enzymes, it is well understood that for previous the decreases in KM and increase in kcat virtually similar keff values (Lonhienne et al., 2000, Marx et al., 2007). An investigation of molecular tools through which these thermodynamic changes are accomplished needs a comprehensive determination of the conformational and structural properties of psychrophilic enzymes (Marx, et al., 2007; Siddiqui and Cavicchioli, 2006). In psychrophilic enzymes, there is a constant trend: at colder
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 36 Chapter 2 Review of Literature temperature the low level of conformational stability allows higher stability rates. Cavicchioli et al., (2002) hypothesized that the complementarity between substrate and active sites of cold active enzymes are increased due to their elevated flexibility, at colder temperature and low energy cost that leads to high specific activities. Many scientists believe that polypeptide backbone of active site of psychrophilic enzyme is significantly more stable as compared to other part of proteins(Siddiqui and Cavicchioli, 2006). Some minor structural changes generally led to the either decrease or increase in thermostabilities in low temperature adapted enzymes like modifying the non- covalent interactions in protein structure (Marx, et al., 2007). Several mechanisms are employed in thermostable proteins that are not found in all enzymes (Li, et al., 2005) and such studies are based on molecular analysis of protein thermophily (Fields, 2001). Crystallographic studies have revealed the catalytic sites of low temperature adapted enzymes are comparatively more available than mesophilic and thermophilic enzymes (Aghajari , et al., 2003) . This capacity may be associated to structural flexibility and to decrease the energetic load of induced fit mechanism.
The current information regarding low temperature adaptation has been obtained from experimental data. Although, with the comparatively new era of genomics, metagenomics and proteomics, more comprehensive studies of these adaptations is probably needed which can influence future outcomes (Casanueva et al., 2010).
Microbial Diversity in cold regions
Glaciers and ice sheets are the major sources of fresh water on the Earth, which covers almost 10 % of its surface. Global warming increase the melting rates of glaciers which lead to rise in sea level and affecting freshwater availability to millions of people across the world (Meier et al., 2007). Glaciers are the most extreme environments and considered free of microbial life till now (Hodson et al., 2008; Anesio and Laybourn-Parry, 2012), though recently they are found to contain all three domains of life comprising bacteria, Archaea and eukarya (Anesio and Laybourn- Parry, 2012). Different fungal and bacterial strains have been isolated from prehistoric samples of ice in Greenland, Antarctica and Tibet the ancient reaching 750,000 years (Liu et al., 2009a: Miteva et al., 2009: Zhang et al., 2009b). The dominant microbial community characterized from glacier communities belonging to proteobacteria, Actinobacteria, Firmicutes Cytophaga-Flavobacterium-Bacteroides (CFB),
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 37 Chapter 2 Review of Literature psychrophilic fungi and yeast as some bacterial and plant viruses and Archaea (Simon et al., 2009b).
Bacterial Diversity
Snow sheets of Tibetan plateau glacier revealed high diversity of 15 bacterial genera from the total of 82 i.e. common for all the glaciers (Liu et al., 2009b). The culture dependent and metagenomic studies revealed the bacterial diversity (Miteva et al., 2009) and great abundance in mountainous and Arctic snow as compared to Antarctica (Liu et al., 2006a). Diverse psychrophilic and psychrotolerant bacterial and eukaryotes have been detected (Amato et al., 2007a; Segawa et al., 2005) with seasonal fluctuation (Larose et al., 2010; Liu et al., 2006b). The microbial community in the dry regions of polar snow revealed to rule the biogeochemical cycling at such low temperatures (Amoroso et al., 2010) this has been supported strongly by bacterial and fungal diversity with snow cover dynamics in soils of alpine tundra (Zinger et al., 2009). In Polar Regions, the primary producer of organic matter is mostly algae including snow algae, photosynthetic cyanobacteria, and diatoms. Homoacetogenic bacteria and methanogenic archaea that can grow on CO2, CO2/CO and Hydrogen are a chemolithoautotropic producer of organic matter (Simankova et al. 2000).
Studies regarding diversity of microbial communities in Alpine and Polar cryconite holes were detected algae and cyanobacteria, yeasts, heterotrophic bacteria and viruses (Anesio et al., 2007; Vincent, 2007; Zhakia et al., 2008). Several novel cold adapted bacteria was detected including Sphingomonas glacialis and cryconitis, Pedobacter, and yeast Rhodotorula glacialis (Margesin and Fell, 2008; Zhang et al., 2010b). Members of cyanobacteria have also been reported to dominate the High Arctic ice, streams and lakes communities (Bonilla et al., 2005; Jungblut et al., 2010).
Liebner et al. (2009) reported the first data on aerobic methanotropic bacterial (MOB) diversity from soil of Arctic permafrost, Lena Delta, Siberia. 16S rRNA, denaturing gradient gel electrophoresis (DGGE) and pmoA gene analysis data of methanotrophic diversity of bacteria shows that the genera found was closely related to Methylosarcina and Methylobactor, both type I MOB. The 8 operational taxonomic units out of 13 were found to belong to cluster of Methylobacter tundripaludum and Methylobacter psychrophilus isolated from Arctic.
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Annually, almost 20% of natural methane emission to environment is contributed by Tundra and Northern wetlands (Cao et al., 1996; Christensen et al., 1996; Fung et al., 1991).
MOB communities are the major sink of methane to the environments. Cold environments like Eastern Antarctica, deep ground water of Fennoscandia and northern peat lands are abundant in methanotrophic communities of bacteria (Trotsenko et al., 2005). The report illustrated the prevalence of biologically active MOB in ancient deep Siberian permafrost of about 100,000 years (Khmelenina et al., 2002). The rate of methane oxidation in response to temperature was observed and the study determined MOB are effectively adapted to temperature regime of Lena Delta permafrost soil (Liebner et al., 2007).
Permafrost soil is an extreme niche for microbial community due to subzero temperatures, freeze thaw stress, gamma radiation, an extensive array of antibiotics (Petrova et al., 2009). The microorganisms have been studied employing both culture dependent and independent methods (Steven et al., 2006, 2009) and bacterial communities comprising aerobic and anaerobes (acetoclastic and hydrogenotrophic methanogens, denitrifies, sulfate reducers and Fe (III) reducers (Gilichinsky et al., 2008) have been reported. In different permafrost regions, the viable fraction ranges from (0.1 to 1%) that might be assigned to almost 70 genera dominated by gram positive (Actinobacteria and Firmicutes) while among Gram negative bacteria, Gamma-proteobacteria (esp. Xanthomonadaceae) have been dominated while the CFB phylum have been revealed in low extent (Gilichinsky et al., 2008; Steven et al., 2009). Molecular studies conducted in Antarctica permafrost and Siberian regions showed the dominant Gram positive bacteria (i.e. up to 57 and 45% respectively) and Gamma proteobacteria (Gilichinsky et al., 2008; Vishnivetskaya et al., 2006). There is scarcity of information regarding alpine permafrost, although the abundance of Gram positive bacteria (Arthrobacter) have been revealed from permafrost in China (Bai et al., 2006), while the culture independent analysis exhibited the dominant classes of proteobacteria (Yang et al., 2008). Microbiological analysis of permafrost at the Tibet plateau also showed the presence of Gram positive bacteria more as compared to Gram negative bacteria (9:1) (Zhang et al., 2007). Currently elevated abundance of Exiguobacterium and Psychrobacter have been noticed in Antarctic and
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Siberian permafrost (Rodrigues et al., 2009). Microbial diversity in Finnish Lapland (Arctic) soil revealed the abundance of Gram negative bacteria α- β- and γ- proteobacteria and CFB phylum (Männistö and Häggblom, 2006; Männistö et al., 2007). Arctic tundra soil is represented by 60% of pseudomonads, while 30% belong to unclassified bacteria that might play a substantial ecological role (Gilichinsky et al., 2008). Arctic Lakes have been studied for microbial diversity and diverse bacterial species have been identified (Adams et al., 2010). However, the alpine lakes have been observed to be dominated by α- β-proteobacteria and CFB (Alfreider et al., 1996). The abundance of actinobacteria and β-proteobacteria have also been reported from high mountain lakes (Hörtnagl et al., 2010; Sommaruga and Casamayor, 2009), as well as in different strata like surface layer and underlying water of different alpine lakes, followed by Actinobacteria (Hörtnagl et al., 2010). Li et al. (2012) reported a study based on one 16S rRNA gene report the presence of Actinobacteria in Wuli, QTP cold springs. However, the actinobacterial diversity might be due to employing the universal primers for bacteria (Cottrell and Kirchman, 2000; Jiang et al., 2010a).
Diversity on sulphate reducing bacteria in Antarctica (Lake Fryxell) reported six major phylogenetic groups including Desulfobacterium, Desulfovibrio, Desulfobacter, Desulfotomaculum, Desulfosarcina and Desulfobulbus (Karr et al., 2006). In Mount Everest lakes, the Bacteroidetes are dominant among bacteria (Sommaruga and Casamayor, 2009).
The ancient permafrost sediments are reported to be dominated by acetoclastic methanogens and denitrifiers (Rivkina et al., 1998) and methanotrophic bacteria (Methylomicrobium, Methylobacter) that oxidise methane at subzero temperatures (Trotsenko and Khmelenina, 2005). Psychrophilic methanotrophs have also been reported from Arctic soil (Trotsenko and Khmelenina, 2005; Wartiainen et al., 2003), Proteobacteria with 73% abundance have also been revealed via molecular methods from Himalayan mountains. Viable bacteria comprising , similar and equal amount of gram positive (48%) and 51% gram negative bacteria. All these isolates were shown to produce various hydrolytic enzymes (Gangwar et al., 2009). The culture dependent and metagenomic analysis have shown an altered picture (Babalola et al., 2009; Smith et al., 2006). For instance, the soils of Dry valley, Antarctica, were dominated by
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actinobacteria, though majority of culture dependent analysis were dominated by (>80%) Streptomyces (Babalola et al., 2009).
Bak in 1988, isolated “Acetobacterium carbinolicum HP4” and reported the first psychrophilic homoacetogenic bacteria (Conrad et al., 1989), whereas Eichler and Schink (1984) previously described it. Later Kotsyurbenko et al. (1995) reported three homoacetogenic bacteria A. paludosum, A. bakii and A. fimetarium. Other psychrotolerant homoacetogen bacteria isolated from tundra wetland soil is A. tundra (Simankova et al., 2000). Paarup et al. (2005) isolated new subspecies A. carbinolicum SyrA5 strain from sediments of brackish fjord. The strain show psychrotolerant nature and was has the ability to propagate lithotrophically on the CO
and CO2+H2. Sattley and Madigan, (2007) isolated acetogenic bacterial strains (LS1 and LS2) from Fryxell Lake, McMurdo Dry Valley, Antarctica. The homo-acetogenic
bacteria compete for the substrates like H2 and other organic inorganic substances with sulphate reducing bacteria and methanogens in Polar habitats. The significant activity of cold adapted homoacetogenic bacteria was observed as compared to sulfate-reducing bacteria and methanogens (Simankova et al., 2000; Kotsyrbenko et al., 2001; Nozhevnikova et al., 2001). Gaidos et al. (2008) isolated genus Acetobacterium “str. A7AC-96m” and “str. A7AC-DS7” true psychrophilic homo- acetogenic bacteria from sediments and water samples of Lake Untersee Antarctica,
which showed propagation at 14°C, on CO2+H2.
The Antarctic glaciers contain both saline and fresh water glaciers and microbiological surveys have shown abundant and diverse microbial population including 30 novel genera and species as a true psychrophiles (Sawstrom et al., 2008; Stingl et al., 2008). Mulicki and Priscu (2007) determined the bacterial diversity from iron-rich ancient sub-glacial marine brine in Antarctica (Taylor Glacier). The isolates from polar ecosystem on the basis 16S rRNA gene, clone library of phylotypes showed 99% similarity with Thiomicrospira arctica, i.e. psychrophilic totrophic psychrophilic sulfur oxidizer. Other division isolated was Bacteroidetes and the classes of γ, β, δ proteobacteria. The glacier hydrology, lithology and preglacial ecosystem possibily rules the phylogenetic and metabolic structure of these subglacial ecosystem, the propagation of microorganisms is sustained by using energy from reduced compounds of iron and sulfur. Perreault et al. (2007) reported that sulfur
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compounds are major chemical energy source for perennially cold saline spring’s ecosystem at Colour Peak and Gypsum Hill on Axel Heiberg Island in the Canadian Arctic.
The Deep Sea and sea ice microbial population have several adaptation strategies to survive in such environment (Deming, 2009b) and consist of piezophilic, psychrophilic and psychropiezophilic microorganisms (Nogi, 2008). The deep sea inhabitants are distinct from polar region microorganisms (Lauro et al., 2007), majority i.e. 98% are primary producers (Whitman et al., 1998). The deep sea have an enormous phylogenetic diversity and the microbial communities (Sogin et al., 2006), the most dominant being member of γ- proteobacteria including novel genera of Photobacterium, Colwellia, Psychromonas, Moritella, Shewanella and Marinomonas (Dang et al., 2009; Nogi, 2008).
Various fungal and bacterial communities have been isolated from the water of tropospheric cloud ranging from 103-105 CFU/mL comprising novel species like Bacillus stratosphericus and Deinococcus aethius) (Ahern et al., 2007; Amato et al., 2007b). Cloud is most encouraging habitat for microbial growth as cloud droplets remain liquid at subzero temperatures (Sattler et al., 2001). The microbial community of cloud play a vital part in condensation of clouds and as ice-forming nuclei, impacting the formation of cloud therefore has gained chief scientific interest.
Archaeal diversity
Archaea is the 3rd domain of life, initially it was thought that archaea inhabited the extreme level of temperature, pH and salinity and present universally (Fierer et al., 2007). In low temperature environment, the archaea were first identified in Antarctic environment by Franzmann et al. (1988), and till now archaeal species have been recognized in Antarctic marine ecosystem, marine water and ice covered lakes (DeLong et al., 1994; Cowie et al., 2011). Earlier studies revealed the high prevalence of archaea accounting for 34% of all prokaryotes in Antarctic water (DeLong et al., 1994; Thomas and Dieckmann, 2002). The archaeal diversity in soils remain unexplored as compared to bacteria, particularly in plant free environments (Zhang et al., 2009; Lynch et al. 2012). Crenarchaeota and Euryarchaeota inhabit various cold environments. They are present in abundance among archaeal communities in high
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 42 Chapter 2 Review of Literature stratified arctic lakes (Galand et al., 2008a; Pouliot et al., 2009). Euryarchaeota dominate oxygen rich layer but also exists in anaerobic region (Pouliot et al., 2009). Arctic riverine and coastal water Euryarchaeota are present in association with particle rich water, while Crenarchaeota mainly exist as free living dwellers in marine water (Galand et al., 2008a). In cold oceans, 40% of microbial biomass is composed of Crenarchaeota (DeLong et al., 1994), they may dominate huge subsurface of cold ocean (Biddle et al. 2006). Additionally, Crenarchaeota are determined in molecular surveys (Brochier-Armanet et al., 2008) of soil microbial population containing high altitude and cold soils (Zhang et al., 2009: Oline et al., 2006). An archaeal DNA from Dry Valley soils belonging to Thaumarchaeota groups have been reported (Bates et al., 2011). Communities of archaea in Arctic permafrost environments have been described, although their function and diversity require further investigation (Steven et al., 2008; Yergeau et al., 2010). The Antarctic frozen lakes contain both fresh as well as extremely saline environments (salinity > 7X sea water). The ice sheet might reach 3 to 6 meters and water columns of such lakes having diverse and abundant archaea (Mosier et al., 2007: Laybourn-Parry and Pearce, 2007; Sawstrom et al., 2008: Stingl et al., 2008).
In deep sea, majority of archaea are ammonia oxidizers particularly the Crenarchaeota (Francis et al., 2005; Nakagawa et al., 2007). It oxidizes ammonia at ~10°C and it is supposed that such archaea is accountable for the process of nitrification in oceans (Nakagawa et al., 2007; Kalanetra et al., 2009). Methanogenic archaea also inhibit the cold habitat are associated with Euryarchaeota (Hoj et al., 2005). Such archaea are mostly studied Mount Everest soils at (4000-6500 m) altitude (Zhang et al., 2009). Though the diversity and activity of methanogen in permafrost soils is yet to be studied (Ganzert et al., 2007). Methanogenium frigidum, a Psychrotolerant methanogenic archaea, isolated from the Ace Lake, Vestfold Hills, Antarctica anaerobic water sample (Franzmann et al. 1997). Best growth observed on
H2+CO2, tolerated salinity up to 10%, and propagate optimally at 15°C but not in range of 18-20°C confirmed its lithoautothrophic nature. Other species Methanolobus psychrophilus isolated from Zoige wetland also showed optimum growth temperature of 15°C (Zhang et al., 2008), and have a immense role in methanogenesis. Similarly, Methanosarcina lacustris, reported from anaerobic sediments of lake (Switzerland)
(Simankova et al., 2004), produce methane by utilizing H2/CO2, mono-, di-,
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 43 Chapter 2 Review of Literature trimethylamine and methanol and grew optimally at 25°C. Methanogenium marinum AK-1 was studied from marine sediments of Skan Bay, Alaska show growth at 5-
25°C temperature (Chong et al., 2002). The isolate grow on formate+ CO2 or
H2+CO2, pH (6.0-6.6) and salinity (0.25-1.25M). Likewise, Nozhevnikova et al., (2003) reported psychrophilic methanogenic communities growing optimally at 4 to 5°C from sediments of deep lakes. Beside these, Karr et al., (2006) reported methanogenic archaea isolated from permanently frozen Lake Fryxell (Antarctica). The phylogenetic analysis showed homology with Methanosarcina species and Methanoculleus. Members of Euryarchaeota including Methanosaetaceae, Methanosarcinaceae, and Methanomicrobiaceae and to smaller extent of Crenarchaeota have been identified in alpine and Siberian permafrost (Yang et al., 2008: Ganzert et al., 2007: Rivkina et al., 2007). Archaea is becoming a major contributor to cold environments. The real ratio of archaeal consortia tends to be geologically and seasonally dynamic. Differences in the described archaeal population might be due to changes in site of sampling (Wells and Deming, 2003). It has been reported that the archaeal population in oceanic samples fluctuates, showing an absence of Euryarchaeota (group II marine) and an abundance of Crenarchaeota (group I marine). In non-marine environment archaeal population are also progressively recognized. Archaea have been revealed to be exist with vast diversity in a number of cold lakes (Koch et al., 2006; Auguet and Casamayor, 2008; Lliros et al., 2008). Euryarchaeota (Group II marine) have also been isolated from gastrointestinal tracts of North Sea fish (Van Der Maarel et al., 1998). In comparison to this, a single archaeal clone has been recognized from an arctic ice cover microbial mat through 16S rRNA gene clone library (Junge et al., 2004; Bottos et al., 2008). Facts documenting the presence of archaea in huge numbers in low temperature habitats tend to vary, with spatial and temporal variation. As techniques for archaeal identification progress and become more common, it is possible that the actual abundances of such organism in low temperature environments will be proven.
Fungal diversity
The extreme coldest environments is dominated by microorganisms like bacteria, protists and fungi as well as microscopic animals like rotifers, springtails, mites nematodes, tardigrades (Hogg et al., 2006; Arenz and Blanchette, 2011). The Arctic
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 44 Chapter 2 Review of Literature and Antarctica have been mainly investigated for psychrophiles belonging to bacteria and archaea, but less for fungi (Gunde-Cimerman et al., 2003). Some definite fungal species are considered environmentally most prosperous eukaryotic extremophiles. Various kind of fungi have been reported from extreme environments like highly saline water (Gunde-Cimerman et al., 2000), from arid rocks (Steflinger, 1998), ocean pits (LopezGarcia et al., 2001), dry and hot deserts (Abdel-Hafez et al., 1989), very low pH, (Lopez-Archilla, 2001) as well as in coldest polar environments (Tojo and Newsham, 2012).
Antarctica is very widely investigated for the presence of all the kind of Fungi including Basidiomycetes, Ascomycetes, Chytidiomycota, Zygomycota, Cryptococcus (Arenz et al., 2006; Malosso et al., 2006; Fell et al., 2006). The Antarctic fungal diversity has been studied from the various parts of the Antarctic regions (Onofri et al., 2006; Onofri et al., 2005a; Bridge and Worland, 2004). This biodiversity studies have been carried from the floristic (Onofri et al., 1994), Eco- physiologically (Tosi et al., 2002; Onofri et al., 2000), molecular level (Vishniac and Onofri, 2002) and with phylogenetically (Selbmann et al., 2005).
Most of the mycological studies that carried out in Antarctica, determined different species that exist in lakes (Goncalves et al., 2012), historic woodlands, soil, (Arenz et al., 2006; Fell et al., 2006) as well as live on the macroalgae (Loque et al., 2010) and also on the plants (Rosa et al., 2009; Uspon et al., 2009). A single unculturable taxon of fungus has been discovered employing metagenomic sequencing of antarctic marine plankton (Lopez-Garcia et al., 2001). In Antarctica, approximately, 0.6% of fungi are composed of water molds and 99.4% of other including filamentous fungi and yeasts (Onofri et al., 2005b; 2006). Paleo-biological and paleo-ecological studies have shown that the Antarctic fossil fungal biota present in degraded organic material that signified as key decomposers (White and Taylor, 1988; Stubblefield and Taylor, 1983).
In Antarctica, various Historic HUTS sites are present and they are extensively investigated for the fungal diversity. Numerous filamentous fungi are also reported (Duncan et al., 2006) from Terra Nova Hut and Nimrod Hut Cape Royds (Blanchette et al., 2010). Different species belonging to Thielavia has also been identified from Ross Sea Region (Blanchette et al., 2010) and King George Island (Stchigel et al.,
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2001) from lichen. Geomyces pannorum species have widely been documented from many locations of Antarctica (Arenz et al., 2011; Loque et al., 2010; Rosa et al., 2010; Tosi et al., 2002). Cadophora and some others fungal species have isolated from Antarctic mosses and liverworts (Tosi et al., 2002; Bradner et al., 2000) and oil polluted sites in the Terra Nova Hut and McMurdo Sound region (Arenz et al., 2006). Several other fungi such as Basidiomycetes, Ascomycetes, Zygomycetes, Cryptococcus, Cladosporium cladosporioides, Rhodotorula, Hormonema, Exophiala, Hormonema dematioides, species of Geomyces and Penicillium were also obtained from the pieces and structural wood in the Terra Nova Hut sites and other Ross Sea Region (Held et al., 2005). Diverse fungal species have also been reported from the marine sediments (Singh et al., 2011; Nagano et al., 2010; Le Calvez et al., 2009). Mycological investigations in Victoria Land have been carried out by many authors, which reported fungi that present in the nearby areas of this Antarctic region (Broady et al., 1987). The black meristematic fungi have been studied in Northern and Southern Victoria Land (Gunde-Cimerman et al., 2005; Selbmann et al., 2005). Antarctic crypto- endolithic black fungi have potential to survive in extreme condition but their mechanism of living and tolerance to harsh conditions were still unfamiliar (Onofri et al., 2004). The Cryptococcus genus has been reported from McMurdo Dry Valley (Bridge et al., 2009; Vishniac and Kurtzman, 1992). Pythium belongs to Oomycete genera and they are well known fungal pathogens. Pythium species have been studied by various researchers and have been reported in vascular plants from vegetated areas of Sub-antarctic islands such as Kerguelen, Macquarie and South Georgia (Uspon et al., 2009; Bridge et al., 2008; Bridge et al., 2007; Fell et al., 2006; Lawley et al., 2004; Hughes and Lawley 2003).
The endophytic fungi belonging to Ascomycetes and Basidiomycetes (Huang et al., 2001) have been explored in various plants (Rosa et al., 2009; Gianoli et al., 2004) which help the plant to face biotic and abiotic stresses (Rodriguez et al., 2010). The filamentous Penicillium spp. has been studied in the three different polythermal glaciers of Arctic region (Svalbard, Norway) (Sonjak et al., 2006).
In arctic environment the Mycorrhizal fungal communities are common. They are important for growth and survival of their host plants because they provide water and limiting nutrients in exchange for photosynthetic carbon (Smith and Read, 2002).
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Some of the ectomycorrhizal fungal communities have been investigated in the Arctic-Alpine ecosystems that were associated with Dryas octopetala or associated with chronosequences (Cripps and Eddington, 2005; Harrington and Mitchell, 2002). Some of the Basidiomycetes were found as partners of ericoid mycorrhizas e.g. Sebacina spp. in roots of Gaultheria shallon, northern Vancouver Island, British Columbia (Selosse et al., 2007; Weix et al., 2004). The arbuscular mycorrhizal (AM) fungal communities have also been found in Arctic ecosystems (Allen et al., 2006). Ectomycorrhizal fungi (EMF) are widely distributed in arctic and alpine habitats on all continents. Some widely distributed EMF genera include Inocybe, Cortinarius, Hebeloma, Russula, Thelephora, Tomentella, Cenococcum, and Laccaria (Deslippe et al., 2011a). Several types of molecular methods have been used to study the biodiversity of EMF in Arctic habitat (Geml et al., 2012; Deslippe et al., 2011b).
From the Svalbard, the Russian Arctic and Iceland, there are about 2600 morphologically described macrofungi reported, with at least 150 ectomycorrhizal species (Hallgrimsson and Eyjolfsdottir, 2004; Borgen et al., 2006). The Arctic and Alpine plants that host black septate endophytes have also been reported but their special effects on hosted plants or phylogenetic histories have not fully explored (Schadt et al., 2001; Piercey et al., 2004). Arctic environment also harbour some fungal pathogens that belong to obligate Basidiomycete plant pathogens (Scholler et al., 2003; Tojo and Nishitani, 2005).
Various reports from deep sea including Singh et al., (2010) and Damare and Raghukumar (2008) documented filamentous fungi from Central Indian Basin sediments. Aspergillus sydowii and many other fungi have been isolated at 5°C from deep-sea sediment core of Indian Ocean (Damare et al., 2006a). Majority of the fungal species of deep-sea habitats are of psychrotrophic nature, but in some cases, deep-sea fungal isolates also grew well at 30°C comparatively 5°C (Singh et al., 2010).
Diversity of psychrophilic and psychrotrophic fungi has been investigated in the European Alps. Eight unknown fungal strains (could belong to ascomycete genus Phialosimplex) were isolated from water samples of the salt mine in Berchtesgaden (Bavaria Alps, Germany) (Greiner et al., 2014). The psychrophilic yeasts have been documented in ice, subglacial sediments, melted water from two different Italian
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 47 Chapter 2 Review of Literature alpines glaciers. Margesin et al., (2007) have described three new psychrophilic species belonging to the genus Rhodotorula from soil collected from an alpine railway area, from mud in the thawing zone of a glacier foot and from glacier cryoconite, respectively. Buzzini et al., (2005) reported the presence of viable yeast cells in melted waters running off from ice glaciers in Italian Alps. Two novel species of the genus Acaulospora has also been reported from numerous mountains in Southern Chile and Switzerland (Oehl, et al., 2011) and Swiss alpine (Oehl et al., 2006). Several fungal species have been reported from fine granite sediments of Damma glacier in the central Swiss Alps (Brunner et al., 2011). The endophytic mycobiota have been studied in outermost sapwood of Scots pine trees in the western Italian Alps (Giordano et al., 2009). Tretiach et al., (2008) have reported lichenised and lichenicolous fungi from several localities of the Apuan Alps and the Tuscan-Emilian Apennine (central Italy).
There is scarcity of data regarding bacterial as well as fungal diversity from HKKH glacier. While there is not a single report published regarding these glaciers located in Pakistan. However, only a few studies carried out by Sati et al., (2014 a, b, 2009), and Sati and Belwal (2005) have identified low temperature fungi from Kumaun Himalaya, India. Similarly, Anupama et al., (2011) reported the psychrophilic and halotolerant Thelebolus microsporus from the Pangong Lake Himalayan region and Singh and Palni (2011) have collected 35 species belonging to 7 families of rust fungi from herbaceous and shrubby hosts in central Himalayan region. Moreover, 25 psychrophilic yeasts have been isolated from the Roopkund Lake soil of Himalayas, India (Shivaji et al., 2008). Three anti-fungal Trichodermal species, T. harzianum, T. konengii and T. viride have isolated from forest sites of Indian Himalayan Region (Ghildiyal and Pandey, 2008). Wang et al., (2014) studied glaciers on the Qinghai- Tibet Plateau for the presence cold-adapted fungi and identified 150 species dominated by Phoma sclerotioides and Pseudogymnoascus pannorum. Hirose et al., (2009) have isolated 24 fungal species from three different altitudes on the Tibetan Plateau and assessed the environmental variables influencing them.
Snow Algae
The species of various microalgae are well adapted to low temperature and thrive in snow melt thus colour the snow yellow, pink, red or green (Hoham, 1975). The
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 48 Chapter 2 Review of Literature dominated specie of snow algae is Chlamydomonas nivalis others including; species of following genera Chloromonas, Raphidonema and Ankistrodesmis. Green alga Chlamydomonas nivalis, actively propagates when snow melts, having bright red spores and their large number presence shows a red “watermelon snow”. Beside these, Chlamydomonas nivalis and UV resistant species which resist UV by the production of antioxidants, flavonoids and astaxanthin fatty acids accumulation (Duval et al., 1999; Hoham and Ling, 2000).
Applications of psychrophiles
The significance of studying psychrophilic microorganisms makes them potent candidates for numerous diverse applications, In industry, food, environment as well as pharmaceuticals and cosmetics.
Psychrotolerant microorganisms maintaining activity at low temperature can be used for bioremediation of cold hydrocarbon polluted soil of Antarctica as well as other Polar environments (Bej et al. 2000; Paniker et al. 2002, 2006). Various isolates of psychrophilic or psychrotolerant bacteria are reported from Antarctic oil-polluted soil having ability to degrade oil (Aislabie et al., 2000; Bej et al., 2000). Aislabie et al., (2004, 2006) also reported the potential of cold-adapted bacteria for aromatic compounds degradation.
Exploration of psychrophilic microorganisms in polar environments is significant to understand global warming, environmental change and Astrobiology. Astrobiology is the study of extreme environments on biosphere regarding the limits and composition of microbial community. Most significant target of astrobiology is frozen world of earth where water present in solid or liquid form. These include asteroids having water; craters, permafrost, Europa, Ganymede, Polar Ice Caps of Mars, Callisto (the Jupiter’s icy moons), Enceladus or Titan (Saturn) and comets. The polar and other cold areas of biosphere offer the perfect analogues for such systems. Similarly, the distribution and nature extremophilic microorganisms that flourish in ecosystems of Polar Regions can provide significant data for the advancement of operational techniques and instruments required to recognise the signatures of extinict and extant life somewhere in Cosmos (Hoovera and Pikutab, 2010). Investigation of methanogens in Polar Regions also plays a part to accelerate the field of Astrobiology.
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Methanogenis Archaea isolated from Siberian permafrost showed survival in simulated Martian thermal conditions Morozova et al., (2007).
Montes-Hugo et al. (2009) reported biological productivity of ocean zone and west Antarctic Peninsula through surface chlorophyll measurements and observed that there was 12% decline. This decline leads to environmental changes and large scale will modify the microbial composition in Polar habitats, possibly either through gene transfer or other such processes that led to the substitution of true psychrophile by psychrotolerant species (Hoovera and Pikutab, 2010).
The biotechnological potential of psychrophilic or psychrotolerant enzyme can be estimated by their efficient activity from low to range of temperature, extreme thermoliablity at high temperatures and active in the presence of organic solvents (Cavicchioli et al., 2002; Siddiqui and Cavicchioli, 2006; Gerday et al., 2000; Margesin and Feller, 2010; Marx et al., 2007). Enzymes from psychrophiles can contribute in economic progress as being more productive than thermophilic or mesophilic, thereby used as energy savings. As a result, the enzymes of psychrophilic microorganisms have vast applications in the industries of molecular biology, baking and household detergents. These enzymes could use in heat sensitive substrate processes and also minimize the undesirable chemical reactions (Jeon et al., 2009a). Most importantly used in feed and food industries to circumvent the spoilage and increase nutritional value of product (Gerday et al., 2000; Russell, 1998; Cavicchioli et al., 2002; Tutino et al., 2009).
Psychrophilic enzymes rules the progress of molecular biosciences, the reactions needs the removal of enzymes very specifically. As cold-adapted enzymes are heat labile and are easily inactivates at elevated temperature that does not cause double‐stranded DNA to melt in molecular reactions.
Most important cold active enzyme is DNA modifying alkaline phosphatase enzyme, used for removel of phosphates at 5` termini of DNA and dephosphorylating DNA vectors before cloning for preventing re‐circularization (self‐ligation). Alkaline phosphatases available in market are from E. coli and calf intestine with some drawbacks including heat resistance and need inorganic extraction whereas the alkaline phosphatase from Arctic shrimp can be inactivated at 65ºC. Moreover this
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 50 Chapter 2 Review of Literature enzyme isolated Antarctic bacteria require comparatively much less temperature for inactivation i.e. 50-55ºC, short time of heating (Kobori et al., 1984; Rina et al., 2000). Various other psychrophilic enzymes like esterases (Heath, et al., 2009; Jeon, et al., 2009a), lipases (Jeon, et al., 2009b; Cieoelin˜ ski, et al., 2009) and cellulases (Berlemont, et al., 2009), has also been identified via functional metagenomics library screening of Antarctica. Cold-adapted cellulase isolated from earthworm are found to contain both β‐1,4‐glucosidase and endo‐β‐1,4‐D‐glucanase which has the ability to directly convert cellulase to glucose (Ueda et al., 2010). Usually the production of ethanol by cellulase is carried out at high temperature and requires high costs. Cold- adapted cellulase complex from yeasts produce ethanol from cellulase at the low temperature (Ueda et al., 2010). This is a significant step regarding biofuels production from cellulase at low temperatures.
Cold‐loving enzymes are characterized by inherent flexibility and have potential use in non‐aqueous or mixed aqueous‐organic solvents for the synthesis of organic that results in stabilization under low water activity in the presence of organic solvents (Sellek and Chaudhuri, 1999; Apenten, 1999; Gerday et al., 2000). The high amplitude of stereo specificity is being exhibited during the synthesis of fine chemical by psychrophilic lipases and esterases (Joseph et al., 2008; Aurilia et al., 2008; Tutino et al., 2009). Chiral drugs are more potent than racemic mixture, so the stereo specificity of psychrophilic enzymes can be utilized for the production of chiral drugs (Jeon et al., 2009a).
Polyunsaturated fatty acids of cold-adapted Archaea are of great significance and have range of applications as dietary supplements in human mariculture and neutraceuticals (Nichols et al., 1999). PUFAs like decosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) are used in human retina and brain as component of membrane acyl-lipids and also function as regulatory compounds precursors for thromboxanes, prostaglandins and leukotriens (Nichols et al., 1999 and Caldar and Grimble 2002). PUFA is also an essential dietary ingredient for larval fish and aquaculture species (Nichols et al., 1999; Rothschild and Mancinelli, 2001). Fish oil is the major source of PUFAs nowadays and inevitably numbers of difficulties are associated at large scale production due to decline of fish and unpleasant odor. Psychrophilic archaea is an interesting alternative and promising source of PUFA that
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 51 Chapter 2 Review of Literature is currently under investigation as they assure rapid production rate and contain significant proportions of PUFA (Yang et al., 2007).
Antifreeze proteins (AFPs) have dynamic applications in agriculture cryosurgery, aquaculture cryoprotection and food storage (Yang et al., 2007). Introduction of AFPs in fish make them freeze-resistant that results in substantial economic benefits in aquaculture. Crops tissue and cell damages can also be protected with AFPs by combating ice formation. Likewise, low AFPs concentrations helps cryoprotection of tissues, organs and cells through decreasing temperature of thawing and reduce the potential damage and costs associated with heat (Carpenter and Hansen, 1992; Arav et al., 1993; Fletcher et al., 1999). AFPs are also used in destroying tumor cells (Fletcher et al., 1999) and food storage (Griffith and Ewart, 1995; Russell, 1998).
Sarkar et al. (2013) isolated psychrotolerant bacteria Pseudomonas chlororaphis from soil samples of Kashmir (India) that are able to produce excess L-tryptophan and accumulate it extracellularly. Findings in this study indicate the possibility that the isolated psychrophilic strain may be used for industrial production of L-tryptophan.
Selection pressure in hydrocarbon-polluted soils may leads to increased antimicrobials production and also induces resistance to antibiotics. Petroleum polluted bacterial strains antimicrobials production and resistance reveals that penicillin resistance was 49% rifampicin and chlorophenicol 28%, and tetracycline 9%. Antimicrobial production ability against indicator bacterial and yeast strains showed that almost two-third of the isolates inhibit at least on indicator strain. Most versatile bacteria regarding antimicrobial resistance and productions belongs Gammaproteobacteria and Actinobacteria. Characterization of compounds shows that the compounds was proteinaceous nature (Ferrara et al., 2014).
Psychrophilic Streptomyces sp. reported from Antarctica has the ability to produce nigercin, azalomycin B and non-polyenic macrolides antibiotics inhibiting the growth of different bacteria and fungi (Gesheva, 2009).
Progress in psychrophiles genomics, metagenomics, and proteomics
So far, more than 30 psychrophilic microorganisms have been completely sequenced. A considerable amount of genomic sequence information has been
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 52 Chapter 2 Review of Literature
obtained by shotgun sequencing of whole genome from deep sea sample (Konstantinidis, et al., 2009), Antarctica metagenomic fosmid sequencing (Grzymski, et al., 2006; Be´ja`, et al., 2002; Lo´pez-Garcı´a, et al., 2004; Martin-Cuadrado, et al., 2008) and pyrosequencing of glacial ice (Simon, et al., 2009a). Numerous psychrophilic enzymes like cellulases (Berlemont, et al., 2009), esterases (Heath, et al., 2009; Jeon, et al., 2009a) and lipases (Jeon, et al., 2009b; Cieoelin˜ ski, et al., 2009) has also been identified via functional metagenomic libraries for Antarctic samples. One of the key emphasis of psychrophiles genome and metagenomic sequencing is the characterization of genes and sequences.
Adaptations to psychrophily from metagenomic data
A range of adaptations are showed by microbes in psychrophilic conditions, the study employing comparative metagenomic method of Antarctic marine bacteria revealed amino acid alteration respective to cold temperature in 6 genome fragment of about 40 Kb (Grzymski, et al., 2006). The changes that increase the conformational entropy like reduction of hydrophobic and proline contents, substantial reduction in numbers of glutamic acid, arginine and aspartic acid, reduced salt bridge formation has been observed in predicted proteins involved in transcription, DNA metabolism and amino acid biosynthesis. These changes could be interpreted in terms cold adaptation that has been predicted from genomic contents of metagenomic sequences. In metagenomic clones of marine Crenarchaeota group I the presence of multiple horizontal genes transfer is assumed to play a part in psychrophily (Lo´pez-Garcı´a, et al., 2004). The information from fosmid clones of Antarctic archaea recognized the RNA binding proteins belonging to cold-shock family protein (Be´ja`, et al., 2002; ). Number of genes for cryprotectants biosynthesis including choline, glutamate glycine, sarcosine and betaine along with genes involved in membrane fluidity i.e. genesis of unsaturated fatty acids and genes responsible for conversion of saturated into unsaturated fatty acid has been identified from sequencing glacier ice metagenome (Simon, et al., 2009 a, b). The largely higher metabolic adoptability and the occurrence prophages and transposes (Konstantinidis, et al., 2009; Simon, et al., 2009b) propose a broader mechanism of psychrophily. Together these finding signify the cold adaptation mechanisms that can be predictable within immense extent of metagenomic data that probably can be rich source for mining of low temperature
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 53 Chapter 2 Review of Literature adaptation from uncultrable microorganisms. The genomic data analysis of low temperature adaptation shown comparable results to the metagenomic studies. Considerably, low content of hydrophobic amino acid (chiefly leucine) and elevated level of non-charged polar amino acids (mainly threonine and glutamine) were characterized from Methanococcoides burtonii and Methanogenium frigidum a psychrophilic Archaea (Saunders, et al., 2003). A comprehensive investigation of over 1.0X102 protein homology model exhibit that protein from low temperature archaea have high hydrophobic residue, threonine and glutamine in solvent accessible regions. The concept of reduced thermostability and increased flexibility that results in cold adaptation to enzyme was further supported by a similar study that observed substitution of aspartate for glutamate, increase in polar residues (particularly serine), decrease in charged residues on surface proteins of low temperature from Colwellia psychrerythraea 34H (Methe et al., 2005). A reduction in arginine, alanine and proline has been observed in the genome of both Shewanella sediminis and Shewanella halifaxensis (Zhao, et al., 2010), whereas genomic study revealed a decrease in arginine particularly in genes for reproduction and cell growth of Psychrobacter arcticus (Ayala-Del-Rı´o, et al., 2010). Though, Pseudoalteromonas haloplanktis proteins analysis exhibit an increase in asparagine residue (Me´digue, et al., 2005) however, the genomic analysis of Desulfotalea psychrophila did not indicate any substitution in amino acid supporting to psychrophilicity (Rabus, et al., 2004).
A proteomic analysis of psychrophiles comprising Renibacterium salmonicum, Psychromonas ingrahamii, C. psychrerythraea, Psychrobacter cryohalolentis, D. psychrophila and Pseudoalteromonas atlantica showed a substitution of amino acids leading to elevated protein flexibility in comparison to those six mesophiles (Metpally and Reddy, 2009). The genomic as well as the proteomic analysis have recognised various expressed genes responsible for cold adaptation and other ecological stresses. In different psychrophiles such as P. arcticus (Ayala-Del-Rı´o, et al., 2010), D. psychrophila (Rabus, et al., 2004), C. psychrerythraea (Methe et al., 2005), P. haloplanktis Me´digue, et al., 2005), Photobacterium profundum (Campanaro, et al., 2005) and M. burtonii (Saunders, et al., 2003; Nichols, et al., 2004; Allen, et al., 2009), Halorubrum lacusprofundi (Gibson, et al., 2005), the genes responsible for membrane fluidity and genes encoding unsaturated fatty acids have been recognized.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 54 References Background and Review of Literature
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Chapter 3. Bacterial Diversity
Paper 1 (Tirich Mir Glacier)
Title:
Muhammad Rafiq1, Alexandre M. Anesio2, Muhammad Hayat1, Sahib Zada1, Wasim
Sajjad1, Aamer Ali Shah1 and Fariha Hasan Characterization of psychrophilic bacteria from Tirich Mir glacier, Pakistan, and their potential as industrial candidates
Status: Under review in Journal Research in Microbiology
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 3 Bacterial Diversity
Characterization of of psychrophilic bacteria from Tirich Mir glacier, Pakistan, and their potential as industrial candidates
Muhammad Rafiq, Alexandre M. Anesio, Muhammad Hayat, Sahib Zada, Wasim Sajjad, Aamer Ali Shah and Fariha Hasan
Abstract There is not any report available on the microbial communities of glaciers in Hindu Kush region, Chitral, Pakistan. This is the first exploration of the culturable cold adapted bacterial diversity of Tirich Mir glacier. Subsurface ice, sediment and glacier melt water samples were collected and analyzed geochemically and microbiologically. The average total viable count was 6.09 × 104, 4.39 × 105, 1.81 × 105 CFU/ml and 4.01 × 108 CFU/g for glacier melt water, subsurface ice, glacier ice and glacial sediment, respectively. Total 43 isolates were selected on the basis of morphology. Most of the isolates (74%) showed tolerance up to 10% of NaCl concentration, while the maximum tolerance showed by some isolates was up to 36% NaCl. Most of the isolates were able to grow at 4°C and 15°C, while some showed growth at 25°C and 37°C. Most of the isolates were able to tolerate different toxic metals like Cd+2, Cr+3, Hg+2, Fe+3, Ar+3 and Ni+2. The highest resistant was against Fe+3, and least against Hg+2. Many isolates showed antimicrobial activity against ATCC and clinically isolated Gram positive and Gram negative bacteria and fungi. 16S rDNA sequence analysis revealed that all isolates belong to Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. The most abundant group was Proteobacteria with 53% of the total isolates, followed by Firmicutes with 23%, Actinobacteria with 15% and Bacteroidetes with 9%. The subgroups of Proteobacteria were dominated by Beta-proteobacteria (44%), Gamma-proteobacteria (40%) and Alpha-proteobacteria (16%). We conclude that non-polar glaciers such as of HKKH region, are a rich source of cultivable microbiota, such unexplored cold and frozen habitat should be further explored for understanding the microbial life style, microbial diversity both culturable and unculturable, the role they are playing in cycling of nutrients, climate change and for their potential industrial applications. Key words: Bacterial diversity, Psychrophiles, Non-polar glaciers, Hindu Kush, Tirich Mir
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 89 Chapter 3 Bacterial Diversity
Introduction
The temperature of about 85% of Earth’s crust is < 5ºC. Glaciers are unique ecosystems covering a surface of about 15 million km; approximately 10% of the total land surface is composed of glaciers in polar and non-polar regions [1, 2]. The main reservoir of glaciers is in polar regions. Outside polar region, the largest glacier reservoir lays in Hindu Kush, Karakoram and Himalaya (HKKH) region and referred to as ‘third pole’ by many scientists. HKKH represent a total of 54,252 small and large glaciers which cover an area of 60,000 km2. These glaciers feed 10 rivers of eight countries covering 9 million km2 [3]. Hindu Kush is a sub- range of HKKH and spread over the northern areas of Pakistan (Chitral, a district of Khyber Pakhtunkhwa, Pakistan) to central Afghanistan. There are a number of small and large glaciers covering the valleys of Tirich Mir, where temperature remains below zero degrees Celsius throughout the year. These glaciers may provide an interesting niche for microorganisms which is still unexplored.
Low temperature environments are considered as extreme habitats and usually require particular adaptations by the microbial community for its successful colonization and survival. Many microorganisms have the ability to adapt and even thrive in these harsh conditions of low temperature, low water availability and nutrient deficiency. In 1911, Omelyansky for the first time and later Isachenko [4] reported microorganisms from permafrost. Later, James and Sutherland [5] and Becker and Volkmann [6] isolated microbes from cold habitats. Since then, viable bacteria have been isolated from approximately two million year old Siberian permafrost and grown in lab conditions [7- 9]. These tiny life forms have a vital role in food web, biogeochemical processes and immobilization and mineralization of many important compounds [10- 12].
Glaciers’ microflora has to face many challenges for survival such as low temperature, poor nutrients and high salt concentration especially in sea glaciers. Glaciers are usually not very salty but only when they are originated from sea, ocean or due to geochemistry of under-laying bedrock. The microbes in the glaciers are
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 90 Chapter 3 Bacterial Diversity mostly of allochthonous in nature therefore for their survival in such conditions they must develop different strategies for adaptation in their new and changing habitats. These psychrotolerant and psychrophilic microbes have the ability to produce antifreeze proteins, exopolysaccharides, cold active enzymes, unsaturated fatty acids and ice nucleating proteins to maintain the integrity and fluidity of the cell for normal biochemical reactions [2, 13, 14]. In addition therefore, these microbes have extraordinary ability of producing valuable enzymes and metabolites having potential use in different industries, even used for the degradation of xenobiotic compounds [15, 16].
Recent research has focused on the microbial diversity of ice, permafrost, sediments and glacier melt water of polar regions and alpine glaciers [17- 24]. A major portion of the glacial microbial flora is composed of bacteria and algae. The abundance of fungi and archaea is relatively very low [2]. Some studies on glaciers of different parts of the world, e.g. Alaska [25], Tibet [26, 27], China [28, 29, 30], Canada [31] and New Zealand [32] revealed that the most abundant bacterial group is Proteobacteria, comprising ~ 65% of the total isolates, of which Beta-proteobacteria is the dominant class. Proteobacteria is followed by Bacteroidetes, Actinobacteria, Gemmatimonadates, Chloroflexi, Acidobacteria and Firmicutes. The Korean Polar and Alpine Microbial Collection (PAMC) comprising about 1500 identified strains, also support these findings [33].
Much attention is attained by the study of psychrophilic microbial ecology of polar regions including Greenland and Antarctica [34- 36], alpine and eastern Himalaya (China) [37]. The glaciers of eastern Himalaya were studied for the bacterial diversity which showed that these glaciers are rich habitats of bacteria and also a number of novel strains were reported [38- 44] while there is no single study on the bacterial diversity of the glaciers of Hindu Kush ranges.
The present study aims to unveil the culturable bacterial diversity of the Tirich Mir glacier and thus, adding to our understanding of the bacterial diversity of psychrophilic niches. This investigation provides a comparative study of culturable bacterial diversity of other cold habitats with that of Tirich Mir glacier. These isolates can further be screened for industrially important metabolites, including; cold active
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 91 Chapter 3 Bacterial Diversity enzymes, antibiotics, extracellular polysaccharides and unsaturated fatty acids. It is also of significance that study of low temperature ecosystem, its components and processes provides a model to study habitability of low temperature environments and is also considered as a potential analog for habitats on other icy worlds/planets where reactions between water-rock may take place with saline deposits and subsurface oceans [45].
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 92 Chapter 3 Bacterial Diversity
Materials and Methods
Description of the study site and sampling
Tirich Mir glacier is one of the main glaciers of the Hindu Kush mountain range, spreading over a large area of about 800 km extending from northern areas of Pakistan to central Afghanistan. Its highest peak is Tirich Mir 7,708 m and ranked highest outside Karakoram and Himalaya and 33rd in the world. Tirich Mir dominates this 322 km long Chitral valley. Chitral is situated in the mountains of Hindu Kush between 35° and 37° North and 71° and 74° East. To the North, famous Afghan Wakhan Corridor separates it from the Republic of Tajikistan and Pamirs, to Northeast the Hunza Valley forms border to China. The mountains of Chitral are considered the most difficult for expeditions [46] because of its rough terrain. No mountain in the region is less than 1200 m and more than 40 peaks have an altitude of 6096 m. Samples were collected from snout of one of the glaciers near Upper Tirich valley, Chitral. Sampling tools were sterilized by autoclaving (bottles and bags), UV radiation (tissue paper) and 70% ethanol (ice axe). Samples collected include, surface ice, subsurface ice, sediment and glacial melt water. GPS (Garmin eTrex 20) was used for determining geographic coordinates of sample locations. Temperature was recorded using thermometer, while pH was determined by pH strips on site and pH meter (Sartorius Professional Meter PP-15) in lab. To collect the subsurface ice, the surface ice was removed by sterilized ice axe and large ice chunks were cut into smaller pieces and collected in sterile bottles aseptically. All the collected samples were transported to the Microbiology Research Lab., Quaid-i-Azam University, Islamabad, in ice box and stored at -20°C (Fig. 3.3.1).
Geochemical analysis of the sample
Dissolved free amino acid (DFAA) concentration was determined by utilizing a Dionex ICS-3000 ion chromatography system. Amino acids (aspartic acid, tyrosine, serine, tricine, adenosine, valine and alanine) were isocratically determined with a CarboPac PA20 column.
2+ 2+ + 2- While the concentration of Cation (Ca , Mg , Na , Ammonium) and Anions (PO4 , 2- - acetate, SO4 , Cl , NO3, NO2) was determined by using a Dionex ICS-5000 reagent- free, capillary ion chromatography system. Ions were detected by their specific
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 93 Chapter 3 Bacterial Diversity
retention times over an eluent gradient (KOH, MSA, K2CO3, LiOH). The concentration of ammonia in all samples was determined by FIA.
A
B
Fig. 3.1.1. Location of the sampling site (A), photograph of the glacier from where samples were collected (B)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 94 Chapter 3 Bacterial Diversity
Soil digestion for metal detection by Aqua regia method
For detection of metals, soil samples were digested as; One gram of soil (powdered) was taken and added to 15 ml aqua regia (HCl:HNO3 = 3:1), the sample was then heated at 150°C till brown fumes appear. After this, 5 ml hypochloric acid (about 2-3 ml) was added and again heated at 150°C until whitish fumes appear. Then the samples were filtered and diluted (raised the volume to 50 ml) with double deionized water. The water/ice samples were filtered to remove the suspended particles and acidified with HNO3 to a pH ranging from 2 to 4.
Isolation and characterization of bacteria
The samples were spread on LB agar (1X and 5X diluted) and incubated at 2 different temperatures (4°C and 15°C) for four to eight weeks. The isolates were selected on the basis of their distinct colony morphology and subcultured on fresh LB plates to get the pure cultures and confirmation. All isolates with different characteristics were further purified by subculturing and preserved in 15% glycerol in triplicates and stored at -70°C. For determination of optimal temperature growth, all isolates were incubated at different temperatures, 4, 15, 37 and 55°C. The growth was determined on LB agar medium in triplicate. The organisms were selected positive with visible growth. To determine their salt tolerance, all isolates were grown on increasing salt concentrations starting from 2% and then gradually increasing up to 36%.
Determination of Viable Cell Count
Total viable cells were calculated as colony forming units per ml (or g) (CFU/ml or g) of the sample. Each sample was serially diluted using autoclaved normal saline and then 200 µl from each dilution spread onto a separate plate and incubated at two different temperatures 4°C and 15°C. After incubation of 3 to 5 weeks, the CFU/ml was determined for each sample.
DNA extraction
Genomic DNA was extracted from all study isolates using CTAB method. Fresh cultures were pelleted down by centrifugation and resuspended in 567 µl TE buffer. Three µl proteinase K and 30 µl 10% SDS were added to the suspension and
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Sequencing and Analysis
Sequencing was done commercially using Macrogen Inc. Seoul, Korea. The primers used for PCR amplification and sequencing were bacterial 16S rDNA universal primers 27F (5’ - 3’) AGAGTTTGATCMTGGCTCAG and 1492R (5’ - 3’) TACGGYTACCTTGTTACGACTT. The sequencing was done by Sanger Dideoxy chain termination method. Sequence database searches using NCBI nucleotide blast to find out the closest related microbes with the study isolates. All the obtained sequences were assembled through DNA baser software [50] (DNA Baser 2013). The weak sequences were trimmed and BLAST search was done using the National Centre for Biotechnology Information (NCBI) for strain homology. The related sequences were obtained from NCBI in fasta format and aligned with MUSCLE (build in MEGA 6) software for phylogeny.
Phylogenetic tree construction and analysis
After alignment of all the sequences and related sequences obtained from NCBI, evolutionary analyses were conducted using MEGA6 [47]. The evolutionary history was inferred using the Neighbor-Joining (NJ) method [48]. The percentage of replicate trees in which the associated taxa was clustered together in the bootstrap test (1000 replicates) is shown next to the branches [49]. The evolutionary distances were computed using the Maximum Composite Likelihood method [50] and are shown in the units of the number of base substitutions per site. All sequences were prepared by sequin and send to NCBI GeneBank for acquisition of accession numbers.
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Metal Tolerance
The minimum inhibitory concentration for heavy metal resistance was performed on LB agar medium (Sigma) comprising Cd+2, Cr+3, Hg+2, Fe+3 and Ar+3 and Ni+2 ranging from (10-1900) ppm. The heavy metals were supplemented as CdCl2.2H2O, CrCl3,
HgCl2, FeCl2 and ArCl3. NiCl2.
Screening of Antimicrobial activity
The antimicrobial activity was performed by spot on lawn assay. Briefly, the bacterial and Candida cells and fungal spore suspension was prepared according to 0.5 McFarland standard and were spread on Muller-Hinton agar and a spot of isolates was applied and incubated at 15°C for 72 to 96 hours. A clear zone of inhibition around the indicator organism indicates the antagonistic effect and was recorded.
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Results
Geochemical analysis of the samples
Metal Concentration
The metal concentration of the samples showed that all the samples were rich in many important metals. The ratio of concentration was highest in sediment sample. Metal presence wise the highest metal detected was Magnesium followed by Iron. The concentration of Mg was 1941 ppm, Fe 1816 ppm in sediment, in glacial ice the concentration of Mg was highest 35 ppm followed by Ca 24 ppm. The lowest concentration recorded was Cu for sediment and Glacial ice less than 1 ppm (Table 3.1.1).
Table 3.1.1. Concentration of different metals in samples, The figures were round to one digit, < have a value in between 0.1 to 0.4 ppm concentration.
Sample Concentration ppm) Zn Fe Na Ni Mn Ca Mg K Cu Cr Pb Ice 1 6 4 < < 24 35 1 < 1 < Melt water 1 2 5 < < 25 45 1 < 1 < Sediment 21 1816 771 7 37 495 1941 229 6 27 18
Amino acid concentration
The concentration of free amino acid in sample was determined which indicated that the sediment was rich in free amino acid almost contain all amino acid in some content. The concentration of amino acid was very less in glacial melt water. Tyrosine amino acid is found in high concentration comparatively to other amino acids in the samples (Table 3.1.2).
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Table 3.1.2. Concentration of amino acids in samples, All values in µM, no value indicates no measurement available for the respective sample.
Samples Concentration of amino acid µM Aspartic acid Tyrosine Tricine Adenosine Valine Alanine Ice - 0.8 - - 0.1 0.5 Melt water - 0.6 - - - - Sediment 0.07 0.5 0.08 0.003 0.21 0.1
Concentration of Cations and Anions
Different Cations and Anions were found in samples in different concentrations. The cation the concentration of Na and Ca was high in sediment followed by glacial melt water. While anion (SO4) concentration was high in water and sediment samples as compared to ice (Table 3.1.3).
Table 3.1.3. Cation and Anion concentrations in samples
Sample FIA Cation and Anion concentration in µM DIONEX ++ + + − NH Acetat NH Ca Mg Na Cl NO PO4 SO4 4 + 3 e 3 Ice 27 433 354 2650 204 2106 2181 38 - 60 Melt 5 72 74 6807 2166 161 135 494 4 160 Water 9 Sedime 346 2886 108 12032 2302 249393 - - - 157 nt 1 7
All values are given in µM, no value indicates no measurement available for the respective sample. Note: Ammonia was analysed by FIA (Flow Injection Analysis) while all other analysis was carried out by Dionex ion exchange chromatography.
Physiochemical conditions and viable count
The temperature and pH of the samples were observed on the site of sampling. pH of all samples was neutral (7), and the temperature was in the range of -5 to +2°C (Table 3.1.4). After incubation for three to five weeks at 4ºC, the number of cells (CFU/ml or
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/g) were calculated as 6.09 × 104, 4.01 × 108, 4.39 × 105 and 1.81 × 105, respectively, in meltwater, sediment, surface ice and glacial ice (1 m deep in glacier) (Table 3.1.4).
Table 3.1.4. Total viable cells (CFU/ml) and physiochemical conditions of the glacial samples
Sample pH Temperature (°C) CFU/ml or CFU/g Glacier melt water 7 2 6.09 × 104 Glacial sediment 7 1 4.01 × 108 Glacial subsurface ice 7 -2 4.39 × 105 Glacial ice 7 -2 1.81 × 105
Phenotypic characterization and identification
On the basis of distinct morphological characteristics (size, shape, color, margin, opacity) 23 different colonies were isolated at 4ºC and 20 colonies at 15ºC (Table 3.1.5). The study isolates were identified on the basis of 16S rDNA sequencing and BLAST search in NCBI. The sequence homology revealed that our isolates belonged to 4 major groups, Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes (Table 3.1.5).
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Table 3.1.5. 16S rDNA sequence based identification and characteristics of selected isolates from the Tirich Mir glacier Isolate Colony morphology Gram’s Accession Nearest similar species in the % % Reaction and Number NCBI GenBank 16S rDNA Coverage Identity cell shape sequence database (with Accession No.) Proteobacteria LT1 Medium, light pink, opaque, thread –, rods KP318030 Pseudomonas sp (AB379688.1) 99 99 forming. LT6 Small, dark orange, opaque, convex –, coccobacilli KP771865 Serratia sp. (KJ739884.1) 100 99 LT7 Medium, light orange, opaque, circular. –, coccobacilli KP318034 Ralstonia pickettii (NR_102967.1) 99 98
LT8 Large, white, opaque, circular –, rods KP318035 Serratia sp. (KJ739884.1) 98 99 LT10 Small, white, opaque, circular –, coccobacilli KP318037 Serratia sp. (AB893940.1) 98 99 LT11 Small, shiny off white, –, rods KP318038 Pseudomonas sp. (JF313042.1) 99 99 LT12 Pin pointed, white, opaque, convex –, coccobacilli KP318039 Devosia sp. (JQ977241.1) 99 99 LT13 Small, white, transparent, entire convex. –, rods KP318040 Ochrobactrum sp. (HM016872.1) 99 96 LT16 Small, orange, dry colony –, rods KP318043 Massilia aurea (KF911334.1) 99 97 LT17 Small, orange, opaque, convex –, coccobacilli KP318044 Massilia aurea (KF911334.1) 100 96 LT19 Medium, yellow, entire transparent –, rods KP318046 Pseudomonas sp.(JQ977323.1) 100 97 margins LT24 Medium, white then turn brick red –, coccobacilli KF550058 Serratia sp (CP005927.1) 99 99 HT3 X- large, off white, transparent centre –, coccbacilli KP318054 Alcaligenes sp. (JF710954.1) 99 100 HT4 Large, yellow, opaque, flat –, rods KP318055 Uncultured bacterium/Alcaligenes 99 99 sp. (KJ453983.1) HT5 Large, bright yellow, opaque, mucoid –, rods KP318056 Brucellaceae bacterium 100 91 (KC493614.1) HT8 Large, greyish white, thick edges, –, rods KP318059 Pseudomonas sp (HF678987.1) 100 98 translucent centre
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HT10 Small, convex, off white, opaque. –, rods KP318061 Alcaligenes sp. (KF641845.1) 100 91 HT12 Small, transparent, convex entire –, rods KP318063 Stenotrophomonas rhizophila 95 99 (HQ689684.1) HT13 Large, greyish, flat, mucoid, opaque –, rods KP318064 Ochrobactrum sp. (AF452128.1) 100 97 HT15 Medium, off white, convex, opaque. –, rods KP318066 Stenotrophomonas rhizophila 100 93 (HQ689684.1) HT16 Small, white, convex, dry –, rods KP318067 Ralstonia sp. (KM051530.1) 99 99 HT17 Medium, white (pointed at centre) –, rods KP318068 Uncultured bacterium (Alcaligenes) 100 99 (KJ454266.1) HT18 Large, yellow, dry appearance, –, rods KP318069 Uncultured bacterium (Alcaligenes) 99 99 (KJ454216.1) HT20 Large, brown (yellow), mucoid, opaque –, rods KP318071 Advenella sp.(KM191133.1) 99 99 HT22 Small. Yellow translucent –, rods KF550057 Massilia sp. (FR865960.1) 100 99 Firmicutes LT2 Medium, yellow, opaque convex sticky +, cocci KP318031 Bacillus sp. (JN593078.1) 100 99 LT4 Medium, off white, opaque, entire +, cocci KP318032 Planococcus psychrotoleratus 98 98 (AY771727.1) LT9 Large off white brownish, opaque +, cocci KP318036 Staphylococcus haemolyticus 100 99 (KJ623603.1) LT15 Small, orange, entire, convex +, rods KP318042 Bacillus cereus (JN700144.1) 98 99 LT20 Small, white transparent shiny margins +, KP318047 Paenibacillus polymyxa 98 98 coccobacilli (HE577054.1) LT23 Medium, Light green colour +, rods KP318050 Brevibacillus parabrevis 99 82 (KF600765.1) LT25 Medium, Orange +, rods KF550059 Exiguobacterium sibiricum 100 99 (KF054759.1) HT9 Medium, greyish brown, dark centre, +, Cocci KP318060 Staphylococcus haemolyticus 100 99 light edges (KJ623603.1)
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HT11 X-large, flat entire, margin translucent +, Rods KP318062 Paenibacillus sp (JQ345703.1) 99 95 HT14 Small pin pointed, off white to golden, +, Rods KP318065 Lysinibacillus sp. (KC310819.1) 100 83 transparent HT21 Large, off white opaque +, rods KF471118 Bacillus cereus (KF601958.1) 99 99 Actinobacteria LT3 Medium, off white opaque, convex +, cocci KP771864 Arthrobacter (AF197054.1) 100 97 sticky LT5 Large, yellow, opaque, convex. +, cocci KP318033 Arthrobacter gangotriensis 99 97 (KF306344.1) LT14 Small, white, transparent +, KP318041 Arthrobacter sp. (JX949317.1) 100 96 Pleomorphic LT18 Large, off white +, rods KP318045 Arthrobacter antarcticus 100 99 (LK391539.1) HT6 Medium, brown, dry, opaque, convex +, Cocci KP318057 Arthrobacter sp (GU062484.1) 100 96 HT7 Medium, white, opaque, round, flat. +, Cocci KP318058 Rhodococcus sp. (KF011682.1) 100 83 HT19 Large, off white, flat, mucoid. +, Cocci KP318070 Arthrobacter sp. (GU062484.1) 99 99 Bactroidetes LT21 Pin pointed, off white –, rods KP318048 Sediminibacterium sp. (JF733396.1) 98 98 LT22 Black colour tough surface –, rods KP318049 Uncultured bacterium (Bacteroidetes) 99 98 (KF598774.1) HT1 Medium, yellow, opaque, convex, –, rods KP318051 Sphingobacterium psychroaquaticum 98 95 circular (NR_108297.1) HT2 Medium, Off white, opaque, circular –, rods KP318053 Uncultured bacterium (KF911124.1) 100 92
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Growth characterization
Growth on NaCl
All isolates were cultured on increasing salt concentrations to check for their salt tolerance. Most of the isolates showed tolerance to high salt concentrations, whereas some showed optimum growth at higher concentrations. A total of six isolates (LT12, LT14, HT3, HT8, HT17 and HT18) showed growth above 25% salt concentration and their optima at 20% ±4. A total of 28 isolates were able to tolerate salt up to 24% and their optimum concentration was 14%±4. Maximum concentration for growth recorded was up to 36% in three isolates: HT3, HT8 and HT17. On the other hand, the lesser tolerant isolates were HT1 and HT7 which did not show any growth above 2% NaCl (Table 3.1.6).
Table 3.1.6. Salt tolerance profile of the study isolates
Isolate Name NaCl conc. (%) Tested Range Optimum Range Proteobacteria LT1 0.9 – 14 2-8 LT6 0.9-10 2-4 LT7 0.9-22 2-14 LT8 0.9-18 2-8 LT10 0.9-10 2-4 LT11 0.9-2 0.9 LT12 0.9-36 2-26 LT13 0.9-14 2-8 LT16 0.9-10 2-4 LT17 0.9-12 2-6 LT19 0.9-14 2-6 LT24(TG3) 0.9-6 2-4 HT3 0.9-36 2-24 HT4 0.9-14 2-8 HT5 0.9-10 2-6 HT8 0.9-36 2-26 HT10 0.9-14 2-8 HT12 0.9-6 2 HT13 0.9-10 2-4 HT15 0.9-8 2-6 HT16 0.9-14 2-8 HT17 0.9-36 2-24 HT18 0.9-28 2-20 HT20 0.9-10 2-6
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HT22(TG2) 0.9-2 0.9 Firmicutes LT2 0.9-10 2-6 LT4 0.9-18 2-10 LT9 0.9-10 2-4 LT15 0.9-14 2-6 LT20 0.9-10 2-4 LT23 0.9-12 2-4 LT25(TG4) 0.9-8 2-4 HT9 0.9-6 2-4 HT11 0.9-8 2-4 HT14 0.9-12 2-6 HT21(TG1) 0.9-4 1-2 Actinobacteria LT3 0.9-14 2-8 LT5 0.9-20 2-12 LT14 0.9-26 2-18 LT18 0.9-12 2-6 HT6 0.9-10 2-6 HT7 0.9-2 0.9 HT19 0.9-8 2-4 Bacteroidetes LT21 0.9-12 2-6 LT22 0.9-10 2-4 HT1 0.9-2 0.9 HT2 0.9-10 2-6 (The optimum growth is on the basis incubation time and growth)
Effect of temperature on growth
All isolates were grown at different temperatures. It was observed that all the isolates were able to grow well at 4°C and 15°C. Most of the isolates were able to grow at 25°C except the isolates LT1, LT3, LT4, LT5, LT6, LT8, LT18, LT21 and HT3. Some isolates were stenopsychrophiles, having broad range of temperature requirement for growth with good growth at 25°C and 37°C as well. None of the isolates showed growth at 55°C. Overall, all 47 isolates showed good growth at 15°C, 45 showed growth at 4°C, 38 isolates were capable to grow at 25°C, 21 isolates at 37°C and there was no growth at 55°C (Table 3.1.7). An important change with increasing incubation temperature is a very drastic decrease in the pigmentation, and most of the pigmented strains lost their ability to produce pigment at 25°C and higher temperature (Table 3.1.8).
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Table 3.1.7. Temperature profile of all isolates from Tirich Mir glaciers
Isolate Temperature (°C) 4 15 25 37 55 Proteobacteria LT1 + + - - - LT6 + + - - - LT7 + + + + - LT8 + + - - - LT10 + + + + - LT11 + + + + - LT12 + + + + - LT13 + + + + - LT16 + + + - - LT17 + + + - - LT19 + + + - - LT24(TG3) + + + + - HT3 + + - - - HT4 + + + + - HT5 + + + - - HT8 + + + - - HT10 + + + - - HT12 + + + + - HT13 + + + + - HT15 + + + + - HT16 + + + + - HT17 + + + - - HT18 + + + + - HT20 + + + - - HT22(TG2) - + + - - Firmicutes LT2 + + + - - LT4 + + - - - LT9 + + + + - LT15 + + + - - LT20 + + - - - LT23 + + + - - LT25(TG4) + + + - - HT9 + + + + - HT11 + + + + - HT14 + + + + - HT21 (TG1) - + + + - Actinobacteria LT3 + + - - - LT5 + + - - - LT14 + + + + - LT18 + + - - - HT6 + + + - -
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HT7 + + + + - HT19 + + + + - Bacteroidetes LT21 + + - - - LT22 + + + - - HT1 + + + + - HT2 + + + - - Key: + is growth, - is no growth
Table 3.1.8. Effect of temperature on pigment production of the isolates from Tirich Mir glacier
Isolate Primary pigment/color Temperature (°C) 4 15 25 37 LT1 light pink +++ +++ ++ - LT2 Yellow ++ ++ - - LT3 Non pigmented - - - - LT4 Non pigmented - - - - LT5 Yellow +++ +++ + _ LT6 Dark orange +++ +++ ++ - LT7 Light orange ++ ++ - - LT8 Non pigmented - - - - LT9 Non pigmented - - - - LT10 Non pigmented - - - - LT11 Non pigmented - - - - LT12 Non pigmented - - - - LT13 Non pigmented - - - - LT14 Non pigmented - - - - LT15 Orange +++ +++ ++ - LT16 Orange +++ ++ + - LT17 Orange +++ +++ + - LT18 Non pigmented - - - - LT19 Yellow ++ ++ + - LT20 Non pigmented - - - - LT21 Non pigmented - - - - LT22 Black +++ +++ +++ - LT23 Light green +++ ++ - - HT1 Yellow +++ +++ ++ _ HT2 Non pigmented - - - - HT3 Non pigmented - - - - HT4 Yellow +++ ++ + - HT5 Bright yellow ++ + - - HT6 Brown +++ ++ _ - HT7 Non pigmented - - - - HT8 Greyish white. +++ +++ + -
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HT9 Greyish brown +++ +++ + _ HT10 Non pigmented - - - - HT11 Non pigmented - - - - HT12 Non pigmented - - - - HT13 Greyish +++ +++ + HT14 Off white to golden +++ +++ ++ - HT15 Non pigmented - - - - HT16 Non pigmented - - - - HT17 Non pigmented - - - - HT18 Yellow ++ ++ + - HT19 Non pigmented - - - - HT20 Brown (yellow) +++ ++ + -
Phylogenetic analysis
Analysis of the sequences indicated that all study isolates were from four major groups (Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes), two groups belonging to Gram positive and two to Gram negative bacteria (Table 3.1.5, Fig. 3.1.2, 3.1.3, 3.1.4 and 3.1.5). The most diverse and abundant group was Proteobacteria. Analysis of 16S rDNA sequences revealed that 25 isolates of the total study have highest similarity to Proteobacteria phylum of bacteria. It represents 53% of the total isolated strains and 86% of the Gram negative isolates. The isolates belonging to Proteobacteria are further subdivided into 3 subgroups dominated by Beta-Proteobacteria followed by Gamma-Proteobacteria and Alpha-proteobacteria (Fig. 3.1.6). Beta- Proteobacteria comprised of 5 isolates related to genus Alcaligenes in which 4 were >97% similar, while one isolate (HT10) was 91% similar. Two isolates (LT16 and LT17) were similar to genus Massilia with 99% similarity. Two isolates (HT16 and LT7) were similar to Ralstonia >97%, while HT20 was 99% identical to Advenella sp.
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Fig 3.1.2: Distribution of phylogenetic groups (%) of the culturable isolates of the study isolates from Tirich Mir glacier
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30 HT13 46 Uncultured bacterium (JX644332) 100 Ochrobactrum sp.(HM016872) 59 Ochrobactrum sp. (HM016872) 100 LT13 HT5 100 Pseudochrobactrum kiredjianiae (NR 042519) 99 Brucellaceae bacterium (KC493614) 99 69 Unidentified bacterium (AJ223456) LT12 61 Devosia sp (JQ977241) 100 Devosia limi (NR 042324)
33 Alphaproteobacteria LT19 95 LT1 Pseudomonas sp.(AB379687) 100 58 HT8 49 97 Pseudomonas sp.(HF678987) Pseudomonas sp.(JQ977323) 34 LT11 44 Pseudomonas sp.(JF313042) 51 65 Pseudomonas mandelii (KF704104) HT15 71 HT12 100 Stenotrophomonas rhizophila (NR 121739) 94 Uncultured bacterium (GQ379399) 57 Stenotrophomonas rhizophila (HQ689684) LT24 18 Serratia sp. (AB893940) 9 Uncultured proteobacterium (AJ310681) 66 Gammaproteobacteria 100 LT10 LT6 97 LT8 Serratia sp (KJ739884) 47 Serratia sp (DQ103511) 39 13 Serratia sp (FJ231172) 96 LT16 18 LT17 9 13 Massilia sp. (FR865962) 68 Massilia aurea (KF911334) 100 Massilia sp.(FR865960) HT22 67 Massilia sp.(FR865954) Ralstonia pickettii (LN681565)
HT16 100 Uncultured bacterium (HQ910290) 72 Uncultured bacterium (GQ359968) 17 LT7 14 100 19 Ralstonia pickettii (ref|NR 102967) 35 Advenella sp. (KM191133) 100 Advenella sp. (KJ733990) HT20 Alcaligenes sp.(KF641845) 100 HT10 34 100 HT18 Uncultured bacterium (KJ454216) Betaproteobacteria 19 21 Uncultured bacterium (KJ454266) 46 Alcaligenes faecalis (JQ612515) 42 HT17 16 HT3 4 HT4 65 Alcaligenes sp (AB968096) 15 Alcaligenes sp. (JF710954)
Fig 3.1.3: Evolutionary relationships of taxa of Proteobacteria group. The evolutionary history was inferred using the Maximum Likelihood method based on the Tamura-Nei model method and the phylogenetic tree was conducted in MEGA6. The study isolates were indicated by ♦ mark. All other isolates were obtained from GenBank, their names and accession numbers are given in the tree. The bootstrap values are shown on the branches.
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11 LT15 15 Bacillus cereus (KF601957) 67 Bacillus cereus (KF601958) HT21 73 12 Bacillus sp. (KF021758) 100 LT2 75 Bacillus sp. (KC434978) HT9 LT9 100 26 14 Staphylococcus haemolyticus (KJ623603) 21 Staphylococcus haemolyticus (KJ623598) HT14 38 46 Lysinibacillus sp. (KC310819) 95 Lysinibacillus sp.(JF768718) LT4
100 Uncultured Planococcus sp (JF905991) 51 Planococcus psychrotoleratus (AY771727) LT25 (TG4)
100 Exiguobacterium sp (KF054759) 59 Exiguobacterium sp.(DQ019169)
100 Brevibacillus parabrevis (KF600765) 73 Brevibacillus parabrevis (HE963223) LT23
99 LT20 72 Paenibacillus polymyxa (HQ538845)
100 HT11
100 Paenibacillus sp (JQ345703) 71 Paenibacillus vortex (HQ005270)
Fig. 3.1.4. Evolutionary relationships of taxa of Firmicutes group.
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33 Arthrobacter sp.(GU062484) 99 Arthrobacter sp. (GU062483) 64 HT19
51 HT6 Uncultured bacterium (KF064699) 79 48 LT14 24 Arthrobacter sp.(JX949317) LT3 LT18 Arthrobacter gangotriensis (KF306344) 67 43 LT5 57 Uncultured bacterium (KJ454013) HT7 Rhodococcus sp (KF011682) 100 84 Rhodococcus erythropolis (KF439699) 85 Rhodococcus sp (FM986392)
Fig. 3.1.5. Evolutionary relationships of taxa of Actinobacteria group.
44 HT1 94 HT2 86 Uncultured bacterium (KF911124)
95 Sphingobacterium psychroaquaticum (NR 108297) Sphingobacterium sp(KJ152099) Sphingobacterium sp (AB680845) 99 69 Sphingobacterium nematocida (NR 122101) 29 Sphingobacterium sp (GU353116)
54 Uncultured Sediminibacterium (JF733396) Uncultured Bacteroidetes (EF123551)
100 Uncultured bacterium (DQ404676) LT21 65 40 Uncultured bacterium (KF598774) 57 Bacteroidetes bacterium (FJ816610) LT22
Fig. 3.1.6. Evolutionary relationships of taxa of Bacteroidetes group.
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The second dominant group of Proteobacteria was Gamma-Proteobacteria consisting of 10 isolates. Isolates of Gamma-Proteobacteria constituted 21% of total isolates and 40% of Proteobacteria group. The most abundant genus of this group was Pseudomonas. Three out of 4 isolates showed >97% similarity to Pseudomonas sp., while LT19 showed 95% similarity. Isolates HT12 and HT15 were similar to Stenotrophomonas rhizophilia with 99% and 93% identity, respectively, indicating that HT15 as the probable new specie. Three isolates, LT6, LT8 and LT10 showed 99% resemblance to genus Serratia. The Alpha- Proteobacteria group consists of 4 isolates which are 9% of total and 17% of Proteobacteria. Isolates similar to genus Ochrobactrum were LT13 and HT13 with 96% and 97% identity, respectively. Isolate LT12 was 100% identical to Devosia sp., and HT5 to Brucellaceae bactrum.
Second group of Gram negative bacteria is Bacteroidetes. Bacteroidetes represent 9%of the total isolates. Total 4 strains belonged to Bacteroidetes and 2 to Sediminibactrium sp. The isolates LT21 and LT22 both were 98% identical to Sediminibactrium sp. While 2 of the isolates (HT1 and HT2), were similar to Sphingobacterium psychroaquaticum 95% and 92%, respectively. These two are potential new species. The Gram positive isolates belonged to two major phylum Firmicutes and Actinobacteria. A total of 18 isolates were grouped into Firmicutes (11 isolates) and Actinobacteria (7 isolates), representing 23% and 15%, respectively, of the total isolates. Firmicutes isolates were diverse and belong to different genera including Staphylococcus haemolyticus, Bacillus sp., Plancoccus psychrotoleratus, Paenibacillus, polymaxa, Exiguobacterium and Brevibacillus parabrevis.All isolates showed >97% similarity except one (LT23) which is 82% similar to Brevibacillus parabrevis and probably is also a new species. The second group of Gram positive bacteria is Actinobacteria. Seven isolates belonged to Actinobacteria group. Arthrobacter is a dominant group of Actinobacteria and 6 out of 7 were similar to Arthrobacter sp. Two isolates HT6 and LT14 were 96% similar to genus Arthrobacter. The isolate HT7 was related to Rhodococcus sp. which is 83% similar and may be a potential new isolate.
Screening for Antimicrobial activity
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A total of 43 isolates were screened via spot on lawn assay against different bacterial and fungal pathogens. A total of 23 isolates (4°C) showed activity only against fungal pathogen, while no activity was observed against bacterial pathogens. Among these 5 (21.73%) isolates showed activity against A. flavus while 2 showed activity against Candida albicans and A. flavus.
Among bacteria isolated at 15°C, 5 showed activity against both bacterial and fungal test strains. Among these 2 isolates (10%) showed inhibitory activity against S. aureus (ATCC). One (5%) isolate showed activity against A. flavus (clinical isolate). Three (15%) isolates showed broad spectrum activity against 6 isolates while 2 (10%) showed activity against all selected strains except vancomycin resistant Enterococcus faecalis. Among high- temperature isolates, a total of 9 (45%) showed antimicrobial activity. The best activity was observed in 32% of the isolates (Table. 3.1.9).
Table 3.1.9. Antibacterial and antifungal activity of potent bacterial isolates of Tirich Mir Glacier. Isolates Test organisms (zone in mm ±2) ATCC isolates Clinical isolates
P. K.
E. coli E. coli
A. flavus
S. aureus S. aureus
aeruginosa C. albicans
pneumoniae
A. fumigatus
Enterococcus LT4 - - - - 21 - - - - - LT5 - - - - 22 - - - - - LT6 - - - - 20 - - - - - LT7 - - - 11 10 - - - - - LT23 - - - 15 20 - - - - - HT3 21 15 18 22 24 23 - - - - HT5 9 ------HT7 14 - 14 28 18 21 - - HT9 - - - - 19 - - - - - HT10 16 15 12 - 24 - - - - - HT13 14 ------HT16 13 - 12 14 18 21 - 12 9 - HT17 14 14 20 18 24 24 14 11 8 - HT18 12 12 10 10 9 9 13 12 9 -
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 114 Chapter 3 Bacterial Diversity
Metal resistance
All the isolates were checked for tolerance against six heavy metals, and showed tolerance to varying concentrations of different heavy metals. The maximum tolerance was observed to FeCl2, while the isolates showed the lowest level of resistance to HgCl2. The low temperature isolates showed maximum level of tolerance to all heavy metals as showed in ppm (µg/mL) like, Iron (1820 ppm), Nickle (1020 ppm), Cadmium (940 ppm), Chromium (800 ppm), Arsenic (680 ppm) and Mercury
(90 ppm). The tolerance among low- temperature isolates was observed as Fe > Ni > Cd > Cr > Ar > Hg. While among high- temperature isolates, the rate of metal tolerance was; Fe > Cr > Cd > Ni > Ar > Hg. The maximum level of tolerance in Iron (1600 ppm), Chromium (900 ppm), Cadmium (880 ppm), Nickle (820 ppm), Arsenic (680 ppm) and Mercury (120 ppm). The details of both high and low temperature isolates are given in Fig. 6 and 7. While the high temperature isolates showed tolerance to Fe (1600 ppm) and Ni (820 ppm).
Fig. 3.1.7. Metal tolerance of Tirich Mir low- temperature isolates. Each dot on X- axis shows a chronological order of isolates (LT1-LT23) from left to right. While Y- axis represent metal concentration in ppm or µg/ml.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 115 Chapter 3 Bacterial Diversity
Fig. 8. Metal tolerance of Tirich Mir high- temperature isolates. Each dot on X- axis shows a chronological order of isolates (HT1-HT20) from left to right. While Y- axis metal represent metal concentration.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 116 Chapter 3 Bacterial Diversity
Discussion
This is the first ever attempt to study the bacterial diversity of any glacier in the Hindu Kush range Pakistan. The geochemical analysis of the samples indicated that these harsh condition have multiple nutrients in the form of cation, anions, free amino acids and many trace metals (micronutrients) in abundant. These components are part of the environment as well as produce by different live forms. These tools are required for growth. The study isolates are mostly heterotrophic in nature which is under the influence of the micro and macro nutrients available. Our estimations of total viable cells (CFU/ml or /g) was 6.09 × 104, 4.01 × 108, 4.39 × 105 and 1.81 × 105, in melt water, sediment, surface ice and glacial ice, respectively, indicated that bacterial population in study site is in the higher range as compared to other polar and some non-polar glaciers. Previously reported values were 104 to 105 CFU /ml (Alaska) [25], 9.6 × 103 CFU/g (Antarctica) [51] and 3.7 × 104 cells/ml (Italy, Madaccio Glacier) [52].
The temperature requirements for optimum growth were similar to that of the previous results and definitions for psychrophiles [53, 54, 55]. The optimum growth temperature was 15°C for some isolates while some isolates grew efficiently at 25°C but most of the isolates lost their ability of pigment production at 25°C. Some strains showed good growth at 37°C as well. The possible reason for losing the ability of pigmentation in response to increase in temperature may be due to the production of colored product to minimize the adverse effects of low temperature environment. Whereas, when temperature increases, the genes responsible for pigmentation are switched off to save the energy [56].
In our study, the salt tolerance ability of the bacterial isolates was high and unique in comparison to previous reports [57- 60]. Very high levels of Na and Cl ions have been detected in our samples; 2105.77, 160.5331 and 249394.5 micromoles in glacier ice, water and sediment, respectively, which justify the isolation of salt tolerant and extreme halophiles from that unique environment (unpublished data by authors). Most of the isolates were able to tolerate NaCl, thus fall into the category of halophiles. Some isolates were able to withstand 36% of salt concentration in the culture medium.
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As far as it is in our knowledge, there is lack of reports on psychrophilic bacterial strains tolerating such high salt concentrations. The tolerance of salt up to 36% is observed for the first time among glacial psychrophilic isolates. Previous reports revealed that psychrophilic bacterial strains can tolerate salt concentration up to 10% [59] and 25% [57]. In 2002, Romanenko and his colleagues [61] reported that Psychrobacter submarinus was the most halophilic psychrophilic strain discovered at that time, and could tolerate up to 15% of salt concentration [58, 61]. Another study of halophiles from foreshore soils showed that bacteria can tolerate salt up to 20% of NaCl. Previous reports demonstrated optimum salt concentration for growth as 3 – 5% [60], while our result showed optimum growth in the presence of 8 – 16% NaCl, with highest at 32%. Similarly, Vahed et al. [62] demonstrated the isolation of halophiles and halotolerants in the range of 7 – 20%. Beta-galactosidase produced by a member of the genus Planococcus, a halotolerant psychrophile from a hypersaline pond in McMurdo Ice Shelf, Antarctica, was active at high salt concentrations, which renders it a possible reporter enzyme for halotolerant and halophilic organisms [57]. Two novel cold-tolerant, Gram- positive, motile, facultatively anaerobic bacterial strains were isolated from moss-covered soil from Livingston Island, Antarctica. They were able to grow at 0-10 % (w/v) NaCl, with optimum growth at 0-1 % (w/v) for Arthrobacter livingstonensis sp. nov. type strain LI2(T) and 0.5-3 % (w/v) for Arthrobacter cryotolerans sp. nov. type strain LI3(T) [63]. Planococcus halocryophilus strain Or1, isolated from high Arctic permafrost, grows and divides at −15 °C and 18% NaCl [64]. As these examples are of halophiles or halotolerants isolated from high salt reservoirs, whereas, our finding is unique as they are from psychrophilic source and showed tolerance up to 36% NaCl (w/v). These are the highest salt resistant bacteria isolated from glaciers or any other source. This is expected to be due the formation and origin of glaciers and the bed rock, making the ice and melt water salty.
Similar to previous reports [25, 26, 29, 32], we report that the percent representation of the Gram negative bacterial isolates was higher than that of the Gram positive. 16S rDNA sequence based phylogenetic analysis revealed that all isolates belonged to four different groups. Abundance-wise these groups were Proteobacteria (53%), Firmicutes (23%), Actinobacteria (15%) and Bacteroidetes (9%). This is in agreement with previous studies that reported Proteobacteria as the most abundant group among
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 118 Chapter 3 Bacterial Diversity the cold inhabitant bacteria [1, 2, 17, 25- 27, 29, 30, 32]. There are some reports of abundance of Actinobacteria and high G+C Gram positive bacteria [29] and Bacteroidetes [31] in cold environments. The difference in the diversity of microbial communities may be due to the variance in physicochemical nature of the habitats e.g. differences in geochemistry, altitude, freeze thaw cycles, nutrients, water availability, etc.
The isolates belonging to Proteobacteria were further classified into 3 subgroups Beta-proteobacteria, Gamma-proteobacteria and Alpha-proteobacteria. In our study, a total of 4 isolates of Beta-proteobacteria showed >97% similarity with the species of Alcaligenes while one isolate HT10 was 91% similar to Alcaligenes. Alcaligenes genus was previously recovered from lake sediment of Antarctica [65]. Three isolates LT7, HT16 and HT17 were found similar to Massilia sp. Shivaji et al. [65] also reported Massilia sp. from Pindari glacier, India. Similarly, 3 strains were grouped into genus Ralstonia. Ralstonia is also previously reported from subglacial volcanic lake [66], from Guliya China [67]. The isolate HT20 was similar to Advenella sp. 99%, there is no report of Advenella sp. from psychrophilic habitat.
Gamma-proteobacteria is also one of the prominent group isolated from the polar region, permafrost, alpine and non-polar Himalayan glaciers [1, 17, 26, 27, 65, 68]. The most abundant candidates of this group are Pseudomonas sp., Serratia and Stenotrophomonas sp. The Alpha-proteobacteria group is also commonly recovered from psychrophilic environment. The isolates similar to Ochrobactrum sp. are only reported from non-polar glaciers [51, 69]. In our study, we reported Brucellaceae for the first time from the glaciers.
Four isolates were found to belong to Bacteroidetes phylum. Bacteroidetes are also prevalent in the cold habitats like Alaska [25], Himalayan glaciers [26, 65], Canadian Arctic region [70] and Germany [71]. Firmicutes is also reported as high G+C content bacteria and the 2nd largest reported group from psychrophilic environments. It is reported from almost all cold habitats like Antarctica, Greenland, Alpines and non- polar Himalayan glaciers [1, 2, 17, 27, 29, 51, 65, 66, 71]. Many isolates of this group are <97% identical to known isolates therefore they may be new potent isolates.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 119 Chapter 3 Bacterial Diversity
Similarly, the Actinobacteria group is also reported from almost all psychrophilic bacterial niches from polar to non-polar region [1, 2, 17, 25- 27, 72]. Arthrobacter sp. is the most abundant isolate of this group.
According to the pair- wise base comparison, 13 isolates showed <97% identity with the known organisms in NCBI GenBank. These isolates may be considered as new species. So this will be a good addition to the culturable diversity of bacteria, and exploration of the physiological and genetic properties of these isolates will help in netting the knowledge for microbial survival in extreme condition and production of valuable industrial compounds like antibiotic and enzymes [73]. The 16S rDNA sequence result of HT1 suggested that this strain is first time recovered by culturing method. The study isolate HT1 was similar to uncultured bacteria with Accession No. (KF911124) 98% on BLAST search while 95% similar to the known bacteria Sphingobacterium psychroaquaticum (NR_108297).
The current study was comparable to previous studies documented in literature [74, 75, 76, 77] describing the isolation of bacterial strains with broad spectrum antimicrobial compounds against both fungal and bacterial pathogens. Our results are also in close association with data documented by Biondi et al. [78] and with low temperature psychrophilic bacteria with detection of 35 % antimicrobial producer isolates. Other study reveals 72% [79] and 18% [80] of isolates with antimicrobial activity from Antarctic region. Our results show a considerable ratio of antibiotic producer isolates. This could be due to nutritional limitation in particular environment and such phenomenon might be helpful in interspecies competition.
Here we report 4 highly toxic and 2 least toxic metals to examine the tolerance in psychrophilic and psychrotrophic bacteria isolated from Upper Tirich Mir Glacier, Chitral, Pakistan. This high level of metal resistance in low- temperature isolates might be described by the fact that zinc is a key micronutrient that is involved in cellular function including DNA replication, cell activation and cell division [81, 82]. However, in high temperature isolates the rate of metal resistance was significantly different.
Microorganisms develop various mechanisms to tolerate heavy metals present in their habitat [83]. The resistance in our isolates as well as previous report [84] suggests that
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 120 Chapter 3 Bacterial Diversity the resistance might be heavy metals could be due to presence of multidrug resistance genes as described by metagenomic analysis of Glacier sample by (Rafiq, unpublished data) and multidrug resistant bacteria in these isolates [85] that could possibly lead to antibiotic driven metal co-resistance in these isolates, which is strongly supported by Alonso et al. [86], Summers [87] and Matyar et al. [88]. Antibiotics are widespread among environmental microorganisms even in low anthropogenic environment (Tirich Mir Glacier, Hindu Kush, Pakistan) and Antarctica as described by De Souza et al. [81] and Lo Giudice et al. [89]. The resistance to heavy metals is supposed to be due to overproduction of multiple antibiotic resistance and toxic metabolites efflux pumps in our isolates. The tolerance and resistance in these bacteria might provide a base for bioremediation of different metals as documented by Filali et al. [90] and Malik [91].
We have recovered bacteria by ordinary cultural methods. This gives us a pleasant look inside the culturable bacterial diversity of Tirich Mir glacier. In conclusion, Hindu Kush is one of the main mountain range with huge glaciers of rich ecology. The Tirich Mir glacier is rich bacterial source and we isolated 4 different groups constituting 21 genera with abundance of Proteobacteria and Firmicutes. The isolates tolerated high salt concentration. The isolates of Tirich Mir glacier are versatile in terms of temperature and salt tolerance as compared to those reported from other polar and non-polar isolates. Many isolates does not show much similarity with the existing isolates therefore, further studies are required to identify these isolates.
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[61] Romanenko LA, Schumann P, Rohde M, Lysenko AM, Mikhailov VV, Stackebrandt E. Psychrobacter submarinus sp. nov. and Psychrobacter marincola sp. nov., psychrophilic halophiles from marine environments. Inter J Syst Evol Microbiol 2002; 52: 1291-1297. [62] Vahed SZ, Forouhandeh H, Hassanzadeh S, Klenk HP, Hejazi MA, Hejazi MS. Isolation and characterization of halophilic bacteria from Urmia Lake in Iran. Mikrobiologiia 2011; 80:826-33. [63] Ganzert L, Bajerski F, Mangelsdorf K, Lipski A, Wagner D (2011) Arthrobacter livingstonensis sp. nov. and Arthrobacter cryotolerans sp. nov., salt-tolerant and psychrotolerant species from Antarctic soil. Inter J Syst Evol Microbiol 61(Pt 4): 979-984. [64] Mykytczuk NCS, Foote SJ, Omelon CR, Southam G, Greer CW, Whyte LG (2013) Bacterial growth at -15°C; molecular insights from the permafrost bacterium Planococcus halocryophilus Or1. ISME J 7: 1211–1226. [65] Shivaji S, Pratibha MS, Sailaja B, Kishore K, Singh AK, Begum Z, Anarasi U, Prabagaran SR, Reddy GS, Srinivas TN (2011) Bacterial diversity of soil in the vicinity of Pindari glacier, Himalayan mountain ranges, India, using culturable bacteria and soil 16S rRNA gene clones. Extremophiles: life under extreme conditions 15:1-22. [66] Gaidos E, Marteinsson V, Thorsteinsson T, Jóhannesson T, Rúnarsson AR, Stefansson A, Glazer B, Lanoil B, Skidmore M, Han S, Miller M, Rusch A, Foo W (2008) An oligarchic microbial assemblage in the anoxic bottom waters of a volcanic subglacial lake. ISME J 3: 486-497. [67] Christner BC, Mosley-Thompson E, Thompson LG, Zagorodnov V, Sandman K, Reeve JN (2000) Recovery and identification of viable bacteria immured in glacial ice. Icarus 144:479–485. [68] Katayama T, Tanaka M, Moriizumi J, Nakamura T, Brouchkov A, Douglas TA, Fukuda M, Tomita F, Asano K (2007) Phylogenetic analysis of bacteria preserved in a permafrost ice wedge for 25,000 years. Appl Environ Microbiol 73: 2360-2363. [69] Li G, Jiang H, Hou W, Wang S, Huang L, Ren H, Deng S, Dong H (2012) Microbial diversity in two cold springs on the Qinghai-Tibetan Plateau. Geosci Front 3: 317-325. [70] Bottos EM, Vincent WF, Greer CW, Whyte LG (2008) Prokaryotic diversity of arctic ice shelf microbial mats. Environ Microbiol 10: 950-966. [71] Simon C, Wiezer A, Strittmatter AW, Daniel R (2009) Phylogenetic diversity and metabolic potential revealed in a glacier ice metagenome. Appl Environ Microbiol 75: 7519-7526. [72] Antony R, Krishnan KP, Laluraj CM, Thamban M, Dhakephalkar PK, Engineer AS, Shivaji S (2012) Diversity and physiology of culturable bacteria associated with a coastal Antarctic ice core. Microbiol Res 167: 372-380. [73] Wasim S, Rafiq M, Zada S, Zeb N, Khan I, Shah AA, Hasan F (2015). Phylogenetic analysis of newly isolated protease producing strains from Tirich Mir glacier, Pakistan. Inter J Biosci 7:159-169.
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[74] Asencio G, Lavin P, Alegría K, Domínguez M, Bello H, González-Rocha G, González-Aravena M (2014) Antibacterial activity of the Antarctic bacterium Janthinobacterium sp.: SMN 33.6 against multi-resistant Gram-negative bacteria. Elect J Biotech 17: 1-1. [75] Shekh RM, Singh P, Singh SM, Roy U (2011) Antifungal activity of Arctic and Antarctic bacteria isolates. Pol Biol 34: 139-143. [76] Sanchez LA, Gómez FF, Delgado OD (2009) Cold-adapted microorganisms as a source of new antimicrobials. Extremophile 13:111-120. [77] O'Brien A, Sharp R, Russell NJ, Roller S (2004) Antarctic bacteria inhibit growth of food-borne microorganisms at low temperatures. FEMS Microbiol Ecol 48:157-167. [78] Biondi N, Tredici MR, Taton A, Wilmotte A, Hodgson DA, Losi D, et al. (2008) Cyanobacteria from benthic mats of Antarctic lakes as a source of new bioactivities. J Appl Microbiol 105:105e15. [79] Hemala L, Zhang D, Margesin R (2014) Cold-active antibacterial and antifungal activities and antibiotic resistance of bacteria isolated from an alpine hydrocarbon-contaminated industrial site. Res Microbiol 165: 447-456. [80] Rodríguez-Rojas A, Rodríguez-Beltrán J, Couce A, Blázquez J (2013) Antibiotics and antibiotic resistance: a bitter fight against evolution. Inter J Med Microbiol 303: 293-297. [81] De Souza M-J, Nair S, Loka Bharathi PA, Chandramohan D (2006) Metal and antibiotic-resistance in psychrotrophic bacterial from Antarctic marine waters. Ecotoxicology 15:379–384. [82] Mangano S, Michaud L, Caruso C, Giudice AL (2014) Metal and antibiotic resistance in psychrotrophic bacteria associated with the Antarctic sponge Hemigellius pilosus (Kirkpatrick, 1907). Pol Biol 37: 227-235. [83] Haferburg G, Kothe E (2007) Microbes and metals: interactions in the environment. J Basic Microbiol 47:453-467. [84] Pages D, Rose J, Conrod S, Cuine S, Carrier P, Heulin T, Achouak W (2008) Heavy metal tolerance in Stenotrophomonas maltophilia. PLoS One 3: p.e1539. [85] Hayat M. 2015. Studies on antimicrobial activity of psychrophilic bacteria isolated from Tirich Mir glacier. MPhil Thesis, Department of Microbiology. Quaid-i-Azam University, Islamabad, Pakistan. [86] Alonso A, Sanchez P, Martinez JL (2001) Environmental selection of antibiotic resistance genes. Environ Microbiol 3:1–9. [87] Summers AO (2002) Generally overlooked fundamentals of bacterial genetics and ecology. Clin Infect Dis 34(Supplement 3) pp S85-S92 [88] Matyar F, Kaya A, Dincer S (2008) Antibacterial agents and heavy metal resistance in Gram-negative bacteria isolated from seawater, shrimp and sediment in Iskenderun Bay, Turkey. Sci Total Environ 407: 279–285. [89] Lo Giudice A, Casella P, Bruni V, Michaud L (2013) Response of bacterial isolates from Antarctic shallow sediments towards heavy metals, antibiotics and polychlorinated biphenyls. Ecotoxicol 22:240–250.
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[90] Filali BK, Taoufik J, Zeroual Y, Dzairi FZ, Talbi M, Blaghen M (2000) Waste water bacterial isolates resistant to heavy metals and antibiotics. Curr microbiol 41:151-156. [91] Malik A (2004) Metal bioremediation through growing cells. Environ inter 30:261-278.
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Chapter 3. Bacterial Diversity
Paper 2 (Siachen glacier)
Title:
Muhammad Rafiq, Muhammad, Alexandre M. Anesio, Noor Hassan, Aamer Ali Shah, Fariha Hasan . Metal and antibiotic resistant psychrophilic bacteria from Siachen glacier: natural resistance in bacteria or impact of anthropogenic pollution?
Status: Under review in Journal Research in Microbiology
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 3 Bacterial Diversity
Title: Metal and antibiotic resistant psychrophilic bacteria from Siachen glacier: natural resistance in bacteria or impact of anthropogenic pollution? Authors’s names: Muhammad Rafiqa, Muhammad Hayata, Alexandre M. Anesiob, Noor Hassana, Aamer Ali Shaha, Fariha Hasana* Affiliations: aDepartment of Microbiology, Quaid-i-Azam University, Islamabad, 45320, Pakistan bBristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
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Abstract
Bacterial diversity of previously unexplored Siachen glacier, Pakistan, was studied. Out of 50 isolates 33 (66%) were Gram negative and 17 (34%) Gram positive. About half of the isolates were pigment producers and grow at 4- 37°C. 16S rRNA gene sequences revealed Gram negative bacteria dominated by Proteobacteria, (especially γ-proteobacteria and β-proteobacteria) and Flavobacteria. The genus Pseudomonas (51.51%, 17) dominated γ- proteobacteria. β-proteobacteria constituted 4 (12.12%) Alcaligenes and 4 (12.12%) Janthinobacterium isolates. In Gram positive bacteria phylum Actinobacteria, and Rhodococcus (23.52%, 4) and Arthrobacter (23.52%, 4) as dominating genra. Other bacteria belonged to Phylum Firmicutes with representative genus Carnobacterium (11.76%, 2) and 4 isolates represented 4 genera Bacillus, Lysinibacillus, Staphylococcus and Planomicrobium. Most of the Gram negative bacteria were moderate halophiles, while most of the Gram positives were extreme halophiles and grow up to 6.12 M NaCl. Gram positive bacteria (94.11%) were more resistant to heavy metals as compared to Gram negative (78.79%) and showed multiple heavy metal resistance with maximum tolerance against iron while least tolerance against mercury. More than 2/3 of the isolates showed antimicrobial activity against multidrug resistant S. aureus, E. coli, Klebsiella pneumonia, Enterococcus faecium, Candida albicans, Aspergillus flavus and Aspergillus fumigatus and ATCC strains.
Keywords: Siachen glacier, heavy metal resistance, antimicrobial activity, halophiles, psychrophiles
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Introduction
Glacier is a huge mass of moving ice that runs slowly over the land. Generally, glaciers are stable bodies of ice that consist mostly of re-crystallized snow that displays evidence of depressed slope or outward movement due to gravity. In glacier bionetwork, microorganisms play significant roles in cycling of carbon and other nutrients. For example, snow algae act as primary producers that sustain heterotrophic populations on glaciers, such as copepods, insects, fungi and bacteria [1]. Organic carbon is trapped deep in the glacial ice, the microbes metabolize it and form methane [2], a greenhouse gas. This conversion of carbon to methane could be of significance in climate change [3]. Subglacial microbes perform mineral weathering [4] and making available the minerals and other chemicals as nutrient for fellow life forms. Moss can survive for centuries underneath glaciers, and recolonizes land as the ice retreats [5]. As microorganisms play significant role in subglacial weathering and carbon cycling [6]. There is a potent connection between geochemical signatures in subglacial materials and the metabolic processes occurring in that environment. The physical isolation, low temperatures and permanent darkness of the subglacial environment make subglacial systems ideal sites for studying the relationship between microbial diversity and processes of ecosystem.
Studies have exposed relatively bolted ecosystems in glaciers and other habitats of permanent snow and ice that harbour a diverse range of cold tolerant organisms [1, 7]. Earlier glacial ice has been considered biologically inactive for long or to act only as a life-entrapping medium that collects and preserves microorganisms deposited through rain or snow [8] Scientists have uncovered the fact that glacier can be a favorable environment to support active and diverse communities of micro- as well as macrobiota [9, 10]. The presence of bacteria in polar and non-polar glaciers have been reported by many researchers through both culture-dependent and culture-independent techniques [11-13]. It is proposed that dormant and vegetative forms of bacteria exist under ice of glacier and is adapted to the ecosystem by one or mixture of diverse mechanisms of adaptation [14] . Comparisons of geographically distinct glaciers worldwide have shown a great variation in microbial biomass and community structure [15-17] which is mainly controlled by climatic and environmental factors, including geographic location [6, 18] wind direction, wind speed, light intensity, and
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 131 Chapter 3 Bacterial Diversity availability of nutrients and liquid water [19]. There is some limited evidence of biogeographic effects on the distribution of microorganisms in the geographically different glaciers [15-17, 20] but the factors driving the dynamics of microbial community in glacial systems are still not clear.
Many bacterial species including Pedobacter himalayensis [21], Exiguobacterium indicum [22], Dyadobacter hamtensis [23], Leifsonia pindariensis, Bacillus cecembensis [24], Cryobacterium roopkundense [25], Cryobacterium Pindariense [26], Paenibacillus glacialis [27] have been isolated from snow, water, soil samples of different glaciers, located in Himalaya. [13] reported the psychrotrophic proteolytic bacteria from Gangotri Glacier, Western Himalaya, India. Bacterial population in Roopkund Glacier, Himalayan mountain ranges, was studied by [28]. They found Actinobacteria as the most predominant class, followed by Betaproteobacteria. We know that Actinobacteria are potent producers of antimicrobial compounds and thus can have dominant role in generating a stress on other microbial life to compete for the nutrients. Bacterial diversity of soil sample of Drass, (a town in Kargil District, Jammu and Kashmir, India, and is called 'The Gateway to Ladakh' and is a coldest place after Siberia) was explored and screened for various hydrolytic enzymes. For isolation of bacteria six different growth media (R2A, nutrient agar, King’s B media, tryptic soy agar, Luria-Bertani agar and minimal media) were used, and about 100 bacterial isolates were further differentiated on the basis of colony/cell morphology analysis, pigmentation and growth patterns. Phylogenetic analysis revealed 40 bacteria, grouped into three major phyla, Proteobacteria, Actinobacteria and Firmicutes differentiated into 17 different genera. These isolates were also investigated for production of hydrolases at 4-30°C. All the isolates secreted one or the other hydrolytic enzyme, that is, esterase (90%), lipase (80%), protease (32.5%), amylase (20%), cellulase (17.5%). These results indicate that culturable bacteria in soil of Drass could serve as an ideal candidate region for enzyme bioprospecting.
The aim of the present study was to determine the bacterial diversity in Siachen glacier, Pakistan, and to characterize strains on the basis of different physiological characteristics and determine antibiotic and metal resistance and production of antimicrobial metabolites.
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Materials and methods
Reagents and chemicals
Media, sodium chloride, metal salts, H2SO4 and HCl, NaCl were obtained from Sigma Chemicals Co. (St. Louis, MO, USA). Antibiotic discs were from (Oxoid, Limited, Basingstoke, Hampshire, England). Sample collection The bacterial strains used in this study were isolated from Siachen glacier 35°25′16″N 77°06′34″E/35.421226°N 77.109540°E, Pakistan, following standard protocols. The glacier ice, sediment and water samples were collected in sterile bottles and transported to Microbiology Research Laboratory (MRL), Department of Microbiology, Quaid-i-Azam University, Islamabad. The samples were stored at low temperature for further analysis. Temperature and pH of sample site were also recorded. Isolation and identification of Bacteria The isolation and characterization of culturable bacterial isolates were done according to [29]. About 50 distinct colonies of the isolates were identified according to phenotypic properties like (colony morphology, growth properties pigment production), physiological characteristics (pH, temperature range, sodium chloride tolerance) and 16S rRNA gene sequencing. The accession numbers (GeneBank) of these isolates are submitted to NCBI. In the current study, a total of all the 68 isolates were checked for antibacterial and antifungal metabolite production, metal tolerance and antibiotic resistance. The isolates were consistently cultured on LB agar and R2A agar and stored as glycerol stock at -70°C.
DNA extraction, sequencing and phylogenetic analysis
The bacterial DNA was extracted according to protocols previously described by [30]. . The 16S rRNA sequencing was done by Macrogen Inc. Seoul, Korea. The sequences obtained were further evaluated by comparing the nucleotide sequences available in NCBI database [31]. The evolutionary history was inferred on method based on the Tamura-Nei model [32]. The phylogenetic tree was constructed in MEGA software as described by [32]. at the bootstrap value 1000.
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Deposition for accession number
Sequences of all isolates described in this study were deposited in NCBI under the accession number from KX128918 to KX128967, as the following
HS1 KX128918, HS2 KX128919, HS3 KX128920, HS4 KX128921, HS5 KX128922, HS6 KX128923, HS7 KX128924, HS8 KX128925, HS9 KX128926, HS10 KX128927, HS11 KX128928, HS13 KX128929, HS14 KX128930, HS16 KX128931, HS17 KX128932, HS18 KX128933, HS19 KX128934, HS21 KX128935, HS22 KX128936, HS23 KX128937, HS24 KX128938, HS25 KX128939, HS26 KX128940, HS27 KX128941, HS28 KX128942, HS29 KX128943, HS30 KX128944, LS1 KX128945, LS2 KX128946, LS3 KX128947, LS4 KX128948, LS5 KX128949, LS7 KX128950, LS8 KX128951, LS15 KX128952, LS16 KX128953, LS17 KX128954, LS18 KX128955, LS19 KX128956, LS20 KX128957, LS22 KX128958, LS23 KX128959, LS24 KX128960, LS25 KX128961, LS26 KX128962, LS27 KX128963, LS29 KX128964, LS30 KX128965, LS35 KX128966, LS36 KX128967
Antibiotic resistance
Antimicrobial susceptibility test was performed through disk diffusion method, following the guidelines of the Clinical and Laboratory Standards Institute CLSI, 2013. A total of 9 antibiotics representing different classes of antibiotics; colistin sulphate (CT 10 μg); sulfamethoxazole/trimethoprim (SXT 23.75/1.25 μg), clindamycin (DA 2 μg), Ofloxacin (OFX 5 μg), imipenem (IMI 10 μg), cefotaxime (CTX 30 μg) and nalidixic acid (NA 30 μg), Vancomycin (VA 30 μg) and Methicillin (ME 5 μg) were used for determination of antibiotic resistance. MAR index Multiple antibiotic resistance indexes were carried out using formula: MAR index = a/b, where “a” represents the number of antibiotics to which the isolates were resistant, while “b” represents the total number of antibiotics used. Metal tolerance To check the metal tolerance the stock solution (4000 ppm) of each heavy metal was prepared. The minimum inhibitory concentration of heavy metals was determined using LB medium (Sigma) containing Cd+2, Cr+3, Hg+2, Fe+3 and Ar+3 and Ni+3 (5-
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1300 ppm). The metals were supplemented as CdCl2. 2H2O, CrCl3, HgCL2, FeCl2 and
ArCl3 and NiCl3. The isolates were considered resistant when the minimum inhibitory concentration (MIC) values exceeded that of E. coli and S. aureus used as a control. Screening of Antimicrobial activity The antimicrobial activity was determined by spot on lawn assay. Briefly, the cell suspensions of bacteria, Candida and fungal spores was prepared according to 0.5 McFarland standard and were spread on Muller-Hinton agar and a spot (~ 5 µL) of isolates was applied and incubated at 15°C for 72 to 96 hours. A clear zone of inhibition around the indicator organisms indicated the antagonistic effect. Indicator microorganisms
In order to screen the isolates for antimicrobial compounds production both drug resistant bacterial, fungal cultures and ATCC cultures of bacteria were used. The multidrug resistant isolates including S. aureus, E. coli, Klebsiella pneumonia, Enterococcus faecium, Candida albicans, Aspergillus flavus and Aspergillus fumigatus, while ATCC strains of S. aureus (ATCC6538), E. coli (ATCC10536) and Pseudomonas aeruginosa (ATCC27853) were used as indicator microorganisms.
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Results
Microscopic, morphological and physiological identification
The identification and classification was done according to Zhang et al. [29]. The isolates were placed in two distinct groups on the basis of microscopic analysis. Gram negative bacterial isolates [66% (33)] were more prevalent than Gram positive [34% (17)] bacteria. Almost half of the isolates were observed to produce pigments.
All the isolates could grow at temperature ranging from 4°C to 37 °C, however, these isolates fail to grow at 45°C. Among Gram negative bacteria 81.81% (27 isolates) did not show growth at 37 °C, while 6.06% (2 isolates) failed to grow at 15°C and 6.06% (2 isolates) were unable to grow at 4°C. Among Gram positive bacteria 41.17% (7 isolates) were unable to grow at 37°C, 5.88% (1 isolate) and 11.76% (2 isolates) could not grow at 15 and 4°C, respectively.
The salt tolerance of these isolates was checked and the strains showed a remarkable level of tolerance to increasing concentrations of NaCl ranging from 0.9 to 36% (0.14-6.12 M). The NaCl tolerance ranging from 0.15 to 1.33 M (0.9 to 8%) was observed in 14 (42.42% ) Gram negative bacteria, 15 (45.45%) isolates showed growth at NaCl ranging from 1.33 to 3.4 M (8 to 20%), while 4 (12.12%) isolates showed tolerance to 3.4-6.12 M (20-36%) concentration of NaCl. Of Gram positive bacteria a single bacterial isolate (5.88%) showed growth at 0.9 to 2% (0.15-0.34 M NaCl, 3 (17.64%) isolates showed growth at salt concentration 1.8 - 3.4 M (8 to 20%) while, 13 (76.47%) isolates tolerated 22 to 36% (3.74-6.12 M) NaCl concentration (Table 3.2.1).
Most of the Gram negative isolates belonged to proteobacteria with predominance of γ- proteobacteria and β-proteobacteria. The genus Pseudomonas (17 isolates) dominated the γ- proteobacteria group, while the other genera belonging to this class were Psychrobacter (2 isolates) and Acinetobacter (1 isolate). The Class β- proteobacteria constitutes 4 isolates of Alcaligenes and 4 isolates of Janthinobacterium, however, a single isolate of genus Afipia belongs to class α- proteobacteria. Similarly, Flavobacteria belonging to phylum Bacteroides was represented by Flavobacterium (2 isolates), Chryseobacterium (1 isolate) and 1 novel isolate (Table 3.2.2). Gram positive isolates belonging to phylum and class
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Actinobacteria with dominating genera of Rhodococcus (4 isolates), Arthrobacter (4 isolates), Leucobacter (2 isolates) and Brevibacterium (1 isolate), while Firmicutes with representative genera Carnobacterium (2 isolates) and 4 isolates representing 4 genera including Bacillus, Lysinibacillus, Staphylococcus and Planomicrobium.
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Table 3.2.1. Morphological and microscopic charactarization of study isolates
Isolates Gram Morphology of the colony Pigment Temperature range (°C) NaCl tolerance staining production 4 15 37 Range tested (% ) Optimum range (% ) LS1 -ive White large, convex, diplobacilli/tetrods 0.9–16 2-10
LS 2 -ive Orange, flate dry, diplobacilli 0.9-18 2-10
LS 3 -ive Greyish white, large, Bacilli scattered/diplo 0.9-18 2-6
LS4 -ive White shiny, coccobacilli in scattered form 0.9-14 0.9-2
LS5 -ive White, large and viscous, coccobacilli 0.9-14 2-6
LS15 -ive white transparent, fluidy coccobacilli 0.9-18 2-10
LS20 -ive Orange colour, Diplococci 0.9-22 2-16 LS23 -ive Large yellowish fluidy, thin diplobacilli 0.9-26 2-16
LS24 -ive Extra-large off white rounded, scattered cocci 0.9-18 2-10
LS26 -ive White rounded scattered bacilli 0.9-14 2-6
LS30 -ive Off-white, raised, scattered cocci 0.9-18 2-10
LS35 -ive White circular, coccobacilli 2/3 cell 0.9-12 2-6
LS36 -ive White small rounded colony, coccobacilli 0.9-22 2-14
HS2 -ive Large off-white shiny, mucoid thick bacilli 0.9-4 0.9-2
HS3 -ive Light yellow raised cantered, scattered bacilli 0.9-12 2-6
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HS4 -ive Off-white, like fry egg, bacilli 0.9-36 2-28
HS7 -ive Large orange colour, scattered bacilli 0.9-2 0.9
HS8 -ive Off-white dark opaque, bacilli 0.9-2 0.9
HS9 -ive Yellowish, medium and opaque, bacilli 0.9-8 0.9-2
HS10 -ive Rough surface like fried egg dry diplobacilli 0.9-4 0.9-2
HS11 -ive Light yellow with unique margin bacilli 0.9-8 0.9-2
HS13 -ive White small transparent, 2/3 pair of cells 0.9-8 2-4 HS14 -ive White shiny, medium sized bacilli 0.9-4 0.9
HS17 -ive Large yellow, shiny opaque, scattered bacilli 0.9-8 2-4
HS18 -ive Orange colour, bacilli in scattered form 0.9-10 2-6
HS19 -ive Large flat, orange colour bacilli scattered form 0.9-4 1-2
HS21 -ive Large yellowish flate and transparent bacilli 0.9-8 0.9-2
HS22 -ive Pale yellow, large flate transparent, bacilli 0.9-6 1-2
HS23 -ive Deep orange colour, thin coccobacilli 0.9-8 2-6
HS24 -ive Extra-large, raised convex fluidy water bacilli 0.9-10 1-2
HS25 -ive Large bright yellow, opaque, bacilli 0.9-8 0.9-2
HS26 -ive Off white large rough surface dry, bacilli 0.9-12 1-4
HS28 -ive Light yellow, raised opaque thick coccobacilli 0.9-14 2-10
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 139 Chapter 3 Bacterial Diversity
LS7 +ive Deep yellow, large sticky, rods 0.9-14 2-6
LS8 +ive Large white, thick rods, in pair of 2/4 cells 0.9-26 2-18
LS16 +ive Yellow, medium sized diplobacilli 0.9-22 2-16
LS17 +ive White, thick diplobacilli 0.9-22 2-16
LS18 +ive Brownish white , Bacilli 0.9-22 2-14
LS19 +ive White, cocci or diplococci 0.9-18 2-14
LS22 +ive Small orange to light yellow, diplobacilli 0.9-22 2-16
LS25 +ive Large white colony, diplobacilli 0.9-22 2-14
LS27 +ive Yellow rounded streptococci 0.9-26 2-20
LS29 +ive Purple colour colony, scattered cocci 0.9-18 2-12
HS1 +ive White, medium sized, cocci 0.9-36 2-26
HS5 +ive Yellowish colony, thick bacilli 0.9-36 2-24
HS6 +ive Light yellow colony, bunch/ chain form 0.9-36 2-26
HS20 +ive White, large and opaque, staphylococci 0.9-2 0.9
HS27 +ive Yellow, medium sized, short/thick bacilli 0.9-36 2-28
HS29 +ive Dark orange, diplococci 0.9-22 2-14
HS30 +ive Small white, bacilli 0.9-22 2-10
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Phylogenetic analysis The evolutionary history was inferred by using the Maximum Likelihood method based on the Tamura-Nei model 42. The tree with the highest log likelihood (- 4713.0244) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 53 nucleotide sequences. Codon positions included were 1st+2nd+3rd+Noncoding. All positions containing gaps and missing data were eliminated. There were a total of 593 positions in the final dataset. Evolutionary analyses were conducted in MEGA6 [30]. The phylogenetic tree of both High and Low temperature isolates are given as Fig. 3.2.1 & Fig. 3.2.2.
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HS9 Pseudomonas salomonii (HG424436) Pseudomonas fluorescens (KT580595) HS8 Pseudomonas antarctica (KR233795) HS21 HS22 HS3 HS28 HS2 HS24 HS11 Acinetobacter johnsonii (KF831405) Acinetobacter johnsonii (KR002423) HS14 HS23 Uncultured bacterium (KJ454279) Unidentified marine bacterioplankton (KC002372) HS4 Janthinobacterium sp.(KT767678) HS7 Janthinobacterium sp.(JQ977347) HS17 HS19 HS18 Alcaligenes faecalis (JQ612515) HS10 Alcaligenes sp.(KP318054) Alcaligenes faecalis (KP318053) HS25 HS6 Brevibacterium epidermidis (KT818810) Brevibacterium epidermidis (HQ455048) Arthrobacter citreus (KR233753) HS27 Arthrobacter citreus (HQ323433) HS13 Leucobacter sp.(HQ436424) Leucobacter komagatae (KC845231) HS16 Leucobacter komagatae (EU370411) Uncultured bacterium (AM696996) Carnobacterium sp.(EU517560) HS30 HS1 Staphylococcus lentus (KT260509) Staphylococcus lentus (KT260621) HS5 Lysinibacillus fusiformis (KP192008) Lysinibacillus fusiformis (KP191979) Planococcus sp. (HM352391) HS29 Planococcus sp. Smarlab (AY538695)
0.05
Fig. 3.2.1. Molecular Phylogenetic analysis of HTS (15°C) by Maximum Likelihood method
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Rhodococcus erythropolis (KT369969) Rhodococcus erythropolis (KM670434) LS17 LS7 Rhodococcus sp.(JQ977382) Rhodococcus sp.(AM942744) Rhodococcus qingshengii (KT265744) LS25 Rhodococcus erythropolis (KR906527) Rhodococcus qingshengii (KT958885) Rhodococcus sp.(KR919795) LS22 Rhodococcus sp.(KR611864) Rhodococcus sp. (KP715893) Rhodococcus sp. (KM361868) Rhodococcus fascians (KM262809) Rhodococcus fascians (KM262808) LS27 Arthrobacter sp.(KR085774) Arthrobacter sp.(KF870410) Arthrobacter sp.(HF563566) LS16 LS18 Arthrobacter sp.(JX949309) Uncultured bacterium (EU466451) Arthrobacter citreus (KR085774) Bacillus simplex (KR085785) Bacillus simplex (JX840386) Bacillus simplex (KR233764) LS8 LS19 Carnobacterium jeotgali (NR 116460) Uncultured bacterium (EU845269) Uncultured bacterium (EU844893) Janthinobacterium svalbardensis (KR085903) Janthinobacterium sp. (KM187530) Janthinobacterium lividum (KR233788) Janthinobacterium sp (KT767678) Janthinobacterium sp (EU584527) LS1 Janthinobacterium sp (JQ977347) LS24 Psychrobacter sp.(JX196606) Psychrobacter maritimus (JQ409519) Psychrobacter sp.(JX196620) LS20 LS4 Pseudomonas fragi (AM933514) LS3 LS2 LS30 Pseudomonas deceptionensis (KR338996) Pseudomonas sp.(HF911369) Pseudomonas fragi (AB685632) Pseudomonas veronii (KT767928) Pseudomonas veronii (KP976104) LS26 LS15 Pseudomonas reinekei (KC790261) LS5 Pseudomonas reinekei (KR085824) Pseudomonas reinekei (NR 042541) Chryseobacterium antarcticum (AY553293) Chryseobacterium antarcticum (NR 025809) LS23 Chryseobacterium antarcticum (KJ958494) Flavobacterium antarcticum (KF054987) Flavobacterium antarcticum (NR 042998) LS35 LS36 LS29 Uncultured bacterium (EF509349) Uncultured bacterium (KF911155) Uncultured bacterium (HM270849)
0.05
Fig. 3.2.2. Molecular Phylogenetic analysis of low temperature isolates (LTS) by Maximum Likelihood method
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Antibiotic resistance A total of 9 antibiotics (5, broad spectrum antibiotics, 2 antibiotics against Gram positive and 2 against Gram negative bacteria) were used to evaluate the antibiotic resistance pattern. Interestingly these isolates showed some varying resistance to all antibiotics used in the current study. Among Gram negative study isolates, more resistance was found against imipenem (51.51%, 17 isolates) then cefotaxime (CTX) and clindamycin (DA) each 45.45%, (15 isolates) followed by resistance to Ofloxacin (OFX) 24.24%, 8 isolates. Only 21.21%, (7 isolates) showed resistance to colistin sulphate (CT), 15.15%, 5 isolates were resistant to Nalidixic acid, while 12.12%, 4 isolates were resistant to sulfamethoxazole/trimethoprim (SXT). The Gram positive isolates were highly resistant to majority of the antibiotics. Resistance to cefotaxime (CTX) was more prevalent in 76.47% (13 isolates) followed by resistance to imipenem and Vancomycin in 64.70%, 11 strains each. Resistance to CTX and Methicillin was observed in 58.82% (10 isolates). Only (11.76%, 2 isolates showed resistance to Ofloxacin while all the isolates were sensitive to combination of sulphamethaxazole/trimethoprim (Table. 3.2.2) Table 3.2.2. Comparative study of bacteria isolates resistant to different antibiotics
Gram negative (n = 33) Gram positive (n = 17) Antibiotics S I R S I R Imipenem 48.48 0.0 51.51 35.29 0.0 64. 70 Oflaxacin 75.75 0.0 24.24 88.23 0.0 11.76 Sulfamethoxazole/ 87.87 0.0 12.12 94.12 5.88 0.0 trimethoprim Cefotaxime 54.54 0.0 45.45 11.76 11.76 76.47 Clindamycin 45.45 9.09 45.45 29.41 11.76 58.82 Colistin sulphate 69.7 9.09 21.21 NA NA NA Nalidixic Acid* 72. 12.12 15.15 NA NA NA Methicillin NA NA NA 35.29 5.88 58.82 Vancomycin NA NA NA 17.65 17.64 64.70 Key: S – Sensitive, R – Resistant, I – Intermediate
Multiple Antibiotic Resistance (MAR) Index Multiple antibiotic resistance index were determined using formula (MAR index = a/b), where ‘a’ is number of antibiotics to which the isolates were resistant, while ‘b’ represents the total number of antibiotics. Among Gram negative bacteria, 78.79% (26
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 144 Chapter 3 Bacterial Diversity isolates) were resistant to multiple antibiotic resistance, 9.09% (3 isolates) showed resistance to 1 antibiotic and 12.12% (4 isolates) were sensitive to all antibiotics (Table. 3.2.3). About 94.11% (16 isolates) Gram positive bacteria showed multiple antibiotic resistance, while 5.89% (1 isolate) showed resistance to a single antibiotic (Table 3.2.4). Screening for antimicrobial activity All the 50 isolates were screened for their antimicrobial activity. Among Gram negative bacteria, 13 (39.39%) isolates showed antimicrobial activity against 4 or more than 4 test strains, while 3 distinct isolates showed inhibitory effects against 1, 2 and 3 isolates. About 3 (17.64%) Gram positive bacteria showed antimicrobial activity against 1 test strain, 3 (17.64%) showed activity against 3 and 2 (11.76%) of the isolates showed antimicrobial activity against 4 or more than 4 test strains (Table 3.2.3 & 3.2.4).
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Table 3.2.3. Antibiotic resistance and production of antimicrobial compounds in Gram negative bacteria isolated from Siachen Glacier
Isolate Nearest phylogenetic Antibiotic resistance and production of antimicrobial compounds in Gram negative bacteria s species* Antibiotic Resistance and Antibacterial and antifungal activity sensitivity pattern
IMI CTX CT NA SXT OFX DA MAR index S. aureus* E. coli* P. aeruginosa* C. albicans A. fumigatus A. flavus S. aureus E. coli K. pneumonia Enterococcus Gammaproteobacteria LS 2 Pseudomonas sp. R R I R S S I 0.71 - 1 2 - - - - - 1 1 LS 3 Pseudomonas fragi S S I S S S R 0.28 - - - - - NA NA NA NA NA LS4 Pseudomonas fragi S R S S S S R 0.28 - - - - - NA NA NA NA NA LS5 Pseudomonas reinekei S R R S R R S 0.57 1 - - - - NA NA NA NA NA LS15 Pseudomonas sp S R R I S S R 0.57 - - - - - NA NA NA NA NA LS20 Psychrobacter sp. S S S I S S R 0.28 - - - - - NA NA NA NA NA LS26 Pseudomonas veronii S R S S S S S 0.14 - - - - - NA NA NA NA NA LS30 Pseudomonas fragi R R S S S S R 0.42 - - - 2 1 1 NA NA NA NA HS2 Pseudomonas fragi S S S S S S R 0.14 - - - - - NA NA NA NA NA HS3 Pseudomonas R S S S S S R 0.28 - - - - - NA NA NA NA NA deceptionensis HS8 Pseudomonas antarctica R S S I R S S 0.42 - - - - NA NA NA NA NA HS9 Pseudomonas salomonii R S S S R S S 0.28 1 1 1 1 1 1 1 1 1 1 HS11 Pseudomonas S S S S S S S 0.00 1 1 1 1 - - - 1 1 -
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frederiksbergensis HS14 Acinetobacter johnsonii S S S S S S S 0.00 1 2 1 2 2 2 1 - 1 1 HS21 Pseudomonas sp. R S R S S R R 0.57 1 2 2 2 - - 1 1 - - HS22 Pseudomonas S S R I S R S 0.42 - - - - - 1 1 NA NA NA arsenicoxydans HS23 Psychrobacter sp. R S S S S R S 0.28 - - - - - NA NA NA NA NA HS24 Pseudomonas sp. R S S R R S I 0.57 - - - - - NA NA NA NA NA HS26 Pseudomonas sp. S R S S S S S 0.14 - - - - - NA NA NA NA NA HS28 Pseudomonas sp. R R S S S S R 0.42 - - - - - NA NA NA NA NA Betaproteobacteria LS1 Janthinobacterium sp. R S I S S S S 0.28 - - - - - NA NA NA NA NA LS24 Janthinobacterium sp. R R S S S S R 0.42 2 2 1 1 - 2 1 - - - HS4 Janthinobacterium lividum S S S S S S S 0.00 - - - - - NA NA NA NA NA HS7 Janthinobacterium sp. S R S S S S I 0.28 - - - - - NA NA NA NA NA HS10 Alcaligenes sp. R R S R S S S 0.42 1 1 - 2 2 2 - - 1 - HS17 Alcaligenes sp. HT4-MRL S R R S S R S 0.42 1 1 1 1 - 1 - 1 1 - HS18 Alcaligenes faecalis R S S S S R S 0.28 1 1 1 2 - 1 2 - 1 - HS19 Alcaligenes sp. HT4-MRL R S R S S S R 0.42 1 1 - 1 - - 1 - - - Alpha proteobacteria HS25 Afipia sp. S S S S S S S 0.00 - - - - - NA NA NA NA NA Flavobacteria LS23 Chryseobacterium S R S S S S R 0.28 - - - - - NA NA NA NA NA antarcticum Novel isolate R S S R R R S 0.57 2 2 1 - - - - - 1 1 LS29 gb|EF509349.1|
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LS35 Flavobacterium R R R R S R R 0.85 2 2 - - 1 - 1 1 1 - antarcticum LS36 Flavobacterium R R S S S S R 0.42 2 2 2 1 - 2 1 1 2 - antarcticum
Table 3.2.4. Antibiotic resistance, mutliple antibiotic resistant (MAR) index and antimicrobial activity of Gram positive bacterial isolates
Isolates Nearest phylogenetic neighbour Antibiotic resistance and antimicrobial compounds production in Gram Positive bacteria or belonging to the species* Resistance to antibiotics Antimicrobial and antifungal compounds
IndexR
IMI OFX SXT CTX DA VA ME MA S. auroes* E. coli* P. aeruginosa* A. flavus A. fumigatus C. albicans
S. S. aureus E. coli K. pneumoniae Enterococcus Actinobacteria LS7 Rhodococcus sp. R S S R R R R 0.71 - 1 - NA NA NA NA - - - Rhodococcus erythropolis R S S R S I R 0.57 - - - NA NA NA NA - - - LS17 LS22 Rhodococcus sp. S S S R R R R 0.57 - - - NA NA NA NA - - - LS25 Rhodococcus sp. S S S R R R R 0.57 - - - 1 - - - 2 2 1 LS16 Arthrobacter sp. S S S I S R S 0.14 1 - - NA NA NA NA - - - LS18 Arthrobacter sp. R S S R R R R 0.71 - - - NA NA NA NA - - - LS27 Arthrobacter sp. R S S R R R R 0.71 - - - NA NA NA NA - - 2 HS27 Arthrobacter citreus R S S I S S R 0.42 - - - NA NA NA NA - - - HS13 Leucobacter R S S R S R R 0.57 - 2 1 - - 2 1 - - 1 HS20 Leucobacter sp. S R S R I S R 0.57 - - - NA NA NA NA - - -
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HS6 Brevibacterium sp. R S I R R I R 0.85 - - - NA NA NA NA Bacilli LS8 Bacillus simplex R S S R R R R 0.71 - 2 1 - - - 1 - - - HS5 Lysinibacillus fusiformis S R S R I I S 0.57 ------1 1 2 LS19 Carnobacterium pleistocenium R S S R S S S 0.28 - - - NA NA NA NA - - - HS30 Carnobacterium alterfunditum R S S S R R S 0.42 ------1 1 2 HS1 Staphylococcus lentus S S S R R R I 0.57 - - - NA NA NA NA - - - HS29 Planomicrobium sp R S S S S R S 0.28 - - - NA NA NA NA - - -
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Metal tolerance
All isolates were screened for their tolerance against 6 different metal ions and minimum inhibitory concentration was determined. Among Gram negative bacteria the minimum inhibitory concentration of Cadmium were 651-850 ppm in (36.36%, 12 isolates), (39.39%, 13 isolates) and (54.54%, 18 isolates) showed tolerance to 651-850 ppm of chromium and nickel respectively, 27.27%, 9 isolates tolerate arsenic level ranging from 851-1050, and (27.27%, 9 isolates tolerate iron level greater than 1050 ppm, however the MIC level in case of Mercury was ≤ 50 in 18 (54.54%) isolates. Of Gram positive bacteria 8, 47.05% isolates showed tolerance to cadmium and 6 (35.29%) showed tolerance to nickel, in the range of 651-850 ppm. Minimum inhibitory concentration of chromium was 451-651 ppm in 5 isolates while 5 (29.41%) isolates showed tolerance to 851-1050 ppm of cadmium. A minimum inhibitory concentration of arsenic and iron ranging from (851-1050 ppm) was noted in 6 (35.29%) and 7 (41.17%) isolates respectively. The MIC of mercury was ≤ 50 in 11 (64.70%) while the highest tolerable level was observed ˂ 120 ppm in mercury. The comparative analysis of both Gram positive and Gram negative bacterial strains is given in Table 3.2.5.
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Table 3.2.5. Tolerance of Gram negative and Gram positive bacteria to varying concentrations of metal ions Represe Heavy metal concentration (µL/mL or PPM) ntative Metal ≤ 50 51-250 251-450 451-650 651-850 851-1050 >1050 groups Cadmium All All 18.18, 6 24.24, 8 36.36, 12 12.12, 4 9.09, 3 Gram Chromium All All 24.24, 8 30.31, 10 39.39, 13 6.06, 2 non negative Arsenic All 9.09, 3 15.15, 5 24.24, 8 21.21, 7 27.27, 9 6.06, 2 bacteria Nickel All 12.12, 4 9.09, 3 18.18, 6 54.54, 18 3. 03, 1 non n= 33 Iron All All 15.15, 5 12. 12, 4 21.21, 7 24.24, 8 27.27, 9 Mercury 54.54, 18 45.46 , 15 Non Non Non Non Non Cadmium All All All 23.52, 4 47.05, 8 17.64, 3 11.76, 2 Gram Chromium All All 17.64, 3 29.41, 5 23.52, 4 29.41, 5 non positive Arsenic All All 5.88, 1 23.52, 4 29.41, 5 35.29, 6 5.88, 1 bacteria Nickel All 11.76, 2 23.52, 4 17.64, 3 35.29, 6 11.76, 2 non n= 17 Iron All All 5.88, 1 17.64, 3 29.41, 5 41,17, 7 17.64, 3 Mercury 64.70, 11 35.29, 6 Non Non Non Non Non
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Discussion
To our understanding, this is the first time that the diversity of antibiotic producing, metal and antibiotic resistant bacteria isolated from Siachen glacier are studied. In the current research work, Gram negative bacteria were found to be dominant and abundant as compared to Gram positive bacteria, which is in a close association with previous studies [33-35] who also reported high prevalence of Gram negative bacteria with predominance of γ-proteobacteria, α-proteobacteria and β-proteobacteria in Finish Lapland. The dominance of bacterial diversity in a particular glacier or cold environments might be due to the seasonal variation in glaciers which can counter- select the bacteria with greater adaptability. Boetius et al. [36] identified bacterial isolates with greater abundance of Gram positive bacteria which is contradictory to our finding. The predominance of Gram negative bacteria in the current study could be related to the psychrophilic nature of Gram negative bacteria, as psychrophiles have been reported to grow faster and out-compete psychrotrophic bacteria [37]. In our study, the bacterial isolates were identified on the basis of 16S rRNA genes. Many researchers have identified and documented the microbial diversity of glaciers on the basis of 16S rRNA gene sequnces [38-42]. There was a significant difference in terms of growth range among Gram negative and Gram positive bacteria. Most of the Gram negative bacteria (78.78%) were able to grow at 15°C, while most of the Gram positive (58.82 %) isolates were able to grow at 37°C. According to definition of Turley [43], the Gram negative bacteria can be placed in psychrophilic, while Gram positive isolates in psychrotrophic bacteria. Previously, Carpenter et al. [44] identified bacteria from South Pole snow, all of which were true psychrophiles while, Morita [45] isolated and characterised bacteria from Ellesmere Island ice as psychrotrophs. The temperature of Siachen glacier stays below 0°C and plunges to -41°C in winters or may rise to 11°C during summers [46]. It is unclear how these bacteria survive under such a diverse conditions. However, the survival of psychrotrophic bacteria in extremely stressful conditions is due to formation of spores in Gram positive bacteria as described earlier [47-49]. Their findings strongly support our study as most of the Gram positive bacteria in our study were psychrotrophic and spore formers. Spore formation might help overcome the stress conditions to low temperature, desiccation and damage of bacteria by UV [50, 51]. The possible mechanism of survival in Gram negative bacteria could be
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 152 Chapter 3 Bacterial Diversity associated with upregulation of desaturase genes and increase of membrane lipids like Poly-unsaturated fatty acids (PUFAs) in association with decrease in temperature [52, 53]. Our isolates also showed tolerance to different concentrations of NaCl ranging from 0.14-6.12 M (0.9 to 36%). In active ecological environment in glacial habitats, water nuclei forms inside glacier mass, the solutes around that environment diffuse to this active ecological environment and make it hypertonic. The exposure of bacteria to such a condition leads to salt tolerance. In our isolates the increased tolerance could be due to this phenomenon. Interestingly, the elevated salt tolerance in our isolates above 5.1 molar concentration is reported for the first time, although detailed investigation and research is required to investigate the phenomenon of such a high tolerance in depth. The current research also showed increased antibiotic resistance in our isolates. Previous investigations from pristine cold environments like ancient Siberian permafrost, alpine glacier cryoconite and non-anthropogenic alpine soil [29, 54, 55] opposed our results as bacteria from such environments have been reported to have greater sensitivity to antibiotics. However, wide distribution and multiple antibiotic resistance genes have been previously documented in different glaciers except antarctic glaciers and has been well described by transmission of migratory birds and air borne bacteria [56] . Our isolates also showed increased tolerance to various heavy metals. Previous reports [57, 58] also supported our findings, however, the studies does not include all the heavy metals as used in our studies. This is the first study from Siachen glacier, Pakistan, related to intrinsic property of low temperature bacteria to demonstrate metal and antibiotic resistance with antimicrobial activity. Siachen glacier is known as the world’s highest non-polar glacier and considered as the highest and world’s biggest garbage dump, 40% of which are plastics and metals, worn out gun barrels, splinters from gun shelling, empty fuel barrels and burnt shelters [59], which permanently pollute glacial ice and water and leaching toxins like cobalt, cadmium, chromium and other metals due to unavailability of natural biodegrading agents [59]. The heavy metal tolerance could possibly be due to these pollutants, and could possibly lead to antibiotic resistance too, as metal and antibiotic resistance is often present as co-resistance. On the other hand Siachen glacier is the world’s highest warzones. The antibiotic resistance in such area could also be due to
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 153 Chapter 3 Bacterial Diversity army patrolling that might harbour pathogenic or opportunistic bacteria that can transmit resistance genes to environmental bacteria. The third possible reason to antibiotic resistance is the production of antimicrobial compounds that leads to natural resistance in such bacteria. About 40% of the isolates produced antimicrobial compounds against American Type Culture Collection (ATCC) and clinical isolates of bacteria, yeasts and molds. Our results are strongly supported by works of previous scientists [60-62] who identified potent bacterial isolates from diverse cold habitats, a large number of which produced antimicrobial compounds. However, our results are in contrast to the research carried out by many scientists [63-66] on Antarctic, arctic, Argentine soil and marine organisms. The low temperature habitats are less explored as compared to mesophiles and data regarding antimicrobial compounds is very rare. Therefore, it is necessary to study these isolates along with neighbour glaciers, ice caps and glacial lakes to reveal the microbial compounds. We conclude that the bacteria belonging to diverse groups were present with Pseudomonas as the most dominant genus, with Gram positive more abundant than the Gram negative bacteria. Low temperature adapted bacteria isolated from Siachen glacier, showed varying degree of resistance to heavy metals and commonly used antibiotics and also they showed pronounced ability to inhibit the other ATCC as well as pathogenic bacteria. They were also moderate to extreme halophilic in nature.
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[47]. https://www.meteoblue.com/en/weather/forecast/modelclimate/siachen-glacier pakistan 1164949 [48]. Sheridan PP, Miteva VI, Brenchley JE, Phylogenetic analysis of anaerobic psychrophilic enrichment cultures obtained from a Greenland glacier ice core. Appl Environ Microbiol 2003; 69:2153-2160. [49]. Miteva VI, Brenchley JE. Detection and isolation of ultrasmall microorganisms from a 120,000-year-old Greenland glacier ice core. Appl Environ Microbiol 2005; 71:7806-7818. [50]. Yung PT, Shafaat HS, Connon SA, Ponce A. Quantification of viable endospores from a Greenland ice core. FEMS Microbiol Ecol 2007; 59:300-306. [51]. Nicholson WL, Munakata N, Horneck G, Melosh HJ, Setlow P. Resistance of Bacillus endospores to extreme terrestrial and extraterrestrial environments. Microbiol Mol Biol Rev 2000; 64:548-572. [52]. Onyenwoke RU, Brill JA, Farahi K, Wiegel J. Sporulation genes in members of the low GþC Gram-type-positive phylogenetic branch (Firmicutes). Arch Microbiol 2004; 182:182-192. [53]. Okuyama H, Orikasa Y, Nishida T, Watanabe K, Morita N. Bacterial genes responsible for the biosynthesis of eicosapentaenoic and docosahexaenoic acids and their heterologous expression. Appl Environ Microbiol 2007; 73:665-670. [54]. Bergé JP, Gilles B. "Fatty acids from lipids of marine organisms: molecular biodiversity, roles as biomarkers, biologically active compounds, and economical aspects." In Marine biotechnology 2005; 49-125. [55]. Zhang D, Schumann P, Liu HC, Xin YH, Zhou YG, Schinner F, et al. Arthrobacter alpinus sp. nov., a psychrophilic bacterium isolated from alpine soil. Int J Syst Evol Microbiol 2010; 60:2149-2153. [56]. Zhang D, Busse HJ, Liu HC, Zhou YG, Schinner F, Margesin R. Sphingomonas glacialis sp. nov., a psychrophilic bacterium isolated from alpine glacier cryoconite. Int J Syst Evol Microbiol 2011; 61:587-591. [57]. Segawa T, Takeuchi N, Rivera A, Yamada A, Yoshimura Y, Barcaza G, et al. Distribution of antibiotic resistance genes in glacier environments. Environ Microbiol Rep 2013; 5:127-134. [58]. Mangano S, Luigi M, Caruso C, Giudice AL. Metal and antibiotic resistance in psychrotrophic bacteria associated with the Antarctic sponge Hemigellius pilosus (Kirkpatrick, 1907). Polar Biol 2014; 37:227-235. [59]. Tomova I. Characterization of heavy metals resistant heterotrophic bacteria from soils in the Windmill Islands region, Wilkes Land, East Antarctica. Polish Polar Research 2014; 35(4):593-607. [60]. Kemkar NA. Environmental peacemaking: Ending conflict between India and Pakistan on the Siachen Glacier through the creation of a transboundary peace park. Stan Envtl LJ 2006; 25:67. [61]. Hemala L, Zhang D, Margesin R. Cold-active antibacterial and antifungal activities and antibiotic resistance of bacteria isolated from an alpine hydrocarbon-contaminated industrial site. Research in Microbiology 2014; 165:447-456
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[62]. Dimitrova S, Pavlova K, Lukanov L, Korotkova E, Petrova E, Zagorchev P, Kuncheva M. Production of metabolites with antioxidant and emulsifying properties by Antarctic strain Sporobolomyces salmonicolor AL1. Applied biochemistry and biotechnology. 2013 Jan 1;169(1):301-11. [63]. Biondi N, Tredici MR, Taton A, Wilmotte A, Hodgson DA, Losi D, et al. Cyanobacteria from benthic mats of Antarctic lakes as a source of new bioactivities. J Appl Microbiol 2008; 105:105-115. [64]. Sanchez LA, Gomez FF, Delgado OD. Cold-adapted microorganisms as a source of new antimicrobials. Extremophiles 2009; 13: 111-120. [65].O'Brien A, Sharp R, Russell NJ, Roller S. Antarctic bacteria inhibit growth of food-borne microorganisms at low temperatures. FEMS Microbiol Ecol 2004; 11:157e67. [66]. Lo-Giudice A, Bruni V, Michaud L. Characterization of Antarctic psychrotrophic bacteria with antibacterial activities against terrestrial microorganisms. J Basic Microbiol 2007; 47:496-505.
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Chapter 3. Bacterial Diversity
Paper 3 (Passu glacier)
Title:
Muhammad Rafiq, Muhammad Hayat, Noor Hassan, Muhammad Ibrar, Abdul Haleem, Maliha Rehman, Faisal Ahmad, Aamer Ali Shah, Fariha Hasan. Characterization of antibacterial compounds produced by psychrotrophic Alcaligenes faecalis HTP6 isolated from Passu glacier, Pakistan
Status: Accepted in journal “International journal of Biosciences”
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 3 Bacterial Diversity
Characterization of antibacterial compounds produced by psychrotrophic Alcaligenes faecalis HTP6 isolated from Passu glacier, Pakistan Muhammad Rafiq, Muhammad Hayat, Noor Hassan, Muhammad Ibrar, Abdul Haleem, Maliha Rehman, Faisal Ahmad, Aamer Ali Shah, Fariha Hasan Department of Microbiology, Quaid-i-Azam University, Islamabad, Pakistan
Abstract
Low temperature microorganisms can produce secondary metabolites including anticancer, antiviral and antibacterial compounds. The purpose of the study was to evaluate the possibility of using cold adapted bacteria for production of antibiotics. In the present research work, bacteria were isolated from sediment sample, collected from Passu glacier, using R2A medium. These isolates were screened for their resistance towards various antibiotics, antimicrobial activity against P. aeruginosa, E. coli, S. aureus, E. faecalis, C. albicans and A. fumigatus and storage stability of crude extract along with cytotoxicity and haemolytic activity. The isolate HTP6 showed best inhibition using spot on lawn test and was selected for further study. The isolate HTP6 was Gram negative, non-pigmented rod, moderate halophilic, with optimum growth at mesophilic range and was identified as Alcaligenes faecalis HTP6 on the basis of 16S rRNA gene sequence analysis. The strain showed resistance to clindamycin, cefotaxime and sulfamethoxazole/trimethoprim and was able to inhibit P. aeruginosa, E. coli, S. aureus, E. faecalis, C. albicans and A. fumigatus. Maximum growth and inhibitory activity of Alcaligenes faecalis HTP6 was observed against selected ATCC strains [Staphylococcus aureus (ATCC 25923) and Pseudomonas aeruginosa (ATCC 27853)] and various clinical isolates (S. aureus, E. faecalis, Candida albicans and Aspergillus fumigatus) at pH 7 and 30°C, when LB (Luria
Bertani) and LB1 (medium supplemented by FeSO4) broth media were used. The crude extract showed good storage and thermal stability at 55°C, and pH stability at 7 along with brine shrimp lethality up to 30%, however, there was no DNA binding and haemolytic activity observed. We can conclude from the study that Alcaligenes faecalis HTP6, isolated from Passu glacier, can be a good candidate for the production of wide spectrum potent thermostable antibiotic with less cytotoxicity. Keywords: Psychrotrophic Alcaligenes faecalis HTP6, Passu glacier, Antimicrobial compound
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Introduction
Low temperature environments are the world’s biggest extreme locations, provide harsh conditions for life but still harbour large microbial community. They usually require particular adaptations by the microbial community for its successful colonization and survival (Margesin and Miteva, 2011). Many microorganisms are reported to possess the ability to adapt and even thrive in these harsh conditions of low temperature, low water availability and nutrient deficiency (Feller and Gerday, 2003). The microbes living in harsh conditions like glaciers, harbour many extraordinary characteristics. These characteristics may include tolerating low temperature shocks, high salinity, capability of producing antibiotics, extracellular polysaccharides and different commercially important enzymes (Sajjad et al., 2015). The microbes living there evolved different adaptive mechanisms to subside the harmful effects of nature like stress conditions; desiccation, radiation, extreme pH, high osmotic pressure and low nutrient availability (Tehei et al., 2005; Morgan-kiss et al., 2006; Rodrigues and Tiedje, 2008). Antibiotic production in cold environments, enable microorganisms to reduce interspecies competition in such limited nutrient availability during their life cycle (O’Brien et al., 2004). Cold environments are less explored that prompt the scientist’s interest due to the probability of new species with potential for valuable antibiotics (Bruntner et al., 2005). There are a few reports on antimicrobial compounds from low temperature environment like marine as well as from terrestrial environments. The reports (Bruntner et al., 2005; Al-zereini et al., 2007; Shekh et al., 2011) on secondary antimicrobial compounds from low temperature bacterial isolates are mostly restricted to Polar regions.
The bacteria from genus Alcaligenes are relatively less reported for the production of antibiotics or antimicrobial compounds than Actinomycetes (Kapley et al., 2013). There are two species of genus Alcaligenes with genome drafts in NCBI GenBank (Kapley et al., 2013) that demonstrate the antimicrobial potential against pathogenic bacterial strains. The genome draft of Alcaligenes sp. HPC1271 identified six metabolite synthesizing clusters and suggested amongst them non-ribosomal peptide synthase (NRPS) and dTDP-glucose 4,6-dehydratase showed their role in antibiotic synthesis (Kapley et al., 2013). Species of genus Alcaligenes has the ability to
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 162 Chapter 3 Bacterial Diversity produce antimicrobial compounds against bacteria, fungi and as well algae (Jayanth, 2001).
The reports showed that A. faecalis has the ability to produce broad range antimicrobial compounds against Gram positive/ negative bacteria and fungi (Honda et al., 1998; Li et al., 2007; Zahir et al., 2013). Alcaligenes sp. was reported for the production of antibiotic Kalimantacin A, B and C active against MDR Staphylococcal pathogens. Alcaligenes sp. HPC1271 synthesized nucleoside antibiotic, the tunicamycin, which was initially reported from Streptomyces (Kapley et al., 2013).
To the best of our knowledge there is no published data regarding the antimicrobial activity of microorganisms isolated from Karakoram range. Over all few reports is available regarding the antimicrobial compounds from glaciers’ microorganisms. It is the need of time to explore such habitats for microbes having potential to produce novel secondary metabolites including antimicrobial compounds. Therefore, in the current study, bacterial isolates previously characterised from this glacier, were screened for the production of antimicrobial compounds. The aim of the present study was to characterize the psychrotrophic Alcaligenes faecalis HTP6 isolated from Passu glacier, Karakoram range, for its polyextremophilic nature of tolerating high salt concentration, varying temperature range, different metal ion concentrations and ability to produce antimicrobial compounds.
Material and Methods
Reagents and chemicals
Media, metal salts, methanol, chloroform, H2SO4, HCl, NaCl, ethyl acetate and ethanol were obtained from Sigma Chemical Co. (St. Louis, MO, USA) and antibiotic discs were from Liofilchem, (Roseto TE), Italy.
Sampling site and isolation
Sediment sample was collected from Passu glacier (Karakoram range), Pakistan (36°27.424N to 074°52.010E), following standard protocol described by Yegneswaran et al. (1988).
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Screening of isolate for antimicrobial activity
Different bacterial strains were isolated from Passu glacier sediment using minimal medium R2A agar. Many bacterial isolates were selected on the basis on colony morphology. All the isolates were screened from antimicrobial activity by spot on lawn assay against bacterial and fungal isolates. Inoculum of test strains was prepared in sterile normal saline and the suspension was adjusted to 0.5 McFarland standards. Then Muller-Hinton agar medium was evenly inoculated with test microorganisms using sterile swab. The isolates were spotted on the lawn and the plates were incubated at 15°C for 3-4 days. The inhibitory zones were measured in mm and mean values were calculated. The isolate HTP6 (Alcaligenes faecalis) showed best results and was selected for further optimization and characterization. Microscopic, morphological and physiological characterization of isolate was done according to Garrity et al. (2004).
Test microorganisms
Microorganisms used in the current study as test organism included: Staphylococcus aureus (ATCC 25923), Pseudomonas aeruginosa (ATCC 27853), S. aureus (clinical isolate), E. faecalis (clinical isolate), Candida albicans (clinical isolate) and Aspergillus fumigatus (clinical isolate).
Molecular characterization and phylogenetic analysis
For molecular characterization, the genomic DNA of isolate HTP6 was extracted using Invitrogen™ genomic DNA extraction kit. The DNA was amplified by using universal primers 27F (AGAGTTTGATCMTGGCTCAG) and 1492F (TACGGYTACCTTGTTACGACTT) and sequencing was performed commercially from Macrogen Inc., Seoul, Korea. The obtained sequences were aligned and homology was determined by BLAST search tool in NCBI. Phylogenetic tree was constructed by MEGA 6 software with similar sequences obtained from NCBI GenBank. The sequence of the isolate HTP6 was prepared by sequin and submitted to NCBI GenBank for acquisition of accession number.
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Tolerance to sodium chloride (NaCl)
To evaluate the halophilic nature, the isolate HTP6 was grown in LB broth containing different concentrations of NaCl ranging from 2 to 8%.
Temperature range determination
The isolate HTP6 was grown on LB agar medium and incubated at 4, 15, 30, 37 and 45°C for 3 to 7 days and the plates were observed after incubation.
Metal tolerance
To check the minimum inhibitory concentration of heavy metals, the isolate was grown on LB medium containing Cd+2, Cr+3, Hg+2, Fe+3, Ni+2, Ar+3 and Zn+2 ranging from 5-1600 ppm. The metal ions were supplemented as CdCl2.2H2O, CrCl3, HgCl2,
FeCl2 and ArCl3, NiCl3 and ZnCl2.
Antibacterial susceptibility testing
Antibacterial susceptibility was performed based on the disc diffusion method, following the guidelines of the Clinical and Laboratory Standards Institute (CLSI, 2013). A total of 7 antibiotics including colistin sulphate (CT, 50 μg); sulfamethoxazole/trimethoprim (SXT, 23.75/1.25 μg), clindamycin (DA 2 μg), ofloxacin (OFX 5 μg), imipenem (IMI 30 μg), cefotaxime (CTX 30 μg) and nalidixic acid (NA 30 μg) were used for determination of antibiotic resistance.
Effect of growth factors on biomass and metabolite production
Incubation period: The biomass production of the isolate HTP6 was carried out by growing it in 50 mL LB broth in shaking incubator at 15°C. Optical density was determined for biomass production while 2 mL of aliquots were withdrawn at regular intervals of 24 hours for four days and inhibitory activity was checked against S. aureus, P. aeruginosa, C. albicans and A. fumigatus.
Temperature: To check the maximum inhibitory activity and increase in biomass, the isolate HTP6 was grown in LB broth at three different temperatures (4, 15 and 30°C).
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The optical density was checked at regular intervals of 24 hours, for 5 days the antibacterial and antifungal activity was determined. pH: The optimal pH for biomass production and inhibitory activity was evaluated by growing the isolate HTP6 in LB broth at varying pH (5-9) and their inhibitory activity was observed against the above mentioned organisms.
Effect of carbon and nitrogen sources on growth and antimicrobial activity
To find the best carbon and nitrogen source, the isolate HTP6 was grown in five different media including (Luria Bertani broth, Nutrient broth, Tryptic soy broth, peptone water, Brain heart infusion and R2A broth) keeping a constant temperature of 15°C. The biomass production was carried out by optical density and inhibitory activity was determined against the test organisms by well diffusion method.
Effect of stress conditions on growth and antimicrobial activity
The effect of stress conditions like addition of metal salt (FeSO4), and dilution of medium composition was evaluated for biomass and antimicrobial metabolite production after 24 hours of interval for 5 days.
Extraction of the compounds
The isolate HTP6 was grown in 500 mL LB broth and incubated for 72 hours at 15°C. After incubation, the supernatant was centrifuged at 10,000 rpm for 30 minutes at 4°C, extracted with ethyl acetate (1:1) and evaporated using Rota vapour. The extracts were weighed and dissolved again in DMSO for bioassays.
Storage and thermal stability of the crude extract
To evaluate the thermal stability, 2 mL of crude extracts were kept at -70°C for three months, while thermal stability was checked by keeping 2 mL of aliquots at 4, 20°C for 24 hours, at 35°C, 60°C for 1 hour and 100°C for 15 minutes. The antibacterial and antifungal activities were determined after incubation time and zone of inhibition was measured.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 166 Chapter 3 Bacterial Diversity pH stability: The pH stability was evaluated by adjusting the pH of cell free supernatant from 3 to 10 and incubated for 3 hours. After incubation, pH was again adjusted to neutral and evaluated for antimicrobial activity.
Brine shrimp lethality assay
The cytotoxicity of the crude extract was carried out by brine shrimp assay as previously described by Maridass (2008), using brine shrimp (Artemia salina) in Artificial Sea water (34 g/L). After 48 hours of incubation 10 nauplii (larvae) were transferred in a test tube having 5 mL of sea water. Different concentrations of crude extract (50 µL to 200 µL) were transferred to each vial and recorded their cytotoxic activity. Normal saline was used as negative control.
Haemolytic assay
The haemolytic assay was carried out on Muller-Hinton Agar supplemented with 5% human blood. A well was formed, filled with 80 µL of the crude extract and incubated at 37°C for 48 hours.
DNA binding assay
DNA binding assay was carried out by mixing 100 µL of human DNA with 1 mL of crude extract and incubated for 6 hours at 15°C. Crude extract without DNA was used as a control. After incubation, the antibacterial and antifungal activity was carried out and the zones of inhibition were compared with that of the control.
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Results
Characteristics of the isolate HTP6
Morphologically, the isolate HTP6 produced small circular, transparent, non- pigmented colonies, while microscopic analysis revealed the isolate HTP6 as Gram negative, thick rod. Isolate HTP6 showed growth up to 37°C suggesting their psychrotolerant nature, and could grow in the presence of ~8% NaCl showing moderate halophilic characteristics. Interestingly, the isolate HTP6 showed some extent of tolerance to all heavy metals like, cadmium (740 ppm), chromium (760 ppm), arsenic (440 ppm), mercury (100 ppm) and iron (1080 ppm) and zinc (1340). Metal tolerance was observed in order as; Zn > Fe > Cr > Cd > Ar > Hg.
Molecular identification
The BLAST search of 16S rRNA sequence showed that the study isolate HTP6 was 99% similar to Alcaligenes faecalis. The phylogenetic tree constructed by MEGA 6 the study isolate clustered into the group of Alcaligenes faecalis (Fig.3.3.1 ).
Uncultured bacterium (KJ454266) Uncultured bacterium (KJ454216) Uncultured bacterium (KJ454288) Uncultured bacterium (KJ454344) Alcaligenes faecalis (KP318053) Alcaligenes sp. (KP318054) Uncultured bacterium (KT900460) Uncultured bacterium (KT900467) HTP6
Fig. 3.3.1. Molecular phylogenetic analysis of HTP6 (Alcaligenes faecalis) by Maximum Likelihood method.
The evolutionary history was inferred by using the Maximum Likelihood method based on the Tamura-Nei model (1993). The tree with the highest log likelihood (- 1084.4799) is shown. The percentage of trees in which the associated taxa clustered
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 168 Chapter 3 Bacterial Diversity together is shown next to the branches. Initial tree (s) for the heuristic search were obtained automatically by applying Neighbour-Joining and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The analysis involved 9 nucleotide sequences. Codon positions included were 1st +2nd +3rd + Noncoding. All positions containing gaps and missing data were eliminated. There were a total of 792 positions in the final dataset. Evolutionary analyses were conducted in MEGA6 (2013).
Antibiotic sensitivity assay
The antibiotic resistance was accomplished by disc diffusion method. Alcaligenes faecalis HTP6 showed multiple antibiotic resistance to clindamycin (DA), cefotaxime (CTX), and sulfamethoxazole/trimethoprim (SXT), however, the isolate was sensitive to imipenem (IMI), nalidixic acid (NA), ofloxacin (OFX) and colistin sulphate (CT) (Fig. 3.3.2).
Fig. 3.3.2. Antibiotic sensitivity profile of Alcaligenes faecalis HTP6, showing variable zones of inhibition against different antibiotics
Alcaligenes faecalis HTP6 showed broad spectrum activity against both bacterial and fungal pathogens. Maximum activity was observed against multidrug resistant E. coli and S. aureus (ATCC 25923) followed by Enterococcus faecalis (Fig. 3.3.3).
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Fig. 3.3.3. Zone of inhibition (mm) of Alcaligenes faecalis HTP6 against tested ATCC cultures* [Staphylococcus aureus (ATCC 25923), Pseudomonas aeruginosa (ATCC 27853)] and clinically isolated bacterial strains (S. aureus, E. faecalis, Candida albicans, and Aspergillus fumigatus)
Effect of growth factor on biomass production
Effect of different parameters (incubation period, pH and temperature) on production of biomass was evaluated. Alcaligenes faecalis HTP6 showed maximum growth after 72 hours of incubation, and the optimum temperature required for growth was 30°C. The Alcaligenes faecalis HTP6 showed optimum growth at pH 7, and best medium for biomass production was found to be LB (Luria Bertani) broth, followed by Brain heart infusion broth. The FeSO4 supplementation was also observed to have a positive impact on growth of the strain (Fig. 3.3.4). Maximum activity was observed after 96 hours of incubation at pH 7 and 30°C. The modified culture medium was also observed to increase the production of antimicrobial compounds (Fig. 3.3.5, 3.3.6).
Extraction and antibacterial activity of crude extract
Ethyl acetate extract (dissolved in DMSO) exhibited maximum activity against S. aureus, P. aeruginosa, C. albicans, A. fumigatus and E. faecalis (Fig. 3.3.7).
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A
B
C
D
Figure 3.3.4. Optimization of isolate for biomass production with different parameters, these parameters include (A) Optimization of temperature for biomass production. X-axis represent Temperature, Y-axis represent Optical density, (B) Optimization of pH for biomass production. X-axis represents pH and Time interval. Y-axis represents Optical density, (C) Optimization of various synthetic media for biomass production. X-axis represent Media while Y-axis represent Optical density, (D) Optimization of modified media for biomass production (LB normal media, LB1 LB media with addition of FeSO4, LB2 Dilution of LB medium from 1.5 -1% with addition of 0.75% NaCl, LB3 Dilution of LB media from 1.5-0.75% with addition of 1.5% NaCl X- axis represent Media (modified) Y-axis represent optical density
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A
B
C
D
Figure 3.3.5. Optimization of parameters for the maximum production of antimicrobial compounds. (A) Media optimization for the production of antimicrobial copounds. X-axis represent media Y-axis represent Zone of inhibation, (B) Temperature optimization for the production of antimicrobial copounds. X-axis represent temperature Y-axis represent Zone of inhibation, (C) Media (Modified)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 172 Chapter 3 Bacterial Diversity optimization for the production of antimicrobial copounds. X-axis represent media (modifed) Y-axis represent Zone of inhibation, (D) pH optimization for the production of antimicrobial copounds. X- axis represent pH Y-axis represent Zone of inhibation.
Fig 3.3.6. The effect of incubation time on the antimicrobial compounds activity showed best inhibition at 96 hours of incubation
Storage, thermal and pH stability of crude extract
The antimicrobial activity of crude cell free supernatant retained at low temperature storage for long time. The extract withstood heating up to 55°C, however, the activity was completely lost at 90 and 120°C. The crude extract showed maximum activity at pH 7 followed by pH 8, and the activity was reduced at pH 10 and pH 5, while the activity was completely lost at pH 3 and pH 4 (Fig 3.3.7 - 8).
Brine shrimp lethality, haemolytic and DNA binding assay
The crude extract of Alcaligenes faecalis HTP6 showed no lethal effect on brine shrimps at low concentration (25 µg/ml), however, at higher concentration (200 µg/ml) the crude extract showed 40% lethality. The extract showed no haemolytic activity and DNA binding activity as compared to the control.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 173 Chapter 3 Bacterial Diversity
Fig. 3.3.7. Zone of inhibition (mm) of crude extract of Alcaligenes faecalis HTP6 against the test bacterial and fungal strains. Best inhibition was found against A. fumigatus followed by S. aureus
Fig. 3.3.8. The tolerance of Alcaligenes faecalis HTP6 to different metal ions(ppm) showed best tolerance against Fe++.and least against Hg++
FTIR analysis
The FTIR analysis of crude ethyl acetate extract obtained from Alcaligenes faecalis HTP6 showed the presence of various functional groups (Fig. 9). Peak in the range of
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3311 cm-1 represent OH group from carboxylic acid, while, peak obtained at 1117 cm- 1 and 1290 cm-1 represent ‘C-O’ from alcohol, carboxylic acid and its derivatives. Two peaks at 2854 cm-1 and 2924 cm-1 represent C-H stretch. Peak at 1742 cm-1 indicated the presence of C=O from aldehyde, ketone or esters. The presence of alkene (C=C) is confirmed by peak at 1655 cm-1. The presence of nitro compounds (N-O) was confirmed by peak 1538 cm-1. Multiple medium and week bands in the range of 1600-1400 cm-1 attributed to aromatic compounds. Arenes may be present indicated by a peak at the range of 699 cm-1 and also from pleasant smell of extract. The FTIR analysis shows that the crude extract of Alcaligenes faecalis HTP6 constitutes of variety of valuable organic compounds of interest which are required to be purified and characterized. The presence of multiple compounds was also confirmed by various bands on thin layer chromatography (TLC) as shown in Fig. 10.
Fig. 3.3.9. FTIR analysis of the antimicrobial metabolite produced by Alcaligenes faecalis HTP6 showing the presence of various functional groups
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a b
Fig. 3.3.10. Multiple bands of the antimicrobial crude extract under (a) UV 365 nm and (b) 254 nm. The arrows showed metabolites of different molecular weight, probably having antimicrobial activity.
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Discussion
Microbial secondary metabolites are important bioactive compounds for the treatment of infectious diseases. However, the emerging multi and extensive drug resistant microbes are major threats and challenges for the effective management of infections caused by these superbugs (Walsh, 2003; Talbot et al., 2006). Therefore, there is a growing interest to search for better secondary metabolites from unexplored environments. Psychrophilic microorganisms are known as a potential source of antimicrobial metabolites (Sanchez et al., 2009), however data regarding these compounds is uncommon (Ravot et al., 2006).
In the present study, sediment sample from Passu glacier, Karakoram, was screened for the presence of an efficient producer of broad spectrum antimicrobial compounds against bacterial and fungal pathogens. The studied isolate was polyextremophilic in nature having the ability to tolerate low temperature, high metal concentrations, higher salt concentrations and varying pH. The selected isolate, Alcaligenes faecalis HTP6 was able to grow at low temperature as well as at mesophilic temperature range. Alcaligenes faecalis HTP6 as well as previous reports documented psychrotolerant bacteria with optimum growth at mesophilic range but they can thrive at cold temperature that might be possible due to their greater nutritional adaptability as described by Russell et al. (1990). The broad temperature range of Alcaligenes faecalis HTP6 indicated that it was Eurypsychrophile (Psychrotroph) in nature according to the definition of Morita (1975). Similar finding was also documented by Hemala et al. (2014) who identified the psychrotolerant bacteria with optimum growth at mesophilic temperature. Alcaligenes faecalis HTP6 showed moderate tolerance to NaCl concentration. Previous investigations revealed the psychrotrophic bacteria that could tolerate NaCl concentration up to 10%. One of the possible reasons for salt tolerance is the accumulation of solutes to the point where the microbes are growing and have relatively higher temperature than surroundings. In active ecological environment in glacial habitats, water nuclei forms inside glacier mass, the solutes around that environment diffuse to this active ecological environment and make it hypertonic. The exposure of bacteria to such condition leads to salt tolerance. The salt tolerance of our study isolate may be due to this phenomenon.
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Alcaligenes faecalis HTP6 was capable of producing broad spectrum compounds active against bacterial and fungal pathogens. Similar finding revealed the broad spectrum antibacterial and antifungal compounds from low temperature environment (O’Brien et al., 2004; Sanchez 2009; Shekh et al., 2011; Asencio et al., 2014). The Alcaligenes sp. is well identified to produce antibacterial and antifungal compounds (Martinez et al., 2006). Several studies (Li et al., 2008), supports our finding that Alcaligenes faecalis HTP6 is an efficient producer of antimicrobial metabolites. However, this is the first report of psychrotrophic Alcaligenes faecalis from glacier environment of Karakoram range. In addition, this is also the first report on antimicrobial activity, metal and salt tolerance from non-polar glaciers of Pakistan. The antibiotic production in Alcaligenes faecalis HTP6 could be due to selective pressure of heavy metals as revealed by the presence of increased level of heavy metals in water and sediment samples of Passu glacier, Pakistan (unpublished data by the authors).
Alcaligenes faecalis HTP6 showed resistance to several classes of antibiotics as well as metals. In non-anthropogenic environment, the resistance among microbial population is intrinsic. Such environment could serve as reservoir for antibiotic resistance genes that can be transmitted to pathogenic bacteria. Our finding was strongly associated by Giudice et al. (2013) who determined antibiotic resistance in Antarctic bacteria.
The increased resistance to zinc in Alcaligenes faecalis HTP6 was confirms the previous observation (De-Souza et al., 2006; Mangano et al., 2014). This high level of resistance might be described by the fact that zinc is a key micronutrient, which is involved in cellular function including DNA replication, cell activation and division (Mangano et al., 2014).
Alcaligenes faecalis HTP6 showed maximum growth after 72 hours of incubation while the antimicrobial compounds production was observed after 96 hours. Alcaligenes faecalis HTP6 showed optimum growth after 72 hours of incubation and was similar to the work reported by Kay and Cheeptham (2013) while the temperature and pH optima was 30°C and pH 7, respectively, which is supported by the findings of Usha et al. (2011) who found the maximum antibiotic production at pH 7 and temperature 30°C. The best medium for growth was LB broth, while decreasing the
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 178 Chapter 3 Bacterial Diversity medium concentration had positive impact on antibiotic production. The antibiotic production was also enhanced by adding FeSO4. In our studies the production of antimicrobial compounds started in idiophase after exhaustion of carbon (Sanchez et al., 2010).
The effect of media on antibiotic production has been revealed by Al-Judaibi (2011). The media used in our study were complex one containing carbon, nitrogen, ammonia phosphate etc. in unknown concentration, and these substances have both positive and negative impact on antibiotic production in culture media (Omura, 1986; Yegneswaran et al., 1988; Ripa, 2009) with enhanced antibiotic production at 1% NaCl which supports our finding. The increased antibiotic production in auxotrophic condition (reducing nutrients contents) in our study could be due to NaCl supplementation.
Regarding the stability to pH, temperature and long term storage, our results were closely related to that reported by Shekh et al., (2011) on antifungal activity of arctic and antarctic bacteria. Similar results regarding storage and thermal stability were observed by Sanchez et al. (2009), however, pH stability was different as he observed broad pH ranging from 1-12. Over all the psychrotrophic isolated HTP6 (Alcaligenes faecalis) from Passu glacier Pakistan, has tremendous ability of production of antimicrobial compounds at a varying conditions. The isolate had broad spectrum antagonistic activity against ATCC and clinical gram positive, gram negative and fungal strains. Furthermore purification model testing and formulation will be needed for a successful antibiotic.
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References
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Chapter 4. Fungal Diversity
Paper 1 (Batura glacier)
Title: Muhammad Rafiq, Noor Hassan, Alexandre M Anesio, Shaukat Nadeem, Muhammad Hayat, Mohsin Khan, Pervaiz Ali, Aamer Ali Shah, Fariha Hasan. Culturable diversity and characterization of fungi isolated from Batura glacier Hunza valley, Pakistan
Status:
Revised in Journal Extremophiles
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 4 Fungal Diversity
Title: Culturable diversity and characterization of fungi isolated from Batura glacier Hunza valley, Pakistan Muhammad Rafiq, Noor Hassan, Alexandre M Anesio, Shaukat Nadeem, Muhammad
Hayat, Mohsin Khan, Pervaiz Ali, Aamer Ali Shah, Fariha Hasan
Abstract Batura glacier has not been investigated for the presence of psychrotrophic fungi. The current study reports isolation and characterization of psychrotrophic fungi from ice, sediments and water samples, taken from Batura glacier, Karakoram range, Pakistan. The isolation and Total Viable count (CFU/mL/gm) was done by spread plate method at 4°C and 15°C to isolate psychrophilic and psychrotrophic fungi. A total of 33 fungal isolates were isolated from three samples, sediments (29), ice (2) and water (2). Fungal isolates were identified morphologically and microscopically and confirmed by 18S rRNA gene sequencing. Most of the fungal isolates belonged to the genus Penicillium, followed by Cladosporium, Geomyces, Cordyceps, Mrakia, Cadophora, Tetracladium, Eupenicillium, Trametes, Mortierella, Scopulariopsis, Beauveria, Candida and Pseudogymnoascus. Growth of fungi was characterized at various pHs, temperature and salt concentrations. All the isolates could grow between 4 and 37°C, whereas, some fungal isolates were able to grow at 45°C as well. The majority of the isolates showed growth at pH from 1 to 13, except for seven isolates which could not tolerate pH 1. Fungal isolates were able to grow at salt concentration between 2-26%. Highest tolerance to NaCl was demonstrated by Mrakia robertii with growth at 26%. All isolates were screened for their antimicrobial activity against clinically isolated bacterial and fungal strains and extracellular enzymes (amylase, cellulase, deoxyribonuclease, lipase, phosphatase and protease). The majority of fungal isolates shown best activity against Staphylococcus sp. Mrakia robertii was found to produce four different enzymes. Key words: Karakoram Mountains Ranges, Batura glacier, psychrotrophic fungi, Isolation and identification
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Introduction Psychrophiles are known as “cryophile” or freeze loving organism (Margesin et al. 2007) that have the ability to grow and survive in cold environment. Psychrophiles have an optimum growth temperature of 15°C or lower but can also grow at 20°C or less (Morita 1975). However, the cold environment is not only occupied by psychrophiles, the psychrotrophs are also able to grow at very low temperatures, albeit they have an optimum growth temperature above 15°C and maximum growth temperature up to 40°C (Baross and Morita 1978; Gounot, 1986; Cavicchioli et al. 2002). Mostly, psychrotrophic community have been described as ‘‘the survivors community’’ (Friedmann 1994), perhaps because of their survival lifestyle and their normal physiological state under low temperature (Morita 2000). Psychrophilic and psychrotrophic fungi have widely been studied for their presence in several cold environments in Arctic and Antarctica regions (Azmi and Seppelt 1997; Babjeva and Reshetova 1998; Selbmann et al. 2005; Vishniac 2006). Furthermore, fungi have been investigated in different cold environments, including permafrost (Broady and Weinstein 1998; Golubev 1998), cold water (Dmitriev 1997; Botha and Wolfaardt 2000;), glacial ice (Ma et al. 1999), snow and below snow-covered tundra (Schadt et al. 2003), and off shore polar waters (Broady and Weinstein 1998), glaciers, ice sheets and shelves, freshwater ice, sea ice, icebergs (Bridge 2010; Tojo and Newsham 2012).
Antibiotics resistant pathogens emerge faster than the rate of discovery of new antibiotics. Extended spectrum beta-lactamase (ESBL) Enterobacteriaceae bacteria, vancomycin resistant enterococci sp. and methicillin-resistant Staphylococcus aureus (MRSA), are all examples of the pathogens that are difficult to treat due to the lack of operative antibiotics. It is important to work out on discovery of new antibiotics from the extreme type sources that have not yet explored for this purpose. There are many sources of extreme environment, however, cold habitats could be prove important sources for the discovery of novel antibiotics. Therefore, we need to investigate antibiotics production from new extreme and unexplored sites against both multi-drug resistant bacteria and fungi.
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Pakistan has one of the world’s largest glacier reserves in the Karakoram-Hindu Kush- Himalaya ranges. The Northern Areas of Pakistan are found at the junction of the Karakoram, Western Himalayan and Hindu Kush mountain ranges (Rahman et al. 2008). Batura glacier is one of the biggest glaciers outside the polar region. It is present in the north of Passu 7,500 m above sea level. Batura glacier has not been yet explored for the presence of psychrophilic and psychrotrophic fungi. The main aim of the current study was to isolate and to characterize the psychrophilic and psychrotrophic fungal community from the glacial ice, sediments and melted water samples, collected from Batura glacier.
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Materials and Methods
Sampling
The Batura glacier is 57 km long and terminates at ~3000 m altitude in Hunza Valley of the upper Indus basin. The glacier basin is ~48% glacierised and surrounded by several major peaks of Karakoram that reach summit altitude >7000 m in south and >5500 m in the north (A1 & A4). Different samples (glacier ice, sediments and water) were collected from Batura glacier of the Karakoram range, Pakistan (36°30.302N to 074°51.138E), in sterile bottles by considering standard microbiological protocols and procedures. The pH for the all samples was 7.0, whereas, temperatures of glacial sediments and water was 1°C while glacial ice had -2°C. All the collected samples were transported to Microbiology Research Lab, Department of Microbiology, Quaid- i-Azam University, Islamabad, in ice box and stored at -20°C.
Fungal isolation
For fungal isolation, Sabouraud Dextrose Agar (SDA) along with other media, Potato Dextrose Agar (PDA) and Malt Extract Agar (MEA), were used as growth medium. The fungal cultures were incubated at 4°C and 15°C. The total viable counts were determined in terms of fungal colony forming units (CFUs/mL/gm) and subcultures made of all morphologically distinct colonies from each sample. The cultures were preserved on PDA slants at 4°C for further use.
Morphological characterization
The isolated fungal cultures were grown on different media such as PDA, Tryptic Soy Agar (TSA), SDA and Malt Extract Agar (MEA), following incubation at 4°C and 15°C for 10 days. The colony morphology was noted mainly for their color, texture and size (front and reverse). Microscopic characteristics of the fungal isolates were observed following lacto-phenol cotton blue staining (40x).
Physiological characterization
All the physiological parameters were measured on SDA, MEA and PDA using 10 day old colony. For determination of the temperature optimum, the fungal isolates Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 185 Chapter 4 Fungal Diversity were incubated at different temperatures ranging from 4 to 50°C (4, 15, 37, 45, 50°C) for 10 days. The pH tolerance of fungal isolates was determined by inoculating them separately in the medium (pH 1 to 13), following incubation at 4°C and 15°C for 10 days. For determination of salt tolerance, the fungal isolates were grown on SDA supplemented with NaCl up to 26% concentration, following incubation at 4°C and 15°C for 10 days.
Molecular characterization
DNA extraction and amplification
The fungal DNA extraction was done according to protocols formerly described by Rosa et al. (2009). The primers ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′- TCCTCCGCTTATTGATATGC-3′) were used for amplification of ITS regions (ITS1-5.8S ITS2). The PCR conditions were: initial denaturation at 94°C for 1 min, 30 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 1 min, followed by 10 min final extension at 72°C. PCR products were run on agarose gel with DNA ladder to confirm the correct size of the gene.
Sequencing and phylogenetic analysis
The fungal isolates sequencing was done commercially by Macrogen (Macrogen Inc. Seoul, Korea). The obtained sequences were analysed by Chromas Lite and were further evaluated by comparing the nucleotide sequences available in NCBI database (Thompson et al. 1997). The evolutionary history was inferred by using the Maximum Likelihood method based on the Tamura-Nei model (Tamura and Nie 1993). The phylogenetic tree was constructed in MEGA software using maximum likely hood method (Tamura et al. 2007) at the bootstrap value 1,000.
Evaluation of antimicrobial activity
Different clinical bacterial isolates, E. coli (Multi-drug resistanat), Klebsiella pneumonia (MDR), Staphylococcus aureus (MDR), Staphylococcus sp., Enterococcus sp. (vancomycin resistant enterococci) and fungal isolates Candida albicans and Aspergillus niger were used as test microbes. 0.5 McFarland solution was used as
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 186 Chapter 4 Fungal Diversity turbidity standard. Evaluation of antimicrobial activity was carried out by point inoculation. Using a sterile wire loop, a pure test microbial colony was transferred into the test tubes containing normal saline solution and adjusted the turbidity with 0.5 McFarland solutions. A sterile cotton swab was used to prepare homogenous lawn on PDA and TSA. A small portion of each fungal mycelium was inoculated on plates containing test microbial lawn.
Screening for extracellular enzyme activity
Extracellular enzyme activity was determined on solid media. Ten day old fungal cultures were used as inoculum. Amylase, deoxyribonuclease, lipase and protease activities were screened using the protocol given by Hankin and Anagnostakis (1975). The phosphate or phosphatase activity was determined on Pikovskaya's medium (Pikovskaya 1948). The isolates were screened for cellulolytic activity by using carboxymethylcellulose (CMC) as a substrate. For cellulolytic activity, the plates were flooded with 0.5% Congo red solution for 10 minutes, then washed with distilled water and flooded with 1 M NaCl. The clearing zone around the colony was observed. All qualitative extracellular enzyme activities were assayed at 4 and 15°C.
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Results
In the present study, 33 fungal isolates were isolated from glacial ice, water and sediments of the Batura glaciers, Pakistan, by culturing at two temperatures 4°C and 15°C. The CFU/g/mL in sediments was highest at both temperatures followed by water and ice (Table 4.1.1).
Table 4.1.1. Total viable count (CFU/mL/gm) of fungal isolates at 15°C and 4°C
Temperature (°C) Samples No. of CFU/mL / gm colonies/200µL
1 Glacier ice 2 1.0 x10 Glacier water 3 1 4 1.5 x10 2 3 Glacier sediment 2.2 x10 1.11x10
1 Glacier ice 7 3.5 x10 Glacier water 4 1 15 2.0 x10 1 2 Glacier sediment 1.55x10 7.75x10
Morphological and microscopic characterization
The fungal isolates were different in colony morphology, mostly were of cottony to powdery textures, irregular shapes and size, blue to green color was common. The macroscopic characteristics of different fungal isolates on the Sabouraud Dextrose Agar (SDA) and microscopic features are given in (Table 4.1.2). The microscopic features of the fungal isolates were observed and found that hyphal structure were septate, cylindrical to ovoid shaped spores were common, mostly hyphae were colorless.
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Table 4.1.2. Colony morphology and microscopic characteristics of fungal isolates on SDA
Isola Sample Temp Colony morphology Microscopic characteristics te form (°C) Front Reverse
LB1 Sediment 4 Powdery, initially cottony, white Golden to brown center Branched and septate hyphae, smooth-walled to broadly with white margins then turned to with dim gray margins ellipsoidal and scattered conidia, cylindrical phialides and dim gray metulae
LB2 Sediment 4 Mucoid, light goldenrod center with Lemmon chiffon center Cylindrical to ovoid shaped and scattered spores, no off-white edges with off-white margins pseudo- hyphae observed
LB3 Sediment 4 Cottony, initially salmon to white Saddle brown center Hyaline, thin-walled and branched hyphae with frequent with salmon edges then turned to with golden edges clamp connections, chlamydospores hyaline, pear to oval slate gray to white shaped.
LB4 Sediment 4 Velvety, initially dry mucoid to Saddle brown center Hyphae septate, branched, Conidiophores simple or yellow then turned to dark orange with golden edges sparsely branched and scattered conidiophores with goldenrod margins
LB5 Sediment 4 Velvety, initially dark olive green Black center with Off- Branched, pale olivaceous brown hyphae, conidia with light yellow edges then turned white edges ellipsoidal to limoni-form, smooth-walled or slightly to black to dark green with white verrucose, olivaceous brown surface
LB6 Sediment 4 Cottony, initially white velvety with Golden to brown center Terverticillate to quaterverticillate conidiophores, off-white margins then turned to dim with dim gray margins. smooth-walled, globose to suglobose conidia and
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gray cylindrical metulae and phialides
LB7 Sediment 4 Cottony, initially yellow to green Dark brown center with Hyphae hyaline to pale yellow and septate, scattered and then turned to sea green with dim saddle brown edges erect conidiophores, and branched conidia gray edges
LB8 Sediment 4 Velvety, initially cottony white then Dark brown center with Septate and branched hyphae, globose to subglobose turned to gray with slate gray light goldenrod margins shaped conidia, scattered conidiophores margins
LB9 Sediment 4 Cottony, initially velvety with blue Dark orange to brown Branched and septate hyphae, conidiophores to green center, white margin then center with off-white biverticillate, grey to green and echinulate to globose turned to light gray to dark sea green margins shaped conidia
LB10 Sediment 4 Velvety, initially gray to black center Gray to black center and Hyaline, smooth and thin-walled conidia, ovoidal to with off-white edges then turned to light yellow edges ellipsoidal shaped spores light slate gray
LB11 Sediment 4 Cottony, initially slate gray center Brown center and Conspicuously roughened and branched conidiophores, with white margins then turned to yellow to off-white septate hyphae, scattered conidia dim gray margins
LB12 Sediment 4 Velvety, initially white center with Black to brown center Scattered and branched hyphae, curved, branched and off-white margins then turned into with brown margins pale greenish conidia light gray
LB13 Sediment 4 Dry mucoid, initially white center Golden center and light Spores are globose to ovoid shape, no pseudohyphae was with off-white margins then turned goldenrod margins observed
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to light goldenrod
LB14 Sediment 4 Powdery, initially cottony, white Golden to brown center Cylindrical metulae and phialides, scattered and branched with white margins then turned to with dim gray margins hyphae, scattered conidiophores dim gray
LB15 Sediment 4 Velvety, initially white with white Saddle brown center Septate to multiseptate and branched hyphae, colorless edges then turned to light cyan with light goldenrod and cylindrical to ovoid shape spores yellow edges
LB16 Ice 4 Velvety, initially dark olive green Black center with off- Septate and branched hyphae, elliptical to cylindrical in gray center with off-white edges then white edges shape, pale to dark brown in color turned to dark green to black
LB17 Water 4 Velvety, dark olive green with light Black center with light Branched hyphae, conidia ellipsoidal to limoni-form, yellow edges goldenrod yellow edges smooth-walled or slightly verrucose, olivaceous brown
HB1 Sediment 15 Cottony, initially green to blue then Brown center with Septate, branched hyphae, longer and visibly roughened turned to dim gray with white golden- rod margins conidiophores producing smooth to finely roughened conidia margins
HB2 Sediment 15 Cottony, initially white to light Khaki center with pale Pseudomycelium and septate hyphae, cylindrical to ovoid yellow then converted to gray with goldenrod edges shaped and scattered conidia whit to off-white edges
HB3 Sediment 15 Powdery, initially dark sea green Black center with dark Branched, septate hyphae, numerous, large and densely then turned to black with pale green orange to golden edges packed phialides conidiophore edges
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HB4 Sediment 15 Cottony, light yellow to light golden- Golden center with light Septate and hyaline hyphae, short and globose to ovoid rod yellow center with white margins goldenrod margins conidiophore, scattered conidia
HB5 Sediment 15 Cottony, initially white to gray then Off-white to yellow Round to ovoid in shape conidia, septate and branched turned to brown-black with off-white center and light yellow hyphae, and scattered conidiophores edges edges
HB6 Sediment 15 Cottony, white to light goldenrod Dark orange to brown Short distinct branched conidiophores, conidia are 1-celled yellow center with white margins center with goldenrod and either white or yellow margins
HB7 Sediment 15 Cottony, initially green center with Off-white to yellow Conspicuously roughened and branched conidiophores, white margins then turned to light center and light yellow septate hyphae, scattered conidia gray to white edges
HB8 Sediment 15 Cottony, initially velvety with blue Dark orange to brown Conidiophores biverticillate, grey to green and echinulate to to green center, white margin then center with off-white globose shaped conidia turned to light gray to dark sea green margins
HB9 Sediment 15 Powdery, initially cottony with dark Off-white to yellow Hyphae are septate and hyaline, kidney-shaped to brush- green center and white edges then center and light yellow shaped conidiophores on conidia turned to dim gray edges
HB10 Sediment 15 Cottony, initially gray center with Off-white to yellow Divergent biverticillate to terverticillate conidiophores, white edges then turned to light gray center and light yellow smooth-walled and scattered conidia edges
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HB11 Sediment 15 Cottony, white center with white Golden to yellow center Sporangiophores subulate, hyaline, smooth, unbranched. margins and off-white margins Sporangia mainly globose
HB12 Sediment 15 Powdery, initially white center with Black center with dark Septate and brown hyphae erected and pigmented dark sea green margins then turned olive green margins conidiophores with conidia into black to brown
HB13 Sediment 15 Cottony, white center with dark Golden to brown center Short chains or branched conidiophores, obovoidal and salmon margins and yellow margins scattered conidia
HB14 Sediment 15 Powdery, initially velvety with blue Light golden- rod center Septate and branched hyphae, chains of spores (or conidia) to green center, white margin then with light golden- rod from brush-shaped conidiophores turned to gray to green yellow margin
HB15 Ice 15 Velvety, initially dark olive green Black center with light Septate, light colored hyphae, erect, pigmented, scattered with light yellow edges then turned goldenrod yellow edges conidiophores, and conidia to black to green
HB16 Water 15 Velvety, dark olive green with light Black center with light Septate and branched hyphae, elliptical to cylindrical in yellow edges golden red yellow edges shape conidia, scattered conidiophores
Keys: LB: Low (Temperature, 4°C) Batura Isolates, HB: High (Temperature, 15°C) Batura Isolates
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Molecular characterization On the basis of DNA sequence of 18S rDNA (ITS1 – ITS4) the 33 isolates were found to belong to diverse taxonomic groups. The phylogenetic tree demonstrating their relationship among all fungal isolates and their narrowly related species is given in Fig. 4.1.1 and the resemblance directory of isolates with respective homology of the isolates is summarized in Table 4.1.3. Table 4.1.3. The resemblance directory of the fungal isolates with respective homologous strains Isolate Accession No. Homologous strains with accession No. Identity(%) LB1 KR019737 Penicillium camemberti (FJ025142.1) 99 LB2 KR019738 Mrakia robertii (KC333173.1) 84 LB3 KR019739 Trametes dickinsii (EU661878.1) 87 LB4 KR019740 Tetracladium sp. (JX029110.1) 100 LB5 KR019741 Cladosporium uredinicola (FJ025160.1) 99 LB6 KR019742 Penicillium polonicum (KF597019.1) 97 LB7 KR019743 Geomyces sp. (HQ914918.1) 99 LB8 KR019744 Calluna vulgaris root associated fungus (FM172812.1) 99 LB9 KR019745 Penicillium canescens (AY373901.1) 100 LB10 KR019746 Cadophora sp. (JN859258.1) 99 LB11 KR019747 Cladosporium cladosporioides (KM979939.1) 100 LB12 KR019748 Geomyces sp. (JX512256.1) 99 LB13 KR019749 Mrakia cf. gelida (KC455909.1) 99 LB14 KR019750 Penicillium chrysogenum (JX139706.1) 99 LB15 KR019751 Cordyceps confragosa (KJ093501.1) 91 LB16 KR019752 Cladosporium tenuissimum (KM577646.1) 100 LB17 KR019753 Cladosporium cladosporioides (KJ589555.1) 95 HB1 KR019754 Penicillium canescens (FJ025212.1) 99 HB2 KR019755 Candida deformans (FJ515168.1) 100 HB3 KR019756 Eupenicillium tularense (EU142874.1) 99 HB4 KR019757 Beauveria bassiana (KM114549.1) 100 HB5 KR019758 Penicillium brevicompactum (KF990149.1) 99 HB6 KR019759 Geomyces sp. (HQ914918.1) 99 HB7 KR019760 Penicillium sp. (KF428217.1) 100 HB8 KR019761 Penicillium canescens (AY373901.1) 100 HB9 KR019762 Scopulariopsis brevicaulis (FJ025211.1) 100 HB10 KR019763 Penicillium dipodomyicola (FJ025211.1) 100 HB11 KR019764 Mortierella alpine (KJ469841.1) 100 HB12 KR019765 Cladosporium sp. (KP050653.1) 100 HB13 KR019766 Pseudogymnoascus sp. (KF686756.1) 100 HB14 KR019767 Penicillium chrysogenum (KM853015.1) 100 HB15 KR019768 Cladosporium sphaerospermum (KJ728690.1) 99 HB16 KR019769 Cladosporium sphaerospermum (KJ728690.1) 99 Keys: LB: Low (Temperature, 4°C) Batura Isolates, HB: High (Temperature, 15°C) Batura Isolates
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Physiological characterization Temperature, pH and the salt tolerance of the fungal isolates are shown in Table 4.1.4.
All the isolates showed growth between 4 and 37°C except HB3 and LB13 that could also grow at 45°C but none of them exhibited growth at 50°C. However, the optimum
temperature for all the isolates was between 4 and 15°C except HB2, HB7 and HB14
that also optimally grown at 37°C. Very little growth was observed at 37 and 45°C. The fungal isolates showed growth at broad range of pH. The optimum pH for all fungal isolates was observed between 4 and 9. Most of the isolates (79%) grew on acidic range, only 7 isolates could not grow at pH 1 while all other isolates showed growth at the lowest pH. Towards alkaline range, all the isolates tolerated pH up to 13. Salt tolerance of the fungal isolates was between 2 and 26% (33 between 2 and 14%, 32 at 16%, 24 at 18%, 17 at 20%, 11 at 22 and 24% and 1 showing growth at 26% salt concentration). Based on these results, the isolates were considered as cold, pH and salt tolerant.
Table 4.1.4. Temperature, pH and the salt tolerance range of the fungal isolates (Numbers between brackets are the optimal growth)
Isolates Temperature (°C) range pH range Salt range (%)
LB1 4−37, opt. 4 1−13, opt. 5–8 2−24, opt. 2–8
LB2 4−37, opt. 4 1−13, opt. 5–7 2−26, opt. 2–10
LB3 4−37, opt. 4 1−13, opt. 5–7 2−16, opt. 2–6
LB4 4−37, opt. 4 1−13, opt. 5–8 2−18, opt. 2–6
LB5 4−37, opt. 4 1−13, opt. 5–8 2−16, opt. 2–6
LB6 4−37, opt. 4 1−13, opt. 5–7 2−24, opt. 2–8
LB7 4−37, opt. 4 2−13, opt. 5–7 2−16, opt. 2–6
LB8 4−37, opt. 4 1−13, opt. 5–8 2−16, opt. 2–6
LB9 4−37, opt. 4 1−13, opt. 5–8 2−18, opt. 2–6
LB10 4−37, opt. 4 1−13, opt. 5–8 2−16, opt. 2–6
LB11 4−37, opt. 4 1−13, opt. 5–7 2−18, opt. 2–6
LB12 4−37, opt. 4 1−13, opt. 5–7 2−16, opt. 2–6
LB13 4−45, opt. 4 1−13, opt. 5–7 2−18, opt. 2–6
LB14 4−37, opt. 4 1−13, opt. 5–7 2−18, opt. 2–6
LB15 4−37, opt. 4 1−13, opt. 5–8 2−16, opt. 2–6
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LB16 4−37, opt. 4 1−13, opt. 5–8 2−16, opt. 2–6
LB17 4−37, opt. 4 1−13, opt. 5–8 2−20, opt. 2–6
HB1 4−37, opt. 15 2−13, opt. 5–7 2−24, opt. 2–10
HB2 4−37, opt. 15 1−13, opt. 5–8 2−20, opt. 2–8
HB3 4−37, opt. 15 2−13, opt. 5–7 2−24, opt. 2–10
HB4 4−37, opt. 15 1−13, opt. 5–8 2−20, opt. 2–8
HB5 4−37, opt. 15 2−13, opt. 5–7 2−24, opt. 2–10
HB6 4−37, opt. 15 1−13, opt. 5–8 2−14, opt. 2–6
HB7 4−37, opt. 15 1−13, opt. 5–8 2−24, opt. 2–10
HB8 4−37, opt. 15 2−13, opt. 5–7 2−18, opt. 2–8
HB9 4−37, opt. 15 1−13, opt. 5–8 2−20, opt. 2–8
HB10 4−37, opt. 15 1−13, opt. 5–8 2−24, opt. 2–8
HB11 4−37, opt. 15 2−13, opt. 5–7 2−18, opt. 2–8
HB12 4−37, opt. 15 2−13, opt. 5–7 2−24, opt. 2–8
HB13 4−37, opt. 15 2−13, opt. 5–7 2−24, opt. 2–10
HB14 4−37, opt. 15 2−13, opt. 5–7 2−20, opt. 2–8
HB15 4−37, opt. 15 1−13, opt. 5–7 2−20, opt. 2–8
HB16 4−37, opt. 15 1−13, opt. 5–8 2−20, opt. 2–8
Evaluation of antimicrobial activity
During the screening of the fungal isolates for antimicrobial activity, it was found that they showed greater antibacterial activities than antifungal activities (Table 4.1.5). The fungal isolates showed good antimicrobial activity against Gram positive bacteria (21 showed activity against Staphylococcus sp., 5 against Staphylococcus aureus, 3 against Enterococcus sp.) as compared to Gram negative bacteria (2 against E. coli but none showed antimicrobial activity against Klebsiella pneumoniae). Ten and 4 fungal isolates showed antifungal activities against Candida albicans and Aspergillus niger, respectively.
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Table 4.1.5. Antibacterial and antifungal activity of the fungal isolates by point inoculation method Isolates Bacteria Fungi E. Klebsiella Staph. Staph. Enterococcus Aspergillus Canda coli pneumonie aureus sp. sp. niger albicas LB1 − − − ++ − − +
LB2 − − − − ++ − − LB3 − − − +++ − − ++ LB4 + − − +++ − − + LB5 − − − +++ − − − LB6 − − − − − − −
LB7 − − − +++ − − − LB8 − − − +++ ++ − + LB9 − − + + − ++ ++ LB10 − − − +++ − − LB11 − − − +++ − − + LB12 − − − ++ − − − LB13 − − − +++ − − − LB14 − − − +++ − − ++ LB15 − − ++ ++ − − + LB16 − − − ++ − − − LB17 − − − − − − − HB1 − − − − − ++ − HB2 − − − +++ − − −
HB3 − − − − − − − HB4 − − ++ + − − − HB5 − − +++ − ++ + − HB6 − − − − ++ − − HB7 − − − + − − −
HB8 − − ++ − − ++ + HB9 − − − − − − −
HB10 − − − ++ − − − HB11 − − − +++ − − − HB12 ++ − − +++ − − −
HB13 − − − +++ − − − HB14 − − − − − − −
HB15 − − − − − − − HB16 − − − − − − − Key: (-) No Zone, (+) Zone up to 8 mm, (++) Zone up to 16 mm, (+++) Zone above 16 mm
Screening for extracellular enzyme activity Out of 33 fungal isolates, 6 exhibited positive amylolytic activity, 7 showed cellulosic activities and only 1 isolate showed positive production for DNase (Table 4.1.7).
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While, 10 fungal isolates exhibited lipolytic activity, 13 isolates were found positive by exhibiting phosphate solubilizing activity and only 1 isolate showed proteolytic activity. They were good in lipase production but were very poor in production of DNase and protease. The studies clearly demonstrated that fungi were capable of producing a wide range of extracellular enzymes. Table 4.1.6. Production of various extracellular enzymes by fungal isolates Isolates Enzymes Amylase Cellulase DNase Lipase Phosphatase Protease LB1 − − − − + − LB2 − + + + + − LB3 − − − − − − LB4 − − − + − − LB5 − − − − − − LB6 ++ + − − + − LB7 ++ ++ − ++ − − LB8 − − − − − − LB9 − − − − + − LB10 ++ − − − − − LB11 − − − − − − LB12 − − − ++ − − LB13 + − − − − − LB14 − + − − + − LB15 − − − − + − LB16 ++ − − − − ++ LB17 − − − − − − HB1 − − − − + − HB2 − − − − − − HB3 − − − ++ + − HB4 − − − − ++ − HB5 + − − − + − HB6 − − − ++ − − HB7 − − − ++ + − HB8 − ++ − +++ − − HB9 − +++ − − + − HB10 − ++ − − + − HB11 − − − − − − HB12 − − − − − − HB13 − − − − − − HB14 − − − − − − HB15 − − − − − − HB16 − − − − − − Keys:
(-) No Zone , (+) Zone up to 6 mm, (++) Zone up to 12 mm, (+++) Zone above 12 mm
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Discussion
The main objective of this research was to isolate and characterize the psychrotrophic and psychrophilic fungal community from Batura glacier, Pakistan. A total of 33 fungal isolates were obtained from three different samples, sediments (29), ice (2) and water (2). All the fungal isolates were isolated at two different temperatures 4°C (17 isolates) and 15°C (16 isolates). In the current study, macro and micro-morphological analysis has successfully carried out for screening of the fungal isolates that were further subjected to species level identification following molecular methods. Out of 33 fungal isolates, 29 showed high similarity (between 97 and 100%) to their respective available strains in NCBI database. The four isolates, LB2, LB3, LB15 and
LB17 showed maximum similarity up to 84, 87, 91 and 95%, respectively, and their sequences are deposited in database and need further investigation to determine their taxonomic affiliation. Mostly, fungal isolates belong to genus Penicillium (10), followed by Cladosporium (7), Geomyces (3), Cordyceps (1), Mrakia (2), Cadophora (1), Tetracladium (1), Trametes (1), Mortierella (1), Scopulariopsis (1), Beauveria (1), Candida (1), Eupenicillium (1) and Pseudogymnoascus (1).
The members of the genus Geomyces are keratinophilic, psychrophilic and psychrotolerant in nature has been reported widely from Antartica and Arctic habitats as well as characterized as halotolerant and moderately cellulolytic (Blehert et al. 2009; Arenz et al. 2011). Mrakia species related to obligate psychrophilic nature, have been documented from Alpine, Arctic and Antarctic habitats (Fell and Stalzell- Tallman 1998; Margesin et al. 2005). Fungal species belonged to the genera Penicillium, Cladosporium, Candida, Cadophora and Pseudogymnoascus isolated in the present study, have previously been found in polar and non-polar habitats (Duncan et al. 2006; Burgaud et al. 2010; Vivian et al. 2012; Dhakar et al. 2014; Wang et al. 2015).
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Penicillium chrysogenum|JX139706.1| Penicillium dipodomyicola|LN482566.1| LB14 Penicillium dipodomyicola|FJ025172.1| LB6 Penicillium camemberti |FJ025142.1|(2) LB1 Penicillium chrysogenum|KM853015.1| HB14 62 Penicillium camemberti |FJ025142.1| Penicillium dipodomyicola |FJ025172.1| HB10 Scopulariopsis brevicaulis|FJ025211.1| HB9 HB7 5565 Penicillium ochrochloron|KF313088.1| 65 Eupenicillium tularense|JF911774.1| Eupenicillium sp|EU142874.1| HB3 HB5 99 86 Penicillium brevicompactum |KF990149.1| Penicillium brevicompactum |AY373897.1| Penicillium polonicum|KF597019.1| HB1 HB8 Penicillium canescens |AY373901.1| Penicillium dunedinense |KJ775678.1| 64 LB9 37 Penicillium canescens|AY373901.1| Penicillium dunedinense|KJ775678.1| HB16 Cladosporium sphaerospermum|KJ728690.1|(2) Cladosporium sp|KF986417.1| Cladosporium sphaerospermum|KJ728690.1| HB15 LB17 95 65 HB12 Cladosporium macrocarpum |KM396371.1| LB5 12 Cladosporium uredinicola|FJ025160.1| LB11 Cladosporium cladosporioides|KM979939.1| 63 Cladosporium cladosporioides|KM979928.1| LB16 Cladosporium tenuissimum|KM577646.1| Cladosporium sp|KM280043.1| Cladosporium cladosporioides|KJ589555.1| HB6 4 Geomyces sp|HQ914918.1| Uncultured fungus|KM877207.1| HB13 Pseudogymnoascus sp|KF686750.1| LB7 94 Geomyces sp|HQ914918.1|(2) Uncultured fungus clone|KM877207.1| 9 LB12 Pseudogymnoascus sp|KF686756.1| LB8 98 Uncultured fungus clone|KM504443.1| 95 HB4 44 Beauveria bassiana |KM114549.1| Uncultured fungus|JX135689.1| LB15 100 Cordyceps confragosa |KJ093501.1| 91 71 Cordyceps confragosa|JQ387577.1| LB10 Cadophora sp|JN859258.1| 97 Cadophora sp|JN859252.1| LB4 Tetracladium sp|JX029110.1| 99 Tetracladium sp|JX029133.1| 100 Mortierella alpina|KJ469841.1| Mortierella alpina|FJ025167.1| 58 HB11 HB2 Candida deformans |FJ515168.1| 99 Trametes dickinsii|EU661878.1| 100 88 Daedalea dickinsii|FJ481049.1| LB3 LB2 47 Mrakia robertii|KC333173.1| 84 Uncultured fungus clone|JN889739.1| 99 LB13 Mrakia cf. gelida|KC455909.1| 68 Uncultured fungus clone|HQ267084.1|
0.05
Fig 4.1.1. Molecular Phylogenetic analysis of the Batura fungal isolates by Maximum Likelihood method
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Tetracladium species have been found in alpine glaciers and snow-covered soil and considered to be cold-adapted (Robinson et al. 2000; Kuhnert et al. 2012). Mortierella species have been detected in Antarctical soil (Bridge and Newsham 2009) and associated with mosses (Tosi et al. 2002). The fungal species, Eupenicillium tularense, Beauveria bassiana and Scopulariopsis brevicaulis have not yet been reported from the low temperature habitats, these species have been isolated for the first time from non-polar glacier in this study. Although, Trametes dickinsii and Cordyceps confragosa, have been found for the first time in non-polar glaciers in this study but as they showed low similarity (87% and 91%, respectively) to known isolates upon blast in NCBI, which could represent other fungal genera upon complete identification.
The Batura glacier is one of coldest non-polar glacier that contains very low temperature, often below freezing point. In this study, the fungal isolation from such low temperature habitat, indicating the possible role of the spores in their survival. The spores play an important role in the existence of both bacteria and fungi in extreme environments, especially spores protect them from UV-radiation and DNA damages (Ma et al. 2000). According to Robinson (2001), fungal persistence in Arctic and Antarctic habitats may happen because of cold evasion, rather than cold tolerance. Vishniac (1996) believe that spores helped more fungi to endure freezing than vulnerable hyphomycete hyphae. Several of fungal of isolates up to 140,000 years old, have been isolated from Greenland ice cores (Catranis and Starmer 1991; Ma et al. 2000). These studies show that fungal spores are central to survival of fungi in cold environments.
In the current study, the fungal isolates showed tolerance against three key physiological characters temperature, pH and salt. On the basis of their surviving efficiency at low and high temperature (from 4 to 45°C) and high salt concentration (up to 26%), they can be categorized as psychrotolerants, thermotolerants and halotolerants, respectively. The isolates are highly diverse in terms of temperature requirement. They have the ability to grow well at 4 - 15°C, which is a key property of psychrophilic organisms, but they also showed growth at higher temperatures. The ability of fungal isolates to grow on low and high temperature and high levels of salt possibly indicated mechanisms involved in the protection against such stressful
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 201 Chapter 4 Fungal Diversity conditions. Numerous mechanisms such as antifreeze proteins, polyols, lipid/fatty acids etc. have been suggested central to the phenomenon of cold adaptation (Robinson, 2001). In this study, the isolate Mrakia cf. gelida was capable of surviving at 45°C. For the first time, Mrakia cf. gelida reported as a fungus of thermophilic nature from the glacier because members of genus Mrakia have been reported as of psychrophilic nature (Xin and Zhou 2007). Thermophilic fungi have a growth temperature minimum at or above 20°C and a growth temperature maximum at or above 50°C, and the thermotolerant fungi have a temperature range of growth from below 20 to 55°C (Maheshwari et al. 2000). Our results are supported by Zucconi et al. (1996), who isolated a thermotolerant-mesophilic fungal species from Victoria Land, Antarctica that was able to grow at 45°C.
The fungal isolates showed growth on wide range of pH (1–13), which is a remarkable discovery of the present study. Generally, fungi are well-known to grow best in acidic media. On other hand, fungal isolates showed great tolerance to different salt concentrations (2-26%). 9 isolates grown at 24% of NaCl, whereas 1 isolate grew at 26% salt concentration as well. According to existing literature, many of the fungal isolates representing different genera (Cladosporium, Cordyceps, Mrakia, Cadophora, Tetracladium, Trametes, Mortierella, Scopulariopsis, Beauveria, Candida, Eupenicillium and Pseudogymnoascus) of the present study, characterized for the first time at such an extreme pH and salts conditions from the low temperature environments. However, species of the genera Penicillium, Geomyces and few other fungal genera have been reported from cold and other habitats that were able to grow at both acidic and alkaline pH as well as high NaCl concentrations (Eliades et al. 2006; Kochkina et al. 2007; Grum-Grzhimaylo et al. 2013; Dhakar et al. 2014). Production of secondary metabolites, most importantly, antimicrobial metabolites have also been analyzed in this study. Many fungal isolates have been found to produce secondary metabolites with bactericidal and fungicidal activity. The 24 out of 33 fungal isolates showed good activities against Gram positive bacteria but their antibacterial and antifungal activity towards Gram negative bacterial and fungal strains were not sufficient. The screening of fungi from cold habitats against clinically isolated multi-drug resistant bacterial and fungal strains has not yet been reported. However, Brunati et al. (2009) screened 160 filamentous fungi and 171 yeasts (isolated from benthic mats of Antarctic lakes) against bacterial and fungal human
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 202 Chapter 4 Fungal Diversity pathogens from American Type Culture Collection (ATCC) and the Merck Culture Collection (MB, MY) including Staphylococcus aureus, Enterococcus faecium, Escherichia coli, Moraxella catarrhalis, Pseudomonas aeruginosa, Candida albicans, Aspergillus fumigatus and Cryptococcus neoformans but they were not multi-drug resistant. A total of 47 (29%) filamentous fungi inhibited the growth of Staphylococcus aureus (14%), Escherichia coli (10%) and Candida albicans (11%) and Cryptococcus neoformans (8%).
In this study, fungal isolates showed a broad range of enzymatic production. Many isolates exhibited extracellular enzyme production. Generally, fungal isolates were good producers of lipases, phosphatases and cellulases. Many of the fungi from cold regions have been found good producers of different extracellular enzymes in various research studies including amylase, lipase, cellulose, chitinase, polygalacturonase and phosphatase (Fenice et al. 1997; Singh et al. 2012; Singh et al. 2014).
Conclusions
The study site explored for the first time for the presence of psychrotrophic and psychrophilic fungi in Batura glacier. Fungal isolates mostly belonging to Ascomycetes, followed by Basidiomycetes and Zygomycetes were found. They were very versatile being able to grow at a broad range of temperature, pH and salt conditions, and were also capable of antibiotic and enzyme production at low temperatures.
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Maheshwari R, Bharadwaj G, Bhat MK (2000) Thermophilic Fungi: Their Physiology and Enzymes. Micro Mole Bio Rev 64:461–488 Maheswari R (2005) Fungal biology in the 21st century. Cur Sci 88:1406-1418 Margesin R, Fauster V, Fonteyne PA (2005) Characterization of cold-active pectate lyases from psychrophilic Mrakia frigida. Lett App Micro 40:453–459 Margesin R, Fonteyne PA, Schinner F, Sampaio JP (2007) Novel psychrophilic basidiomycetous yeasts from Alpine environments: Rhodotorula psychrophila sp. nov., Rhodotorula psychrophenolica sp. nov. and Rhodotorula glacialis sp. nov. Int J Sys and Evo Micro 57:2179–2184 Morita R (2000) Low-temperature environments. In: Lederberg J (ed) Encyclopedia of Microbiology, vol. 3 L–P, Academic Press, New York, pp 93–98 Morita RY (1975) Psychrophilic bacteria. Bact Rev 39:144–167 Oh JY, Kim EN, Ryoo MII, Kim KD (2008) Morphological and molecular identification of Penicillium islandicum Isolate KU101 from stored rice. P Path J 24:469–473 Pikovskaya RI (1948) Mobilization of phosphorus in soil connection with the vital activity of some microbial species. Microbiologia 17:362-370 Rahman A, Duncan AlJ, Miller DW et al (2008) Livestock feed resources, production and management in the agro-pastoral system of the Hindu Kush – Karakoram – Himalayan region of Pakistan. The eff of acces Agr Sys 96:26–36 Robinson CH (2001) Cold adaptation in Arctic and Antarctic fungi. New Phytologist 151:341–353 Robinson CT, Gessner MO, Callies KA et al (2000) Larch needle breakdown in contrasting streams of an alpine glacial floodplain. J North Americ Bentho Soc 19:250–262 Rosa LH, Vaz ABM, Caligiorne RB, Campolina S, Rosa CA (2009) Endophytic fungi associated with the Antarctic Grass Deschampsia Antarctica Desv. (Poaceae). Pol Bio 32:161–167 Schadt CW, Martin AP, Lipson DA, Schmidt SK (2003) Seasonal dynamics of previously unknown fungal lineages in tundra soils. Sci 301:1359–1361 Selbmann L, de-Hoog GS, Mazzaglia A, Friedmann EI, Onofri S (2005) Fungi at the edge of life: cryptoendolithic black fungi from Antarctic desert. Stud in Myco 51:1– 32 Singh PN, Singh SK, Sharma PK (2014) Pigment, fatty acid and extracellular enzyme analysis of fungal strain Thelebolus microspores from Larsemann Hills, Antarctica. Pol Rec 50:31–36 Singh SM, Singh SK, Yadav LS, Singh PN, Ravindra R (2012) Filamentous Soil Fungi from Ny-Ålesund, Spitsbergen, and Screening for Extracellular Enzymes. Arctic 65:45-55 Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Bio Evo 24:1596–1599
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Tamura K, Nei M (1993) Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Bio Evo 10:512-26 Thompson JD, Toby JG, Plewniak F, Jeanmougin F, Desmond GH (1997) The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25:4876–4882 Tojo M, Newsham KK (2012) Snow moulds in polar environments. Fung Eco 5:379- 480 Vishniac H.S (2006) Yeast biodiversity in the Antarctic. In: Rosa CA, Gabor P (ed) Biodiversity and ecophysiology of Yeasts, Springer, pp 419–440 Vishniac HS (1996) Biodiversity of yeasts and filamentous microfungi in terrestrial Antarctic ecosystems. Biodiver Conserv 5:1365–1378 Vivian N, Goncalves Aline BMV, Rosa CA, Luiz H, (2012) Rosa Diversity and distribution of fungal communities in lakes of Antarctica. FEMS Micro Eco 82:459– 471 Wang M, Jiang X, Wu W, Hao Y, Su Y, Cai L, Xiang M, Liu X (2015) Psychrophilic fungi from the world’s roof. Persoonia 34:100–112 Xin M, Zhou P (2007) Mrakia psychrophila sp. nov, a new species isolated from Antarctic soil. J Zhej Uni Sci B 8:260-265 Zucconi L, Pagano S, Fenice M et al (1996) Growth temperature preferences of fungal strains from Victoria Land, Antarctica. Pol Bio 16:53-61
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Chapter 4: Fungal l Diversity Paper 2: (Passu glacier) Title: Insights into the Distribution and Diversity of Fungal Communities in Non-polar Karakoram Valley Glacier (Passu), Pakistan
Muhammad Rafiq, Noor Hassan, Alexandre M Anesio, Aamer Ali Shah, Fariha Hasan
Status: Submitted in “Ecological Research”
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 4 Fungal Diversity
Insights into the Distribution and Diversity of Fungal Communities in Non-polar Karakoram Valley Glacier (Passu), Pakistan Muhammad Rafiq1, Noor Hassan1, Alexandre M Anesio2, Aamer Ali Shah1, Fariha Hasan1 1Department of Microbiology, Quaid-i-Azam University, Islamabad, Pakistan 2Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, UK
Abstract The current study is the first report of the isolation and culturable diversity of psychrotrophic fungi from glacial ice, water and sediment samples collected from Passu glacier, Pakistan, and some important characteristics related to their physiological requirements and growth are also included. Conventional and molecular techniques (18S rDNA sequencing), were used to identify fungi. A total of 27 fungal isolates were identified. The most predominant genus was Penicillium, followed by Mrakia, Cladosporium, Pseudeurotium, Fontanospora, Trichoderma, Antrodia, Sporobolomyces, Phoma, Beauveria and Pseudogymnoascus while one isolate belonged to Pleosporales order and one belonged to Dothideomycetes class. Tolerance of all isolates to wide pH, temperature and salt concentration was studied. All the fungal isolates showed growth between 4 and 37°C, whereas some fungal isolates were able to grow at 45°C. Most of the isolates (~80%) showed growth at pH 1-13 except 5 isolates that could not tolerate pH 1. Fungal isolates tolerated salt concentration between 2-26% with maximum range of all as 16% and above, i.e. all moderate to extreme halophiles. Fungal isolates were screened for their antimicrobial activity against clinically isolated bacterial and fungal strains and the findings were quite promising. Fontanospora sp. was able to show activity against Staphylococcus aureus and Candida sp. Fungal isolates were screened for the production of extracellular enzymes (amylase, cellulase, deoxyribonuclease, lipase, phosphatase and protease) of valuable commercial and economic importance. Many isolates were able to produce one or more enzyme, whereas, Sporobolomyces ruberrimus produced all enzymes except lipase. Key words: Passu glacier, psychrotrophic fungi, fungal diversity, isolation, identification, characterization
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Introduction The term psychrophiles was first used by Schmidt-Nielsen in 1902. Psychrophilic and psychrotrophic organisms are defined as the organisms that can grow at or near to zero temperature. Psychrophiles can be found everywhere, where the cold environments exist (Ingram 1965; Morita 1975). It has been evident from different studies of polar, alpine and deep ocean environments that microbial life exists in cold habitats (Cavicchioli et al. 2002) and in fact, microbial metabolic reactions have been observed at -17°C (Brunatia et al. 2009). Psychrophiles cover all three domains of life. In eukaryotes, the fungi have been found a good survivor community in psychrophilic condition. Psychrophilic fungi grow optimally at 15°C or lower but can also grow at temperature of 20°C or below, while psychrotrophic fungi grow well at temperature above 20°C (Robinson 2001).
The fungi have broadly been studied for their presence in Polar and Non-polar cold environments (Hassan et al. 2016), such as Arctic and Antarctica habitats (Azmi and Seppelt 1997; Babjeva and Reshetova 1998; Tosi et al. 2002; Onofri et al. 2004; Selbmann et al. 2005). The studies related fungal diversity and characterization in non-polar regions such as Hindukush-Karakoram-Himalayas (HKKH) glaciers is very poor. The HKKH glaciers have not so properly investigated for presence of psychrophilic and psychrotrophic life (microorganisms). Five species of aquatic hyphomycetes belonging to the genus Lemonniera and aquatic hyphomycete, Tetracladium nainitalense as a root endophyte have isolated from Kumaun Himalaya, India (Sati et al. 2009; Sati et al. 2014). Anupama et al. (2011) reported the psychrophilic and halotolerant Thelebolus microsporus from the Pangong Lake Himalayan region.
Singh and Palni. (2011) have collected 35 species belonging to 7 families of rust fungi from herbaceous and shrubby hosts in central Himalayan region. Moreover, 25 psychrophilic yeasts determined from the Roop Kund Lake soil of Himalayas, India (Shivaji et al. 2008). Three anti-fungal Trichodermal species, T. harzianum, T. konengii and T. viride have been isolated from forest of Indian Himalayan Region (Ghildiyal and Pandey 2008). Wang et al. (2015) studied glaciers of Qinghai-Tibet Plateau for the presence cold-adapted fungi and isolated 1428 fungi in which 150 species were identified and Phoma sclerotioides and Pseudogymnoascus pannorum were the most dominant species. Hirose et al. (2009) have isolated 24 fungal species
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 210 Chapter 4 Fungal Diversity and carried out their comparison studies on cotton strips at three different altitudes on the Tibetan Plateau and assessed the environmental variables influencing them.
Psychrophilic fungi are capable of providing a large number of biotechnological and pharmaceutical applications. Psychrophilic fungi are capable of synthesizing secondary metabolites that are very unique to cold ecosystems (Rosa et al. 2008). It is a fact that the appearances of multidrug resistant pathogenic strains caused substantial morbidity and mortality especially among the elderly and immunocompromised patients. To overcome this situation, there is an interest to improve or discover novel class antibiotics that have different mechanisms of action worldwide. There is an extreme need of continuous screening of secondary microbial products produced from potential psychrophilic fungal taxa. Although, there are no significant studies have been conducted so far to isolate and evaluate psychrophilic fungi from different cold habitats that could produce useful antibiotics.
The aim of this study was to isolate and identify fungi from samples of glacial ice, sediments and water taken from Passu glacier, Pakistan, as well as to determine their physiological characteristics and their ability to produce antimicrobial metabolites and extracellular enzymes.
Materials and Methods
Sampling and fungal isolation
The samples (glacial ice, sediments and water) were collected from Passu glacier of the Karakoram Range, Pakistan (36°27.424N to 074°52.010E) using sterile bottles followings standard microbiological protocol. The samples were retained in ice until arrival at the laboratory and stored at -20°C. The pH for the all samples was neutral (7.0), whereas, temperatures of sediments and water was 1°C while ice had -2°C.
The isolation of fungal isolates was carried out on Sabouraud Dextrose Agar (SDA), Potato Dextrose Agar (PDA) and Malt Extract Agar (MEA) by spreading serially diluted samples on to the plates. The plates were incubated at 4°C and 15°C for 3-4 weeks. Fungal colony-forming units (CFUs) were calculated and fungi growing on the agar plates with different texture and morphology were transferred to new plates by
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 211 Chapter 4 Fungal Diversity subculturing techniques. For subculturing purpose, Potato Dextrose Agar (PDA), Malt Extract Agar (MEA) and Tryptic Soy Agar (TSA) were used.
Morphological and microscopic analysis
Colonies of fungal isolates were cultured on SDA at corresponding fungal isolates isolated temperature for 10 days. The morphological characteristics were recorded in terms of colony growth (length and width), presence or absence of aerial mycelium, colony color, presence of wrinkles and furrows etc. Microscopic morphology was observed using lacto-phenol cotton blue staining (40x).
DNA extraction, Sequencing and phylogenetic analysis
The fungal DNA extraction was done according to protocols earlier described by Wang and Zhuang (2004). The extracted DNA was amplified using universal fungal primers. The primers ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′- TCCTCCGCTTATTGATATGC-3′) were used for amplification of ITS regions (ITS1-5.8S ITS2). The PCR conditions were: initial denaturation at 94°C for 1 min, 30 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 1 min, followed by 10 min final extension at 72°C. PCR products were confirmed by running on 1% agarose gel. The extracted fungal DNA was sent to Macrogen, (Macrogen Inc. Seoul, Korea) for 18S rRNA sequencing purpose. The gained sequences were analysed DNA baser and were further evaluated by comparing the nucleotide sequences available in NCBI database (Thompson et al. 1997) by BLAST search analysis. The evolutionary history was inferred by using the Maximum Likelihood method based on the (Tamura-Nei model 1993). The phylogenetic tree was constructed in MEGA software using maximum likely hood method (Tamura et al. 2007) at the bootstrap value 1,000 replicates.
Physiological analysis
The physiological parameter analysis including growth at different temperature, pH and salt concentration were carried out on SDA using 7 days old fungal culture colony. Temperature tolerance was determined by cultivation of the fungi isolates on 4, 15, 37, 45 and 50°C. For determination of pH tolerance, fungi isolates grown in the
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 212 Chapter 4 Fungal Diversity medium containing pH from 1 to 13. The salt tolerance of fungal isolates was determined by inoculating cultures in the SDA medium accompanied with different concentrations of NaCl up to 26%.
Screening for the antimicrobial metabolites production
Antimicrobial activity of fungal cultures was tested against the clinical isolates, E. coli (Multi-drug resistant), Klebsiella pneumoniae (Multi-drug resistant), Staphylococcus aureus (Multi-drug resistant), Staphylococcus sp., Enterococcus sp. (vancomycin resistant enterococci), Candida albicans and Aspergillus niger. The suspension of all test pathogens was prepared in normal saline according to 0.5 McFarland standard. The point inoculation method was used in antimicrobial activity analysis. A sterile cotton swab was used to prepare uniform lawn on PDA and TSA. A small portion of each fungal mycelium was inoculated on plates containing test microbial lawn.
Screening for the extracellular enzymes production
The fungal isolates were screened for the production of extracellular enzymes including amylase, cellulase, deoxyribonuclease, lipase, phosphatase and protease. SDA was used for this purpose. Ten day old fungal cultures were used as inoculum. Amylase, deoxyribonuclease, lipase and protease activity was screened using the protocol given by (Hankin and Anagnostakis 1975). The phosphatase activity was determined on Pikovskaya's medium (Pikovskaya 1948). Whereas for cellulolytic activity, carboxymethylcellulose (CMC) was used as a substrate. The plates were flooded with 0.5% Congo red solution for 10 minutes, washed with distilled water and then flooded with 1 M NaCl. The clearing zone around the colony was observed. All qualitative extracellular enzyme activities were assayed at 4 and 15°C.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 213 Chapter 4 Fungal Diversity
Results
In the current study, 27 fungal isolates were isolated on the basis of distinct colony morphology from glacial ice, water and sediments samples taken from the Passu glacier, Pakistan. 15 fungal isolates were isolated at 15°C and 12 isolated at 4°C. The total fungal CFU/g/mL was high in sediments followed by water and ice respectively (Table 4.2.1).
Table 4.2.1 Total viable count (CFU/g/mL) of fungal isolates at 15°C and 4°C.
Temperature (°C) Samples No. of CFU/g/mL colonies/200µL Glacier ice 5 25 15 Glacier water 4 20 2 3 Glacier sediment 1.8x10 9.0x10 Glacier ice 1 5
4 Glacier water 3 15 2 3 Glacier sediment 1.4 x10 7.0x10
Morphological and microscopic analysis
Most of fungal isolates produced extensive spores, powdery and cottony texture, different colors (blue to green and olive green color was most common), however some mucoid type fungal isolates were also observed. Microscopic studies showed that hyphae were septate, spores varied in shape and yeast like structures were also observed (S 4.2.1 Appendix).
Molecular analysis
Sequence analysis of the ITS1 and ITS4 regions of the 18S rRNA gene was carried out to identify fungal species (Table 4.2.2). A total of 27 fungal isolates were identified, in which, species representing Penicillium genus were dominant. The phylogenetic relationships were determined for all 27 isolates (Fig. 4.2.1).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 214 Chapter 4 Fungal Diversity
70 HP1 39 Penicillium brevicompactum|AY373897.1| 53 HP2 55 Penicillium brevicompactum|KF876834.1| Uncultured Penicillium |HG917282.1| 9470 HP9 Penicillium sp|GU934555.1| HP15 93 Penicillium brevicompactum|DQ888731.1| 77 Penicillium biourgeianum|KM357335.1| HP3 Eurotiales sp|KP202976.1| HP11 100 Penicillium rubens|KM873044.1| 98 HP13 Penicillium dipodomyicola|FJ025172.1| Penicillium camemberti|FJ025142.1| 44 Penicillium sp|KF428217.1| HP12 78 Penicillium ochrochloron |AF033441.1| 90 HP6 Cladosporium sphaerospermum|KJ728690.1| Cladosporium sp|KF986417.1| 28 100 HP14 Cladosporium cladosporioides|KJ589555.1| 72 Cladosporium sp|JQ780629.1| 67 96 HP4 100 Beauveria bassiana |FJ792827.1| 17 Beauveria bassiana |LN809026.1| HP7 89 Trichoderma sp|KJ542313.1| 100 HP10 92 Trichoderma viridescens|KP009338.1| 17 Trichoderma atroviride|EU715667.1| LP8 Geomyces sp|HQ914918.1| 79 Pseudogymnoascus pannorum|KR019743.1| 62Uncultured Pseudeurotium|FJ378726.1| 85 HP5 HP8 96 Pseudeurotium bakeri|JN104513.1| LP5 Fontanosporasp|HQ533798.1| Varicosporium elodeae|JN995640.1| 100 LP13 Fontanospora sp|HQ533798.1| 71 LP2 99 Uncultured fungus|GU817183.1| 72 Pleosporales sp|AB751503.1| Phoma sclerotioides|DQ530450.1| 89 LP7 100 Phoma sclerotioides|GU395501.1| 94 Dothideomycetes sp|JQ759617.1| LP10 99 Uncultured fungus|KC965928.1| 92 69 LP3 99 Trametes dickinsii|EU661878.1| Antrodia juniperina|FM872464.1| 100 LP6 Sporobolomyces ruberrimus|KM376406.1| 99 Sporobolomyces ruberrimus|KM376407.1| 100 LP1 53 LP4 Uncultured fungus clone|JN889739.1| 98 LP9 94 Mrakia robertii|KC333173.1| LP11 97 Mrakia robertii|KC455915.1|
0.05
Fig. 4.2.1. Phylogenetic tree of the fungal isolates prepared by Maximum Likelihood analysis of ITS1 and ITS4 sequences.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 215 Chapter 4 Fungal Diversity
Table 4.2.2 Similarity of the fungal isolates to their corresponding homologous species and accession no. Isolate Accession No. Homologous Species (Accession No.) QC(%) ID(%) HP1 KR610963 Penicillium brevicompactum [AY373897.1] 100 100
HP2 KR610964 Penicillium brevicompactum [KF876834.1] 97 99
HP3 KR610965 Penicillium rubens [KM873044.1] 100 100
HP4 KR610966 Beauveria bassiana |FJ792827.1| 91 99
HP5 KR610967 Pseudeurotium bakeri [JN104513.1] 99 100
HP6 KR610968 Cladosporium spherospermum [KJ728690.1] 100 99
HP7 KR610969 Trichoderma viridescens [KP009338.1] 100 100
HP8 KR610970 Pseudeurotium bakeri [JN104513.1] 99 100
HP9 KR610971 Penicillium biourgeianum [KM357335.1] 99 100
HP10 KR610972 Trichoderma viridescens [KP009338.1] 100 100
HP11 KR610973 Penicillium rubens [KM873044.1] 100 100
HP12 KR610974 Penicillium ochrochloron [AFO33441.1] 99 100
HP13 KR610975 Penicillium dipodomyicola [FJ025211.1] 99 100
HP14 KR610976 Cladosporium cladosporioides [KJ589555.1] 99 95
HP15 KR610977 Penicillium brevicompactum [DQ888731.1] 99 100
LP1 KR610978 Mrakia robertii |KC455915.1| 93 84
LP2 KR610979 Pleosporales sp. |AB751503.1| 100 100
LP3 KR610980 Antrodia juniperina [FM872464.1] 100 88
LP4 KR610981 Mrakia robertii |KC455915.1| 93 84
LP5 KR610982 Fontanospora sp. [HQ533798.1] 97 100
LP6 KR610983 Sporobolomyces ruberrimus [KM376407.1] 100 100
LP7 KR610984 Phoma sclerotioides [GU395501.1] 100 100
LP8 KR610985 Pseudogymnoascus pannorum |KR019743.1| 100 100
LP9 KR610986 Mrakia robertii [KC333173.1] 99 100
LP10 KR610987 Dothideomycetes sp. [JQ759617.1] 100 99
LP11 KR610988 Mrakia robertii [KC333173.1] 99 100
LP13 KR610989 Fontanospora sp. [HQ533798.1] 97 100
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 216 Chapter 4 Fungal Diversity
Physiological analysis
The fungal isolates showed growth at wide range of pH (pH 1-13). All the fungal isolates tolerated pH from 2 to 13, whereas, 8 isolates did not grow at pH 1 while the remaining 27 isolates were able to grow at pH 1 (Table 4.2.3). The optimum pH for all fungal isolates was observed between pH 5 and 9. The fungal isolates showed growth at temperatures between 4-37°C, with an optimum growth temperature of 4
and 15°C, while four isolates (LP6, LP9, LP11 and LP12) also showed growth at 45°C but none of them exhibited growth at 50°C (Table 4.2.3). The fungal isolates tolerated salt concentrations up to 26%. All isolates showed growth between 2 and 16%,
whereas, 5 isolates (LP1, LP1, LP6, LP9 and LP11) were able to grow at 26% salt concentration as well (Table 4.2.3).
Table 4.2.3 Physiological analysis of the fungal isolates on different temperature, pH and salt concentrations
Isolates Temperature (°C) range pH range Salt range (%) HP1 4−37, opt. 15 1−13, opt. 6–8 2−24, opt. 2–8
HP2 4−37, opt. 15 1−13, opt. 6–7 2−20, opt. 2–6
HP3 4−37, opt. 15 1−13, opt. 6–7 2−24, opt. 2–8
HP4 4−37, opt. 15 1−13, opt. 6–8 2−20, opt. 2–6
HP5 4−37, opt. 15 1−13, opt. 6–8 2−20, opt. 2–6
HP6 4−37, opt. 15 1−13, opt. 6–8 2−20, opt. 2–6
HP7 4−37, opt. 15 2−13, opt. 6–7 2−18, opt. 2–6
HP8 4−37, opt. 15 1−13, opt. 6–7 2−20, opt. 2–6
HP9 4−37, opt. 15 1−13, opt. 6–7 2−20, opt. 2–6
HP10 4−37, opt. 15 2−13, opt. 6–7 2−18, opt. 2–6
HP11 4−37, opt. 15 2−13, opt. 6–7 2−20, opt. 2–6
HP12 4−37, opt. 15 1−13, opt. 6–8 2−24, opt. 2–8
HP13 4−37, opt. 15 1−13, opt. 6–8 2−24, opt. 2–8
HP14 4−37, opt. 15 1−13, opt. 6–8 2−20, opt. 2–6
HP15 4−37, opt. 15 1−13, opt. 6–7 2−20, opt. 2–6
LP1 4−37, opt. 4 1−13, opt. 6–7 2−26, opt. 2–8
LP2 4−37, opt. 4 2−13, opt. 6–7 2−18, opt. 2–4
LP3 4−37, opt. 4 1−13, opt. 6–7 2−18, opt. 2–4
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 217 Chapter 4 Fungal Diversity
LP4 4−37, opt. 4 1−13, opt. 6–7 2−26, opt. 2–8
LP5 4−37, opt. 4 1−13, opt. 6–7 2−18, opt. 2–6
LP6 4−45, opt. 4 1−13, opt. 6–8 2−26, opt. 2–8
LP7 4−37, opt. 4 2−13, opt. 6–7 2−20, opt. 2–6
LP8 4−37, opt. 4 2−13, opt. 6–7 2−16, opt. 2–6
LP9 4−45, opt. 4 1−13, opt. 6–7 2−26, opt. 2–8
LP10 4−37, opt. 4 1−13, opt. 6–7 2−16, opt. 2–6
LP11 4−45, opt. 4 1−13, opt. 6–8 2−26, opt. 2–8
LP13 4−37, opt. 4 1−13, opt. 6–8 2−18, opt. 2–6
Screening for the antimicrobial metabolite production
Most of the fungal isolates exhibited antimicrobial activity against Gram positive bacteria followed by fungal strains and then Gram negative bacteria. Antimicrobial activity of the fungal isolates against the clinically isolated bacterial and fungal strains is given in Table 4.2.4. Thirteen fungal isolates showed antimicrobial activity against Staphylococcus sp., 4 against Staphylococcus aureus, 2 against Enterococcus sp., 3 against E. coli, while 4 fungal strains showed antifungal activities against both Candida albicans and Aspergillus niger, respectively. But none showed antimicrobial activity against Klebsiella pneumoniae.
Screening for the extracellular enzymes production
Out of 27 fungal isolates, 9 displayed positive phosphate solubilizing activity on Pikovskaya medium, only 1 showed proteolytic activity, 5 isolates exhibited amylolytic activity, 8 fungal isolates found positive for lipase production, 13 isolates exhibited cellulase activity and DNase activity was found positive in 3 fungal isolates. The results of the preliminary screening for the extracellular enzymes production (qualitatively) are given in Table 4.2.5.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 218 Chapter 4 Fungal Diversity
Table 4.2.4 Antimicrobial activity of the fungal isolates against the clinically isolated bacterial and fungal strains
Bacteria Fungi Isolates E. Klebsiella S. Staph: Enterococcus Aspergillus C. coli pneumoniae aureus sp. sp. niger albicans HP1 − − − − − ++ −
HP2 − − − ++ − + −
HP3 − − − − − − −
HP4 − − − + − − −
HP5 − − − − − − −
HP6 − − − − − − −
HP10 − − − − − − −
HP8 − − − − − − −
HP9 − − − − − ++ −
HP10 − − − − − − −
HP11 − − − − − − −
HP12 − − − + − − −
HP13 − − − ++ − − −
HP14 − − − − − − −
HP15 − − − + − + −
LP1 − − − − − − −
LP2 + − +++ +++ +++ − −
LP3 − − − +++ − − −
LP4 − − − − − − −
LP5 + − ++ +++ − − ++
LP6 − − − +++ − − −
LP7 − − + +++ − − +
LP8 − − − +++ − − −
LP9 − − − +++ − − +
LP10 − − − − − − −
LP11 − − − +++ − − +
LP13 + − ++ +++ − − ++ Key: (-) No Zone, (+) Zone up to 8 mm, (++) Zone up to 16 mm, (+++) Zone above 16 mm
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 219 Chapter 4 Fungal Diversity
Table 4.2.5 Screening of the fungal isolates for the extracellular enzymes production (qualitatively). Isolates Enzymes Amylase Cellulase DNase Lipase Phosphatase Protease HP1 − − − ++ + −
HP2 − ++ − − + −
HP3 − + − − − −
HP4 − − − − − −
HP5 − − − − − −
HP6 − − − − − −
HP17 − +++ − − − −
HP8 − − − − +++ −
HP9 − ++ − − − −
HP10 − +++ − − − −
HP11 − − − − − −
HP12 − ++ − ++ + −
HP13 − − − − + −
HP14 − − − − − −
HP15 − ++ − − + −
LP1 − + + + + −
LP2 − − − − − −
LP3 − − − − − −
LP4 − + + + + −
LP5 − − − − + −
LP6 + ++ ++ ++ − ++
LP7 ++ − − − − −
LP8 ++ ++ − ++ − −
LP9 ++ ++ − + − −
LP10 − − − − − −
LP11 ++ ++ − + − −
LP13 − − − − − − Keys: (-) No Zone , (+) Zone up to 6 mm, (++) Zone up to 12 mm, (+++) Zone above 12 mm
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 220 Chapter 4 Fungal Diversity
Discussion
The aim of this study was to isolate and identify psychrotrophic fungi from Passu glacier, Pakistan. The fungal biota has not been investigated in this glacier previously. A total of 27 fungal strains were isolated from three different samples i.e. glacial ice (3 isolates), sediments (18 isolates) and water (6 isolates). For the identification purpose, culture morphology and microscopic characteristics of the fungal isolates was observed and species level identification further confirmed by molecular analysis (Table 4.2.2 and S 4.2.1). Out of 27 fungal isolates, 23 showed most similarity (between 99 and 100 %) to their homologous strains in NCBI database. Four isolates
HP4, HP14, LP1 and LP3 showed maximum similarity 91, 95, 84 and 88%, respectively, with the homologous strains deposited in NCBI database that need further investigation in terms of their taxonomic studies. Several of fungi have been identified on the basis of the combination of morphological and molecular methods (Onofri et al. 2004, Dhakar et al. 2014). Mostly fungal isolates belong to phyla Ascomycota whereas only few isolates have been found belong to phyla Basidiomycota. A total of 11 genera, one order and one class of fungi have been found. The most predominant genus was Penicillium (8 isolates), followed by Mrakia (4), Cladosporium (2), Pseudeurotium (2), Fontanospora (2), Trichoderma (2), Antrodia (1), Sporobolomyces (1), Phoma (1), Beauveria (1) and Pseudogymnoascus (1) while one isolate belonged to Pleosporales order and one belonged to Dothideomycetes class.
We are reporting for the first time the presence of Beauveria bassiana, Pseudeurotium bakeri, Antrodia juniperina, Pleosporales sp., Dothideomycetes sp., Fontanospora sp. and Sporobolomyces ruberrimus in non-polar glaciers. To our knowledge, Antrodia juniperina has isolated for the first time from polar and non-polar habitats. However, the same species or genus of the above mentioned fungal isolates (except Antrodia juniperina) has been reported from different Polar Regions. The genus Penicillium displays tolerance for cold environments and even growth of many Penicillium species have found on food preserved in refrigerators (Pitt and Hocking, 1999), or also isolated from alpine, tundra (Domsch et al. 1980), and even polar habitats (McRae et al. 1999). Due to their psychrotolerant nature and prolific conidia
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 221 Chapter 4 Fungal Diversity production, Penicillium are among the few viable fungi that have isolated from glacial ice cores even up to 38,600 years old (Abyzov 1993).
The psychrophilic and psychrotrophic species of genus Mrakia have been isolated from low temperature habitats (Xin and Zhou 2007; Turchetti et al. 2008). Recently, some Mrakia species have isolated from Tinto River (López-Archilla et al. 2004). Margesin et al. (2005) reported the cold-active pectate lyases from psychrophilic Mrakia frigida. Pseudogymnoascus sp. are widely found nearly everywhere from Arctic to Antarctica (Marshall 1998). They have the ability to tolerate low temperatures and high salinity, although they are not true psychrophilic or halophilic fungi (Lowry and Gill 1984; Robinson 2001; Ozerskaya et al. 2004).
The Pseudeurotium bakeri was isolated as dominant species from pristine and diesel fuel contaminated sub-Antarctic soil via cultivation using both a high and a low nutrient media approach (Belinda et al. 2011). Cladosporium species have been repetitively reported from the different location of Antarctica (McRae et al. 1999; Ma et al. 2000; Blanchette et al. 2010). They have been found tolerated to low temperature and low oxygen tensions (Horak 1960; Vargo et al. 1986). The genus Sporobolomyces and Beauveria in polar habits, has reported very rarely (Bergauer et al. 2005; Onofri et al. 2007; Hughes and Bridge 2010). The presence of genus Fontanospora, Trichoderma, Phoma and class Dothideomycetes in various polar and non-polar habitats, have been reported by many authors (Zacconi et al. 1996; Bergero et al. 1999; Edwards et al. 2013; Wang et al. 2014).
The growth of the fungal isolates has been analyzed for various physiological parameters (pH, temperature and salt concentration). All the isolates were allowed to grow on media with different pH. Ability of the fungal isolates to grow under wide range of pH (1–13), is an outstanding outcome of the current study. The tolerance of the fungal isolates to different salt concentrations (2-26%) was remarkable. All isolates showed growth between 2 and 16% whereas 4 isolates (LP1, LP6, LP9 and
LP11) grew at 26% salt concentration as well. The fungal isolates of the present study, including Beauveria bassiana, Pseudeurotium bakeri, Cladosporium species, Trichoderma viridescens, Mrakia robertii, Pleosporales sp., Antrodia juniperina, Fontanospora sp., Sporobolomyces ruberrimus, Phoma sclerotioides and Dothideomycetes sp., have not been characterized on such extreme conditions of pH
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 222 Chapter 4 Fungal Diversity and NaCl concentration. However, species of the Penicillium genus and few other fungal genera have reported from cold and other habitats that were capable to grow at both acidic and alkaline pH as well as high NaCl concentrations (Eliades et al. 2006; Kochkina et al. 2007; Yamazaki et al. 2010; Isobe et al. 2013; Greiner et al. 2014; Dhakar et al. 2014). Moreover, the psychrotrophic fungus demonstrated their growth in wide temperature range between 4 and 45°C. Most of the fungal isolates were Eurypsychrophile that grew healthy at low temperatures (4 and 15°C) but could also slightly grow up to mesophilic range but none was Stenopsychrophile (that can grow at or below 20°C) (Cavicchioli, 2006). Few isolates (LP6, LP9, LP11 and LP12) showed growth at 45°C and thus considered as thermotolerant. Zucconi et al. (1996) and Morgenstern et al. (2012) have reported fungus species that were able to grow at 45°C. In this study, the fungal isolates were checked for their antibacterial and antifungal activities against clinically isolated bacterial and fungal strains such as E. coli (MDR), Klebsiella pneumonae (MDR), Staphylococcus aureus (MDR), Staphylococcus sp., Enterococcus sp. (VRE), Candida albicans and Aspergillus niger, respectively. Many fungal isolates have been found to produce secondary metabolites with bactericidal and fungicidal activity. The fungal isolates showed good activities against Gram (+) bacteria but their antifungal activity and activity towards Gram (‒) bacteria and fungi was low. The activity of fungi from cold habitats against clinically isolated multi-drug resistant bacteria and Candida has not been reported before. Extensive research has been carried out by researchers to find out the antibacterial activity of fungi from mesophilic habitats against clinically isolated bacterial and fungal strains (Brunatia et al. 2009; Svahn et al. 2012). Moreover, our results are also supported by Suay et al. (1997). About 317 Basidiomycetes isolates expressing 204 species, collected in Spain were selected for their anti-bacterial and anti-fungal activity against a variety of human clinical pathogens (including MDR as well) and laboratory controls. About 109 species showed antimicrobial activity but their antibacterial activity was more noticeable than antifungal activity. The extracellular enzyme production has not been reported from fungal isolates of Passu glacier, Pakistan. Most of the fungal isolates were cellulolytic in nature followed by phosphatase, lipase, amylase, deoxyribonuclease and protease. None of the isolate was able to produce all enzymes, onlyisolate LP6 produced 5 enzymes except phosphatase. Our results are also supported by Fenice et al. (1997) who
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 223 Chapter 4 Fungal Diversity screened 33 fungal strains isolated from various sites of Victoria Land (continental Antarctica) and reported production of 12 extracellular enzymes Gawas-Sakhalkar et al. (2012) isolated Aspergillus niger strains and Penicillium citrinum from Arctic having phosphate solubilizing abilities.
Conclusions In conclusions, 27 isolates of fungi were isolated from glacial ice, water and sediments of the Passu glaciers, Pakistan at two temperatures, 4°C and 15°C. After morphological, microscopical and molecular analysis, it has been found that most of the isolates were Ascomycetes, followed by Basidiomycetes. The fungal isolates were able to tolerate a wide range of temperature, pH and salt, also capable of antibiotic and enzyme production. Among these fungi, many isolates showed good antimicrobial activity against clinically isolated bacterial and fungal strains while exhibited enzymatic potential for industrial uses.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 224 Chapter 4 Fungal Diversity
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Chapter 4: Fungal Diversity Paper 3: (Siachen glacier) Title: Isolation and characterization of psychrotrophic fungi from Siachen glacier, Pakistan.
Muhammad Rafiq, Noor Hassan, Shauka Nadeem, Aamer Ali Shah, Fariha Hasan.
Status: Under review in ‘Folia Microbiologica’
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 4 Fungal Diversity
Title: Isolation and characterization of psychrotrophic fungi from
Siachen glacier, Pakistan
Muhammad Rafiq, Noor Hassan, Shaukat Nadeem, Aamer Ali Shah, Fariha Hasan
Department of Microbiology, Quaid-i-Azam University, Islamabad, Pakistan
ABSTRACT
This is the first study of diversity and distribution of fungi in ice, sediments and water samples from Siachen glacier, located at Himalaya Range, Pakistan. The isolation and Total Viable count (CFU/ml or g) was carried out by spread plate technique at 4°C and 15°C. Seventeen fungal isolates were obtained and identified by analysis of 18S rRNA ITS region. The most frequently isolated fungal isolates were Leotiomycetes sp., followed by Thelebolus, Penicillium, Cladosporium, Trichoderma, Periconia, Geomyces, Cryptococcus and Pueraria. All isolates were found halophilic and they were able to tolerate NaCl concentration up to 10-20%. Some isolates showed viability at 45°C, most of the isolates were able to grow at pH 1- 13. All isolates were screened for their antimicrobial activity against clinically isolated bacterial and fungal strains but they showed good antimicrobial activity against Gram (+) bacteria. None of the fungal isolate inhibited Gram negative clinically isolated E. coli and Klebsiella pneumonia but few isolates inhibited tested Gram positive bacterial and fungal strains. Fungal isolates were also screened for extracellular enzyme (amylase, cellulase, deoxyribonuclease, lipase, phosphatase and protease) production. Various isolates were good producers of cellulase, lipase and protease whereas only 2 out of 17 produced DNase and 4 produced phosphatase.
Keywords: Non-polar glaciers, psychrophilic fungi, psychrotrophic fungi, phylogenetic, Siachen glacier.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 230 Chapter 4 Fungal Diversity
INTRODUCTION
Psychrophilic fungi grow optimally at 15°C or lower but can also grow at temperature around 20°C or below, while psychrotrophic fungi grow well at temperature above 20°C (Maheswari 2005; Robinson 2001). Such type of fungi have been found and investigated in all major cold habitats, such as Antarctica (Blanchette et al. 2011), Arctic regions (Sonjak et al. 2006), cold deep sea environments (Damare and Chandralata 2008), European Alps (Greiner et al. 2013). Various fungi representing different genera and species e.g. Thelebolus microspores, Lemonniera, Tetracladium, have been isolated from the different regions of Himalaya, India (Sati et al. 2014; Anupama et al. 2011).
The fungi in cold environments are facing numerous extreme limiting factors, including frequent freeze-thaw cycles, high salt concentration, low moisture content, extreme UV radiation, and low nutrient availability (McKenzie et al. 2003; Robinson 2001). To face such harsh conditions, fungi adapt themselves by various physiological and ecological mechanisms (Anupama et al. 2011). Although several cold adaptive mechanisms of psychrophilic fungi have been described but it is assumed that a mixture of such mechanisms are employed by psychrophiles including production of antifreezes, compatible salutes, trehalose, freeze tolerance (Ruisi et al. 2007; Robinson 2001).
Psychrophilic and psychrotrophic fungi are capable of providing a large number of biotechnological and pharmaceutical applications. Psychrophilic fungi are capable of synthesizing secondary metabolites that are very unique to cold ecosystems (Rosa et al. 2008). Psychrophilic fungi are producer source of cold shock and cold-acclimation proteins and enzymes (e.g. proteases, lipases and cellulases) that widely used in various biotechnology fields (Gounot 1991). These include cold-water detergents, food additives and flavor modifying agents, biosensors. The psychrophilic fungi can also be central to astrobiology field as other psychrophiles are (Montes-Hugo et al. 2009). This study was commenced to investigate the presence of psychrotrophic fungi from samples of glacial ice, sediments and water taken from Siachen glacier, Pakistan, as well as to evaluate various physiological parameters and antimicrobial activity and extracellular enzyme production.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 231 Chapter 4 Fungal Diversity
MATERIALS AND METHODS
Sampling
The Siachen glacier is the second longest non-polar glacier in the world, 70 km long and located in the Himalaya Range. The total width of the glacier is between 2-8 km and the total area is less than 1,000 km2. The samples were collected in three different forms (glacier ice, sediments and water) from Siachen glacier, Pakistan, using sterile bottles followings standard microbiological protocol and were transported to Microbiology Research Laboratory, Department of Microbiology, Quaid-i-Azam University Islamabad, on ice within 24 h for further processing. The pH for the all samples was neutral (7.0), whereas, temperatures of sediments and water was 1°C while ice had -3°C.
Fungal cultures isolation
The general purpose fungal medium, Sabouraud Dextrose Agar (SDA) and Potato Dextrose Agar (PDA) were used for the isolation of fungal cultures. The isolation was carried out at two temperatures, 4°C and 15°C. After 4 weeks of incubation, colony forming units (CFU) were counted and expressed as CFU/mL for ice and melt water samples as well as CFU/g for the sediment sample.
Morphology and microscopy evaluation
The colony morphology of fungal cultures was observed on SDA, with respect to their colony color, texture, shape etc. (front and reverse of the colony). Microscopy of the fungal isolates was done using lacto-phenol cotton blue staining method (40x).
DNA extraction, sequencing and phylogenetic evaluation
The fungal DNA extraction was accomplished according to protocols earlier described (Rosa et al. 2009). The extracted DNA was amplified using universal fungal primers, ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′- TCCTCCGCTTATTGATATGC-3′) were used for amplification of ITS regions (ITS1-5.8S ITS2). The PCR conditions were: initial denaturation at 94°C for 1 min, 30 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 1 min, followed by 10 min final extension at 72°C. PCR Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 232 Chapter 4 Fungal Diversity products of the fungal isolates were sent to Macrogen (Macrogen Inc. Seoul, Korea) for 18S rRNA sequencing. The obtained sequences were studied by Chromas Lite and were further examined by comparing the nucleotide sequences available in NCBI database (Thompson et al. 1997). The evolutionary history was inferred via the Maximum Likelihood method based on the Tamura-Nei model (Tamura and Nei 1993). The phylogenetic tree was created in MEGA software using Maximum Likelihood method (Tamura and Nei 1993) at the bootstrap value 1000.
Physiological parameters evaluation
The growth tolerance of all the fungal isolates to varying temperature, pH and salt concentrations, was checked on SDA using 10 day old colonies. For pH tolerance, pH 1 to 13, for temperature optimization, 4 to 50°C (4, 15, 37, 45, 50°C) and for salt tolerance, NaCl up to 26% in concentration were used in this study, following incubation at 4°C and 15°C for 10 days.
Antimicrobial activity evaluation
Clinically isolated human pathogens (multi-drug resistant) such as E. coli (MDR), Klebsiella pneumonia (MDR), Staphylococcus aureus (MDR), Staphylococcus sp., Enterococcus sp. (VRE), Candida albicans and Aspergillus niger were used as target subjects. Point inoculation method was used for evaluation of antimicrobial activity. Using a sterile wire loop, a pure test microbial colony was transferred into the test tubes containing normal saline and adjusted the turbidity with 0.5 McFarland solution as the standard. A sterile cotton swab was used to prepare homogenous lawn on Potato Dextrose Agar and Tryptic Soy Agar. A small portion of each fungal mycelium was inoculated on plates containing test bacterial lawn.
Extracellular enzymes evaluation
Fungal isolates were screened for the production of extracellular enzymes including amylase, deoxyribonuclease, lipase, cellulose, protease and phosphate according to protocols described (Hankin and Anagnostakis 1975; Pikovskaya 1948). The isolates were screened for cellulolytic activity by using carboxymethylcellulose (CMC) as a substrate. For cellulolytic activity, the plates were flooded with 0.5% Congo red solution for 10 minutes, then washed with distilled water and flooded with 1 M NaCl.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 233 Chapter 4 Fungal Diversity
The clearing zone around the colony was observed. All qualitative extracellular enzyme activities were assayed at 4 and 15°C.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 234 Chapter 4 Fungal Diversity
RESULTS
In the current study, 17 fungal isolates were isolated from all the three samples (glacial ice, water and sediments) of the Siachen glacier, Pakistan, by culturing at two temperatures 4°C and 15°C. The fungal CFU/g or mL in sediments was observed highest at both temperatures followed by water and ice (Table 4.3.1).
(Table 4.3.1. Total viable count (CFU/mL/g) of fungal isolates at 15°C and 4°C
Temperature (°C) Samples CFU/mL or g
1 Glacier ice 3.0 x10 1 15 Glacier water 4.0 x10 2 Glacier sediment 3.75x10 1 Glacier ice 1.5 x10 1 4 Glacier water 2.0 x10 2 Glacier sediment 4.5x10
Morphological and microscopic evaluation
The fungal isolates had different colony morphology, mostly were of tough and mucoid texture while powdery and cottony texture was also observed. The microscopic features of the fungal isolates was observed in terms of fruiting bodies, hyphal structure (i.e. branched or single hyphae, septation or aseptation), spore, spore shape (circular, oval, rod or others). The macroscopic and microscopic characteristics of different fungal isolates on the SDA are given in (Supplementary Table S 4.3.1)
Molecular characterization
Based on sequencing of the ITS regions (ITS1 – ITS4), all the fungal isolates were found to belong to varied taxonomic groups. The phylogenetic tree, describing evolutionary relationships among all fungal isolates is given in (Fig. 4.3.1), and the
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 235 Chapter 4 Fungal Diversity resemblance index of strains with respective homology of the isolates is summarized in (Table 4.3.2). Majority of the fungal isolates showed close similarity with the respective homologous species between 99-100% and only LS3 showed 97% similarity with Thelebolus microspores.
Table 4.3.2. The resemblance index of strains with respective homology of the fungal isolates
Isolates Accession Homologous species [accession number] ID No of No. (%) analysed bp
HS1 KR676355 Geomyces pannorum |HQ703417.1| 100 488
HS2 KR676356 Leotiomycetes sp |KC514892.1| 99 480
HS3 KR676357 Pueraria montana |EF432795.1| 100 539
HS4 KR676358 Thelebolus microspores |KM822751.1| 100 481
HS5 KR676359 Penicillium brevicompactum |KF990149.1| 100 517
HS6 KR676360 Cladosporium uredinicola |KM513616.1| 99 491
HS7 KR676361 Trichoderma viride |DQ093772.1| 100 500
HS8 KR676362 Pueraria montana |EF432796.1| 100 537
HS9 KR676363 Leotiomycetes sp |KC514892.1| 99 480
LS1 KR676364 Leotiomycetes sp |KC514892.1| 99 480
LS2 KR676365 Pueraria montana |EF432796.1| 100 539
LS3 KR676366 Thelebolus microspores |KM822751.1| 97 520
LS4 KR676367 Periconia sp |KF907244.1| 99 492
LS5 KR676368 Thelebolus microspores |KM822751.1] 99 512
LS6 KR676369 Leotiomycetes sp |KC514892.1 100 481
LS7 KR676370 Cryptococcus albidus |KP131887.1| 99 532
LS8 KR676371 Thelebolus ellipsoideus |KM816688.1| 100 490
Physiological parameters evaluation
The growth responses of the fungal isolates to varying temperature, pH and the salt concentrations are shown in (Table 4.3.3). The optimum temperature for all the isolates was in between 4 and 15°C but many fungal isolates showed growth up to 37°C while few were able to grow at 45°C as well but none of them displayed growth at 50°C. However, the growth at 37 and 45°C was very small. The fungal isolates exhibited growth at wide range of pH. The optimum pH for all fungal isolates was
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 236 Chapter 4 Fungal Diversity observed between 5 and 8. Most of the isolates were able to grow on pH 2-13, while 6 isolates could also grow on pH 1. Towards alkaline range, all the isolates tolerated pH up to 13. Salt tolerance of the fungal isolates was between 2 and 20%. Based on these results, the isolates were considered as cold, pH and salt tolerant.
34 HS7 100 Trichoderma viride(DQ093772.1) 60 Trichoderma atroviride(EU715667.1) Dothideomycetes sp(JQ759885.1) LS4 29 100 82 Periconia sp(KF907244.1) LS7 10 Penicillium brevicompactum(KF990149.1) 100 33 Penicillium brevicompactum(AY373897.1) Geomyces pannorum(HQ703416.1) HS1 100 Geomyces pannorum(HQ703417.1) 16 34 21 Uncultured fungus clone(KC966103.1) 44 Uncultured Thelebolales(GU911105.1) 51 LS3 HS2 17 Thelebolaceae sp(DQ317350.1) 100 39 Thelebolaceae sp(GU212428.1) LS8 10 Leotiomycetes sp(KC514892.1) HS4 41 Uncultured soil fungus(JX489808.1) 5 LS6 4 12 Uncultured Thelebolales(GU910625.1) 30 HS6 100 Cladosporium uredinicola(KM513616.1) Fungal sp(KM266305.1) 72 LS5 100 Uncultured fungus clone(KM032309.1) Cryptococcus albidus(KP131887.1) 99 Uncultured fungus clone(KJ173567.1)(2) HS3 100 HS8 20 Uncultured fungus clone(KJ173567.1) 5 Fungal sp(KF212214.1) 3 LS2 3 12 Fungal sp(KF212207.1) Fig 4.3.1. Phylogenetic analysis of the Siachen isolates using Maximum Likely hood
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 237 Chapter 4 Fungal Diversity
Table 4.3.3. Growth responses of the fungal isolates to temperature, pH and the salt
Isolates Temperature (°C) range pH range Salt range (%)
HS1 4−37 2−13 2−16
HS2 4−37 2−13 2−16
HS3 4−37 2−13 2−18
HS4 4−37 1−13 2−16
HS5 4−37 1−13 2−20
HS6 4−37 2−13 2−18
HS7 4−37 2−13 2−18
HS8 4−45 1−13 2−16
HS9 4−37 2−13 2−16
LS1 4−37 2−13 2−16
LS2 4−37 1−13 2−16
LS3 4−45 1−13 2−18
LS4 4−37 1−13 2−10
LS5 4−45 2−13 2−14
LS6 4−37 2−13 2−18
LS7 4−45 2−13 2−16
LS8 4−37 2−13 2−14
Antimicrobial activity evaluation
The fungal isolates exhibited good antibacterial activities as compared to antifungal activities (Table 4.3.4). Mostly, they exhibited antimicrobial activity against Gram positive bacteria (6 showed activities against Staphylococcus sp., 5 against Staphylococcus aureus, and 1 against Enterococcus sp.), while only 1 fungal isolates showed antifungal activity against Candida albicans and Aspergillus niger, respectively. None of the isolates exhibited antibacterial activity against Gram negative bacteria (E. coli and Klebsiella pneumoniae).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 238 Chapter 4 Fungal Diversity
Table 4.3.4. Antibacterial and antifungal activity of the fungal isolates by point inoculation
Isolate Bacteria Fungi s E. Klebsiella S. Staphylococcus Enterococc Aspergill C. coli pneumoni aureus sp. us sp. us niger albicans ae
HS1 − − +++ +++ ++ − −
HS2 − − + ++ − − −
HS3 − − − − − − −
HS4 − − − − − − −
HS5 − − − − − ++ ++
HS6 − − − − − − −
HS7 − − − − − − −
HS8 − − − − − − −
HS9 − − + ++ − − −
LS1 − − + ++ − − −
LS2 − − − − − − −
LS3 − − − − − − −
LS4 − − − ++ − − −
LS5 − − − − − − −
LS6 − − − − − − −
LS7 − − ++ ++ − − −
LS8 − − − − − − − Key: (+++) Zone up to 7 mm, (++) Zone up to 14 mm, (+) Zone above 14 mm and (-) No Zone
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 239 Chapter 4 Fungal Diversity
Extracellular enzyme production evaluation
The fungal isolates were good producers of lipase and cellulase. Out of 17 fungal species, 5 exhibited positive amylolytic activity, 12 showed cellulosic activities and only 2 isolates showed positive production for DNase (Table 4.3.5). While, 14 fungal isolates exhibited lipolytic activity, 5 isolates were found positive by exhibiting phosphate solubilizing activity and only 8 isolates showed proteolytic activity. The studies clearly demonstrated that fungal isolates were capable of producing a wide range of cold-active extracellular enzymes.
Table 4.3.5. Production of various extracellular enzymes by fungal isolates
Isolates Enzymes Amylase Cellulase DNase Lipase Phosphatase Protease
HS1 − + − ++ − −
HS2 − + − ++ − + HS3 − − − + − −
HS4 + + − + + − HS5 + − + − + − HS6 − ++ − − − −
HS7 − + − + − + HS8 + + + + − −
HS9 − + − ++ − + LS1 − + − ++ − +
LS2 − − − + − − LS3 + ++ − − − ++ LS4 − + − + + +
LS5 − − − ++ − − LS6 + + − + + −
LS7 − + − ++ − ++ LS8 − − − ++ + ++ Key: (+++) Zone up to 6 mm, (++) Zone up to 12 mm, (+) Zone above 12 mm and (-) No Zone
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 240 Chapter 4 Fungal Diversity
DISCUSSION
The main purpose of our study was the isolation and characterization of psychrotropic fungi from Siachen glacier, Pakistan. The existence of psychrotrophic fungi in this glacier has not been explored previously. In this study, 17 fungal isolates were isolated at two temperatures 4°C (8 isolates) and 15°C (9 isolates) from glacial sediments (5), ice (6) and water (6). After micro-morphological and molecular analysis (18S rRNA sequencing), it has been found that our fungal isolates belonged to 1 fungal genera, 1 family and 1 class. The major fungal isolates belonged to class Leotiomycetes (4), followed by genus Thelebolus (4), Pueraria (3), Penicillium (1), Cladosporium (1), Trichoderma (1), Periconia (1), Geomyces (1) and Cryptococcus (1).
The genus Geomyces (formerly known as Chrysosporium pannorum), frequently reported keratinophilic and psychrophilic fungus from Arctic, Alpine, temperate and Antarctic regions (Vishniac 1996; Mercantini et al. 1989). In Antarctica, G. pannorum was isolated from thalli of seaweeds (Loque et al. 2010), as an endophyte (Rosa et al. 2010), and is associated with mosses (Tosi et al. 2012). According to Montemartini et al. (1983), the genus Thelebolus, mainly Thelebolus microsporus, has been isolated as predominant genus from Arctic and Antarctic climate zones. The genus Penicillium has the ability to tolerate low temperature environments but in fact, many species demonstrated by their growth on food preserved in refrigerators (Pitt et al. 1999) or are isolated from alpine, tundra (Domsch et al. 1980). Penicillium species have been identified from soils, lakes, historic woodlands and macroalgal thalli in Antarctical regions (Loque et al. 2010). In addition, Cryptococcus genus reported from soil from Southern Victoria Land and other locations in Antarctica (Adams et al. 2006; Thomas-Hall et al. 2003). The other genera (Leotiomycetes, Cladosporium, Trichoderma, Periconia) have been reported and isolated from various polar and non- polar cold habitats by other authors (Laura et al. 2013; Kostadinova et al. 2009; Margesin et al. 2007).
In the present study, the fungal isolates showed great tolerance against different physiological parameters (temperature, pH and salt). The effects of pH on fungal growth were variable (from pH1 to pH13). Most of fungal isolates grow best over a pH range of 5-8. However, their growth was slow at pH extremes. Recca and Mrak
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 241 Chapter 4 Fungal Diversity
(1972) and Battley and Bartlett (1996) found some of the fungal strains grown at pH 1.5 and pH 9. In addition, several fungi from cold habitats have been reported for their growth at both acidic and alkaline pH (Dhakar et al. 2014; Grzhimaylo et al. 2013). Most of the fungi were psychrotrophic in nature by growing at temperatures at 4- 37°C. However, some of fungal isolates were able to grow outside this range i.e. at 45°C. Our results are supported by Zucconi et al. (1996), who isolated a thermotolerant-mesophilic fungal species from Victoria Land, Antarctica, having the ability to grow at 45°C. Azmi and Seppelt (1997) reported many fungal genera that show growth in between 4-35°C.. The isolates in the present study showed growth up to 20% of NaCl thus showed halophilic nature. Kochkina et al. (2007) isolated a psychrophilic isolate of Geomyces from cryopegs. The isolate was capable of growth at up to 10% NaCl concentration. Penicillium notatum and P. Chrysogenum isolated from sandy soil of Al-Ain area, U.A.E, were reported to tolerate NaCl up to 20% (El- Mougith et al., 1993). Greiner et al. (2013) isolated different fungal strains from salt mine in Berchtesgaden, Bavaria, Germany. Among them, a new fungal species Phialosimplex salinarum was able to grow in the presence of 25% of salts.
In this study, the fungal isolates were screened for their antibacterial and antifungal activities against clinically isolated bacterial and fungal human pathogens. Although, their bactericidal and fungicidal activities were not very effective, but some of our isolates showed antimicrobial activity against Gram (+) bacterial and fungal strains. The fungi from cold habitats have not yet been reported against clinically isolated multi-drug resistant bacterial and fungal strains but fungi from other habitats have been extensively screened for this purpose and numerous antibiotics are being produced and commercially available. As the resistance against many antibiotics is increasing day by day, therefore new more effective antibiotics are the need of the day. Svahn et al. (2012) and Suay et al. (2000) have tested different filamentous fungi and yeasts against various human clinical pathogens (including MDR as well) and laboratory controls. Brunati et al. (2009) screened 160 filamentous fungi and 171 yeasts against bacterial and fungal human pathogens but none of them was MDR. It is evident from our results that MDR and resistant clinical isolates were inhibited. The metabolites from these fungal isolates can be further characterized.
Moreover, fungal isolates were checked for the extracellular enzymatic production. Generally, fungal isolates were good producer of lipase, protease and cellulase. Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 242 Chapter 4 Fungal Diversity
Different studies have been carried out in cold habitats for this purpose. Singh et al. (2012) has reported production of amylase, cellulase, phosphatase and pectinase enzymes at 4°C and 20°C from various filamentous Ny-Alesund, Spitsbergen. Thelebolus microspore has found a good producer amylase, lipase and chitinase enzymes from Larsemann Hills, Antarctica (Singh et al. 2014). Our results are also supported by Fenice et al. (1997) by screening 33 fungal strains for various extracellular enzymes production, isolated from various sites of Victoria Land (continental Antarctica).
CONCLUSION
The Siachen glacier studied for the first time for the existence of fungi in this study. 17 fungal isolates were isolated that were identified through 18S rRNA sequencing. Majority of the fungal isolates belonged Leotiomycetes, followed by Thelebolus, Penicillium, Cladosporium, Trichoderma, Periconia, Geomyces, Cryptococcus and Thelebolaceae family. Some fungal isolates showed growth in the presence of 26% of salt, at pH 1 to 13 and at temperature 4°C to 45°C. Many isolates showed good antimicrobial activity and were good producers of industrially important enzymes.
ACKNOWLEDGEMENTS
We are thankful Higher Education Commission Pakistan for awarding indigenous scholarship.
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Singh, S. M., Singh, S. K., Yadav, L. S., Singh, P. N., and Ravindra, R., 2012: Filamentous Soil Fungi from Ny-Ålesund, Spitsbergen, and screening for extracellular enzymes. Arctic, 65: 45-55. Sonjak S, Frisvad JC, Gunde-Cimerman N. 2006. Penicillium mycobiota in Arctic subglacial ice. Microbiol Ecol 52:207-216. Suay I, Arenal F, Asensio FJ, Basilio A, Cabello MA, Díez MT, García JB, del Val AG, Gorrochategui J, Hernández P, Peláez F, Vicente MF. 2000. Screening of basidiomycetes for antimicrobial activities. Ant van Leeuwenhoek, 78:129–139. Svahn KS, Goransson U, El-Seedi H, Bohlin L, Larsson DGJ, Olsen B, Chryssanthou E. 2012. Antimicrobial activity of filamentous fungi isolated from highly antibiotic contaminated river sediment. Infection Ecol Epidemiol 2:11591. Tamura K, Nei M. 1993. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Molecular Biol Evol 10:512-26. Thomas-Hall S, Watson K, Scorzetti G. 2002. Cryptococcus statzelliae sp. nov. And three novel strains of Cryptococcus victoriae, yeasts isolated from Antarctic soils. Int J Syst Evol Microbiol 52:2303–2308. Thompson JD, Toby JG, Plewniak F, Jeanmougin F, Desmond GH. 1997. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res, 25:4876–4882. Tosi S, Begona C, Gerdol R, Caretta G. 2002. Fungi isolated from Antarctic mosses. Polar Biol, 25:262–268. Vishniac HS. 1996. Biodiversity of yeasts and filamentous microfungi in terrestrial Antarctic ecosystems. Biodiversity Conservatio, 5:1365–1378. Zucconi L, Pagano S, Fenice M, Selbmann L, Tosi S, Onofri S. 1996. Growth temperature preferences of fungal strains from Victoria Land, Antarctica. Polar Biol 16:53-61.
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Chapter 4: Fungal Diversity Paper 4: (Tirich Mir glacier) Title: Diverse psychrotrophic fungi from Tich Mir glacier, Pakistan, and their potential for antimicrobial metabolites and extracellular enzymes production.
Muhammad Rafiq, Shoukat Nadeem, Noor Hassan, Aamer Ali Shah, Fariha Hasan.
Status: Submitted in “Polar Biology”
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 4 Fungal Diversity
Diverse psychrotrophic fungi from Tirich Mir glacier, Pakistan, and their potential for antimicrobial metabolites and extracellular enzymes production
Muhammad Rafiq, Shoukat Nadeem, Noor Hassan, Aamer Ali Shah, Fariha Hasan
Department of Microbiology, Quaid-i-Azam University, Islamabad, Pakistan
Abstract
This study measured the diversity and dissemination of psychrotrophic fungi in Tich Mir glacier, Pakistan, and their potential to produce antimicrobial metabolites and extracellular enzymes. Different samples (glacier sediments, surface muddy ice and deep ice) were collected. A total of 44 fungi representing 16 genera, 1 family, 1 order and 1 class, were isolated from all the samples. After morphological and molecular (18S rRNA sequencing) analysis, Penicillium was found dominant isolated genus followed by Cladosporium, Didymella, Phoma, Coprinopsis, Epicoccum, Ulocladium, Onygenales (family), Ascochyta, Aspergillus, Comoclathris, Davidiella, Geomyces, Irpex, Pseudogymnoascus, Scopulariopsis, Tomicus, Davidiellaceae (order), Dothideomycetes (class). Fungal isolates showed remarkable abilities to grow on different pH (2-11), temperatures (4-37°C) and NaCl concentration (2-18%). Fungal isolates, Comoclathris spartii and Davidiella tassiana tolerated up to 18% NaCl concentration and pH from 2-11, respectively. Antimicrobial activities of fungal isolates against ATCC bacterial strains, clinical isolated bacterial and fungal strains were quite promising. Ulocladium sp. and Onygenales sp. shown activities against both bacterial (Gram +ve and Gram –ve bacteria) and fungal strains. Fungal isolates were checked for their abilities to produce various extracellular enzymes (amylase, cellulase, deoxyribonuclease and lipase). Penicillium chrysogenum was found able to produce amylase, cellulase, and deoxyribonuclease.
Key words: Hindukush-Karakoram-Himalaya, fungal diversity, isolation, identification, characterization
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 247 Chapter 4 Fungal Diversity
Introduction There are approximately 20,000 glaciers in the whole Hindukush-Karakoram- Himalaya (HKKH) Mountains Range, of which 5,000 glaciers are located in the Karakorum (Inman 2010) and more than 12,000 glaciers are situated in the Himalayas (Thayyen and Gergan 2010) that cover about 60,000 km2 area (Kaab et al. 2012). Glaciers play important role in the regulation of the regional water supplies. The HKKH and Tibetan Plateau (TP) glaciers provide snow and glacier-melt to approximately 1.4 billion people (1/5 of the world’s population) in the Indus, Ganges, Brahmaputra, Yangtze and Yellow River basins (Immerzeel et al. 2010; Schaner et al. 2012). Pakistan is a household of the glaciers that cover about 16933 km² area and hosts 108 peaks above 6000m, and several peaks above 5000 and 4000. The HKKH glaciers have not been investigated systematically for existence of psychrophilic and psychrotrophic fungi. There are few studies have been carried out in this regard e.g 25 psychrophilic yeasts were isolated from the Roop Kund Lake soil of Himalaya, India (Shivaji et al. 2008). Ghildiyal and Pandey (2008) reported 3 anti- fungal Trichodermal species from forest of Indian Himalayan Region. Thelebolus microspores has been reported from the Pangong Lake, Himalayan region (Anupama et al. 2011). In another study, genus Lemonniera and aquatic hyphomycete, Tetracladium nainitalense have been isolated from Kumaun Himalaya, India (Sati et al. 2009; Sati et al. 2014).
Moreover, Singh and Palni (2011) studied 35 species of fungi belonging to 7 different families of rust fungi, from herbaceous and shrubby hosts in central Himalayan region. Wang et al. (2015) investigated Qinghai-Tibet Plateau glaciers for the occurrence of cold-adapted fungi and isolated 1428 fungi, in which 150 species were identified and Phoma sclerotioides and Pseudogymnoascus pannorum were reported as most dominant species. Similarly, Hirose et al. (2009) isolated 24 fungal species and equated them at 3 diverse altitudes on the Tibetan Plateau and assessed the environmental variables manipulating them including cellulose decomposition. In another study, Hassan et al. (2016) has reported 50 fungal strains (Penicillium was predominant genus) from Batura and Siachen glaciers, Pakistan. Similarly, Rafique et al. (2016) has isolated different fungal species that represented various fungal genera including Penicillium, Mrakia, Cladosporium, Pseudeurotium, Fontanospora, Trichoderma, Antrodia, Sporobolomyces, Phoma, Beauveria and Pseudogymnoascus.
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The main purpose of current study was the isolation and identification of the fungi from samples collected from Tirch Mir glacier, Pakistan, to determine their physiological characteristics and their screening for antimicrobial metabolites and extracellular enzymes production.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 249 Chapter 4 Fungal Diversity
Materials and Methods
Sampling
The samples (glacier sediments, surface muddy ice and deep ice) were collected aseptically from Tirich Mir glacier of the Hindu Kush Range, highest peak in Chitral, Pakistan (N36°22.616-E072°08.983). The pH for the all samples was neutral (7.0), whereas, temperatures of sediments and water was 1°C while ice had -2°C. The samples were transported to the laboratory of the Department of Microbiology, Quaid-i-Azam University, Islamabad, in ice bags and stored at 4°C for further processing.
Fungal isolation
Sabouraud Dextrose Agar (SDA), Potato Dextrose Agar (PDA) and Malt Extract Agar (MEA) were used for the fungal isolation. Two different incubation temperatures 4°C and 15°C were used. CFU/ml/gm was determined for all the samples. Fungal colony with different texture and morphology were transferred to new plates by subculturing. For subculturing, PDA, MEA and Tryptic Soy Agar (TSA) were used.
Colony morphology and microscopy
Fungal isolates were cultured on SDA at their corresponding isolating temperatures for 10 days. The morphological characteristics were recorded in terms of colony growth (length and width), presence or absence of aerial mycelia, colony color, presence of wrinkles and furrows etc. Microscopy was performed using lacto-phenol cotton blue staining and observed the sides under 40x.
DNA extraction, sequencing and phylogenetic analysis
The DNA of all the fungal isolates was carried out according to the protocols previous described by Hassan et al. (2016). The PCR amplification of the extracted DNA was done using ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′- TCCTCCGCTTATTGATATGC-3′). The PCR conditions were: initial denaturation at 94°C for 1 min, 30 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 1 min, followed by 10 min final extension at 72°C. The amplified fungal DNA was sent to Macrogen, (Macrogen Inc. Seoul, Korea) for 18S
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 250 Chapter 4 Fungal Diversity rRNA sequencing. The obtained sequences were evaluated through DNA baser and were further evaluated by comparing the nucleotide sequences available in NCBI database (Thompson et al. 1997) by BLAST search examination. The evolutionary history was inferred by using the Maximum Likelihood way based on the Tamura-Nei model (1993). The phylogenetic tree was built in MEGA software using maximum likely hood method (Tamura et al. 2007) at the bootstrap value 1,000 replicates.
Physiological parameters analysis
The fungal isolates were characterized on different physiological parameters including growth at different temperature (4, 15, 37, 45 and 50°C), pH (1-11), media (SDA, TSA and PDA) and salt concentration (2-20%). The physiological parameters analysis was carried out on SDA using 7 day old fungal culture.
Antimicrobial metabolite production analysis
For this purpose, various ATCC bacterial strains, clinical isolated bacterial and fungal strains were selected such as Bacillus sp. ATCC 6633, E. coli ATCC 10536, Staphylococcus aureus ATCC 6538, Klebseilla pnuemonae (clinical isolated), Pseudomonas aeruginosa (clinical isolated), Candida albicans (clinical isolated) and Aspergillus flavus (clinical isolated). All the clinical isolated bacterial and fungal strains were obtained from Medical Microbiology Laboratory, Department of Microbiology, Quaid-i-Azam University Islamabad. 0.5 McFarland solution was used as standard of turbidity. The antimicrobial activity procedure was carried out by point inoculation method.
Extracellular enzymes production analysis
The process of enzymes screening has done on solid media. All fungal isolates were checked for amylase, cellulase, deoxyribonuclease and lipase activities. Amylase, deoxyribonuclease and lipase screening was carried out by following the protocol given by Hankin and Anagnostakis (1975). The cellulolytic activity (carboxymethylcellulose was used as a substrate) was screened according the protocol described by Hassan et al. (2016).
Results
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In the current study, total 44 fungal isolates have been isolated from all the collected samples of the Tirch Mir glaciers, Pakistan. 21 fungal isolates have isolated at 4°C and 23 fungal isolates at 15°C. CFU/ml/gm was observed highest in glacier sediments followed by surface muddy ice and deep ice (Table 4.4.1).
Table 4.4.1. Total viable count (CFU/mL/g) of Tirch Mir fungal isolates at 15°C and 4°C
No. of Temperature (°C) Samples CFU/ml/g colonies/200µL Subsurface Ice 1 5 1 2 15 Surf. Muddy Ice 9.0 x10 4.50 x10 3 3 Glacier Sediment 2.05 x10 1.025 x10 Subsurface Ice Nil Nil 1 1 4 Surf. Muddy Ice 4.2 x10 4.2 x10 1 3 Glacier Sediment 8.5 x10 8.5 x10
Morphological and microscopic analysis
The fungal isolates were different in colony morphology, generally were of cottony and powdery texture but mucoid and tough texture was also perceived. In microscopic analysis, fruiting bodies, hyphal structure (i.e. branched or single hyphae, septation or aseptation), spore, spore shape (circular, oval, rod or others) were observed.
Molecular identification
After the sequencing of the fungal ITS regions (ITS1 – ITS4), all the fungal isolates were found to belong to diverse taxonomic groups. The phylogenetic tree, showing evolutionary affiliations among all fungal isolates is given in Fig. 4.4.1 and the alikeness index of the fungal isolates with their respective homologous fungal strains is summarized in (Table 4.4.2).
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 252 Chapter 4 Fungal Diversity
Cladosporium uredinicola|KR019741.1| LTF25 LT21 LT17 LT16 Aspergillus sydowii|LC094427.1| LTF14 Penicillium camemberti|FJ025142.1| LT11 Pseudogymnoascus pannorum|KP411572.1| LTF2 Irpex lacteus|KR709203.1| HTF30 HTF29 HTF1 Comoclathris spartii|KM577159.1| HTF6 Cladosporium sp|KM977760.1| HTF7 Cladosporium sphaerospermum|JX500353.1| HTF8 HTF9 HTF15 Uncultured fungus clone|KC966096.1| HTF27 Cladosporium sp|KJ598873.1| Cladosporium australiense|KP701978.1| Penicillium chrysogenum|KM115128.1| Scopulariopsis brevicaul|FJ025211.1| LTF4 LTF1 Davidiellaceae sp|HQ540676.1| HTF31 HTF28 HTF21 HTF11 Ulocladium sp|KT192296.1| Davidiella tassiana|JN986782.1| HTF12 Epicoccum nigrum|KT192389.1| Didymella phacae|EU167570.1| Epicoccum nigrum|KT192212.1| LTF3 LT8 LT12 LTF15 LT18 Cladosporium uredinicola|KR676360.1| LT22 LT23 HTF10 Phoma medicaginis|KM977763.1| HTF17 LTF13 Tomicus piniperda|KJ512875.1| Penicillium crustosum|KT192315.1| HTF24 Onygenales sp|KM977752.1| HTF22 HTF2 Phoma medicaginis|JQ929130.1| HTF3 Dothideomycetes sp|GQ153037.1| Phoma herbarum |JF325873.1| HTF14 Coprinopsis atramentaria|KJ817302.1| HTF16 Didymella phacae|KF871438.1| Penicillium chrysogenum|KP963975.1| HTF32 Davidiella tassiana|KC292373.1| LTF7 Penicillium dipodomyicola|KR610975.1| Penicillium griseofulvum|KR703615.1| LT20 LT24
5
Fig 4.4.1. Molecular Phylogenetic analysis by Maximum Likelihood method
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 253 Chapter 4 Fungal Diversity
Table 4.4.2 Resemblance directory of the isolates with homologous strains
Isolate Acc. No. Homologous strains Analysed bp Identity(%) HTF1 KU714703 Comoclathris spartii 530 97 HTF2 KM977756 Phoma medicaginis 531 97 HTF3 KM977757 Dothideomycetes sp 559 99 HTF6 KM977760 Uncultured fungus 498 99 HTF7 KU714704 Cladosporium sphaerospermum 430 100 HTF8 KM977761 Ulocladium sp. 554 99 HTF9 KM977762 Davidiella tassiana 527 99 HTF10 KM977763 Phoma medicaginis var. medicaginis 307 95 HTF11 KM977764 Phoma herbarum 504 99 HTF12 KM977765 Epicoccum nigrum 485 100 HTF14 KM977767 Coprinopsis atramentaria 550 100 HTF15 KM977768 Ulocladium sp. 536 99 HTF16 KM977769 Didymella phacae 480 99 HTF17 KM977770 Didymella phacae 510 99 HTF21 KU714705 Uncultured fungus 414 99 HTF22 KU714706 Coprinopsis atramentaria 444 85 HTF24 KU714707 Penicillium chrysogenum 393 100 HTF27 KM977775 Penicillium chrysogenum 318 100 HTF28 KM977776 Cladosporium sp. 529 99 HTF29 KU714708 Penicillium crustosum 496 100 HTF30 KU714709 Penicillium crustosum 495 99 HTF31 KM977777 Davidiellaceae sp. 518 99 HTF32 KM977778 Irpex lacteus 510 99 LTF1 KM977751 Epicoccum nigrum 510 100 LTF2 KM977752 Onygenales sp . 524 99 LTF3 KT290043 Cladosporium herbarum 462 100 LTF4 KM977753 Onygenales sp. 562 99 LTF6 KM977754 Geomyces sp. 470 99 LTF7 KU714699 Penicillium dipodomyicola 490 100 LTF8 KT290045 Pseudogymnoascus pannorum 481 100 LTF11 KT290048 Cladosporium herbarum 469 100 LTF12 KT290049 Penicillium camemberti 487 100 LTF13 KU714700 Tomicus piniperda 405 100 LTF14 KU714701 Aspergillus sydowii 448 100 LTF15 KU714702 Penicillium griseofulvum 420 99 LTF16 KT290050 Scopulariopsis brevicaulis 486 100 LTF17 KT290051 Penicillium dipodomyicola 469 100 LTF18 KT290052 Penicillium dipodomyicola 469 100 LTF20 KT290053 Cladosporium uredinicola 467 100 LTF21 KT290054 Ascochyta rabiei 511 99 LTF22 KT290054 Cladosporium uredinicola 468 100 LTF23 KT290055 Cladosporium uredinicola 465 99 LTF24 KT290056 Didymella phacae 440 94 LTF25 KT290057 Penicillium chrysogenum 469 99
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 254 Chapter 4 Fungal Diversity
Physiological parameters analysis
The growth tolerance of the fungal isolates was varied to different temperatures, pH, media and NaCl concentrations (Table 4.4.3). The optimum temperature for all the isolates was observed between 4 and 15°C but all fungal isolates were also able to grow at 37°C as well. The fungal isolates exhibited growth at varied range of pH but optimum pH for all fungal isolates was observed between at 6 and 7. Utmost isolates were able to grow on pH from 2-11. All fungal isolates shown good growth on SDA, PDA and TSA media but most of the isolates showed extensive (optimum) growth on SDA. Salt tolerance of the fungal isolates was between 2 and 18%.
Table 4.4.3 Physiological parameters analysis of the fungal isolates on different temperature, pH media and NaCl concentrations
Isolates Temp (°C) range pH range Salt range (%) Media (optm)
HTF1 4−37, opt. 15 2−11, opt. 6–7 2−18, opt. 2–6 SDA
HTF2 4−37, opt. 15 2−9, opt. 6 2−6, opt. 2 SDA
HTF3 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 SDA
HTF6 4−37, opt. 15 3−9, opt. 6 2−6, opt. 2 SDA
HTF7 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 SDA
HTF8 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 PDA
HTF9 4−37, opt. 15 2−11, opt. 6–7 2−18, opt. 2–6 PDA
HTF10 4−37, opt. 15 2−11, opt. 7 2−12, opt. 4 SDA
HTF11 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 SDA
HTF12 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 SDA
HTF14 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 SDA
HTF15 4−37, opt. 15 2−11, opt. 6–7 2−12, opt. 4 SDA
HTF16 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 SDA
HTF17 4−37, opt. 15 2−11, opt. 6 2−6, opt. 2 SDA
HTF21 4−37, opt. 15 3−9, opt. 6 2−6, opt. 2 SDA
HTF22 4−37, opt. 15 3−11, opt. 6 2−6, opt. 2 SDA
HTF24 4−37, opt. 15 2−11, opt. 6–7 2−12, opt. 4 SDA
HTF27 4−37, opt. 15 2−11, opt. 6–7 2−12, opt. 4 SDA
HTF28 4−37, opt. 15 2−11, opt. 6–7 2−6, opt. 2 PDA
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HTF29 4−37, opt. 15 3−11, opt. 7 2−6, opt. 2 SDA
HTF30 4−37, opt. 15 2−11, opt. 6 2−6, opt. 2 SDA
HTF31 4−37, opt. 15 3−11, opt. 6 2−14, opt. 4 SDA
HTF32 4−37, opt. 15 3−11, opt. 6–7 2−6, opt. 2 SDA
LTF1 4−37, opt. 4 2−11, opt. 6–7 2−6, opt. 2 SDA
LTF2 4−37, opt. 4 2−11, opt. 6–7 2−8, opt. 2 SDA
LTF3 4−37, opt. 4 2−11, opt. 6–7 2−12, opt. 4 PDA
LTF4 4−37, opt. 4 2−11, opt. 6 2−6, opt. 2 SDA
LTF6 4−37, opt. 4 2−11, opt. 6–7 2−12, opt. 4 SDA
LTF7 4−37, opt. 4 2−11, opt. 6–7 2−6, opt. 2 SDA
LTF8 4−37, opt. 4 2−11, opt. 7 2−10, opt. 4 SDA
LTF11 4−37, opt. 4 2−11, opt. 6–7 2−14, opt. 4 PDA
LTF12 4−37, opt. 4 2−11, opt. 6–7 2−14, opt. 4 SDA
LTF13 4−37, opt. 4 2−11, opt. 6–7 2−14, opt. 4 PDA
LTF14 4−37, opt. 4 2−11, opt. 6 2−12, opt. 4 SDA
LTF15 4−37, opt. 4 2−11, opt. 6–7 2−12, opt. 4 SDA
LTF16 4−37, opt. 4 2−11, opt. 6–7 2−14, opt. 4 SDA
LTF17 4−37, opt. 4 2−11, opt. 6–7 2−14, opt. 4 SDA
LTF18 4−37, opt. 4 2−11, opt. 6 2−6, opt. 2 SDA
LTF20 4−37, opt. 4 2−11, opt. 7 2−12, opt. 4 PDA
LTF21 4−37, opt. 4 2−11, opt. 6–7 2−8, opt. 2 SDA
LTF22 4−37, opt. 4 2−11, opt. 7 2−16, opt. 4 PDA
LTF23 4−37, opt. 4 2−11, opt. 7 2−6, opt. 2 PDA
LTF24 4−37, opt. 4 2−11, opt. 7 2−6, opt. 2 SDA
LTF25 4−37, opt. 4 2−9, opt. 6 2−14, opt. 4 SDA
Antimicrobial activity analysis
The antibacterial activities of the fungal isolates were quite interesting (Table 4.4.4). Generally, they revealed antimicrobial activity against both Gram positive and Gram negative bacteria such as 9 showed activities against E. coli, 14 against Klebsiella pneumonia, 10 against Bacillus sp., and 16 against Staphylococcus aureus, while 5
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 256 Chapter 4 Fungal Diversity
fungal isolates showed antifungal activity against Aspergillus flavis and 3 against Candida albicans. None of the isolates displayed antibacterial activity against Pseudomonas aeruginosa.
Table 4.4.4 Antibacterial and antifungal activity of the Tirch Mir fungal strains against different bacterial and fungal strains
Fungal Bacteria Fungi isolates E. coli Klebsiella Staph. Bacillus Pseudomonas Asp. C. pneumonie aureus sp. aeruginosa flavis albicas HTF1 + + + + − − −
HTF2 − − − − − + − HTF3 − + + ++ − − − HTF6 − − − − − − − HTF7 − − − − − − − HTF8 − + − − − − + HTF9 − + − − − − − HTF10 − + − − − − − HTF11 − − +++ − − − − HTF12 − − − − − − − HTF14 − + − − − − − HTF15 + + + − − ++ − HTF16 − − − − − − − HTF17 − − ++ + − − − HTF21 − − − − − − − HTF22 − − − − − − − HTF24 − − − + − − − HTF27 − − − − − − − HTF28 − − ++ + − − − HTF29 − − ++ + − − − HTF30 − − − − − − − HTF31 + + + − − − − HTF32 − − − − − − − LTF1 − − − − − − − LTF2 − + +++ +++ − + − LTF3 − − − − − − − LTF4 − − − − − − − LTF6 + + − − − − − LTF7 + − − − − − − LTF8 − + ++ − − − − LTF11 − − − − − + +++ LTF12 − − − − − − − LTF13 − − − − − − − LTF14 + − + − − − − LTF15 + + + +++ − − − LTF16 − + − − − − −
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 257 Chapter 4 Fungal Diversity
LTF17 − − − − − − − LTF18 − − − + − + − LTF20 + − + − − − ++ LTF21 − + + + − − − LTF22 − − − − − − − LTF23 + − − − − − − LTF24 − − + − − − − LTF25 − − ++ − − − − Key: (-) No Zone, (+) Zone up to 8 mm, (++) Zone up to 16 mm, (+++) Zone above 16 mm
Extracellular enzyme production
The fungal isolates were generally virtuous producers of lipase and cellulose enzymes (Table 4.4.5). Out of 44 fungal species, 4 exhibited positive amylolytic activity, 11 showed cellulosic activities, 5 strains showed positive production for DNase and 15 fungal strains exhibited lipolytic activity. The studies clearly established that fungi were proficient of producing a wide range of cold-active extracellular enzymes.
Table 4.4.5 Production of various extracellular enzymes (qualitatively) by fungal isolates Fungal Enzymes Isolates Amylase Cellulase DNase Lipase HTF1 − − − +++ HTF2 − − − − HTF3 − − − − HTF6 − − − − HTF7 − − − − HTF8 − − − − HTF9 − − − +++ HTF10 − − − − HTF11 − + − − HTF12 − − − ++ HTF14 − − − − HTF15 − − − − HTF16 − − − − HTF17 − − − − HTF21 − − − − HTF22 − − − − HTF24 + ++ + − HTF27 − − − − HTF28 − − − +++ HTF29 + ++ − − HTF30 − − − − HTF31 − − − −
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HTF32 − − − + LTF1 − − − − LTF2 − − − ++ LTF3 − + + +++ LTF4 − − − − LTF6 − ++ − ++ LTF7 + + − − LTF8 − − − +++ LTF11 − − − + LTF12 − − − − LTF13 − − − − LTF14 − + + − LTF15 − + + + LTF16 − − − − LTF17 − − − + LTF18 − − ++ − LTF20 − ++ − − LTF21 − ++ − + LTF22 − − − − LTF23 + + − ++ LTF24 − − − + LTF25 − − − − Key: (-) No Zone , (+) Zone up to 6 mm, (++) Zone up to 12 mm, (+++) Zone above 12 mm
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Discussion
This study embodies the first report of fungal species in Tirch Mir glacier, Pakistan. The dissemination and profusion of fungi in Tirch Mir glacier was larger than as expected, with many unreported species and genera isolated. In this study, utmost of fungal isolates shared 97–100% similarity with the existing fungal ITS sequences in the NCBI database. However, some fungal isolates HTF10, HTF22, and LTF24 showed similarity between 85–95% with their contiguous matches, suggesting their chance of being novel species of genera Phoma, Coprinopsis, and Didymella that would need further deep molecular analysis for their complete identification. Most abundant isolated genus of the present study was Penicillium (10 species), followed by Cladosporium (7), Didymella (3), Phoma (3), Coprinopsis (2), Epicoccum (2), Ulocladium (2), Onygenales (2), Ascochyta (1), Aspergillus (1), Comoclathris (1), Davidiella (1), Geomyces (1), Irpex (1), Pseudogymnoascus (1), Scopulariopsis (1), Tomicus (1), Davidiellaceae (1), Dothideomycetes (1). In our knowledge, we are reporting for the first time the genera Davidiella, Didymella, Epicoccum, Irpex, Scopulariopsis and Ulocladium from the glaciers of HKKH range, whereas the genera Coprinopsis, Comoclathris, and Tomicus from any glacier located in Polar and Non-polar regions. Penicillium genus is one of the most commonly occurring fungal genus in all cold habitats such as Arctic (subglacial ice) (Sonjak et al. 2006), Antarctica (Kostadinova et al. 2009), Baima Snow Mountain (Li et al. 2012), deep sea (Nagano et al. 2010), Himalaya, India (Dhakar et al. 2014). Pseudogymnoascus pannorum is a fungus frequent in cold areas such as Antarctica (Farrell et al. 2011), Alpine habitats (Coleine et al. 2015), non-polar glacier (Wang et al. 2015), proficient of growing at very low temperatures, down to −20 °C (Panikov and Sizova 2007; Hayes 2012), and was recurrently found in soil clone libraries from Interior Alaska (Timling 2012). The fungal species representing Phoma genus have been isolated from a decomposing High Arctic moss, Schistidium apocarpum (Leung et al. 2011). It has also isolated from the soils of Taylor Valley, Antarctica (Connell et al. 2006) and from Baima Snow Mountain (Li et al. 2012). Cladosporium genus has been reported from dead leaves of Acaena magellanica and Festuca contracta in South Georgia (peri-Antarctic Island) (Smith 1994), and has been found in relationship with the mosses in Antarctica (Tosi et al. 2002). Aspergillus is a cosmopolitan genus frequently isolated from soil, plant debris, and as an endophyte (Rosa et al. 2010). In Antarctica,
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Aspergillus species were also reported from ornithogenic soil (Wicklow 1968). It has been reported from deep sea (Nagano et al. 2010) and from Baima Snow Mountain (Li et al. 2012). Davidiella tassiana isolated as a most plentiful species from the leaves of Colobanthus quitensis (Rosa et al. 2010). This species is cosmopolitan and has been found in relationship with diverse substrata (Schubertet al. 2007) and as an endophytic fungl species of plants in temperate areas (Brownet al. 1998). It has also been reported from lakes of the Antarctic Peninsula (Goncalves et al. 2012) and subalpine grasslands (Mouhamadou et al. 2011). The genus Geomyces belongs to Myxotrichaceae (Ascomycota) and contains a very small section of the fungal biota, with only 11 known species (Kirk et al. 2001; Gargas et al. 2009). The Geomyces is an omnipresent genus that characterized as cellulolytic, endophytic, keratinophilic and psychrophilic fungal genus and it has been reported in polar (Antarctic and Arctic soils) (Mercantini et al. 1989; Arenz et al. 2006; Rosa et al. 2010) and non-polar habitats (Hassan et al. 2016; Rafique et al. 2016). Moreover, the remaining fungi of current study have been isolated from different cold habitats such as Dothideomycetes was reported from Arctic, alpine rock and plants (Zhang and Yao 2015; Cui et al. 2015), Epicoccum nigrum from Antarctica, deep-sea and Alpine Plants (Farrell et al. 2011; Cui et al. 2015; Galkiewicz et al. 2012). Similarly, Ulocladium genus has reported from Alpine Plants (Cui et al. 2015) and Greenland (Ma et al. 2000), Irpex lacteus was reported from Antarctica (Connell and Staudigel 2013), Onygenales from Antarctica (Farrell et al. 2011), Scopulariopsis brevicaulis from Antarctica (Azmi and Seppelt 1997), and Didymella from Antarctica (Alberto and Guarro 2003).
In the present study, tolerance of the fungal isolates toward different physiological parameters (temperature, pH and salt) was an excellent outcome. Fungal isolates tolerated NaCl between 2-18% range, thus they shown halophilic nature. Out of 44 isolates, 22 fungal species endured NaCl up to 6% and remaining 22 isolates tolerated NaCl between 2-18%. Recently, Hassan et al. (2016) and Rafique et al. (2016) isolated different genera of fungi from Batura and Passu glaciers, respectively that were capable to grow up to 26% NaCl concentration. Similarly, Kochkina et al. (2007) isolated a psychrophilic isolate of Geomyces from cryopegs that was able to grow up to 10% NaCl concentration. Greiner et al. (2014) isolated diverse fungal strains from salt mine in Berchtesgaden, Bavaria, Germany. Among them, a new
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 261 Chapter 4 Fungal Diversity fungal species Phialosimplex salinarum was competent to grow in the presence of 25% of salts. The effects of pH on fungal growth were flexible (from pH2 to pH11). Maximum of fungal isolates grow well over a pH range of 6-7. However, their growth was limited at pH extremes. Recca and Mrak (1972) and Battley and Bartlett (1996) reported some of the fungal strains grown at pH 1.5 and pH 9. In addition, several fungi from cold habitats have been described for their growth at both acidic and alkaline pH (Dhakar et al. 2014; Grzhimaylo et al. 2013). In the present study, maximum of the fungal isolates were psychrotrophic in nature by growing between 4- 37°C. However, none of fungal isolates were able to tolerate outer this range i.e. at 45°C. Our results are supported by Zucconi et al. (1996), who isolated thermotolerant- mesophilic fungal species from Victoria Land, Antarctica, having the ability to grow at between 4-45°C. Moreover, Azmi and Seppelt (1997) reported many fungal genera that show growth in between 4-35°C.
In this study, the abilities of the fungal isolates to produce antibacterial and antifungal metabolites against ATCC and clinically isolated bacterial and fungal human pathogens were remarkable. Their antimicrobial activities were very effective against both against Gram (+) and Gram (-) bacterial strains but very effective against fungal strains. The fungi from cold habitats have not yet been appropriately reported against clinically isolated multi-drug resistant bacterial and fungal strains. Only few studies are available in the literature. Hassan et al. (2016) and Rafique et al. (2016) isolated dissimilar fungi from Batura and Passu glaciers, respectively that were skilled to show antimicrobial activities against multi-drug resistant bacterial and fungal strains. In addition, Svahn et al. (2012) and Suay et al. (2000) have tried diverse filamentous fungi and yeasts against various human clinical pathogens (including MDR as well) and laboratory controls. Brunati et al. (2009) screened 160 filamentous fungi and 171 yeasts against bacterial and fungal human pathogens but none of them was MDR.
In the current study, fungal isolates were screened for the extracellular enzymatic production. Normally, fungal isolates were good producer of lipase and cellulase. Different studies have been carried out in cold habitats for this purpose. Singh et al. (2012) has reported production of amylase, cellulase, phosphatase and pectinase enzymes at 4°C and 20°C from various filamentous Ny-Alesund, Spitsbergen. Thelebolus microspore has found a good producer amylase, lipase and chitinase enzymes from Larsemann Hills, Antarctica (Singh et al. 2014). Our results are also Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 262 Chapter 4 Fungal Diversity supported by Fenice et al. (1997) by screening 33 fungal strains for various extracellular enzymes production, isolated from various sites of Victoria Land (continental Antarctica).
Conclusions
The study place explored for the first time for the occurrence of psychrotrophic fungi in Tirch Mir glacier. Morphological and molecular analysis revealed Penicillium as most an abundant isolated genus. They were very adaptable by growing at a wide range of temperature, pH and salt conditions, and were also proficient in antimicrobial metabolites and enzyme production at low temperatures.
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Chapter 4: Fungal Diversity Paper 5: (Tirich Mir) Title: Culturable diversity of Alternaria spp. in Tirich Mir glacier, Pakistan and their screening for antimicrobial metabolites and extracellular enzymes production
Muhammad Rafiq, Shaukat Nadeem, Noor Hassan, Muhammad Hayat, Mohsin Khan, Muhammad Ibrar, Wasim Sajjad, Sahib Zada, Aamer A Shah, Fariha Hasan.
Status: Under review in ‘Kuwait Journal of Science’
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 4 Fungal Diversity
Culturable diversity of Alternaria spp. in Tirich Mir glacier, Pakistan and their screening for antimicrobial metabolites and extracellular enzymes production
Shaukat Nadeem, Muhammad Rafiq, Noor Hassan, Muhammad Hayat, Mohsin Khan, Muhammad Ibrar, Wasim Sajjad, Sahib Zada, Aamer A Shah, Fariha Hasan
Department of Microbiology, Quaid-i-Azam University, Islamabad, 45320, Pakistan
Abstract
The current study explores the diversity of Alternaria spp. in Tirich Mir glacier, Hindu Kush mountain range, Pakistan. Ten Alternaria spp. were isolated from all the samples (glacier sediments, surface muddy ice and deep ice) in this study. We used both conventional and molecular methods for the identification of fungal isolates. Colony morphology achieved on three different media and found that Sabouraud Dextrose Agar was best for the vegetative growth and sporulation of fungal isolates. Molecular identification was confirmed by 18S rRNA gene sequencing. Based on the phenotypic and molecular analysis, all the isolates were designated to the genus Alternaria. The Alternaria consortialis was found as a predominant species. Growth of Alternaria isolates was checked at various pH, temperature and salt concentrations. All the isolates showed growth between 4 and 37°C, majority of the isolates showed growth at pH from 3 to 11 and were also able to grow at NaCl between 2-18%. All isolates were screened for their antimicrobial activity and for the production of extracellular enzyme (amylase, cellulase, deoxyribonuclease and lipase). Generally, Alternaria isolates showed best activity against Staphylococcus aureus and Bacillus sp. Alternaria alternate (TGF50-MRL), was found to produce three different enzymes.
Key words: Alternaria consortialis; Alternaria alternate TGF50-MRL; diversity; identification; phylogenetic analysis.
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Introduction
Alternaria is an omnipresent fungal genus that exists in this universe in different shapes such as saprobic, endophytic and pathogenic forms, allied with a wide range of substrates including seeds, plants, agricultural products, animals, soil and atmosphere. The genus Alternaria contains more than 50 pathogenic and non-pathogenic morpho- species (Woudenberg et al., 2013), but it is difficult to differentiate between such morpho-species at the sequence level due to the low levels of variation in DNA sequence (Peever et al., 2004; Andrew et al., 2009). Spores of the genus Alternaria belong to one of the most prevailing constituents of the air in all regions of the world. They form infectious inoculum of numerous plant species as well as severe inhaled allergies. Temperature was thought to be the most important factor determining the increase in Alternaria spore concentration in air.
Alternaria spp. often linked with hypersensitivity and allergies in humans but such environmental Alternaria spp. are not called as pathogens (Pastor & Guarro, 2008). Although, their pervasiveness in allergic rhinitis is the most communal form of noninfectious rhinitis (Randriamanantany et al., 2010), while allergic (extrinsic) asthma is the utmost form of asthma, disturbing over 50% of 20 million asthma sufferers (Salo et al., 2006). Members of genus Alternaria are among the common pathogens of fruit and vegetables and can also produce secondary metabolites dangerous to human health (Siciliano et al., 2015). Alternaria alternata causes Black mould lesions in 76% of 228 tomato fruit (Paul et al., 2000). In Korea, Alternaria simsimi was found to cause Leaf spot disease in sesame (Sesamum indicum L.) (Choi et al., 2014). Yield losses due to Alternaria blight disease has also been reported (Singh et al., 2014).
Alternaria spp. are found everywhere but mainly as saprophyte in soil or in rot plant materials and also identified as contaminants of food deposits (Logrieco et al., 2009). They have been isolated from the Mediterranean cypress species (Sordariomycetes) (Soltani & Moghaddam, 2015). Alternaria alternata has been reported from almost all habitats (Farr et al., 1989; EL-Morsy, 2000), but the presence of the Alternaria genus in Polar and Non-polar habitats is investigated very poorly. Only few studies have been carried out for the diversity of Alternaria spp. in cold habitats. Kostadinova et al. (2009) reported different filamentous fungi including Alternaria sp. from Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 269 Chapter 4 Fungal Diversity
Livingston Island, West Antarctica. Fenice et al. (1997) isolated filamentous soil fungal species of Alternaria, Aspergillus, Cladosporium genus as a most frequently isolates. Alternaria spp. have also isolated from ancient glacial ice (Ma et al., 2000).
Greater detailed knowledge is required about Alternaria spp. isolated worldwide from different cold environments and their mechanisms needs to be studied in detail. Up to the date, very little data is present about presence of Alternaria genus in cold habitats. The aim of this study was to investigate the diversity of different Alternaria spp., characterize the isolates on the basis of media, pH, temperature and salt concentrations as well as to screen out for the antimicrobial metabolite and enzymes production.
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Materials and Methods
1.1. Sample collection
Different samples (glacier sediments, surface muddy ice and deep ice) were collected aseptically from Tirich Mir glacier of the Hindu Kush Range, highest peak in Chitral, Pakistan (N36°22.616-E072°08.983). The pH for the all samples was neutral (7.0), whereas, temperatures of sediments and water was 1°C while ice had -2°C. The samples were transported to the laboratory of the Department of Microbiology, Quaid-i-Azam University, Islamabad, in ice bags and stored at 4°C for further processing.
1.2. Isolation of Alternaria spp.
For Alternaria species isolation, Sabouraud Dextrose Agar (SDA) and Potato Dextrose Agar (PDA) were chosen as growth medium. Each sample was diluted 5 times in sterilized distilled water and then spread 200 µL from each dilution on SDA plates and incubated at 4°C and 15°C. The CFU/mL or /g was determined for all the samples. The growth was observed for up to 15-20 days. For subculturing purposes, Potato Dextrose Agar (PDA), SDA and Tryptic Soya Agar (TSA) were used.
1.3. Morphological and microscopic analysis
The Alternaria isolates were cultured on SDA, PDA and Trypticase Soy agar at corresponding isolated temperatures for 3, 7, 10 and 15 days. The subsequent morphological features were assessed including colony growth (length and width), presence or absence of aerial mycelium, colony color, presence of wrinkles and furrows, pigment production etc.
For the microscopy, Lacto phenol cotton blue was used to observe the Alternaria isolates spores and other structures on the slide. The slides were observed under light microscope with 10x and 40x. The characteristics observed included; fruiting bodies, hyphal structure (i.e. branched hyphae or single hyphae, septate hyphae or aseptate hyphae), spore, spore size, spore shape (circular, oval, rod or others).
1.4. Molecular Identification
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The DNA of all the fungal isolates was carried out according to the protocols previous described by Fenice et al. (1997). The PCR amplification of the extracted DNA was done using ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′- TCCTCCGCTTATTGATATGC-3′). The PCR conditions were: initial denaturation at 94°C for 1 min, 30 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 30 sec, and extension at 72°C for 1 min, followed by 10 min final extension at 72°C. The amplified fungal DNA was sent to Macrogen, (Macrogen Inc. Seoul, Korea) for 18S rRNA sequencing.
1.4.1. Phylogenetic analysis
Phylogenetic and molecular evolutionary analyses were performed using MEGA version 4 (Tamura et al., 2007). Sequences were aligned using Clustal W software. A neighbour joining phylogenetic tree was constructed using Mega 4 based on the Kimura 2 parameter model with bootstrap values derived from 1000 replications (Felsenstein, 1985).
1.5. Physiological characterization
Alternaria species were checked for different physiological parameters. Temperature tolerance by the isolated Alternaria isolates, was determined on Potato Dextrose Agar at 4, 37 and 55°C. The growth characteristics of all the Alternaria isolates were observed by inoculating them on growth medium (PDA) containing different salt (NaCl) concentrations (2-20%) at 4 and 15°C. All the Alternaria isolates were inoculated on PDA having pH 1-11. For solidification of media at extreme pH (1, 3 and 11), gel rite was used instead of agar.
1.6. Screening for antimicrobial activity
Different ATCC bacterial strains such as Bacillus sp., E. coli, Klebseilla pnuemonae, Pseudomonas aeruginosa and Staphylococcus aureus, and fungal isolates Candida albicans and Aspergillus flavus were selected as test microbes. 0.5 McFarland solution was used as standard of turbidity. The point inoculation method was used for the evaluation of antimicrobial activity. Using a sterile wire loop, a pure test microbial colony was shifted into the test tubes containing normal saline solution and adjusted the turbidity with 0.5 McFarland solutions. A sterile cotton swab was used to prepare
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 272 Chapter 4 Fungal Diversity uniform lawn on TSA. A small part of each Alternaria mycelium was inoculated on plates containing test microbial lawn.
1.7. Screening for extracellular enzyme activity
Extracellular enzyme activity was carried out on solid media. Amylase, deoxyribonuclease and lipase activities were screened according to the protocol described by Hankin and Anagnostakis (1975). The cellulolytic activity was checked by using carboxymethylcellulose (CMC) as a substrate. For cellulolytic activity, the plates were treated with 0.5% Congo red solution for 10 minutes, then washed out with distilled water and flooded with 1 M NaCl. The clearing zone around the colony was observed. All qualitative extracellular enzyme activities were assayed at 4 and 15°C.
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Results
In the current study, we isolated 10 Alternaria isolates from all the samples, collected from Tirich Mir glacier, Chitral. 7 Alternaria isolates (TGF29-MRL, TGF30-MRL, TGF34-MRL, TGF43-MRL, TGF44-MRL, TGF45-MRL and TGF50-MRL) were isolated at 15°C and 3 Alternaria species (TGF5-MRL, TGF9-MRL and TGF10- MRL) were obtained at 4°C. These isolates were further processed for characterization and identification.
1.8. Morphological and Molecular Identification
Morphological characteristics and ITS sequences were studied in detail (Table 4.5.1 and 4.5.2). Among these isolates, TGF5-MRL showed 99% similarity with Alternaria sp. (KJ542225), TGF9-MRL showed 93% similarity with Alternaria consortialis (KM114288), TGF10-MRL showed 99% similarity with Alternaria alternata (HQ380765), TGF29-MRL showed 99% similarity with Alternaria alternata (HQ380765), TGF30-MRL was 99% similar to Alternaria consortialis (HG798767), TGF38-MRL showed 99% similarity with Alternaria consortialis (HG798767), TGF43-MRL has 99% similarity with Alternaria sp. (KF438014), TGF44-MRL showed 100% similarity with Alternaria consortialis (HG798767), while TGF45- MRL also showed 99% similarity with Alternaria consortialis (HG798767) and TGF50-MRL has 99% similarity with Alternaria alternata (HQ380765) through BLAST search similarity. Phylogenetic relationship of Alternaria spp. with other homologous species is given in (Fig. 4.5.1).
1.9. Physiological Characterizations
The Alternaria isolates were cultivated on PDA containing different salt concentration. TGF30-MRL, TGF44-MRL and TGF50-MRL were able to grow on 18, 12 and 12%, respectively (Table 4.5.3). The growth profile of Alternaria isolates on different temperatures was very diverse. Almost all the isolates showed growth range from 4 to 37°C showing eurypsychrophilic nature (Table 4.5.3). All the isolates showed growth in broad range of pH. Majority of isolates showed their growth between pH 3-11 (Table 4.5.3).
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1.10. Screening for antimicrobial activity
The isolated Alternaria species exhibited good antimicrobial activity against Gram positive bacteria as compared to Gram negative bacterial and fungal strains. Seven isolates showed activity against Staphylococcus aureus, 6 against Bacillus sp., 2 against Pseudomonas aeruginosa, 2 against Klebsiella pneumonia, 3 against Candida albicans but none showed antimicrobial activity against E. coli and Aspergillus flavus (Table 4.5.4).
1.11. Screening for extracellular enzyme activity
Alternaria species were found to be good in lipase production. Six isolates exhibited positive lipolytic activity, 2 showed cellolytic activities, 2 Alternaria isolates were found positive by exhibiting Dnase activity and only 1 isolate showed positive for amylolytic activity (Table 4.5.5). The fungal isolates A. alternata TGF50-MRL, was able to produce 3 different enzymes except amylase.
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Discussion
The aim of the present study was to determine the diversity of Alternaria spp. of the Tirich Mir glacier, Chitral, Pakistan. A total of 10 isolates were obtained after analysis of different ice samples taken from the area of the Tirich Mir glacier, Chitral. Two different temperatures, 15°C and 4°C, were used for isolation purposes. 3 Alternaria spp. were isolated at 4°C while at 15°C, 7 different Alternaria spp. were isolated. All Alternaria isolates were obtained in pure cultures by single conidial transfer onto Sabouraud Dextrose agar plates. The above method of isolation was used for fungi from Antarctica by (Kostadinova et al., 2009).
There is no data available about the diversity of Alternaria spp. in Tirich Mir glacier, Chitral, while knowledge about Alternaria genus in other Polar and Non-polar glaciers is also very scarce. In our knowledge, only Alternaria alternate and A. tenuissima were reported by Hirose et al. (2009) that were linked with cellulose decomposition at various heights on the Tibetan Plateau. In our knowledge, we are reporting Alternaria multiformis, A. consortialis and A. consortialis for the first time from the Polar and Non-polar glaciers. However, few researchers have isolated Alternaria alternate and other Alternaria sp. from other Polar habitats. An wide study on soils sampled across Victoria Land, earlier shown that the samples contains filamentous soil fungi belong to cosmopolitan, globally disseminated species such as Alternaria, Aspergillus, Geomyces and other (Adams et al., 2006; Onofri et al., 2007). Arenz & Blanchette (2011) isolated Alternaria sp. from Peninsula, Ross Sea Region and McMurdo Dry Valleys, Antarctica.
In our study, we checked the effects of different culturing media such as PDA, Trypticase Soy Agar (TSA) and SDA, on the growth of the Alternaria spp. and found that all Alternaria spp. showed different growth appearance on different media in terms texture, color, size and also pigment production. These results proposed that may they utilized some components in the medium to attain such differentiation. We didn’t find any similar studies in previous work, however, Azmi & Seppelt (1997) grown Alternaria alternate on different media including PDA and found a varied growth response to various media.
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The Alternaria spp. were grown on different pH, temperature and NaCl concentrations in this study. The isolates tolerated NaCl concentrations between 2- 18%, whereas isolates TGF30-MRL showed halophilic nature by growing up to 18% of NaCl. The halo-tolerant member of the genus Alternaria and few other genera have been isolated from some extreme hypersaline habitats (Gunde-Cimmerman et al., 2005; Zalar et al., 2005). The temperature tolerance revealed that the Alternaria isolates are classed as eurypsychrophiles by growing at temperatures between the 4- 37°C range. However, their optimum growth temperature was 4 and 15°C except TGF50-MRL that showed maximum growth at 37°C as well. Our result supported by Azmi & Seppelt (1997) by isolating A. alternate with 20°C optimum growth temperature. Curran (1980) found maximum growth of Alternaria sp. at 30°C. In this study, the growth tolerance of the isolated Alternaria sp. toward different pH, was impressive. They showed growth on pH ranges 2-11. In our study, one strain, TGF43- MRL showed normal growth on low pH3. The optimum pH of these isolates was between 5-8 ranges. Alternaria sp. that grew within an experimental range of pH 3-9, showing maximum growth at pH 6, was isolated from the Windmill Islands, continental Antarctica by Azmi & Seppelt (1997). All the above mentioned previous studies about the physiological characterization (pH, temperature and NaCl concentrations) were carried out in Polar habitats that we compared with our Alternaria isolates. In our knowledge, no such studies still reported from Non-polar environments.
In this study, antimicrobial metabolites production has also been analyzed. Few Alternaria isolates have been found to produce antimicrobial metabolites with bactericidal and fungicidal activity. 9 out of 10 Alternaria isolates exhibited good activities against Gram positive bacteria but their antibacterial and antifungal activity towards Gram negative bacterial and fungal strains were not satisfactory. We didn’t find any such similar studies in the literature but screening of fungi from cold habitats against bacterial and fungal human pathogens from American Type Culture Collection (ATCC) and the Merck Culture Collection (MB, MY) existed (Brunati et al., 2009). The isolated Alternaria species showed a wide range of enzymatic production. Few isolates displayed extracellular enzyme production. Generally, Alternaria isolates were good in lipases production. Fenice et al. (1997) reported
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Alternaria sp. from Antarctica that was positive for amylase and cellulose enzymes production.
Conclusions
The presence of cold, pH and salt tolerant species of Alternaria in high altitude of Tirch Mir glacier, Chitral, reported for the first time in this study. The characterization at various physiological parameters as well as screening of Alternaria species for enzymes and antimicrobial production in the present study, would have ecological, biotechnological and taxonomic implications in further research.
Acknowledgments
Higher Education Commission
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Ma, L., Rogers, S.O., Catranis, C.M. & Starmer, W.T. (2000) Detection and characterization of ancient fungi entrapped in glacial ice. Mycologia, 92:286–295. Onofri, S., Zucconi, L. & Tosi, S. (2007) Continental Antarctic Fungi. IHW Verlag, Berlin, Germany. Pastor, F.J. & Guarro, J. (2008) Alternaria infections: laboratory diagnosis and relevant clinical features. Clinical Microbiology and Infection, 14:734–746. Paul, F.M., Mary, S.C. & Dina, A.S.C. (2000) Genetic diversity of Alternaria alternata isolated from tomato in California assessed using RAPDs. 104:286–292. Peever, T.L., Su, G., Carpenter-Boggs, L. & Timmer, L.W. (2004) Molecular systematics of citrus-associated Alternaria species. Mycologia, 96:119–134. Randriamanantany, Z.A., Annesi-Maesano, I. & Moreau, D. (2010) Alternaria sensitization and allergic rhinitis with or without asthma in the French Six Cities study. Allergy, 65:368–375. Robinson, C.H. (2001) Cold adaptation in Arctic and Antarctic fungi. New Phytologist, 151:341–353. Salo, P.M., Arbes, S.J. & Sever, M. (2006) Exposure to Alternaria alternate in US homes is associated with asthma symptoms. Journal of Allergy and Clinical Immunology, 118:892–898. Siciliano, I., Ortu, G., Gilardi, G., Gullino, M.L. & Garibaldi, A. (2015) Mycotoxin production in liquid culture and on plants infected with Alternaria sp. isolated from rocket and cabbage. Toxins (Basel), 7:743–754. Singh, R.B., Singh, H.K. & Parmar, A. (2014) Yield loss assessment due to Alternaria blight and its management in linseed. Pakistan Journal of Biological Sciences, 17:511–516. Soltani, J. & Moghaddam, M.S.H. (2015) Fungal endophyte diversity and bioactivity in the Mediterranean Cypress Cupressus sempervirens. Current. Microbiology, 70:580–586. Tamura, K., Dudley, J., Nei, M. & Kumar, S. (2007) MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molecular Biology and Evolution, 24(8):1596-1599. Woudenberg, J.H.C., Groenewald, J.Z. & Binder, M. (2005) Taxonomy and phylogeny of the xerophilic genus Wallemia (Wallemiomycetes and Wallemiales, cl. et ord. nov). Antonie van Leeuwenhoek, 87:311–328.
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List of Legends
Figure: Fig. 4.5.1. Phylogenetic relationships of Alternaria taxa isolated from Tirich Mir Glacier Tables:
Table 4.5.1. Morphological characteristics of Alterneria isolates Table 4.5.2. Percentage similarity of Alternaria isolates
Table 4.5.3. Physiological analysis of the Alternaria isolates on different temperature, pH and salt concentrations
Table 4.5.4. Antibacterial and antifungal activity of the Alternaria isolates against ATCC cultures Table 4.5.5. Production of various extracellular enzymes by Alternaria isolates
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Alternaria alternata (KJ002059) Alternaria alternata (KC292357) 65 Alternaria alternata (KC292360)
Alternaria alternata (KC292359) Alternaria alternata (HQ380762) Alternaria concatenata (KC584246)
Alternaria aspera (KC584242) Alternaria brassicae (JX308314) Alternaria alternata (JN986770) 98 Alternaria alternata (JN986772) Alternaria alternata (JN986773) Alternaria brassicae (JX308313) Alternaria alternata (JX308309) Alternaria alternata (JX308307) Alternaria alternata (AF218791) Alternaria alternata (HQ380767)
Alternaria brassicae (HQ674659)
Alternaria subcucurbitae (KC584249)
Alternaria brassicae-pekinensis (KC584244)
Alternaria consortialis (HG798767)
Alternaria consortialis.TGF44-MRL (KM977772) Alternaria consortialis. TGF45-MRL (KM977773) Alternaria chartarum (EF568098) Alternaria consortialis (KC584247) Alternaria sp. TGF43-MRL (KM977771) 52 Alternaria alternata (KJ589565) Alternaria alternata TGF29-MRL (KM977758) Fig. 4.5.1.
37 Alternaria consortialis. TGF30-MRL (KM977759) Phylogeneti
Alternaria alternate. TGF50-MRL (KM977774) c
33 Alternaria alternata (HQ380765) relationship s of Alternaria cantlous (KC584245) Alternaria Alternaria alternata (HM204457) taxa Alternaria consortialis. TGF38-MRL (KM977766) isolated Alternaria sp.(KF438014) from Tirich Alternaria consortialis (KF887148) Mir Glacier Alternaria heterospora (KC584248) Alternaria chartarum (KM191129)
Alternaria radicina (EU781949)
99 Alternaria radicina (DQ394074)
0.002
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Table 4.5.1. Morphological characteristics of Alterneria isolates Isolates Morphological characteristics Microscopic characteristics TGF5-MRL Cottony velvety, initially gray brown then turned to dark Septate Conidiophores and conidia at the tip of the brown and dark greenish with grayish edges. Reverse: Brown conidiophores. Conidia round and oval shaped. to light brown and greenish with grayish edges TGF9-MRL Dry velvety, initially dark brown then turned to blackish gray Septate hyphae, conidia, and chlamydospores. Unicellular or with whitish edges. Reverse: Dark bluish to black with multicellular chlamydospores and "alternarioid" in brownish edges. appearance. TGF10-MRL Velvety, initially Gray white to brownish then turned to Septate hyphae, numerous short mycelia threads like brown greenish with brown grayish edges. Reverse: Dark appearance. Spore: numerous, small, round brown to gray and off-white yellowish with grayish edges. TGF29-MRL Cottony, initially brown to yellowish then turned to brown Septate branched hyphae, pluricellular conidia disperse greenish with white yellowish edges. Reverse: Off-white to irregularly containing transverse and longitudinal septa, brown and dark brown with whitish to gray edges. ovoid, pyriform, ellipsoidal, and brownish in color with rough TGF30-MRL Cottony velvety, initially brown to green yellowish then Septate branched hyphae, conidiophores and conidia round turned to brown yellow with white edges. Reverse: Off-white and oval shaped. to greenish then turned to white yellowish with white edges. TGF38-MRL Velvety, initially white then turned to white greenish and its Septate branched hyphae, Conidiophores septate and conidia structure is English alphabet 9 like then fried eggs with at the tip of the conidiophores. Conidia round and oval whitish edges. Reverse: Dark greenish to greenish black with shaped. white margin. TGF43-MRL Velvety, initially light pink whitish to orange yellowish then Septate branched hyphae, single celled conidia were turned to brown yellow with brownish then gray whitish. observed. Conidiophores with septations and the shape of the Reverse: Reddish to off-whitish then turned to red, orange conidia round ovoid and its end nearest to the conidiophore is yellowish. round while it tapers towards the apex thus, giving its typical or club like appearance. TGF44-MRL Velvety, initially brown greenish to greenish gray then turned Septate branched hyphae, branched chains of multi celled to greenish brown and whitish black with white edges. conidia from conidiophores. Conidia ellipsoidal, cylindrical Reverse: Creamy greenish to gray off-white then turned to beak, pale brown, smooth-walled or verrucose. creamy white with off-white black edges. TGF45-MRL Cottony velvety, initially white brownish to gray white and Septate hyphae, pycnidia, conidia, and chlamydospores.
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greenish then turned to brown greenish with white edges. chlamydospores were unicellular and "alternarioid" in Reverse: Light greenish and light brownish to gray off-white appearance. then turned to brown with edges gray white. Cottony velvety, initially white to dark brown and yellowish Septate branched hyphae,, branched chains of multicelled then turned to creamy dark with white edges. Reverse: Off- TGF50-MRL conidia from conidiophores. Conidia ellipsoidal, cylindrical white to off-white greenish then turned to cream and brown beak, pale brown, smooth-walled or verrucose. greenish with white edges.
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Table 4.5.2. Percentage similarity of Alternaria isolates Isolates Accession Closest taxon in Gen Bank BLAST No. (Accession No.) similarity (%) TGF5-MRL KT290044 Alternaria sp. (KJ542225) 99 TGF9-MRL KT290046 Alternaria consortialis (KM114288) 93
TGF10-MRL KT290047 Alternaria multiformis (KP117291) 100 TGF29-MRL KM977758 Alternaria alternata (HQ380765) 99 TGF30-MRL KM977759 Alternaria consortialis (HG798767) 99
TGF38-MRL KM977766 Alternaria consortialis (HG798767) 99
TGF43-MRL KM977771 Alternaria sp. (KF438014) 99 TGF44-MRL KM977772 Alternaria consortialis (HG798767) 100
TGF45-MRL KM977773 Alternaria consortialis (HG798767) 99
TGF50-MRL KM977774 Alternaria alternate (HQ380765) 99
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Table 4.5.3. Physiological analysis of the Alternaria isolates on different temperature, pH and salt concentrations
Isolates Temperature (°C) range pH range Salt range (%)
TGF5-MRL 4−37, opt. 4 2−11, opt. 6–7 2−10, opt. 2–4 TGF9-MRL 4−37, opt. 4 2−11, opt. 6–7 2−10, opt. 2–4 TGF10-MRL 4−37, opt. 4 2−11, opt. 6–7 2−10, opt. 2–4
TGF29-MRL 4−37, opt. 15 2−11, opt. 6–8 2−10, opt. 2–4
TGF30-MRL 4−37, opt. 15 2−11, opt. 6–8 2−18, opt. 2–6 TGF38-MRL 4−37, opt. 15 2−11, opt. 6–7 2−8, opt. 2 TGF43-MRL 4−37, opt. 15 2−11, opt. 6–8 2−6, opt. 2 TGF44-MRL 4−37, opt. 15 2−11, opt. 6–7 2−12, opt. 2–4
TGF45-MRL 4−37, opt. 15 2−11, opt. 6–7 2−8, opt. 2
TGF50-MRL 4−37, opt. 15 2−11, opt. 6–8 2−12, opt. 2–4
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Table 4.5.4. Antibacterial and antifungal activity of the Alternaria isolates against ATCC cultures
Fungal Bacteria Fungi isolates E. Klebsiella Staph. Bacillus Pseudomonas Asp. C. coli pneumonie aureus sp. aeruginosa flavis albicas TGF5- − + ++ ++ − − + MRL TGF9- − − − + − − − MRL TGF10- − − − − − − − MRL TGF29- − − + + − − − MRL TGF30- − − +++ ++ + − − MRL TGF38- − − ++ − − − + MRL TGF43- − − ++ + − − − MRL TGF44- − − − + − − − MRL TGF45- − + + − + − ++ MRL TGF50- − − ++ − − − − MRL Key:
(-) No Zone, (+) Zone up to 7 mm, (++) Zone up to 14 mm, (+++) Zone above 14 mm
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Table 4.5.5. Production of various extracellular enzymes by Alternaria isolates
Fungal Isolates Enzymes Amylase Cellulase DNase Lipase TGF5-MRL − − − ++ TGF9-MRL − − − − TGF10-MRL − − − + TGF29-MRL − − + − TGF30-MRL − − − − TGF38-MRL − − − +++ TGF43-MRL − − − − TGF44-MRL − + − ++ TGF45-MRL + − − +++ TGF50-MRL − ++ + + Key:
(-) No Zone , (+) Zone up to 6 mm, (++) Zone up to 12 mm, (+++) Zone above 12 mm
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Chapter 5: Metagenomics of selected HKKH glaciers
Title: Taxonomic diversity and functional of three glaciers of Hindu Kush, Karakoram and Himalayan range by Metagenomic techniques
Samples:
PS: Passu glacier Sediment
SS: Siachen glacier Sediment
T-05: Tirich Mir glacier Sediment
T-08: Tirich Mir glacier Muddy Surface ice.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range Chapter 5 Mitogenomics Abstract
Abstract Metagenomics is the most powerful technique to study taxonomic and functional diversity of different habitats as it is a known fact that less than 1% of the microorganisms are grown under lab conditions using growth media. Metagenomic techniques, bypass the culturing step and carry out detection of available sequences in a sample. The current study was carried out to evaluate biodiversity and functional potential of the sediment samples collected from HKKH glaciers. Sediment samples from Passu, Siachen and Tirich Mir were collected from Hindu Kush, Karakoram and Himalayan ranges. Whole genomic DNA was extracted using MO-BIO power soil DNA extraction kit. The isolated DNA was quantified and subjected to Next Generation Sequencing through Illumina sequencing technologies. The obtained sequence reads were uploaded on to MG-RAST, an open web source server for the analysis of NGS reads. The uploaded sequences count was 329.3 million, 327, 388 and 374 million for Passu sediment, Siachen sediment, Tirich Mir sediment and Tirich Mir muddy surface with an average length of 100 bp. The analysis of taxonomic diversity was carried out using SILVA and Green genes. The analysis showed that all the samples contained bacteria from all three domains i.e. bacteria, archaea, eukaya and viruses as well, with the abundance of bacteria. Both autotrophic and heterotrophic bacteria were observed with the most abundant heterotrophic bacterial groups like Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and many others. The autotrophic bacteria include Cyanobacteria and Chloroflexi. The eukarya group was dominated by fungi Ascomycota with autotrophic microalgae. Similarly, many micro- vertebrates were also found. The potential of functional group detection was determined by annotations in M5NR database. The Functional hierarchy of all samples was dominated by metabolism group. After metabolism, the major section of gene was responsible for Carbohydrate, protein, cell wall, stress protein, DNA repair, secondary metabolite and many others. The functional potential of psychrophilic organisms is classified into 2 main groups. First, that gives the knowledge and understanding of functional metabolism potential used for cell processes, survival and interactions with other organisms in glacial ecology, second; it provides a vast field for bioprospecting for novel metabolites used in different industries of great commercial value.
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Microbial and functional diversity of non polar glaciers HKKH Mountains ranges of Pakistan Life is consisted of three domains. Archaea and Eucarya distributed throughout in nature. The environment of earth is not uniform across the surface, beneath and above the earth surface. The environment may be varying in temperature, pH, salinity, toxic compounds concentration, availability of water and nutrients. On the bases of temperature most of the earth has temperature below 5 C with permanent frozen glaciers, ice sheet and permafrosts (Anesio et al., 2013; Choudhari et al., 2013). These environments are rich source of microbes and other eukaryotic organisms as well, but previously they were considered as free of life until they were unexplored (Miteva, 2008; Cameron, 2012; Schutte et al.,2010; Price, 2000; Siegert et al., 2001; Cowan and Tow, 2004; Priscu and Christner, 2004). One the extreme environment on the basis of temperature is frozen glacial ice, which is somewhat similar to extraterrestrial environment of Mars and Moon. Most of the glacial environment is unexplored and contain the first-born microbes (Christner et al., 2004; Willerslev et al., 2004; Molnia, 2007). The effect of global warming possibly as a result of accumulation of gasses like CO2, methane etc from anthropogenic and as well microbial source (Methane production beneath the ice sheets) leads to the increase melting of glaciers around the world. The consequences of this speedy melting are depletion of drinking water sources, uneven flooding, rise in sea level and increase in average earth temperature. The low temperature environments are dominated by microbial population like all other extreme environments. Members of all three domains of life (Eukarya, Archaea and bacteria) are present in low temperature habitats. The most dominated studied group is bacteria followed by fungi (Ascomycetes) and archaea (Musilova et al., 2015; Lutz et al., 2015; Blaud et al., 2015; Edwards et al., 2013; Simon et al., 2009). A vast majority of viral load is also reported from different frozen environments. Recent studies confirmed that viruses are one of the most important active members of glacial ecology and play a mean role in the biogeochemical processes (Bellas et al., 2015).
Reports are available that microbial biomass beneath the ice sheet is about thousands times to the mass of human beings on living on the earth (Katz, and Climate 2012). This showed that as cold environment are too though to survive but still a huge life is surviving it (Schutte et al., 2010). Many researchers studied the biology, chemistry
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and biogeochemistry of polar glaciers but very little is known about the glacial ecology and geochemistry of Hindukush, Karakoram and Himalayan mountains range glaciers. There are two main techniques for the study of microbial abundance and way of life in glaciers. The culture dependent technique mainly emphasis on the cultivation of organisms in lab followed by identification and characterization of the isolated microbes. While the other one is most powerful technique, bypassing the cultivation step, and directly determine the taxonomic and functional diversity of the sample Metagenomics “The powerful technique of the day” “Once the diversity of the microbial world is catalogued, it will make astronomy look like a pitiful science.” said Julian Davies. This estimation is quite amazingly understandable as more than 99% of microbes are not culturable in lab due to multiple factors. The culturing technique is unable to study, isolate, identify and characterize a tiny portion of microbes in an ecological place. We can grow only those microbes in lab to which provide all the important and growth limiting conditions and nutrients but most the time we failed to provide the exact ecological conditions in laboratory culturing. The amount of studying microbes was dramatically increased with the discoveries of new sequencing technologies. These technologies have the potential of better and deep understanding of ecological diversity and interactions in no time without culturing the microbes in labs. These problems were addressed by scientists using cloning expression and sequencing of the selected genes of a population DNA extracted from a specific environment. But still there was much more flaws in this technique to fully define the diversity of an ecological site. Still there was capacity of process or methods after the cloning technique to detect the sequence of each DNA available in the environment. This was achieved by advancements in the next generation sequencing (NGS) by metagenomics. Metagenomics is a powerful technique of microbial genomic analysis via direct extraction and sequencing of DNA of a microbial community present in an ecological environment (Handelsman et al., 1998). Dykhuizen, (1998) reported that 10 million to 1 billion different types of species are found in the world. It is difficult to study the microbial diversity of such gigantic number of microbial species throughout the world. Currently the use of NGS technologies using metagenomic approaches is rapidly increased to study the microbial diversity of different environments. These techniques allow us to study the microbial communities in same time, bypassing the cultivation process. DNA is
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obtained directly from the sample and sequenced to get the diversity and functional information of the selected sample. The metagenomic approaches provides information about diversity and functional potential of microbes in a specific locations such as soil, human gut, oral cavity, oceans, glacier, snow etc. These studies not only unveiled the microbial diversity but also helpful in determining the biotechnological potential of microbes along with the discovery of novel isolates as well. Up till now different scientists all over the globe are busy determining the diversity and functional potential of microbes harboring low temperature environments (Simmon et al., 2009, lutz et al., 2015; Frank-Fahle et al., 2014; Musilova et al., 2015; Peter and Sommaruga 2016). Metagenomics not only deliver the taxonomic diversity but also helpful in determining the number of genes present, and biochemical and metabolic summary of the microbes. Now a day’s metagenomics is the most worldwide technique for analysis of microbial communities (von Mering et al., 2007; Simon et al., 2009) Microbial populations of glaciers “Where there is water, there is life”. The pioneer study of microorganisms inhabiting glaciers and frozen environments are reported in 1918 (Miteva, 2008). The microbial finding in largest subglacial Vostok Lake, in Antarctica, received great interest of multidisciplinary researchers (Priscu et al., 1999; Price, 2000; Siegert et al., 2001; Lutz et al., 2015). Christner et al., (2003) reported that the ice enclosed 2-3 × 102 cells/ml. Moreover, several isolates were reported from ice core that was 750,000 year old in Guliya ice cap Tibet (Miteva, 2008). The dominant phylum reported in Arctic permafrost soil was Actinobacteria, followed by Betaproteobacteria (Yergeau et al., 2010). Johnson et al., (2007) reported that the ancient permafrost is dominated by non-spore forming Actinobacteria because at low temperature their metabolic activity is optimum. Several communities of Cyanobacteria were also described based on 16S phylogeny from Chinese glaciers (Segawa and Takeuchi, 2010). Recently, it was described that the high Arctic glacier foreland bacterial diversity was equivalent to tropical and temperate soils (Schutte et al., 2010). Additionally, several bacterial clusters were reported from the remote spot of Canadian high arctic (Skidmore et al., 2005; Cheng and Fogt, 2007), and ten isolates of bacteria were molecularly identified through 16S rRNA gene from the snow in Arctic site (Amato et al., 2007). The cold environments commonly inhabit bacterial phylum of Proteobacteria (Alpha, Beta and Gamma Proteobacteria), Bacteroides, and Actinobacteria, while Archaea are
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understated (Yergeua et al., 2010; Lewin et al., 2013). Recently, during bacterial community’s comparison study in glacial cryoconite holes in Antarctica and Arctic, several of bacterial clusters were successfully identified, showing that diverse microbial communities are present in such an extreme environments (Cameron, 2012). During comparative study of Arctic snow and freshwater, it was discovered that maximum diversity was present in snow (Møller et al., 2013). Phylums of bacteria like Proteobacteria, Bacteroidetes, Actinobacteria, Cyanobacteria, Firmicutes and Fusobacteria were quite high in snow whereas high number of Bacteroidetes, Actinobacteria and Verrucomicrobia and few Proteobacteria and Cyanobacteria were reported in freshwater (Møller et al., 2012). Moreover, numerous investigations from Antarctica (Kol, 1968), New Zealand (Sheridan et al., 2003) and Greenland (Priscu et al., 1999; Miteva, 2008) have inspected 16S rRNA genes phylogeny. The microbial diversity of European glaciers showed autotrophic lifestyle due to nutrient deficient conditions (Simon et al., 2009). This obviously specified that cold environments such as ice lakes, glaciers and snow ice inhabit huge microbial communities. These definite microorganisms influence the glacial ecosystem dynamics, and perform role in soil formation and other biogeochemical processes (Cheng and Foght, 2007). Functional and metabolic diversity of glaciers Microorganisms play a vital role in biogeochemical processes of earth (Nazaries et al., 2013). The diversity of microbes is very high and ubiquitous in nature due to their remarkable metabolic and functional abilities that are vital for biogeochemical processing (Prosser et al., 2007), like nitrogen fixation, carbon sequestration and oxygenic photosynthesis (Kasting and Siefert, 2002; Newman and Banfield, 2002). Functions like this, not only active in usual environments, but also the microbes perform such functions everywhere including unusual extreme conditions (Reysenbach and Shock, 2002; Edwards et al., 2013). Around 10% of terrestrial earth surface is covered by the glaciers holding 77% of fresh water (Paterson 1994), that makes a distinctive ecosystem which preserve microbial diversity. It is generally believed that in such a harsh conditions the biological activities is restricted. Glaciers is simple, somewhat closed ecosystems contain primary producers like photosynthetic bacteria and algae in the ice and snow (Choudhari et al., 2013). Understanding of nitrogen and carbon cycles which determined the total carbon storage in these regions (Mack et al., 2004), and other metabolic and functional processes that are responsible for microbes acclimation at this low temperature environment are very essential.
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Freshly, the approaches of NGS has been used to investigate the functional genes existing in the environmental sample in functional metagenomics. Studies like this, offer comprehensive information of functional and metabolic potential of microbial community present in a particular habitat, and are considered as the most precise quantitative method (von Mering et al., 2007; Simon et al., 2009). Numerous studies conducted for microbial diversity existing in glaciers of Antartica (Priscu et al., 1999), Asia (Christner et al., 2003), New Zealand (Foght et al., 2004), Greenland (Miteva et al., 2004; Sheridan et al., 2003) and Germany (Simon et al., 2009). The comparative load of all genes and metabolic potential of the microbes inhabit in any habitat can be investigated through metagenomics approach. Currently, a detailed phylogenetic diversity and metabolic potential study has been conducted from European glaciers and discovered microbial communities of diverse metabolic capabilities (Simon et al., 2009). Recently, another study of metagenomic and metatrancriptomic inquiry was performed on sub glacial lake of Antarctica (Rogers et al., 2013). Several genes sequences that are responsible in carbon fixation and nitrogen cycle were described. Some methanotrophs and methanogens were reported in Arctic permafrost during functional exploration, and very few number of genes that involved in ammonia oxidation and nitrogen fixation were reported. Which was previously the Arctic region was considered as Nitrogen deficient (Shaver & Chapin, 1980; Martineau et al., 2010). Recently reports of the functional diversity of alpine glaciers and cryoconites revealed many genes responsible for the metabolism and cycling of Fe, N, P and S cycling (Edwards et al., 2013). Frank-Fahle et al., (2014) reported that abundant of genes are involved in different biogeochemical processes like ammonia oxidation, methane oxidation and production and nitrogen fixation from the permafrost soils of NW Canadian Arctic. DNA Sequencing Technologies Sequencing of DNA is the precise sequence determination of nucleotides in a DNA strand. The basic DNA sequencing methods also called first generation sequencing practices comprise Maxam-Gilbert (Maxam and Gilbert, 1977), and most promising technique developed by Sanger also term as Sanger Dideoxy Chain Termination Sequencing (Sanger et al., 1977). In Sanger sequencing technique labeled nucleotides are inserted into DNA template during its extension and elongation. Subsequently, the position of labeled nucleotides is obtained by separating the fragments of DNA based on their length by polyacrylamide gel electrophoresis or capillary electrophoresis.
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This technology get advance with the passage of time and second or NGS technology were established based on idea of “sequencing by synthesis” (Bentley et al., 2008). This advanced approach includes the sequencing process with minimum need of fragment-cloning methods and high throughput yielding. This is fast and cost effective method of sequencing approaches and it can sequence huge DNA amount in short period of time. The most important and widely used NGS approaches used are briefly discussed in following Illumina Sequencing Technologies Illumina approach based on “sequencing-by-synthesis” technology parallel to Sanger sequencing but it uses altered dNTPs having a terminator. This terminator which is fluorescent label stops further polymerization, and a camera can detect the single base added to growing DNA strand by the enzyme. After dNTPs addition, the terminators are detached, and the pictures are documented. This sequencing method is dependent on reversible dye-terminator. 454 Life Sciences (Roche/454) pyrosequencing Technologies Roche 454 is an alternative NGS technology, based on sequencing by synthesis principle. The small dsDNA fragments are fused with adopter having micro sized beads at both ends. This complex of fragment-bead is assorted with emulsion oil that amplifies the DNA fragments inside the bubbles of water in oil emulsion. Every bubble holds a DNA molecule and bead coated primer to which DNA attaches forming a clonal colony (emulsion PCR). Primarily, the signal in the form of light is detected as soon the amplification of products occurs. By using this light signal obtained by CCD camera, this technology of Roche 454 forms a flowgram. The major advantage of this technology is, it can generate and detect sequence up to 400 bases longer than read detected by 2nd generation sequencing techniques. Ion Torrent Sequencing Technologies Ion Torrent technique is fresh technology based on sequencing by synthesis method, facilitates detection of digital information and chemical reaction takes place by incorporation of new nucleotide into the DNA strand. In this method, when incorporation of any base (A, T, G, and C) into DNA strand occurs with the help of polymerase enzyme, it releases one H+ ion, which can be sensed by the sensor. This technology based on electrochemical detection system that can sense H+ ions when they released during addition of nucleotide triphosphate by DNA polymerase. The H+
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release causes a small pH change that is detected by the detector. Labeled nucleotide are used which help in the detection newly incorporated base.
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Methodology Description of the study site and sampling 1. Passu Glacier
Passu glacier is situated in Hunza Valley in the heart of Karakoram Range. The length of Passu glacier is 56 km and it is considered as the 5th largest glacier in the world outside polar region. The samples (glacial ice, sediments and water) were collected from Passu glacier Pakistan at coordinates as 36°27.424N to 074°52.010E, using sterile bottles, following standard microbiological protocols. The pH for the all samples was neutral (7.0), whereas, temperature of sediments and water was 1°C while ice at -2°C (Fig. A2 and A4). 2. Siachen Glacier
The Siachen glacier is the second longest non-polar glacier in the world, 70 km long and located in the Himalayan Karakoram range. The total width of the glacier is between 2-8 km and the total area is about 1,000 km2. The pH for the all samples was neutral (7.0), whereas, temperatures of sediments and water was 1°C while the ice temperature was -3°C. Siachen glacier is situated at 35°25′16″N 77°06′34″E/35.421226°N 77.109540°E, Pakistan. 3. Tirich Mir glacier
Tirich Mir glacier is one of the main glaciers of the Hindu Kush mountain range, spreading over a large area of about 800 km extending from northern areas of Pakistan to central Afghanistan. Its highest peak is Tirich Mir 7,708 m and ranked highest outside Karakoram and Himalaya and 33rd in the world. Tirich Mir dominates this 322 km long Chitral valley. Chitral is situated in the mountains of Hindu Kush between 35° and 37° North and 71° and 74° East (Fig A3 and A4). To the North, famous Afghan Wakhan Corridor separates it from the Republic of Tajikistan and Pamirs, to Northeast the Hunza Valley forms border to China. The mountains of Chitral are considered the most difficult for expeditions (Buchroithner and Zimmer, 1998) because of its rough terrain. No mountain in the region is less than 1200 m and more than 40 peaks have an altitude of 6096 m. Samples were collected from snout of one of the glaciers near Upper Tirich valley, Chitral. GPS (Garmin eTrex 20) was used for determining geographic coordinates of sample locations. Temperature was
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recorded using thermometer, while pH was determined by pH strips on site and pH meter (Sartorius Professional Meter PP-15) in lab. Collection of Samples Collection of samples from all four sampling sites was carried out using standard microbiological procedures. Samples were collected in the form of glacial ice, glacial melt water and glacial sediment. All the collected samples were transported to the Microbiology Research Lab., Quaid-i-Azam University, Islamabad, in ice box and stored at -20°C. Here it is to mention that we have used only sediment samples and one surface muddy moraine sample of Tirich Mir glacier in this study. DNA extraction Four sediment samples of different glaciers of HKKH range mountains. DNA was extracted from all samples following the instructions of the manufacturer as described by MO BIO PowerSoil® DNA Isolation Kit. Added 250 mg sediment samples to the provided PowerBead Tubes and mixed gently. About 60 μl of C1 solution was added and mixed well. Vortexed the beaded tube containing sample with maximum speed for 10 minutes and centrifuged for 60 seconds at 10,000 x g. Carefully transferred the supernatant into sterile tube and added 205 μl C2 solution and incubated for 5 minutes at 4°C followed by centrifugation at for 60 seconds at 10,000 x g. Transfered 600 μl supernatant to a fresh tube and added 200 μl C3 solution, incubated at 4°C for a time of 5 minutes and repeated the centrifugation. Transferred 750 μl clear supernatant to a 2 ml tube then added 1200 μl C4 solution and vortexed slightly to mix well. Assembled the spin filter column and add 675 μl of the mixture and centrifuged and removed the filtrate, repeated the steps for all mixture. The spin filter column was washed twice with 500 μl C5 solution (Wash Solution) for final elution of the DNA 100 μl of C6 solution was added and carefully centrifuge. The DNA was collected and stored at -80°C.
Construction of DNA Libraries and Sequencing
The four samples were sequenced in one lane on an Illumina GAII, with 100 bp paired end reads and an insert size of 400 bp at the Bristol Genomics Facility. Reads were filtered for Illumina adaptors using fastqc-mcf and trimmed to a minimum PHRED score of 20. DNA library preparation was conducted following the manufacturer’s instruction (Illumina). To annotate functional genes, virus scaffolds
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were uploaded to MG-RAST (Meyer et al., 2008) using the assembled contigs pipeline and a coverage of one for all scaffolds. Annotation against the subsystems database was performed with an E-value cut-off 10−5. The output sequences of Illumina were further analyzed.
Bioinformatic Analyses
Taxonomic classification and analysis
The taxonomic classification, group wise distribution, diversity and abundance of different taxonomic ranks were determined using Meta Genome Rapid Annotation using Subsystem Technology (MG-RAST) (http://metagenomics.anl.gov/), using online server at the Argonne National Library (http://www.anl.gov/). The MG-RAST is a power full well equipped database server which helps in many ways to analyze a varying type of data. The MG-RAST is helpful in phylogenetic analysis, alpha and beta diversity determination, species richness of a sample, the metabolic potential of a sample and provides many data bases in one for the comparison and annotations of different reads to detect and predict different protein and functions (Meyer et al., 2008; Urich.et al., 2008). The protein homology was carried out by similarity search in M5NR database at (http://metagenomics.nmpdr.org). These databases include NCBI, KEGG, SEED. M5NR is M5 non redundant protein data base. Currently the data set used for analysis and annotations are with Passu Sediment (MG-RAST ID 4642124.3), Siachen sediment (MG-RAST ID 4642125.3), Tirich Mir sediment MG- (RAST ID 4642126.3) and Tirich Mir muddy surface ice moraine type (4642127.3).
Taxonomic classification
The taxonomic classification was determined by using rRNA pipeline. A reduced data base pipeline of SILVA was used for the detection rRNA reads for the taxon identification. Sequences are pre-screened using qiime-uclust for at least 70% identity to ribosomal sequences from the following RNA databases (Greengenes, LSU, SSU, and RDP). BLAT search were used for longer reads against M5NR data base which integrates many databases like SILVA (Pruesse et al., 2007), Greengenes (DeSantis et al., 2007) and Ribosomal Database Project i.e. RDP (Cole et al., 2003). The
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taxonomic classification was carried out by using the lowest common ancestor (LCA) in MEGAN (Huson et al., 2007).
Protein prediction and identification
Different databases merged in M5NR were used for the protein detection, prediction and functional prediction. SEED subsystems in MG-RAST are used for determination and KEGG mapper system is used to visualize the results.
Plotting Results All the processed data was obtained from MG-RAST and different graphs were plot using Microsoft Excel software. Some result was directly obtained from the MG- RAST online by snap shots.
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Results
Metagenomic study is one of the amazing approaches to study the microbial taxonomic diversity and functional potential of extreme habitats. Previously, many studies have been conducted to determine the functional diversity of such low temperature extreme environments, like deep sea, glacier ice, glacial water, glacial lakes, alpines etc. Here in this study we present the functional potential of glacial ecology of 4 samples from 3 different glaciers of HKKH regions of Pakistani glaciers. These samples include; PS (Passu glacier sediment. Karakoram), SS (Siachen glacier sediment, Himalaya) and 2 samples T-05 (sediment) and T-08 (ice) from Tirich Mir glacier (Hindu Kush range)
Sequences of four different samples were used for comparative analysis of functional potential of biomes. The initial sequences obtained in fastq format were uploaded into MG-RAST for various analyses. These raw sequences were passed through quality filtering, the weak sequences were trimmed and good quality sequences were used for further analysis.
Sequence Breakdown
We obtained a huge number of sequences for all 4 samples. Total 32,930,329 sequence reads were obtained from sediment sample of Passu glacier, 32,705,549 from sediment sample of Siachen glacier, 38,871,311 from sediment of Tirich Mir glacier and 37,464,355 sequences from surface ice sample of Tirich Mir glacier. The Mean Sequence Length of the raw sequence reads are approximately 100 bp. The % GC content of the uploaded sequences is 59 ± 11, 63 ± 11, 60 ± 11 and 51 ± 12 %, respectively, for PS, SS, T-05 and T-08 (Table 1).
After quality control filtering, the Mean Sequence Length was 98 ± 6, 98 ± 7, 98 ± 6 and 98 ± 6 bp of reads, respectively for PS, SS, T-05 and T-08 samples. The mean GC percent was calculated as 59 ± 11, 63 ± 11, 61 ± 11 and52 ± 12 % for PS, SS, T-05 and T-08 samples, respectively. The predicted rRNA features were 371,659, 1,857,811, 2,150,561 and 1,158,114, respectively for PS, SS, T-05 and T-08 samples. The protein features identified by alignment were 6,859,273, 8,458,827, 9,055,136
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and 5,824,161 respectively. The functional categories identified by annotation were 5,480, 077, 6,596,842, 7,431,668 and 5,052,322 respectively (Table 5.1)
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Table 5.1. Sequence break down of the sequences obtained from Illumina for functional categories.
Parameters Passu Sediment Siachen Sediment Tirich Mir Sediment Tirich Mir ice Out put bp Count 3,293,032,900 bp 3,270,554,900 bp 3,887,131,100 bp 3,746,435,500 bp Output Sequences Count 32,930,329 32,705,549 38,871,311 37,464,355 Output Mean Sequence Length 100 ± 0 bp 100 ± 0 bp 100 ± 0 bp 100 ± 0 bp Output Mean GC percent 59 ± 11 % 63 ± 11 % 60 ± 11 % 51 ± 12 % Post QC: bp Count 2,964,302,023 bp 3,038,007,913 bp 3,413,167,041 bp 3,173,215,915 bp Post QC: Sequences Count 30,049,068 30,883,171 34,603,741 32,162,479 Post QC: Mean Sequence Length 98 ± 6 bp 98 ± 7 bp 98 ± 6 bp 98 ± 6 bp Post QC: Mean GC percent 59 ± 11 % 63 ± 11 % 61 ± 11 % 52 ± 12 % Processed: Predicted Protein Features 23,060,122 26,859,757 28,792,854 16,655,941 Processed: Predicted rRNA Features 371,659 1,857,811 2,150,561 1,158,114 Alignment: Identified Protein Features 6,859,273 8,458,827 9,055,136 5,824,161 Alignment: Identified rRNA Features 11,428 19,362 18,253 11,523 Annotation: Identified Functional Categories 5,480,077 6,596,842 7,431,668 5,052,322
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Summary of Metagenomes
Passu Sediment (PS)
Dataset PS contains 32,930,329 sequences totaling up to 3,293,032,900 base pairs with an average length of 100 bps. The pie chart (Fig. 1) breaks down the uploaded sequences into 5 distinct categories. A total of 2,881,261 sequences (8.7%) failed to pass the QC pipeline. Of the sequences that passed QC, 114,227 (0.3%) sequences, contained ribosomal RNA genes. Among the remaining, 10,989,176 (33.4%) sequences contain predicted proteins with known functions and 16,263,331 (49.4%) sequences contain predicted proteins with unknown functions. About 2,682,334 (8.1%) of the sequences that passed QC did not have rRNA genes or predicted proteins (Fig. 5.1, Table 5.1).
Siachen Sediment (SS)
Dataset SS contains 32,705,549 sequences totaling 3,270,554,900 base pairs with an average length of 100 bps. The pie chart (Fig. 1) breaks down the uploaded sequences into 5 distinct categories. A total of 1,822,378 (5.6%) sequences failed to pass the QC pipeline. Among the sequences that passed QC, 2,778,168 (8.5%) sequences contained ribosomal RNA genes. Of the remaining, 9,772,574 (29.9%) sequences contain predicted proteins with known functions and 18,332,429 (56.1%) sequences contain predicted proteins with unknown functions. None of the sequences that passed QC had rRNA genes or predicted proteins (Fig 5.1, Table 5.1).
Tirich Mir Sediment (T-05)
Dataset T5 contained 38,871,311 sequences totaling up to 3,887,131,100 base pairs with an average length of 100 bps. The pie chart (Fig. 1) divides the uploaded sequences into 5 different categories. About 4,267,570 (11.0%) sequences failed to pass the QC pipeline. Of the sequences that passed QC, 3,247,578 (8.4%) sequences contained rRNA genes. Among the remaining, 11,916,039 (30.7%) sequences contain predicted proteins with known functions and 19,440,124 (50.0%) sequences contain
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 304 Chapter 5 Mitogenomics Results predicted proteins with unknown functions. None of the sequences that passed QC had rRNA genes or predicted proteins (Fig 5.1, Table 5.1).
Tirich Muddy Ice (T-08)
Dataset T8 contained 37,464,355 sequences totaling up to 3,746,435,500 base pairs with an average length of 100 bps. The sequences were distinguished into 5 different categories. A total of 5,301,876 sequences (14.2%) failed to pass the QC pipeline. Among the sequences that passed QC, 2,840,841 (7.6%) sequences contained rRNA genes, 18,102,467 (48.3%) sequences contain predicted proteins with known functions and 11,115,219 (29.7%) sequences contain predicted proteins with unknown functions. While, 103,952 (0.3%) sequences that passed QC did not have rRNA genes or predicted proteins (Fig 5.1, Table 5.1)
Fig 5.1. Distribution of sequences of all 4 samples into functional categories
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Rare faction curve Rare faction curve indicate the specie richness of a given habitat. In our study, the rare faction curve revealed that the most specie rich sample was Siachen sediment with a value of 444.91, followed by Passu sediment with 425.91, Tirich Mir sediment with 402,81 and Tirich Mir muddy surface ice with a 93.86 value. The specie richness in graphical form is shown in Fig. 5.2.
Fig 5.2 Rare faction curve showing specie richness of the study samples
Sample Indicator Specie richness Passu Sediment 425.91
Siachen 444.91
T. Mir05 402.81 T. Mir08 93.86
Table 5.2. Rare faction curve showing specie richness of the study samples
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Taxonomic distribution The samples were found to contain representative sequences from all 3 domains of life as well as from the viruses. The most abundant group was found to be Proteobacteria followed by Actinobacteria, Firmicutes, Bacteriodetes, Ascomycota and cyanobacteria. Presence of highest ranked 50 phyla is precisely elaborated in Fig. 3. As the samples belonged to different locations having diverse geochemistry, ecology and physicochemical properties, these parameters are also acting as the driving force to shape the diversity of an ecological niche. Each group of organisms might have specific requirement and the availability of such necessities helps for the growth and survival of specific groups of organisms. The diversity of each sample is briefly summarized in the following and detail in Appendix 2.
Fig 5.3. Domain distribution of all the samples, all samples indicates the absolute abundance of domain bacteria.
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Passu Sediment Passu sediment contains members of all 3 domains as well as sequences of viruses. Domain Eukaya is dominated by fungi. The most abundant group of this domain was Ascomycota which contain dimorphic fungi, and this mechanism helps to live and thrive in such harsh environment. Besides, the Passu sediment also contained some genes from plant and animal Kingdom. The most dominant group was bacteria which constituted about 97% of the total life forms. Bacterial phyla included; Proteobacteria, Actinobacteria, Photosynthetic Cyanobacteria, Firmicutes and radioresistant Deinococcus groups along many more with less representation. Members of the Archaeal domains were also observed. The major groups of Archaea were the unclassified sequences from Archaea and Thaumarchaeota group (Fig 5.4, 5.6 and 5.10a). Siachen Sediment The taxonomic distribution of Siachen sediment samples constituted about 97.7% of the Domain Bacteria, 1.8% of the Eukaryota, 0.4% of Archaea and very little percentage of other sequences including viruses. Bacterial Domain Like other glacial and low temperature environments the sediment of Siachen is dominated by bacteria. The most abundant groups of bacteria observed were Actinobacteria, Proteobacteria, Bacteriodetes and Firmicutes. Some other major groups like photosynthetic bacteria and radioresistant bacteria were also observed. Eukaryota Domain This domain is further divided into 3 groups; Fungi, Plants and animals. The most abundant group was fungi and ascomycetes group was found in highest number. Traces of plant and animals were also detected in Siachen sample site. Archaea Domain Sequences were also found to belong to domain Archaea. Some were identical to the known groups of archaea, while some reads were similar to uncultured sequences. Taxonomic distribution of sample PS and SS is explained in (Fig. 5.3 and Fig. 5.4 and 5.10a).
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Fig.5.4. Taxonomic abundance in Passu sediment (PS) sample and Siachen sediment (SS) sample.
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Fig. 5.5. Taxonomic abundance in Tirich Mir sediment (T-05) sample and Tirich Mir muddy surface ice (T-08) sample
Tirich Mir Sediment (T-05) and Tirich Mir Muddy surface Ice (T-08) The taxonomic distribution of Tirich Mir Sediment (T-05) samples constituted ~ 97.8 % of domain bacteria, 1.7 % of the Eukaryota, 0.3% of Archaea and very low percentage of other sequences including viruses (Fig 5.5, 5.8 and 5.9 and 5.10b). Bacteria Domain Both sediment and surface ice samples of Tirich Mir glacier showed almost similar taxonomic distribution, dominated by domain bacteria. The most abundant groups of bacteria observed were; Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes.
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Some other major groups like photosynthetic bacteria and rRadioresistant bacteria were also observed. Eukaryota Domain A reasonable population of Eukaryota group was present in samples of Tirich Mir glacier. The Eukaryotic domain is further divided into 3 groups; fungi, plants and animals. The most abundant group was fungi with ascomycetes in highest number. Traces of plants and animals were also detected in Siachen samples. Archaea Domain Archaeal sequences were also found of which some were identical to the known groups of archaea, while some showed similarity to uncultured sequences. Taxonomic distribution of samples T-05 and T-08 is explained in Fig. 5.4, 5.5 and 5.10b.
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Archaea
Viruses and other
Fig 5.6. community distribution and Bacterial distribution of Passu Sediment PS in Krona Chart
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Fig 5.7. Community distribution and Bacterial distribution of Siachen Sediment SS in Krona Chart
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Fig 5.8. Community distribution and Bacterial distribution of Tirich Mir Sediment T- 05 sample in Krona Chart
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Archaea Viruses and other
Fig 5.9. Community distribution and bacterial distribution of Tirich Mir muddy surface ice T-08 in Krona Chart.
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Fig 5.10a. Taxonomic rank abundance plots for the metagenomic samples PS and SS
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Fig 5.10b. Taxonomic rank abundance plots for the metagenomic samples T-05 and T- 08.
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Functional Category Hits Distribution Functional category distribution was determined on the basis of annotation to the combined functional data base M5NR using COG (Cluster of Orthologous Genes group) hits. The annotations show that the maximum sequences belonged to metabolism category for each sample. Samples PS, SS, T-05 and T-08 represent 46, 48, 48 and 43 percent of the sequences in the metabolism category. The other functional categories include Cellular processes and signaling and Information storage and processing. Some reads were not categorized clearly in any category (Fig. 5.11).
Fig. 5.11. Functional hits distribution of sample genomes by COG distribution. KEGG Orthology Hits
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Sequences of all samples were used to BLAST against KEGG Orthology hits. The annotations show that major portion of DNA reads were responsible for Metabolism. About 60% of the sequences were present for the metabolism (Fig 5.12). The major subgroups of metabolism are Carbohydrate metabolism, energy, Lipid, amino acid and many others with important enzymes and metabolites. Other sequences found have similarities with Human diseases, cellular processes and Organismal systems. Further explained in subsystem portion section.
Fig 5.12: KEGG orthology functional hits of the study samples
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Subsystem functional hits The Subsystems function pie chart (Fig. 12), shows reads classified into SEED subsystem level-one functions. In contrast to the COG and KEGG classification schemes, there are over 20 top-level subsystem categories, creating a more highly resolved “fingerprint” for the metagenome. The subsystem hit represent the collection of roles which are present to form a single biosynthetic pathway. The subsystem technologies of our study samples showed a wide variety of different functional groups required for metabolism, survival, cellular processes, signaling, production of different metabolites like antagonistic compounds, radioresistant compounds etc. Our samples show that the most abundant sequence reads were determined for Carbohydrate metabolisms, amino acid and derivatives, cell wall and capsule formation. Besides these, sequence reads of important metabolites regarding the low temperature, low nutrient and high radiation habitat were also detected which include antimicrobial compounds, capsule formation, spore forming ability, pigments and synthesis of polyunsaturated fatty acids (PUFA) etc. (Fig. 5.13) and the heat map of the read abundance of the study samples for given categories (Fig 5.14).
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Fig. 5.13. Distribution of functional gene by subsystem technologies
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Fig. 5.14. Heat map of the functional subsystem categories of the study sample
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Discussion
Scientists have been successful in finding various types of active microbial communities in cold habitats (ice, cryoconite holes, ice sheets, permafrost etc) including prokaryotes, eukaryotes and viruses, although biological activity in these low-temperature habitats is generally considered to be limited. For the study of diversity they have employed different techniques ranging from culture dependent to metagenomics techniques, like DGGE, cloning techniques, pyrosequencing, Illumina, Ion Torrent, etc. and constructing clone libraries. For analysis of abundance and finding the dominant species etc. various types of software are being used and represent data graphically. The scientists infer hypotheses regarding the role of all these microbes in the cycling of nutrients, strategies to survive, interaction with each other and with the environment leading to changes in climate in bigger perspective. Scientists can easily construct a model of life forms and their active roles in any given glacial systems, but they are not successful yet. The reason being the glacial systems are not uniform, they are dynamic, in their structure, composition, geochemistry, availability of nutrients, temperature and other physical or chemical factors and ultimately in terms of microbial life. A finding of one study in a specific habitat will not give the same results when done the next same season or even after precipitation or strong winds. Air mass behavior was believed to be one of the main drivers of the zonal distribution of microbial communities across the mountain glaciers in western China (Xiang et al., 2010). Therefore, in order to get more clear picture of the diversity of glaciers, their adaptability mechanisms, their probable importance for industry/biotechnology and impact on climate and vice versa, the studies are to be carried out more extensively and continuously around the globe in the regions having significant number of glaciers like, polar regions and non-polar alpine regions as well as ‘third pole’ HKKH region in Asia. Analysis of the glacial metagenome could also provide information about the microbial life in cold and frozen places on Earth, which leads to speculations about microbial life in extraterrestrial analogs.
Keeping in view the importance of this study in global perspective, we selected different glaciers located in distant valleys of HKKH to carry out the comparative study of microbial diversity employing the metagenomic techniques. In the current study, diversity of four glacial samples collected from different glaciers (Passu,
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Siachen, Tirich Mir) was determined by culture independent/metagenomic method (Illumina Sequencing Technologies). Three sediment samples and one surface muddy sample were selected for the study because of rich ecology. DNA of all the samples was extracted for metagenomic analysis. Samples were from three glaciers of 3 of the highest mountain ranges of the world i.e. Hindu Kush, Karakoram and Himalaya. These mountain ranges contain gigantic ice mass, and considered as world’s Third Pole. Previously, there is not a single study of microbial diversity available pertaining to these glaciers. The diversity of these glaciers is very vast in terms of taxonomic abundance and functional varieties. A change in the microbial composition of glaciers may be the reflection of microbes to the climatic change globally (Christner et al., 2000, 2003; Muller et al., 2004; Simon et al., 2009; Miteva et al., 2009). Reports also indicated phylogenetic variations among the glacial ice and mild environments. This statement is supported by the difference in bacterial diversity of the reports from Malan ice (Xiang et al., 2004), Muztag Ata Glacier (Xiang et al., 2005) and the diversity of ice from Arctic and Antarctic glaciers reported by Christner et al., (2000).
Taxonomic Diversity
All four glacial samples were rich in diversity and representatives of all three domains of life were reported in all samples (Fig. 3, Table 1), besides, a number of sequences derived from viruses or of viral origin was also obtained. The presence of all domains of life and viruses as well, are previously reported from many other low temperature environments like, snow (Lutz et al., 2015), glaciers (Choudhari et al., 2014), ice sheets (Anesio et al., 2008, 2012; Edwards et al., 2011), cryoconites (Lutz et al., 2015; Bellas et al., 2015), glacial lake (Foong et al., 2010). All these reports supported our study of glaciers which are also rich in ecology as well as a source of biome.
Bacterial Diversity
Variability in terms of diversity in the glaciers is mainly operated by many factors of atmosphere and climate origin, containing geographical site (Kikuchi et al., 1994; Battin et al., 2001; Mueller and Pollard, 2004; Takeuchi and Koshima, 2004), direction and speed of air currents, intensity of light, and nutrient and water availability (Kohshima, 1994; Carpenter et al., 2000; Hill et al., 2003; Takeuchi
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 324 Chapter 5 Mitogenomics Discussion and Koshima, 2004; Mueller and Pollard, 2004; Bhatia et al., 2006). It was reported by Bagshaw et al., (2016) that microorganisms in Antarctic cryoconites organisms were stressed by high intensity of light; therefore they must use some strategies to protect themselves against photo damage.
Reports available on the effect of biogeography and microbial distribution are very poor especially in low temperature environment like glaciers, ice sheets, alpine glaciers etc. (Christner et al., 2003; Takeuchi et al., 2006; Zhang et al., 2007; Liu et al., 2009; Zhang et al., 2009). Reports of three different glacial snows from Kuytun 51 (Xiang et al., 2009b), Guoqu (Liu et al., 2009) and Rongbuk (Liu et al., 2006) glaciers revealed that seasonal variations have great impacts on the microbial communities of snow.
The present study revealed the most abundant live form in all glacial samples was bacteria, with comparatively low number in Passu sediment (PS), i.e. about 91%, while in the remaining samples SS, T-05 and T-08 were 98, 98 and 97% of the total isolates, respectively. Similarly, Simon et al., (2009) also observed that prokaryotic glacial ice community in Northern Schneeferner, Germany, was dominated by bacteria.
In all four samples the major groups of bacteria were Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Cyanobacteria, Deinococcus, Acidobacteria, photosynthetic Chloroflexi and many others. Choudhari et al., (2014) reported a very rich and immense diverse environment of Alaskan glacier having more than 2,500 species including Archaea along with the most dominant groups of Proteobacteria, Bacteroidetes and Firmicutes. The phylogenetic abundance of the prokaryotic communities, when assessed by Pyrosequencing of DNA isolated from glacial ice of the Northern Schneeferner, Germany, reported that Proteobacteria (chiefly Betaproteobacteria), Bacteroidetes and Actinobacteria as the predominant phylogenetic groups (Simon et al., 2009). Similarly, Xiang et al. (2009) also reported Proteobacteria as the most dominant bacteria on the glacier surface followed by Bacteroidetes and Cyanobacteria, and a small proportion of Actinobacteria, while only a few clones belonging to the families Chloroflexi and Deinococcales and Firmicutes were reported from ice. Different diversity profile was observed by An et al. (2010). They reported six phylogenetic groups Flavisolibacter, Flexibacter
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(Bacteroidetes), Acinetobacter, Enterobacter (Gammaproteobacteria), Planococcus/Anoxybacillus (Firmicutes), and Propionibacter/Luteococcus (Actinobacteria) along the Muztag Ata Glacier, and their composition varied by seasons.
Proteobacteria has the ability to survive the adverse conditions and adapt due to genome variability. The horizontal gene transfer also helps different microbes to adapt in the glacial environment. Members of Proteobacteria along with Actinobacteria, Firmicutes and Bacteroidetes are heterolithotrophic bacteria and the sediment of the glaciers is actually the reflection of bedrocks beneath. The glacial ice melts and erodes the underlying rocks to form the nutrient rich sediment. On the other hand, the presence of autotrophic organisms is also reported by many researchers (Christner et al., 2003; Anesio et al., 2012; Lutz et al., 2015; Vonnahme et al., 2016). The widely present photoautotrophic bacteria are Cyanobacteria and Chloroflexi (Anesio et al., 2011; Bajerski and Wagner, 2013; Lutz et al., 2015). The presence of these photosynthetic bacteria along with other Eukaryotic photosynthetic algae, serve as primary producers. The number of photosynthetic bacteria usually increases during summer season, when the glacier is retreated to its minimum size. The ablation of glacier occurs in every summer, and each time it exposes the somewhat permanent microbes of the glaciers and due to their persistent presence and possibly horizontal gene transfer through viruses and plasmids, the microbes may evolve autotrophy and start production of compounds which help them in their survival under harsh conditions like low temperature, low available free water, low nutrient and inter specie competition of the glaciers.
Bacterial Diversity in Passu, Siachen and Tirich Mir glaciers
Metagenomic analysis confirmed that Proteobacteria phylum dominated in Tirich Mir (T-08) (85.4%), followed by Tirich Mir sediment (T-05) (60%), Passu sediment (PS) (45%) and Siachen sediment (36%). Proteobacteria was followed by Actinobacteria (43%) in Siachen sediment, Passu sediment (23%), T-05 (22%), and least (7.6%) in T-08 sample. Betaproteobacteria and Gammaproteobacteria are the most dominant classes of Proteobacteria group. The Proteobacteria group is widely dominated in all environments as well as in low temperature environments across the globe from polar to non- polar glaciers. Many reports suggested that a Betaproteobacteria, a class of
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Proteobacteria are the ancient bacteria having the ability to colonize such environments (Fierer et al., 2007, 2010; Pianka, 1970; Zumsteg et al., 2012). Proteobacteria are also reported from snow pack communities and alpine habitats (Hell et al., 2013, Larose et al., 2010). The important role of these microbes is weathering of minerals and debris covered glaciers (Frey et al., 2010; Franzetti et al., 2013).
Siachen sediment was more diverse in nature and contained major groups of bacteria in high number, with Actinobacteria as most abundant group. The filamentous Gram positive Actinobacteria, are predominant group of the cold environments and reported for different functional proteins and nitrogen cycling (Cowan et al., 2011; Chan et al., 2012; Varin et al., 2012). The genome of Actinobacteria revealed that different structural and functional proteins help in the metabolic processes and DNA repair in cold habitats (Johnson et al., 2007; Guerrero et al., 2014). These microbes have the ability to survive the freeze thaw cycle, low water, oxidative stress and radiations (Cowan et al., 2004, 2014; Makhalanyane et al., 2016).
In our study, presence of Cyanobacteria was high (8%) in Passu sediment followed by T-05 (1%) and Siachen sediment (0.9%) but surprisingly Cyanobacterial presence was not detected in the Tirich Mir sediment sample T-08. Among photosynthetic organisms, Planctomycetes were also detected in SS (1%) and few genes were detected in PS samples. Our findings indicate that as the level photosynthetic bacteria is very low, the organisms must be using some other source of energy i.e. they are either chemotrophs or heterotrophs or both, and they are not dependent on photoautotrophs for obtaining their energy or carbon source. Representatives of Cyanobacteria, Actinobacteria and Planctomycetes were reported from Alaskan glacier that indicate the dependence of ecosystem on energy obtained through photosynthesis and close links with the microbial community of the soil (Choudhari et al., 2014). Among photosynthetic bacterial groups, Phylum Chloroflexi (1.3%) was also identified in SS only.
In our case, level of Actinobacteria was high, and second to Proteobacteria, in sediment of all glacier sediments and least in T-08. Xiang et al. (2009) reported phototrophs and heterotrophs as representatives of two distinct metabolic types in the Kuytun Glacier, Tibetean Plateau, China. Actinobacteria are the dominant inhabitants
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 327 Chapter 5 Mitogenomics Discussion of soils (Hill et al., 2011). Actinobacteria play an important role in the geochemical cycling of Carbon, Nitrogen, Potassium, Phosphorus and the other elements (Goodfellow and Williams, 1983; Holmalahti et al., 1994). Actinobacteria has also been reported for the production of different important bioactive compounds including antimicrobial compounds (El-Tarabily and Sivasithamparam, 2006; Eisenlord and Zak, 2010; Miao and Davies, 2010). Most of the natural antibiotics are reported to be isolated from Actinobacteria (Berdy, 2012). They also have the potential of producing different important enzymes which are used in industrial and environmental processes of decontamination and bioremediation (Eisenlord and Zak, 2010; Hill et al., 2011; Kitagawa and Tamura, 2008; Larkin et al., 2005; Martinkova et al., 2009). Moreover, the potential of psychrophilic Actinobacteria can be explored for prospecting different novel uses and metabolites (Beattie et al., 2011). However, in spite of the broad applications of Actinobacteria, the ecology and the roles in environmental communities are not properly understood (Miao and Davies, 2010).
Cyanobacteria were reported as the dominant primary bacterial phototrophs in Kuytun 51 glacier samples with the four subgroups: Phormidium, Pseudanabaena, and Oscillatoria spp. and Stephanopyxidaceae (Xiang et al., 2009). Previously, Cyanobacteria are also reported from different polar and non-polar glaciers, e.g. Alaska (Takeuchi, 2002), Chile Tyndall (Takeuchi and Koshima, 2004), Svalbard (Stibal et al., 2006), Antarctic (Cowan et al., 2011, 2014) and Ronbuk glacier (Liu et al., 2007). These Photosynthetic bacteria are found in the soil of Arctic and Antarctic glaciers and have a main role in the cycling of carbon, nitrogen and other elements (Rhodes et al., 2013; Makhalanyane et al., 2014; 2015). Xiang et al. (2009) suggested that Cyanobacteria are more abundant in some glaciers but rare in others, which most probably is due to difference in the selective climate effect and environmental conditions. These microbes produce different pigments which help in the survival (Varin et al., 2012).
Bacteroidetes were detected more in T-05 (8%), followed by PS (7%), SS (6.3%) and least in T-08 (2.2). Betaproteobacteria and Bacteroidetes are most abundant groups studied in the Kuytung 51 Glacier (Xiang et al., 2009) which is supported by previous information on the bacterial diversity in glaciers (Battin et al., 2001; Stibal et al., 2006; Liu et al., 2007; Liu et al., 2009). Bacteroidetes, were also the plentiful bacteria
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 328 Chapter 5 Mitogenomics Discussion isolated from five ice core samples of three glaciers (Puruogangri, Malan, and Dunde) in the Tibetan Plateau in China (Zhang et al., 2009). The abundance and presence of Bacteroidetes is possibly due to their ability to tolerate the oligotrophic habitats (Takeuchi and Koshima, 2004) and wide substrate range in low-nutrient media (Noble, 1990). Bacteroidetes can produce extracellular polymeric substances on surfaces and have extraordinary catabolic ability to utilize complex and more recalcitrant organic matter (Battin et al., 2001).
Firmicutes group was dominant in SS (4.7%), followed by PS (2%) and T-05 (2%) and least in T-08 (0.8%). Stibal et al. (2012) reported that Lower Wright Glacier subglacial bacterial composition was dominated by Proteobacteria, followed by Firmicutes. Firmicutes is an ecologically and industrially important group of microorganisms and these bacteria can be found in a great variety of habitats (https://micro.cornell.edu/research/epulopiscium/low-g-and-c-gram-positive-bacteria).
The other groups including acidobacteria (0.9%), and radioresistant Deinococcus- thermus (0.7%) were detected in Siachen sediment (SS) and very low level of these two groups detected in Passu sediment (PS). Genes belonging to Gammatimonadetes
(0.8%) were also found in SS only. Acidobacteria have been found to be prevalent in Arctic and Antarctic soils (Yergeau et al., 2012; Makhalanyane et al., 2013; Mannisto et al., 2013; Hultman et al., 2015), and they are well known for their ability to compete in oligotrophic environments (Yergeau et al., 2012). It was found that Heterolithotrophs and Autotrophs are the important bacterial members which inhabit the glaciers and which play an important role in the ecosystem of glaciers.
In our study detection and presence of many sequences related to genera such as Sphingomonas, Cryobacterium, and Stenotrophomonas Comamonadaceae/ Polaromonas (Betaproteobacteria) Flexibacteraceae (Bacteroidetes) Rhodoferax (Betaproteobacteria) and Acinetobacteria (Gammaproteobacteria) Brevundimonas, Flavobacterium, Hymenobacter, Bacillus and Streptomyces are supported by findings of many other scientists (Xiang et al., 2010, Zhang et al., 2010; Simon et al., 2009).
Glaciers of HKKH region are generally categorized as valley glaciers. One of the most important properties of valley glaciers, including HKKH (sampling site) is the presence of eroded soil blended with glaciers. The erosion was due to heavy rains in
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 329 Chapter 5 Mitogenomics Discussion summer and makes the glaciers nutrient rich. Ratio of microbial communities is almost similar to the microbial diversity of other glaciers in polar, alpine and other non-polar zones. The findings reported by Fought et al. (2004), Miteva et al., (2004) and Zhang et al., (2008) supports our observations, except that the prevalence of Proteobacteria in Tirich Mir samples (sediment and surface muddy ice) was much higher than others.
Viruses
The viruses are said to be an important players in frozen habitats of food web and other geochemical processes. They also play a role in Horizontal Gene Transfer which helps in the diversification of such habitats (Anesio and Bellas, 2011). Very few reports are available on the role of viruses in such environments (Winter et al., 2013; Chenard et al., 2015) with only very few of polar soil metaviromes (Zablock et al., 2012; Chauhan et al., 2014). The viruses of cold habitats are dominated by Mycobacterium phage (Zablock et al., 2012). The extent to which phages may influence metabolic processes in cold soil environments is still not known (Makhalanyane et al., 2016). In our study, Passu sediment, Siachen sediment and Tirich Mir sediment samples were found to contain sequences of viruses. According to Anesio and Bellas (2011), glacial habitats have high virus–bacterium ratios, the rarity of viral-associated contigs is unexpected. As the genetic information of viral genomes from cold habitats are very limited (Anesio and Bellas, 2011) and very little sequences are present in database, thus contributing to the residue of reads which could not be assigned to established taxa.
Eukaryotic Diversity
Members of domain Eukarya play an important role in ecology of glaciers. They are divided into two major groups on the basis of their mode of nutrition as Autotrophs and Heterotrophs. The autotrophic members belong to algal group, have the ability of photosynthesis and jointly act as primary producers along with photosynthetic bacteria and some plants. On the other hand, the heterotrophic organisms are of diverse types, from microscopic organisms to macroscopic. The major heterotrophic groups include the fungi and some other invertebrates possibly surviving in moraine particles. Fungi have the ability to degrade xenobiotic polymeric substrates
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(Rodriguez et al., 2013) and this ability makes these organisms important in community heterotrophy (Yergeau et al., 2012). Chlorophyta, Streptophyta, Ciliophora, and fungal groups were represented among the 18S rRNA gene sequences that were obtained by Zhang et al., (2009) and the most abundantly represented glacial eukaryote was Chlamydomonas.
In our study, Domain Eukaya was dominated by fungi. The most abundant group of this domain is Ascomycota which contain dimorphic fungi and this mechanism helps to live and thrive in such harsh environment. Ascomycota was the major group in samples including; PS (1%), SS (1.3%), T-05 (8%) and T-08 (1.1%) followed by basidiomycetes. Besides, the Passu sediment also contained some genes from plant and animal Kingdom. The taxonomic distribution of Tirich Mir sediment (T-05) and Siachen sediment samples constituted about 1.8% of the Eukaryota. The most abundant group in SS was fungi, and ascomycetes group was found in highest number. Traces of plant and animals genes were also detected in these two sample sites.
Archaeal Diversity
Archaea is also one of the most important members of cold environment, yet to fully explore culturably and metagenomically as well. In our study samples, the composition of archaeal presence was highest in Passu sediment with major group of Archaea observed was the unclassified sequences from Archaea and Thaumarchaeota group. Phyla Thaumarchaeota-Crenarchaeota were reported associated with increased soil age (Mateos-Rivera et al., 2016). Archaeal sequences were also observed in Siachen sediment and Tirich Mir samples; some were identical to the known groups of archaea, while some reads were similar to uncultured sequences. Whereas, Tirich Mir surface sample does not contain any archaeal sequences. In the present study, all samples of sediment which might have had anaerobic or microaerophilic environment once, therefore showed archaeal presence while the surface samples does not show any presence of archaea.
Different studies support our findings of low abundance of archaea in Arctic and Antarctic soils samples (Jang et al., 2011; Rao et al., 2011; Chauhan et al., 2014). As the number of archaea is less reported from such environments but still it is important
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 331 Chapter 5 Mitogenomics Discussion member with a variety of functions like methanogenesis (Mackelprang et al., 2011). Archaea are anaerobic in nature therefore the diversity increased with increase in depth due to high anaerobic condition (Alan et al., 2014). In both Antarctic and Arctic soils, Thaumarchoeota dominate, with a high abundance of Nitrososphaerales lineages (Tourna et al., 2011; Karaevskya et al., 2014; Magalhaes et al., 2014). Speculations are made that Thaumarchoeota may be important heterotrophs in soils, use the recalcitrant compound and convert into useful products of energy (Pester et al., 2011). The archaea also have a great impact on the climate change when the methane produced anaerobically released to environment (Makhalanyane et al., 2016).
Functional diversity
Total 32,930,329 sequence reads were obtained from Passu glaciers samples, 32,705,549 from Siachen sediment sample, 38,871,311 from Tirich Mir sediment and 37,464,355 sequences from Tirich Mir surface ice.
As all the samples belong to different locations having diverse geochemistry, ecology, physicochemical properties and these parameters are the driving forces to shape the diversity of an ecological niche. Each group of organisms have specific requirement and the availability of such necessities help for the growth and survival of specific group of organism.
Functional hits distribution of sample genomes by COG distribution revealed highest percentage of genes were found to be actively involved in the process of metabolism and almost equal percentage of genes were present for cellular processes and signaling and information storage and processing, among all the four metagenome samples. Sample PS, SS, T-05 and T-08 represent 46, 48, 48 and 43 percent of the sequences the metabolism category.
The sequences of all samples were used to BLAST against KEGG Orthology hits. The annotations showed that major portion of DNA reads were responsible for metabolism (60%). The major subgroups of metabolism are carbohydrate metabolism, energy, lipid, amino acid and many more others with important enzymes and metabolites. Other sequences found to have similarities with human diseases, cellular processes and organismal systems.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 332 Chapter 5 Mitogenomics Discussion
In contrast to the COG and KEGG classification schemes, there are over 20 top-level subsystem categories, showing a much better understanding and more highly resolved “fingerprint” for the metagenome. The subsystem hit represent the collection of roles which are present to form a single biosynthetic pathway.
The subsystem technologies of our study samples showed a wide variety of different functional groups required for metabolism, survival, cellular processes, signaling, production of different metabolites like antagonistic compounds, radio resistant compounds etc. The most abundant sequences reads were determined for carbohydrate metabolisms, amino acid and derivatives, cell wall and capsule formation. Besides, important metabolites regarding the low temperature, low nutrient and high radiation habitat were also detected which include antimicrobial compounds, capsule formation, spore forming ability, pigments and synthesis of polyunsaturated fatty acids (PUFA) etc.
In our study numerous genes were detected for the microbial metabolism, the processes that include metabolites like enzymes. Different metagenomic studies were carried out to study the extremozymes of cold environment include cellulases, lipases and esterases exploring their potential applications in biocatalysis, detergents and industrial processes (Berlemont et al., 2011; Lopez et al., 2014). The prospecting of new enzymes with potential of working in extreme environments is of great interest in biotechnology and industries. The metagenomic has the advantage of detection of gene responsible for enzymes without culturing step. Mirete et al., (2016) also reported that the functional metagenomic studies not only involve to discover the mechanisms used by the organisms for survival in extreme environments but also very helpful to find out new enzymes and new sources of enzymes already in use.
The genes responsible for antibiotic resistance are spread from one microorganism to another in specific crowded micro-environments where microorganisms facing antibiotic use persistently (Segawa et al., 2012). Some research reports suggested that antibiotic resistance found in natural environment which is not contaminated anthropogenic source. The natural resistance was determined in isolates from different glaciers in Asia, South America, Greenland and Africa, most interestingly isolates from Antarctica were free of antibiotic resistant. Our study samples also have a number of different antibiotic resistant genes. These genes are also of natural source
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 333 Chapter 5 Mitogenomics Discussion except Siachen sample where the impact of anthropogenic activities is high. In our opinion this resistance can be intrinsic or natural characteristic, because we have found and also reported by some scientists that bacteria in glaciers also produce numerous bioactive compounds having antifungal and antibacterial properties, the other organisms especially bacteria in their neighborhood develop resistance towards these metabolites and thus show resistance to antibiotics by similar mechanisms as they would have shown against the clinical isolates.
Distribution of functional gene by subsystem technologies showed genes for amino acids and their derivatives, membrane transport, carbohydrate synthesis and DNA metabolism were maximum in case of all 4 samples, followed by genes for cofactors, vitamins, prosthetic groups and pigments. Pigments play a very important role in the survival of glacier microorganisms in the presence of increase UV rays, light intensity at higher altitudes. Besides genes for dormancy and sporulation were also detected as they have role in helping the microbes to survive under harsh environmental conditions.
Biodiversity and functioning of ecosystem of a habitat is greatly influenced by the interactions between bacteria, archaea, microvertebrates, fungi and viruses. These interactions are directly linked to the climate change and community structure and function. The combinations of diversity, rate of change in composition of communities are needed for better understanding and to tackle the global climate and industrial issues as well as bioprospecting aspects.
Finaly from the metagenomic study of these selected glaciers are concluded that these harsh look condition are full of active life. Members of all 3 domains are found in adundant with viruses as well. The major group detected in all glacial samples was bacteria followed Eukarya and Archaea. Functionaly these organisms are very active and different genes were detected required for an active life. They also have a number of genes which help these organisms to survive there. Besides these gene a number of genes were detected which are responsible for the production of industrial important secondary metabolites.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 334 Chapter 5 References
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Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 343 Chapter 5 References
Zablocki, O., van Zyl, L., Adriaenssens, E.M., Rubagotti, E., Tuffin, M., Cary, S.C. and Cowan, D., 2014. High-level diversity of tailed Phages, eukaryote- associated viruses, and virophage-like elements in the metaviromes of Antarctic soils. Applied and Environmental Microbiology, 80(22), pp.6888-6897. Zhang, S., Yang, G., Wang, Y. and Hou, S., 2010. Abundance and community of snow bacteria from three glaciers in the Tibetan Plateau. Journal of Environmental Sciences, 22(9), pp.1418-1424. Zhang, X., Ma, X., Wang, N. and Yao, T., 2009b. New subgroup of Bacteroidetes and diverse microorganisms in Tibetan plateau glacial ice provide a biological record of environmental conditions. FEMS Microbiology Ecology, 67(1), pp.21- 29. Zhang, X.F., Yao, T.D., Tian, L.D., Xu, S.J. and An, L.Z., 2008. Phylogenetic and physiological diversity of bacteria isolated from Puruogangri ice core. Microbial Ecology, 55(3), pp.476-488 Zumsteg, A., Luster, J., Göransson, H., Smittenberg, R.H., Brunner, I., Bernasconi, S.M., Zeyer, J. and Frey, B., 2012. Bacterial, archaeal and fungal succession in the forefield of a receding glacier. Microbial Ecology, 63(3), pp.552-564.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 344 Conclusions
Conclusions
Bacterial Diversity
• All glaciers were found to be rich in microbial population, with highest CFU/ml or g in Siachen sediment followed by Tirich Mir, Passu and Batura glacier samples. • Viable count was highest in sediments followed by water and ice samples. • The culturable bacterial isolates belonged to four major phyla; Proteobacteria, Firmicutes, Actinobacteria and bacteroidetes. • The glacier with highest bacterial diversity was found to be Passu glacier (sediment sample) • The most abundant genera were Pseudomonas, Arthrobacter and Alcaligenes. • Most of the bacterial isolates were halotolerant and extreme halophilic in nature. • About 60% of the total isolates were eurypsychrophilic bacteria having broad temperature range for growth. • About 105 out of 229 isolates showed antimicrobial activity against both Gram positive and Gram negative bacteria and fungi. • Many isolates were able to produce enzymes like proteases, lipases, cellulases and DNAases
Fungal Diversity
• Glacier samples were also rich in fungal diversity. The richest glacier was Tirich Mir in terms of fungal diversity. • Total 134 fungal strains were isolated on the basis of colony morphology. • The most abundant group was Ascomycota and most abundant genera were Penicillium, Cladosporium and Alternaria. • A total of 16 fungal isolates (Batura 4, Passu 5, Tirich Mir 7) can possibly be new species as indicated by homology search in NCBI. • Fungal strains were salt tolerant in nature. • Many fungal strains showed both antifungal and antibacterial activity.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 345 Conclusions
• Fungal strains also produced a number of enzymes like proteases, lipases, amylases, DNAases and cellulases.
Metagenomic Study
• Metagenomic study revealed that these frozen habitats are very rich in terms of different life forms and contains representatives of all the 3 domains of life; Bacteria, Archaea and Eukarya and as well as viruses. • Both heterotrophic and autotrophic organisms were found in glacial sediment • Major group was domain Bacteria (approximately 97% of total biota), with major members as Proteobacteria (Alpha, Beta and Gammaproteobacteria), Actinobacteria, Firmicutes, CFB, etc. • The major autotrophic groups include photosynthetic and microalgae. • Functional metagenomics showed that these niches are metabolically very active habitats • The functional hits was dominated by metabolism in annotations, and subsystem hits found annotations for carbohydrate, protein, cell wall, stress responses, secondary metabolites and many more. • In each sample ~ 9% of the sequences were for unknown functions. • A further insight into the subsystem revealed that a respectable portion of genes were present for stress responses, secondary metabolites, pigment production, hormones and enzymes.
This study first reported the microbial diversity of the select glaciers in HKKH region Pakistan. These glaciers have rich ecology and members of all three domains and viruses were found. Bacterial and fungal isolates showed an excellent potential to produce metabolites of industrial and biotechnological use. Metagenomic results explained the richness of these habitats both in terms of microorganisms and their potential in biogeochemical processes and a source of novel metabolites.
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 346 Appendices
Fig A1: Location and map of the Batura glacier Karakoram Range Hunza Valley Pakistan
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 347 Appendices
Fig A2: Location and map of the Passu glacier Karakoram Range Hunza Valley Pakistan
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 348 Appendices
Fig A3: Location and map of the Tirich Mir glacier Hindu Kush Range Chitral KP, Pakistan
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 349 Appendices
Fig A4: Locations and map of Batura, Passu and Tirich Mir Glaciers Pakistan. Batura and Passu glaciers are much closer and cannot clearly differentiate in this map
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 350 Appendices
Appendix 1. Colony morphology and microscopic characteristics of fungal isolates on SDA Isol Sample Tempe Colony morphology Microscopic ate form rature Front Reverse characteristics (°C) HS1 Sedime 15 Cottony, initially Dark brown Hyphae hyaline to nt yellow to green center with pale yellow and then turned to sea saddle brown septate, scattered and green with dim edges erect conidiophores, gray edges and branched conidia HS2 Sedime 15 Cottony, initially Saddle brown Spores are hyaline, nt dry mucoid, sandy center and conidia vary in shape brown then turned khaki edges and size, asci to pale goldenrod cylindrical shape. with light yellow margins HS3 Ice 15 Mucoid, lemon Off-white to Round to ovoid chippon center yellow center shaped spores, with off-white and off-white branched or chain margins margins conidia and scattered HS4 Ice 15 Dry mucoid, deep Sandy brown Conidiophores burlywood center to brown hyaline, septate with off-white center and off- hyphae, ovoid shaped margins white margins conidia HS5 Ice 15 Velvety, initially Black center Branched, pale dark olive green with Off-white olivaceous brown with light yellow edges hyphae, conidia edges then turned ellipsoidal to limoni- to black to dark form, smooth-walled green with white or slightly verrucose, surface olivaceous brown HS6 Water 15 Velvety, initially Black center Subglobose to broadly dark olive green with Off-white ellipsoid with light yellow edges conidiophores, conidia edges then turned are less branched and to black to dark darker in nature green HS7 Water 15 Cottony, initially Off-white to Phialides straight or white then surface yellow center sinuous and globose to turned to green with dark subglobose green margins chlamydospores HS8 Water 15 Mucoid, lemon Off-white to Spores are round to chippon center yellow center ovoid shaped, with off-white and off-white branched or chain margins margins hyphae and scattered HS9 Water 15 Cottony, initially Saddle brown Spores are hyaline, dry mucoid, sandy center and conidia vary in shape brown then turned khaki edges and size, asci to pale goldenrod cylindrical shape. with light yellow
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 351 Appendices
margins LS1 Sedime 4 Cottony, initially Brown center Spores are hyaline, nt mucoid, brown and khaki conidia vary in shape then turned to edges and size, asci goldenrod with cylindrical shape. light yellow margins LS2 Sedime 4 Mucoid, lemon Off-white to Round to ovoid nt chippon center yellow center shaped spores, with off-white and off-white branched or chain margins margins conidia and scattered LS3 Sedime 4 Mucoid, light Off-white to Ellipsoid to cylindrical nt goldenrod yellow yellow center ascospores, hyphae center with off- and off-white bundantly septate, white margins margins branched, rich in oleaginous globules LS4 Ice 4 Cottony, deep Black to brown Conidia are spherical brown center with center and light to globose shaped, white margin brown margins septate hyphae and conidial heads are globose to ovoid LS5 Ice 4 Mucoid, pale Off-white to Ellipsoid shaped goldenrod center yellow center ascospores, hyphae with off-white and off-white septate, branched, rich edges margins in oleaginous globules LS6 Ice 4 Dry mucoid, deep Sandy brown Conidiophores burlywood center to brown hyaline, septate with off-white center and off- hyphae, ovoid shaped margins white margins conidia LS7 Water 4 Mucoid, salmon Off-white to Spores are globose to center and off- yellow center ovoid shape, no true or white margins and off-white hyphae pseudohyphae margins observed LS8 Water 4 Mucoid, dark Burlywood Hyaline and septate salmon center and center with off- hyphae, round to off-white edges white margins ovoid shaped spores and in scattered form
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mountain range 352 Appendices
Appendix 2. Diversity, Abundance and, Average and hits of the number of hits of the reads all four samples
Avg Avg Avg % Metagenome Source Domain Phylum Class Abundance align # hits eValue ident len
4642125 (SS) M5NR Bacteria Acidobacteria Acidobacteriia 37046 -6.54 79.73 30.91 6986
4642124 (PS) M5NR Bacteria Acidobacteria Acidobacteriia 19475 -6.43 78.77 30.93 4987
4642126 (T- M5NR Bacteria Acidobacteria Acidobacteriia 30235 -6.55 79.62 30.94 5877 05)
4642127 (T- M5NR Bacteria Acidobacteria Acidobacteriia 5909 -6.49 78.34 30.75 1477 08)
4642126 (T- M5NR Bacteria Acidobacteria Solibacteres 74237 -6.46 78.59 30.62 5524 05)
4642124 (PS) M5NR Bacteria Acidobacteria Solibacteres 59309 -6.78 80.42 30.76 6009
4642127 (T- M5NR Bacteria Acidobacteria Solibacteres 9348 -6.78 78.67 30.83 1461 08)
4642125 (SS) M5NR Bacteria Acidobacteria Solibacteres 83892 -6.53 78.92 30.64 6048
4642126 (T- unclassified (derived M5NR Bacteria Acidobacteria 35994 -6.52 79.64 30.74 3181 05) from Acidobacteria)
4642127 (T- unclassified (derived M5NR Bacteria Acidobacteria 3548 -6.27 77.62 30.85 879 08) from Acidobacteria)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 353 Appendices
unclassified (derived 4642124 (PS) M5NR Bacteria Acidobacteria 19987 -6.14 76.99 30.68 2629 from Acidobacteria)
unclassified (derived 4642125 (SS) M5NR Bacteria Acidobacteria 50396 -6.63 80.45 30.76 3892 from Acidobacteria)
4642124 (PS) M5NR Bacteria Actinobacteria Actinobacteria (class) 3611441 -6.93 81.14 31.13 305532
4642126 (T- M5NR Bacteria Actinobacteria Actinobacteria (class) 4309817 -6.92 81.43 30.99 392336 05)
4642125 (SS) M5NR Bacteria Actinobacteria Actinobacteria (class) 7921103 -7.25 83.24 31.12 522962
4642127 (T- M5NR Bacteria Actinobacteria Actinobacteria (class) 1496422 -7.01 81.65 31.11 200596 08)
4642124 (PS) M5NR Bacteria Aquificae Aquificae (class) 7850 -6.25 76.61 30.78 2893
4642127 (T- M5NR Bacteria Aquificae Aquificae (class) 1974 -6.03 77.23 30.59 683 08)
4642125 (SS) M5NR Bacteria Aquificae Aquificae (class) 14243 -6.13 75.89 30.86 3741
4642126 (T- M5NR Bacteria Aquificae Aquificae (class) 11596 -6.3 76.91 30.86 3541 05)
4642126 (T- M5NR Bacteria Bacteroidetes Bacteroidia 111354 -6.43 77.48 30.87 31580 05)
4642125 (SS) M5NR Bacteria Bacteroidetes Bacteroidia 89248 -6.4 78.12 30.63 29125
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 354 Appendices
4642124 (PS) M5NR Bacteria Bacteroidetes Bacteroidia 152237 -6.58 78.77 30.9 40785
4642127 (T- M5NR Bacteria Bacteroidetes Bacteroidia 33599 -6.52 78.21 30.79 10904 08)
4642126 (T- M5NR Bacteria Bacteroidetes Cytophagia 447296 -7.36 82.8 31.2 24922 05)
4642127 (T- M5NR Bacteria Bacteroidetes Cytophagia 78868 -7.92 86.58 31.32 12366 08)
4642125 (SS) M5NR Bacteria Bacteroidetes Cytophagia 190032 -7.24 82.31 31.61 19251
4642124 (PS) M5NR Bacteria Bacteroidetes Cytophagia 331654 -7.52 84.13 31.55 21319
4642124 (PS) M5NR Bacteria Bacteroidetes Flavobacteriia 224338 -7.09 81.13 31.06 34367
4642127 (T- M5NR Bacteria Bacteroidetes Flavobacteriia 228280 -7.5 83.41 31.11 28380 08)
4642126 (T- M5NR Bacteria Bacteroidetes Flavobacteriia 468650 -7.27 82.05 31.13 41180 05)
4642125 (SS) M5NR Bacteria Bacteroidetes Flavobacteriia 523772 -7.02 81.47 30.97 39019
4642125 (SS) M5NR Bacteria Bacteroidetes Sphingobacteriia 245254 -7.19 81.91 31.17 20197
4642126 (T- M5NR Bacteria Bacteroidetes Sphingobacteriia 401287 -7.06 81.55 31.22 21851 05)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 355 Appendices
4642127 (T- M5NR Bacteria Bacteroidetes Sphingobacteriia 61764 -7 80.76 30.96 11588 08)
4642124 (PS) M5NR Bacteria Bacteroidetes Sphingobacteriia 223195 -7.09 81.45 31.12 17593
4642126 (T- unclassified (derived M5NR Bacteria Bacteroidetes 38262 -6.67 79.33 30.92 5718 05) from Bacteroidetes)
4642127 (T- unclassified (derived M5NR Bacteria Bacteroidetes 8234 -6.61 78.04 30.97 2242 08) from Bacteroidetes)
unclassified (derived 4642124 (PS) M5NR Bacteria Bacteroidetes 25013 -6.96 80.1 30.74 4641 from Bacteroidetes)
unclassified (derived 4642125 (SS) M5NR Bacteria Bacteroidetes 35428 -6.69 79.04 30.98 5451 from Bacteroidetes)
4642124 (PS) M5NR Bacteria Chlamydiae Chlamydiia 5052 -6.68 80.78 30.52 1839
4642127 (T- M5NR Bacteria Chlamydiae Chlamydiia 1776 -7.45 82.84 31.38 549 08)
4642126 (T- M5NR Bacteria Chlamydiae Chlamydiia 10833 -7.03 81.84 30.87 3262 05)
4642125 (SS) M5NR Bacteria Chlamydiae Chlamydiia 8980 -6.74 79.99 30.94 2825
4642124 (PS) M5NR Bacteria Chlorobi Chlorobia 45980 -6.41 78.23 30.9 9004
4642125 (SS) M5NR Bacteria Chlorobi Chlorobia 40464 -6.39 77.79 30.77 9141
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 356 Appendices
4642127 (T- M5NR Bacteria Chlorobi Chlorobia 21025 -6.53 78.56 30.98 3570 08)
4642126 (T- M5NR Bacteria Chlorobi Chlorobia 53516 -6.33 77.65 30.82 9823 05)
4642126 (T- M5NR Bacteria Chloroflexi Anaerolineae 6684 -6.41 78.47 30.69 1366 05)
4642124 (PS) M5NR Bacteria Chloroflexi Anaerolineae 18369 -6.68 80.38 30.79 1906
4642127 (T- M5NR Bacteria Chloroflexi Anaerolineae 534 -6.39 77.28 30.63 171 08)
4642125 (SS) M5NR Bacteria Chloroflexi Anaerolineae 6473 -6.24 77.38 30.68 1256
4642127 (T- M5NR Bacteria Chloroflexi Chloroflexi (class) 11723 -6.49 78.12 30.81 2965 08)
4642124 (PS) M5NR Bacteria Chloroflexi Chloroflexi (class) 120195 -6.53 79.28 30.75 14666
4642126 (T- M5NR Bacteria Chloroflexi Chloroflexi (class) 85376 -6.37 78.26 30.72 13341 05)
4642125 (SS) M5NR Bacteria Chloroflexi Chloroflexi (class) 109105 -6.34 78.33 30.67 14458
4642127 (T- M5NR Bacteria Chloroflexi Dehalococcoidetes 920 -6.49 78.47 30.69 280 08)
4642124 (PS) M5NR Bacteria Chloroflexi Dehalococcoidetes 6630 -6.3 77.61 30.82 1549
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 357 Appendices
4642125 (SS) M5NR Bacteria Chloroflexi Dehalococcoidetes 10463 -6.25 77.54 30.74 1799
4642126 (T- M5NR Bacteria Chloroflexi Dehalococcoidetes 8147 -6.32 77.96 30.78 1605 05)
4642124 (PS) M5NR Bacteria Chloroflexi Ktedonobacteria 15798 -6.18 78.62 30.73 3305
4642126 (T- M5NR Bacteria Chloroflexi Ktedonobacteria 17914 -5.71 78.37 29.14 3801 05)
4642127 (T- M5NR Bacteria Chloroflexi Ktedonobacteria 2983 -6.15 76.53 30.43 848 08)
4642125 (SS) M5NR Bacteria Chloroflexi Ktedonobacteria 30453 -6.68 78.21 31.3 5675
4642124 (PS) M5NR Bacteria Chloroflexi Thermomicrobia (class) 18318 -6.28 77.61 30.83 3144
4642125 (SS) M5NR Bacteria Chloroflexi Thermomicrobia (class) 66223 -6.32 78.55 30.49 4563
4642126 (T- M5NR Bacteria Chloroflexi Thermomicrobia (class) 36030 -6.51 79.93 30.59 4073 05)
4642127 (T- M5NR Bacteria Chloroflexi Thermomicrobia (class) 2718 -6.36 77.5 30.87 904 08)
4642127 (T- unclassified (derived M5NR Bacteria Chloroflexi 5 -5.33 79.01 30 4 08) from Chloroflexi)
unclassified (derived 4642125 (SS) M5NR Bacteria Chloroflexi 288 -6.29 77.38 30.59 70 from Chloroflexi)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 358 Appendices
4642126 (T- unclassified (derived M5NR Bacteria Chloroflexi 343 -6.23 77.42 30.6 83 05) from Chloroflexi)
unclassified (derived 4642124 (PS) M5NR Bacteria Chloroflexi 312 -6.37 78.15 30.63 51 from Chloroflexi)
4642126 (T- M5NR Bacteria Chrysiogenetes Chrysiogenetes (class) 2333 -6.44 78.31 30.87 634 05)
4642124 (PS) M5NR Bacteria Chrysiogenetes Chrysiogenetes (class) 1706 -6.36 78.01 30.88 554
4642127 (T- M5NR Bacteria Chrysiogenetes Chrysiogenetes (class) 901 -6.42 77.83 31.06 201 08)
4642125 (SS) M5NR Bacteria Chrysiogenetes Chrysiogenetes (class) 2016 -6.61 79.36 30.91 635
4642125 (SS) M5NR Bacteria Cyanobacteria Gloeobacteria 15779 -6.2 77.66 30.6 1894
4642127 (T- M5NR Bacteria Cyanobacteria Gloeobacteria 6147 -6.72 78.92 31 797 08)
4642126 (T- M5NR Bacteria Cyanobacteria Gloeobacteria 16686 -6.27 77.82 30.63 1952 05)
4642124 (PS) M5NR Bacteria Cyanobacteria Gloeobacteria 23510 -6.63 79.26 30.87 2258
4642126 (T- unclassified (derived M5NR Bacteria Cyanobacteria 157119 -6.62 78.55 30.75 43467 05) from Cyanobacteria)
4642127 (T- unclassified (derived M5NR Bacteria Cyanobacteria 60766 -6.92 80.2 30.97 17328 08) from Cyanobacteria)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 359 Appendices
unclassified (derived 4642124 (PS) M5NR Bacteria Cyanobacteria 1226003 -7.17 81.77 31.2 87079 from Cyanobacteria)
unclassified (derived 4642125 (SS) M5NR Bacteria Cyanobacteria 140768 -6.42 77.28 31.06 39487 from Cyanobacteria)
4642125 (SS) M5NR Bacteria Deferribacteres Deferribacteres (class) 5987 -7.11 81.16 31.12 1696
4642127 (T- M5NR Bacteria Deferribacteres Deferribacteres (class) 1626 -6.76 79.8 31 421 08)
4642126 (T- M5NR Bacteria Deferribacteres Deferribacteres (class) 5548 -7 80.85 31.02 1608 05)
4642124 (PS) M5NR Bacteria Deferribacteres Deferribacteres (class) 4736 -6.84 79.84 31.02 1525
4642127 (T- M5NR Bacteria Deinococcus-Thermus Deinococci 23698 -6.39 78.83 30.87 6442 08)
4642124 (PS) M5NR Bacteria Deinococcus-Thermus Deinococci 224906 -6.51 79.03 30.83 18703
4642125 (SS) M5NR Bacteria Deinococcus-Thermus Deinococci 113066 -6.47 79.09 30.58 18140
4642126 (T- M5NR Bacteria Deinococcus-Thermus Deinococci 81873 -6.42 78.48 30.81 16125 05)
4642126 (T- M5NR Bacteria Dictyoglomi Dictyoglomia 2937 -6.06 75.6 30.68 836 05)
4642127 (T- M5NR Bacteria Dictyoglomi Dictyoglomia 458 -5.7 73.8 30.51 174 08)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 360 Appendices
4642124 (PS) M5NR Bacteria Dictyoglomi Dictyoglomia 2821 -5.99 75.33 30.68 885
4642125 (SS) M5NR Bacteria Dictyoglomi Dictyoglomia 3780 -6.07 75.66 30.76 969
4642124 (PS) M5NR Bacteria Elusimicrobia Elusimicrobia (class) 1000 -6.36 78.03 30.87 314
4642125 (SS) M5NR Bacteria Elusimicrobia Elusimicrobia (class) 1335 -6.2 77.15 30.62 361
4642126 (T- M5NR Bacteria Elusimicrobia Elusimicrobia (class) 1268 -6.36 78.16 30.66 366 05)
4642127 (T- M5NR Bacteria Elusimicrobia Elusimicrobia (class) 213 -6.74 78.84 30.29 76 08)
4642126 (T- unclassified (derived M5NR Bacteria Elusimicrobia 477 -6.61 79.59 31.4 137 05) from Elusimicrobia)
unclassified (derived 4642124 (PS) M5NR Bacteria Elusimicrobia 396 -6.09 76.32 31.42 147 from Elusimicrobia)
4642127 (T- unclassified (derived M5NR Bacteria Elusimicrobia 25 -5.95 76.18 30.86 17 08) from Elusimicrobia)
unclassified (derived 4642125 (SS) M5NR Bacteria Elusimicrobia 556 -6.29 77.78 30.71 146 from Elusimicrobia)
4642126 (T- M5NR Bacteria Fibrobacteres Fibrobacteria 1571 -6.4 76.21 30.89 590 05)
4642127 (T- M5NR Bacteria Fibrobacteres Fibrobacteria 569 -6.38 77.39 30.43 154 08)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 361 Appendices
4642124 (PS) M5NR Bacteria Fibrobacteres Fibrobacteria 1431 -6.01 80.98 27.5 544
4642125 (SS) M5NR Bacteria Fibrobacteres Fibrobacteria 1559 -6.36 77.83 30.62 594
4642125 (SS) M5NR Bacteria Firmicutes Bacilli 491461 -6.75 80.22 30.94 114555
4642126 (T- M5NR Bacteria Firmicutes Bacilli 150086 -6.33 77.84 30.78 58804 05)
4642127 (T- M5NR Bacteria Firmicutes Bacilli 101900 -6.89 80.67 30.97 33042 08)
4642124 (PS) M5NR Bacteria Firmicutes Bacilli 120052 -6.34 77.87 30.84 50874
4642125 (SS) M5NR Bacteria Firmicutes Clostridia 273060 -6.45 78.41 30.88 86667
4642127 (T- M5NR Bacteria Firmicutes Clostridia 41674 -6.32 77.37 30.84 13951 08)
4642124 (PS) M5NR Bacteria Firmicutes Clostridia 190004 -6.37 77.76 30.88 68893
4642126 (T- M5NR Bacteria Firmicutes Clostridia 169916 -6.19 76.97 30.81 55280 05)
4642125 (SS) M5NR Bacteria Firmicutes Erysipelotrichi 9598 -6.55 79.01 30.96 4974
4642124 (PS) M5NR Bacteria Firmicutes Erysipelotrichi 5172 -6.39 78.3 30.85 2975
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 362 Appendices
4642127 (T- M5NR Bacteria Firmicutes Erysipelotrichi 1364 -6.46 78.21 30.98 567 08)
4642126 (T- M5NR Bacteria Firmicutes Erysipelotrichi 4291 -6.2 76.61 30.96 2172 05)
4642124 (PS) M5NR Bacteria Firmicutes Negativicutes 11761 -6.41 78.39 30.94 5675
4642125 (SS) M5NR Bacteria Firmicutes Negativicutes 16080 -6.24 77.42 30.98 6870
4642127 (T- M5NR Bacteria Firmicutes Negativicutes 3114 -5.99 76.9 30.8 1097 08)
4642126 (T- M5NR Bacteria Firmicutes Negativicutes 11556 -6.32 77.39 31.03 5367 05)
4642127 (T- M5NR Bacteria Fusobacteria Fusobacteriia 3247 -6.14 76.31 30.82 1088 08)
4642125 (SS) M5NR Bacteria Fusobacteria Fusobacteriia 10777 -6.41 78.11 31.01 4726
4642126 (T- M5NR Bacteria Fusobacteria Fusobacteriia 7003 -6.3 77.67 30.81 3430 05)
4642124 (PS) M5NR Bacteria Fusobacteria Fusobacteriia 8068 -6.2 77.32 30.88 3772
Gemmatimonadetes 4642125 (SS) M5NR Bacteria Gemmatimonadetes 125419 -6.67 80.41 30.79 3806 (class)
4642127 (T- Gemmatimonadetes M5NR Bacteria Gemmatimonadetes 3353 -7.04 81.6 31.54 1198 08) (class)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 363 Appendices
4642126 (T- Gemmatimonadetes M5NR Bacteria Gemmatimonadetes 133059 -6.78 80.73 30.83 4104 05) (class)
Gemmatimonadetes 4642124 (PS) M5NR Bacteria Gemmatimonadetes 55687 -6.73 79.44 31.3 3580 (class)
4642126 (T- unclassified (derived M5NR Bacteria Lentisphaerae 3949 -6.31 77.15 30.59 1596 05) from Lentisphaerae)
unclassified (derived 4642124 (PS) M5NR Bacteria Lentisphaerae 3779 -6.36 77.41 30.52 1517 from Lentisphaerae)
4642127 (T- unclassified (derived M5NR Bacteria Lentisphaerae 931 -6.87 80 31.13 370 08) from Lentisphaerae)
unclassified (derived 4642125 (SS) M5NR Bacteria Lentisphaerae 3624 -6.32 76.97 30.6 1566 from Lentisphaerae)
4642127 (T- M5NR Bacteria Nitrospirae Nitrospira (class) 3514 -6.83 79.8 30.78 744 08)
4642126 (T- M5NR Bacteria Nitrospirae Nitrospira (class) 35728 -6.49 79.55 30.8 4749 05)
4642124 (PS) M5NR Bacteria Nitrospirae Nitrospira (class) 8746 -6.38 78.73 30.86 2440
4642125 (SS) M5NR Bacteria Nitrospirae Nitrospira (class) 18412 -6.52 78.51 30.93 4170
unclassified (derived 4642124 (PS) M5NR Bacteria Nitrospirae 348 -6.32 75.13 30.36 23 from Nitrospirae)
4642126 (T- M5NR Bacteria Nitrospirae unclassified (derived 140 -5.84 75.43 30.93 31
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 364 Appendices
05) from Nitrospirae)
4642127 (T- unclassified (derived M5NR Bacteria Nitrospirae 2 -7 84.32 29.5 2 08) from Nitrospirae)
unclassified (derived 4642125 (SS) M5NR Bacteria Nitrospirae 71 -5.64 75.6 30.2 29 from Nitrospirae)
4642124 (PS) M5NR Bacteria Planctomycetes Planctomycetia 124860 -6.41 78.56 30.92 20166
4642127 (T- M5NR Bacteria Planctomycetes Planctomycetia 15880 -6.07 76.55 30.51 3880 08)
4642125 (SS) M5NR Bacteria Planctomycetes Planctomycetia 160700 -6.75 80.11 30.89 24566
4642126 (T- M5NR Bacteria Planctomycetes Planctomycetia 151715 -6.79 79.96 30.78 23600 05)
unclassified (derived 4642124 (PS) M5NR Bacteria Poribacteria 863 -6.8 77.95 30.85 299 from Poribacteria)
4642127 (T- unclassified (derived M5NR Bacteria Poribacteria 213 -6.55 78.18 31.5 77 08) from Poribacteria)
4642126 (T- unclassified (derived M5NR Bacteria Poribacteria 3667 -6.64 78.23 30.98 634 05) from Poribacteria)
unclassified (derived 4642125 (SS) M5NR Bacteria Poribacteria 1926 -6.62 78.23 30.81 511 from Poribacteria)
4642124 (PS) M5NR Bacteria Proteobacteria Alphaproteobacteria 2180889 -7.35 83.32 31.2 291712
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 365 Appendices
4642126 (T- M5NR Bacteria Proteobacteria Alphaproteobacteria 4278779 -7.2 82.48 31.21 396149 05)
4642125 (SS) M5NR Bacteria Proteobacteria Alphaproteobacteria 3155605 -7.32 83.38 31.16 382282
4642127 (T- M5NR Bacteria Proteobacteria Alphaproteobacteria 1652046 -7.1 81.87 31.11 223634 08)
4642127 (T- M5NR Bacteria Proteobacteria Betaproteobacteria 8434622 -7.68 84.42 31.45 189990 08)
4642124 (PS) M5NR Bacteria Proteobacteria Betaproteobacteria 3648813 -7.58 84.14 31.32 226900
4642125 (SS) M5NR Bacteria Proteobacteria Betaproteobacteria 1368346 -7.19 82.49 31.01 223956
4642126 (T- M5NR Bacteria Proteobacteria Betaproteobacteria 6202049 -7.35 83.24 31.14 266278 05)
4642125 (SS) M5NR Bacteria Proteobacteria Deltaproteobacteria 433979 -6.58 79.59 30.92 83522
4642126 (T- M5NR Bacteria Proteobacteria Deltaproteobacteria 386676 -6.5 79.1 30.89 73373 05)
4642124 (PS) M5NR Bacteria Proteobacteria Deltaproteobacteria 402048 -6.71 79.84 30.95 79550
4642127 (T- M5NR Bacteria Proteobacteria Deltaproteobacteria 102798 -6.55 79.06 30.88 21503 08)
4642124 (PS) M5NR Bacteria Proteobacteria Epsilonproteobacteria 18464 -6.54 78.76 30.89 7402
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 366 Appendices
4642125 (SS) M5NR Bacteria Proteobacteria Epsilonproteobacteria 21135 -6.42 77.79 30.92 8752
4642127 (T- M5NR Bacteria Proteobacteria Epsilonproteobacteria 15748 -6.65 79.43 30.65 3015 08)
4642126 (T- M5NR Bacteria Proteobacteria Epsilonproteobacteria 21266 -6.61 79.01 30.76 8559 05)
4642124 (PS) M5NR Bacteria Proteobacteria Gammaproteobacteria 650767 -6.86 80.25 31.04 188630
4642125 (SS) M5NR Bacteria Proteobacteria Gammaproteobacteria 1305311 -7.17 82.34 31.08 260127
4642126 (T- M5NR Bacteria Proteobacteria Gammaproteobacteria 1390851 -6.89 80.77 31.02 266478 05)
4642127 (T- M5NR Bacteria Proteobacteria Gammaproteobacteria 8069317 -7.5 83.73 31.28 135709 08)
4642127 (T- M5NR Bacteria Proteobacteria Zetaproteobacteria 2312 -6.74 79.85 31.02 302 08)
4642126 (T- M5NR Bacteria Proteobacteria Zetaproteobacteria 3756 -6.65 79.76 30.92 950 05)
4642125 (SS) M5NR Bacteria Proteobacteria Zetaproteobacteria 2505 -6.03 77.27 30.9 837
4642124 (PS) M5NR Bacteria Proteobacteria Zetaproteobacteria 2537 -6.14 74.76 30.96 746
4642127 (T- unclassified (derived M5NR Bacteria Proteobacteria 8178 -6.55 79.32 30.45 848 08) from Proteobacteria)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 367 Appendices
4642126 (T- unclassified (derived M5NR Bacteria Proteobacteria 11780 -6.58 79.19 30.71 1720 05) from Proteobacteria)
unclassified (derived 4642124 (PS) M5NR Bacteria Proteobacteria 7511 -6.79 79.77 30.92 1386 from Proteobacteria)
unclassified (derived 4642125 (SS) M5NR Bacteria Proteobacteria 7892 -6.97 81.64 30.48 1504 from Proteobacteria)
4642124 (PS) M5NR Bacteria Spirochaetes Spirochaetia 18148 -6.33 77.68 30.77 5562
4642127 (T- M5NR Bacteria Spirochaetes Spirochaetia 6051 -6.44 79.79 30.83 1596 08)
4642125 (SS) M5NR Bacteria Spirochaetes Spirochaetia 20933 -6.4 77.73 31 6085
4642126 (T- M5NR Bacteria Spirochaetes Spirochaetia 20088 -6.54 78.73 30.94 5838 05)
4642127 (T- M5NR Bacteria Synergistetes Synergistia 1946 -6.23 76.62 30.94 630 08)
4642126 (T- M5NR Bacteria Synergistetes Synergistia 7522 -6.12 76.58 30.78 3005 05)
4642125 (SS) M5NR Bacteria Synergistetes Synergistia 9610 -6.21 77.2 30.82 3359
4642124 (PS) M5NR Bacteria Synergistetes Synergistia 7510 -6.12 76.43 30.82 2870
4642126 (T- unclassified (derived M5NR Bacteria Synergistetes 312 -6.09 76.69 30.77 161 05) from Synergistetes)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 368 Appendices
unclassified (derived 4642124 (PS) M5NR Bacteria Synergistetes 302 -6.11 77 30.8 157 from Synergistetes)
4642127 (T- unclassified (derived M5NR Bacteria Synergistetes 124 -6.62 78.53 30.18 38 08) from Synergistetes)
unclassified (derived 4642125 (SS) M5NR Bacteria Synergistetes 422 -6.31 77.72 30.86 199 from Synergistetes)
4642126 (T- M5NR Bacteria Tenericutes Mollicutes 3354 -6.44 78.13 30.81 1787 05)
4642124 (PS) M5NR Bacteria Tenericutes Mollicutes 3118 -6.34 78.22 30.78 1736
4642125 (SS) M5NR Bacteria Tenericutes Mollicutes 4693 -6.4 78.19 30.85 2241
4642127 (T- M5NR Bacteria Tenericutes Mollicutes 1356 -5.98 76.73 30.55 504 08)
4642125 (SS) M5NR Bacteria Thermotogae Thermotogae (class) 16041 -6.08 75.81 30.79 4273
4642126 (T- M5NR Bacteria Thermotogae Thermotogae (class) 11934 -6.04 75.76 30.91 3621 05)
4642124 (PS) M5NR Bacteria Thermotogae Thermotogae (class) 11176 -6.02 75.99 30.55 3704
4642127 (T- M5NR Bacteria Thermotogae Thermotogae (class) 2148 -6.01 75.88 30.66 840 08)
4642127 (T- M5NR Bacteria Verrucomicrobia Opitutae 7270 -6.79 80.26 30.88 1908 08)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 369 Appendices
4642124 (PS) M5NR Bacteria Verrucomicrobia Opitutae 26084 -6.98 82.02 31.05 5224
4642125 (SS) M5NR Bacteria Verrucomicrobia Opitutae 28214 -6.95 80.36 30.9 4965
4642126 (T- M5NR Bacteria Verrucomicrobia Opitutae 38498 -6.97 82.11 30.87 5931 05)
4642126 (T- M5NR Bacteria Verrucomicrobia Spartobacteria 28586 -6.6 79.18 31.06 4198 05)
4642127 (T- M5NR Bacteria Verrucomicrobia Spartobacteria 4521 -6.57 79.32 30.8 1360 08)
4642124 (PS) M5NR Bacteria Verrucomicrobia Spartobacteria 14081 -6.73 79.87 30.8 3410
4642125 (SS) M5NR Bacteria Verrucomicrobia Spartobacteria 43074 -6.77 80.83 30.83 4758
4642125 (SS) M5NR Bacteria Verrucomicrobia Verrucomicrobiae 43354 -6.41 78.05 30.65 7995
4642126 (T- M5NR Bacteria Verrucomicrobia Verrucomicrobiae 58628 -6.58 78.64 30.97 8871 05)
4642124 (PS) M5NR Bacteria Verrucomicrobia Verrucomicrobiae 28267 -6.44 80.14 30.54 7235
4642127 (T- M5NR Bacteria Verrucomicrobia Verrucomicrobiae 16607 -6.8 80.29 31.38 3609 08)
unclassified (derived 4642125 (SS) M5NR Bacteria Verrucomicrobia 6617 -6.37 78.22 30.64 1063 from Verrucomicrobia)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 370 Appendices
unclassified (derived 4642124 (PS) M5NR Bacteria Verrucomicrobia 2246 -6.68 80.68 30.84 724 from Verrucomicrobia)
4642127 (T- unclassified (derived M5NR Bacteria Verrucomicrobia 1284 -6.61 78.6 30.92 316 08) from Verrucomicrobia)
4642126 (T- unclassified (derived M5NR Bacteria Verrucomicrobia 4649 -6.66 80.23 30.65 983 05) from Verrucomicrobia)
4642126 (T- unclassified (derived unclassified (derived M5NR Bacteria 67349 -6.84 80.18 30.92 10141 05) from Bacteria) from Bacteria)
unclassified (derived unclassified (derived 4642125 (SS) M5NR Bacteria 91858 -6.86 80.53 30.88 10480 from Bacteria) from Bacteria)
4642127 (T- unclassified (derived unclassified (derived M5NR Bacteria 31091 -6.93 80.36 30.98 3156 08) from Bacteria) from Bacteria)
Culture Dependent and Metagenomic study of Microbial Diversity of Glaciers in HKKH (Hindu Kush, Karakoram and Himalaya) mount ain range 371