DOCTOR of PHILOSOPHY in BIOCHEMISTRY

Biochemical Profiling of Medicinal Plants and Bioinformatics of Bacterial Polyketide Synthases in Drug Discovery Perspective

by Ghulam Mustafa M.Phil. (UAF)

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

BIOCHEMISTRY

DEPARTMENT OF BIOCHEMISTRY

FACULTY OF SCIENCES UNIVERSITY OF AGRICULTURE, FAISALABAD PAKISTAN 2016

DECLARATION

I hereby declare that the contents of the thesis, “Biochemical profiling of medicinal plants and bioinformatics of bacterial polyketide synthases in drug discovery perspective” are product of my own research and no part has been copied from any published source (except the references, standard mathematical or genetic models/equations/formulae/protocols etc). I further declare that this work has not been submitted for award of any diploma/degree. The University may take action if the information provided is found inaccurate at any stage.

Ghulam Mustafa 2005-ag-247

The Controller of Examinations, University of Agriculture, Faisalabad.

“We the Supervisory Committee, certify that the contents and form of thesis submitted by Ghulam Mustafa, Regd. No. 2005-ag-247, have been found satisfactory and recommend that it be processed for evaluation, by the External Examiner (s) for the award of degree”.

SUPERVISORY COMMITTEE

1. CHAIRMAN (Prof. Amer Jamil)

2. MEMBER (Dr. Muhammad Shahid)

3. MEMBER (Dr. Nisar Ahmed)

ACKNOWLEDGMENT

Words are bound and knowledge is limited to praise Allah, the omnipotent, the beneficent and merciful. Peace and blessings be upon Holy Prophet Muhammad (SAW), the everlasting source of guidance and knowledge for humanity. With genuine humanity, I acknowledge your aid, God. Please bless this work with your acceptance.

I have a pleasure to ensure my sincere gratitude and deepest thanks to Prof. Amer Jamil, whose stimulating supervision, guidance and support made this work possible. I heartily thank him very much for his valuable help and for his kindness.

I express my gratitude to Dr. Paul R. Jensen, who guided me to the fascinating world of actinomycetes during my research work in University of California, San Diego, CA, USA. His support, encouragement, inspiring attitude and enthusiasm were impressive. The support, help and company of the whole group are appreciated, especially Dr. Sibtain Ahmed, Dr. Nadine Ziemert and Dr. Greg Rouse for their help in research work.

I wish to thank Dr. Muhammad Shahid, Department of Biochemistry and Dr. Nisar Ahmad, Centre of Agricultural Biochemistry and Biotechnology (CABB) for their guidance, encouragement and help throughout my PhD studies.

I am also thankful to my genius friends and fellows Zahid Mushtaq, Muhammad Naeem, Sumaira Sharif, Dr. Asia Atta, Dr. Mazhar Abbas and my MBL fellows for their love providing amenities and friendship.

Many thanks are due to my dearest family for giving me so much joy and happiness outside lab. Special thanks to my brothers Ilyas Ali, Atif Sajjad and Waqar Ali for their prayers, guidance and best wishes at each and every fraction of my life.

I owe immense feelings of love and thanks for my affectionate mother and father, as their prayers are always behind my each success and my loving sisters, bhabhies and nephews for their continuous encouragement, untiring efforts and their patience while I did this work.

Ghulam Mustafa

CONTENTS 1. Introduction 1.1. Natural products …………………………………………………………… 1 1.2. Role of plants in drug discovery …………………………………………… 2 1.3. Biochemical profiling and related techniques ……………………………. 5 1.4. Importance of microbial secondary metabolites …………………………... 7 1.5. Objectives of the study …………………………………………………... 8

2. Review of Literature 2.1. History of medicinal plants …………………………………………….… 9 2.1.1. Bioactive compounds from medicinal plants ………………….. 11 2.2. Herbal medicines today …………………………………………………... 12 2.3. Herbal medicine in Pakistan ……………………………………………… 13 2.4. Medicinal plants from Northern areas of Pakistan ………………………. 15 2.5. Medicinal plants from Cholistan desert of Pakistan……………………… 18 2.5.1. Soil and climate of Cholistan desert ……………………………. 19 2.5.2. Vegetation of Cholistan desert …………………………………… 20 2.5.3. Use of medicinal plants by local inhabitants …………………… 21 2.6. Secondary plant metabolites with medicinal properties …………………. 27 2.6.1. Carbohydrates and related compounds …………………………… 27 2.6.2. Alkaloids ………………………………………………………… 27 2.6.3. Phenolics ………………………………………………………… 28 2.6.4. Terpenoids ………………………………………………………. 29 2.6.5. Glycosides ………………………………………………………. 30 2.7. Bioactive compounds and defense mechanisms in plants ……………… 30 2.7.1. Antimicrobial peptides (AMPs) ………………………………... 32 2.7.2. Anticancerous compounds ……………………………………... 32 2.8. Natural products from bacteria …………………………………………… 33 2.8.1. Polyketides ……………………………………………………… 34 2.8.2. Biosynthesis of polyketides ………………………………….…. 35 2.8.3. Types of Polyketide synthases (PKSs) …………………………. 38 2.9. The Natural Product Domain Seeker (NaPDoS) ………………………... 44 2.9.1. NaPDoS working ……………………………………………..… 44 2.9.2. Domain classification 45

3. Materials and Methods Section A 3.1. Study areas ………………………………………………………………... 48 3.2. Collection and identiﬁcation of plant species ………………………….… 48 3.3. Chemicals …………………………………………………………………. 49 3.4. Preparation of plant extracts ……………………………………………… 49 3.4.1. LC/MS analyses …………………………………………………. 49 3.4.2. Antibacterial activity ……………………………………………. 53 3.4.3. Cytotoxicity Bioassay …………………………………………… 53

Section B 3.5. Comparison of phylogenetic softwares ………………………………...… 55 3.6. Working with bacterial type II PKS sequence data ……………………… 55 3.6.1. Retrieval/Collection of Type II PKS sequences (KSα) ………… 55 3.6.2. Creating alignment of KSα domains of type II PKS …………… 55 3.6.3. Editing the alignment ………………………………………….. 57 3.6.4. Model tests ……………………………………………………… 57 3.6.5. Generating a reference phylogenetic tree for NaPDoS …………… 57 3.6.5.1. Neighbor-Joining (NJ) ………………………………… 58 3.6.5.2. Maximum parsimony (MP) ………………………...… 58 3.6.5.3. Maximum likelihood (ML) …………………………… 58 3.6.5.4. Minimum evolution (ME) ……………………………. 58 3.7. Study of structural similarities …………………………………………… 59 3.8. Gene cluster analyses of type II PKS …………………………………….. 59

4. Results and Discussion Part A 4.1. Biochemical profiling of selected medicinal plants ……………………... 60 4.1.1. Flavonoids ………………………………………………………. 69 4.1.2. Sesquiterpene lactones …………………………………………. 69 4.1.3. Isoflavones ……………………………………………………… 70 4.1.4. Phenolics ………………………………………………………… 70 4.1.5. Non-alkaloids ……………………………………………………. 71 4.2. Antibacterial study of selected plants ……………………………………. 71 4.3. Cytotoxic study of selected medicinal plants ……………………………. 73 Part B 4.4. Comparison between PHYLIP and MEGA ……………………………… 77 4.4.1. Advantages of PHYLIP ………………………………………… 77 4.4.2. Disadvantages of PHYLIP ……………………………………… 77 4.5. Up-gradation of Natural Product Domain Seeker (NaPDoS) …………… 78 4.5.1. Retrieval/Collection of Type II PKS sequences (KSα) ………... 79 4.5.2. Creating and editing the alignment ……………………………. 81 4.6. Generation and analysis of NaPDoS reference PKS tree …………………… 83 4.6.1. Angucyline ……………………………………………………… 86 4.6.2. Naphthoquinone ……………………………………………….. 89 4.6.3. Anthracycline …………………………………………………... 91 4.6.4. Naphthacenequinone and tetracyclic quinone ………………… 93 4.6.5. Pentangular polyphenols and Aureolic acids ………………….. 95 4.6.6. Tetracyclines ……………………………………………………. 97 4.6.7. Resistomycin-like ………………………………………………. 99 4.6.8. Spore pigment …………………………………………………... 100 4.7. The Natural Product Domain Seeker (NaPDoS 2.0) …………………….. 101 Summary ……………………………………………..…………………. . 106 Literature Cited ……………………………………….………………… 108

LIST OF TABLES Table No. Title Page No. 2.1 Medicinal plants which laid the foundation of drug discovery 10 2.2 Major organizations of Pakistan involved in medicinal plants 15 research 2.3 Some medicinal plants from Northern areas with their traditional 17 uses 2.4 Some medicinal plants from Cholistan desert with their traditional 23 uses 2.5 Ethnopharmacological applications of some medicinal plants 24 alongwith their phytochemicals 2.6 Some bacterial polyketides with their activities 36 2.7 Survey of PKSs types 38 3.1 Indigenous medicinal plants used in the study with their reported 50 medicinal uses 3.2 Methods with different models used to generate phylogenetic trees 58 4.1 List of compounds (by Library matching) present in each medicinal 67 plant with their medicinal use 4.2 Antibacterial and cytotoxic activities of indigenous medicinal 74 plants samples 4.3 Compounds with their classes selected to generate a reference 80 phylogenetic tree of KSα domain of type II PKS 4.4 Maximum Likelihood fits of substitution models 86

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LIST OF FIGURES

Figure No. Title Page No. 2.1 Floristic regions of Pakistan 14 2.2 Map of Northern areas of Pakistan (internet source) 16 2.3 Map of Cholistan desert of Pakistan 19 2.4 Structure of reserpine (an alkaloid) 28 2.5 Basic structure of flavonoids 29 2.6 Structure of bisabolol 29 2.7 Structure of aloesin (a glycoside) 30 2.8 Representative examples of some polyketide drugs 37 2.9 Fatty acids and polyketide biosyntheses 39 2.10 Biosynthesis of erythromycin A 40 2.11 Iterative PKS involved in the biosynthesis of lovastatin (fungal 41 iterative type I PKS) 2.12 Schematic view of actinorhodin KSα and KSβ enzyme (type II 42 PKS) 2.13 Biosynthesis of doxorubicin (bacterial type II PKS) 43 2.14 Biosynthesis of naringenin chalcone (plant type III PKS, chalcone 43 synthase) 2.15 NaPDoS bioinformatic pipeline 46 2.16 Phylogeny based KS domain classification 47 3.1 Selected medicinal plants used in this study 52 3.2 Phylogenetic workflow and softwares used in this study 56 4.1 LC-MS Chromatogram of methanolic extract of Dryopteris 61 ramosa 4.2 LC-MS Chromatogram of methanolic extract of Bergenia ciliata 61 4.3 LC-MS Chromatogram of methanolic extract of Quercus baloot 62 4.4 LC-MS Chromatogram of methanolic extract of Isodon rugosus 62 4.5 LC-MS Chromatogram of methanolic extract of Fragaria 63 bucharia 4.6 LC-MS Chromatogram of methanolic extract of Valeriana 63 jatamansi 4.7 LC-MS Chromatogram of methanolic extract of Trillium 64 govanianum 4.8 LC-MS Chromatogram of methanolic extract of Solanum 64 surattense 4.9 LC-MS Chromatogram of methanolic extract of Calligonum 65 polygonoides 4.10 LC-MS Chromatogram of methanolic extract of Fagonia indica 65 4.11 LC-MS Chromatogram of methanolic extract of Suaeda fruticosa 66 4.12 LC-MS Chromatogram of methanolic extract of Heliotropium 66 strigosum 4.13 Antibacterial activities (zones of inhibition) of selected medicinal 72 plants against E. coli 4.14 Phylogenetic tree of fungal actins 77 iv

4.15 Screen shot of the NaPDoS webpage showing working steps of 79 tool 4.16 Multiple sequence alignment of the selected amino acid sequences 83 of KSα domain of type II PKS using MUSCLE in MEGA 5.05 4.17 Molecular phylogenetic analysis for KSα subunits of bacterial type 85 II polyketide synthases 4.18 Phylogenetic and organization of gene clusters of angucyclines 87 4.19 Mauve alignment of biosynthetic gene clusters of angucycline 88 group of polyketides 4.20 Phylogenetic and organization of gene clusters of 89 naphthoquinones and pentangular polyphenoles I 4.21 Mauve alignment of biosynthetic gene clusters of napthoquinone 90 group of polyketides 4.22 Phylogenetic and organization of gene clusters of anthracyclines, 92 naphthoquinones, pentangular polyphenoles II, aureolic acid, tetracyclic quinones and anthracycline II 4.23 Mauve alignment of biosynthetic gene clusters of anthracycline 93 group of polyketides 4.24 Mauve alignment of biosynthetic gene clusters of 94 naphthacenequinone group of polyketides 4.25 Mauve alignment of biosynthetic gene clusters of pentangular 96 polyphenols group of polyketides 4.26 Phylogenetic and organization of gene clusters gilvocarcin-like, 98 tetracyclines and pluramycin 4.27 Mauve alignment of biosynthetic gene clusters of tetracycline 99 group of polyketides 4.28 Phylogenetic and organization of gene clusters of spore pigments 100 and resistomycin-like 4.29 NaPDoS working strategy 102

LIST OF ABBREVIATIONS

BCE Before the Common Era LC/MS Liquid chromatography mass spectrometry 1H NMR Proton nuclear magnetic resonance GC Gas chromatography ESI Electrospray ionization APCI Atmospheric Pressure Chemical Ionization TOF Time of Flight ND Newcastle disease NCEs New chemical entities WHO World Health Organization PR Pathogenesis-related HR Hypersensitive response INA 2,6-dichloroisonicotinic acid SA Salicylic acid BTH Benzo (1,2,3) thiadiazole-7-carbothioic S-methyl ester BABA DL-β-amino-n-butyric acid (BABA) AMP Antimicrobial peptide DMSO Dimethyl sulfoxide FAS Fatty acid synthase PKS Polyketide synthase KS Ketosynthase NaPDoS Natural Product Domain Seeker ACP Acyl carrier protein KR Ketoreductase DH Dehydratase ER Enoyl reductase AT Acyl transferase NRPS Nonribosomal peptide synthetases MT Methyltransferase CLF Chain length factor vi

ARO Aromatase CYC Cyclase MCoA Malonyl Co-enzyme A CDS Coding sequences HMM Hidden Markov Model BLAST Basic Local Alignment Search Tool NCBI National Center for Biotechnology Information DoBISCUIT Database Of BIoSynthesis clusters CUrated and InTegrated MUSCLE MUltiple Sequence Comparison by Log- Expectation MAFFT Multiple Alignment using Fast Fourier Transform ML Maximum likelihood NJ Neighbor-Joining MP Maximum parsimony ME Minimum evolution NSA Not Significantly Active BIC Bayesian Information Criterion antiSMASH antibiotics and Secondary Metabolite Analysis Shell BIQ Benzoisochromanequinone

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Biochemical profiling of medicinal plants and bioinformatics of bacterial polyketide synthases in drug discovery perspective ABSTRACT The present study was planned to conduct biochemical profiling of twelve indigenously selected medicinal plants of Cholistan desert and Northern areas of Pakistan to be used as potential lead constituents in the drug discovery process. Qualitative phytochemical analysis of these plants confirmed the presence of various important secondary metabolites viz isoflavones, sesquiterpene lactones, phenolics, flavonoids and nonalkaloids. Methanolic extracts of Suaeda fruticosa and Solanum surattense also showed significant inhibition against E. coli. Against HCT-116 colon carcinoma, Isodon rugosus exhibited the highest

activity with IC50 = 5.68 μM while Trillium govanianum and Dryopteris ramosa were found

to exhibit in vitro cancer cell cytotoxicity with an IC50 of 8.864 μM and 11.57 μM respectively and indicating that the active constituents from these plants may be of great value as a target for cancer treatment. The occurrence of various bioactive compounds confirmed the studied plants against various diseases as local communities of Swat valley and Cholistan desert still have a strong faith on herbal medicines for their basic healthcare issues. Isolation of individual phytochemical constituents reported here from each medicinal plant may proceed to find some novel natural drugs. A reference phylogenetic tree for KSα domain of type II PKS was generated in this study with more phylogenetic groups. The reference phylogenetic tree will be used to upgrade NaPDoS that serves as a basis for the classification of unknown polyketide antibiotic biosynthesis genes.

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CHAPTER # 1 INTRODUCTION

1.1. Natural products Complex molecular problems are being studied by a new way offered by metabolomics which is predominantly applicable for the research of natural products. In a system (e.g. cell, tissue or organism) metabolomics is the study of global metabolite profiles under a given set of conditions (Ryan and Robards, 2006). Metabolites are synthesized in organisms as a result of interaction between the genome of a system and its environment. They form a part of the regulatory system in an integrated manner and are not just the end product of the gene expression. The use of plants with medicinal properties and the origin of natural products research in ethnoveterinary and ethnopharmacology have been practicing throughout human history. In many cases, using techniques of modern science the isolation, identification and determination of the pharmacological mode of action of these naturally produced active agents have been made. A vast structural diversity and array of pharmacological activities are displayed by the secondary metabolites synthesized by many microorganisms, fungi and medicinal plants. Today, from these three related classes of compounds a variety of natural products are being obtained having clinical values as antiparasitic agents, immunosuppressants, antifungals, antibiotics and anticancer drugs (Newman and Cragg, 2007). From holistic to the reductionist a range of approaches has been covered by the modern natural products research and new ways are offered to the natural product chemists to discover and validate bioactive compounds through metabolomics. In the fields of cancer and antibiotics the plants natural products have been most efficacious in terms of modern pharmaceutics and therefore, it is not astonishing that much research has been focused on whole cells of human or microbes in this area. This has led to identify many extracts or compounds as bioactive but with little explanation of their pharmacological mode of action because this is sometimes extremely difficult and time consuming (Oberlies and Kroll, 2004). It has been widely recognized that for the benefit of human health the innate activities of natural products can be exploited (Baker et al., 2007) and currently there are many pharmaceuticals examples which have been derived from natural products are being

Chapter # 1 Introduction

employed to battle human diseases (Qureshi et al., 2011). Moreover, the natural products continue as the biggest source of new drug leads although the technological developments have been made within pharmaceutical discovery (Newman and Cragg, 2007). Humans have relied on nature throughout their ages to cater for their basic needs including medicines to cure a wide spectrum of diseases and in particular, plants have formed the basis for sophisticated systems of traditional medicines. Dating from around 2600 BCE, approximately 1000 substances derived from different plants substances in Mesopotamia have been documented with the earliest records (Cragg and Newman, 2013). The structurally diverse metabolites of microorganisms and medicinal plants have been a main source for pigments, flavors, dyes, medicines and even poisons since the beginning of human civilization and for therapeutic agents and pesticides many of the presently known lead compounds are natural products or their derivatives. 1.2. Role of plants in drug discovery Medicinal plants have been used as a source of medicine in all cultures since times immemorial (Malik et al., 2005). Initially plants were used by the people to meet their nutritional requirements. The natural flora became a very useful source for health improvement and to cure many diseases across various human communities and a variety of plants species are offered which are still in use in many parts of the world such as Asia (Duraipandiyan et al., 2006), South America (Bolzani et al., 2012) and Africa (Khalid et al., 2012) for remedies against several diseases. Even though World Health Organization reported that the primary health care system for the 60% population of the world is represented by the traditional medicines yet a great number of plant species with potential biological activities were unexplored (Li and Vederas, 2009). The effectiveness of traditional medicines is now a putative fact because of their better compatibility with human body, better cultural acceptability in all over the world and lesser side effects (Verma and Singh, 2008). In various human cultures around the world more than 35,000 plant species are being used for their medicine purposes (Lewington, 1993) and for primary health care nearly 80% of the world populations rely on these traditional medicines which include the use of plant extracts most of the time (Sandhya et al., 2006). Ethnomedicinal studies play a vital role to discover new drugs from indigenous medicinal plants and green pharmaceuticals are getting popularity and extraordinary importance 2

Chapter # 1 Introduction

(Yaseen et al., 2015) because vast chances for new drug discoveries are provided by the unrivaled availability of chemical diversity and natural products either as pure compounds or as homogenous plant extracts (Jigna and Sumitra, 2007). A decade ago the synthetic drugs because of unanticipated side effects were approved as safe and effective and had to be recalled and relabeled. The herbal medicines on the other hand, have no such adverse effects and because of combinations of medicinal constituents coupled with minerals and vitamins have benefits over synthetic ones (Hussain et al., 2007). In current scenario, the attention of scientists has been diverted towards ethnomedinices due to the revival of knowledge in customary health practices throughout the world. Therefore, in recent years the demand for herbal medicines and several natural products from a variety of plant species is consistently increasing. A number of modern drugs have been discovered since the history of ethnobotany paying a distinct importance to the documentation of traditional information of medicinal plants (Gilani and Atta-ur-Rahman, 2005). From medicinal plants 78% of new chemical constituents being natural or natural product-derived molecules are being used as a promising alternative treatment for infectious diseases (Lokhande et al., 2007). At present, in modern pharmacopeia about 25% drugs and also a great number of synthetic analogs prepared on proto-type compounds which have been derived from plants are included (Mahmood et al., 2013a). Plants have an immense importance in the field of medicines because they have been utilized in medicines for the treatment of so many diseases for thousands of years (Samuelsson, 2004). Beginning with morphine which was isolated from opium in the early 19th century, now active compounds are also isolated from medicinal plants (Kinghorn, 2001; Samuelsson, 2004). Earlier, when the role of medicinal plants in drugs was discovered then a number of drugs were isolated such as codeine, cocaine, quinine, digitoxin and morphine. Some of these drugs are still in our use (Butler, 2004; Samuelsson, 2004). The extracts of several medicinal plants are very effective against microbial as well as parasitic infections (Haider et al., 2001). For example, several groups of antifungal proteins like glucanase, chitinase and proteins which are of low molecular weight and non-enzymatic in nature are present in the seeds of many medicinal plants and these proteins are being used for the protection of a developing embryo from many infections (Wu et al., 2003).

Chapter # 1 Introduction

Microorganisms are causing diseases in a huge number of plant hosts and are responsible for big losses in economical crops and also preventing valuable food distribution worldwide (Donini et al., 2005; Ferre et al., 2006). The plants which are continuously exposed to a large number of pathogens are being attacked in both chemical and mechanical ways by these pathogens (Mee Do et al., 2004). It has also been found that against these pathogen attacks, plants show both inducible and constitutive defenses (Hwang, 2001). During last 10-15 years, the fungal pathogens have gained resistance against presently engaged antifungal drugs and the adverse reactions or toxicity of the anti-infective. Due to this reason the importance of medicinal plants has been increased because they possess antimicrobial and antifungal activities (Lucca and Walsh, 2000). Drug discovery from medicinal plants for the treatment of different cancers has played a vital role. Since 1990, a 22% increase in mortality has been observed globally due to different forms of cancers including the four most recurrent cancers being breast, lung, stomach, and colorectal and four most deadly cancers being stomach, lung, colorectal and liver (Parkin, 2001). Over the last century, the secondary metabolites of plants and their derivatives have acquired most new clinical applications as they are being applied towards combating cancers (Newman et al., 2000, 2003). A great number of bioactive compounds comprising anticancerous activity have also been extracted and purified. Between 1940 and 2002, from all the available anticancer drugs, there were 40% natural products or their derivatives with another 8% were considered as a mimic of natural products (Newman et al., 2003). Importance has been given to ethnobotany field in Pakistan (Mahmood et al., 2013b) and a few studies have been done recently (Ullah et al., 2013; Saqib et al., 2014) but the treasure of medicinal plants is being vanished with the passage of time and measures are still needed to save it (Saqib et al., 2014). Pakistan is very rich in botanical wealth and has variety of medicinal and aromatic plants because of its exceptional phytogeography with varied climatic and edaphic factors such as soil conditions and multiple ecological regions. Out of 5700 about 400–600 species of medicinal plants are estimated to be found in Pakistan and only a small percentage of which have been biochemically investigated (Ahmad et al., 2007). In the early 1950s, for their basic healthcare needs about 84% population of Pakistan was relying on traditional medicines (Mahmood et al., 2011a) but now due to modernization and urbanization the practice is limited only in the remote areas (Ibrar et al., 2007). Most

Chapter # 1 Introduction

medicinal plants from Pakistan are confined to the mountainous areas and then desert areas. A total of 1572 genera and 5521 species are identified in Pakistan having medicinal values for many diseases (Ali, 2008). To enlist the applications of these indigenous medicinal plants a very few attempts have been made (Ahmed, 2007) and the information is incomplete as very few common plants are listed. 1.3. Biochemical profiling and related techniques In an organism the presence of complete complement of small molecules is called metabolome (Hall, 2006). Various terms such as metabolomics, metabonomics, metabolic fingerprinting and metabolic profiling have been defined throughout the years. The variations in metabolite fluxes are revealed by metabolomics and therefore it is the decisive level of post-genomic analysis. Minor changes within gene expression is responsible to control these metabolite fluxes and transciptomics and/ or proteomic analysis are the methods to measure these changes while the analyses reveal post-translational control over the activity of enzyme involved. The high-throughput qualitative screening of a tissue or an organism with an analysis of sample comparison and discrimination as a main objective is called metabolite fingerprinting (Hall, 2006). The biochemical status of an organism is revealed by the measurements of intracellular metabolites which would be qualitative or quantitative. These measurements in turn can be used to assess and monitor the functions of different genes (Fiehn et al., 2000a). Different approaches are used to detect and investigate metabolome. For metabolic fingerprinting, liquid chromatography–mass spectrometry (LC-MS) and proton nuclear magnetic resonance (1H NMR) are frequently used techniques. In various fields of plant research, LC-MS as a technique for fingerprinting was applied such as plant biochemistry (Kim and Park, 2009), food chemistry (Pongsuwan et al., 2008), chemotaxonomy (Urbain et al., 2009) and for establishing a control over quality of medicinal plants (Tianniam et al., 2008). Over the past 50 years, spectroscopic techniques coupled with some good extraction methods like chromatography have contributed natural product chemistry to a phenomenal success. Gas chromatography (GC) and liquid chromatography coupled to mass spectrometry (GC- and LC-MS) are the most suited equipment for fast and comprehensive analysis of ultracomplex metabolite samples (Weckwerth, 2008). Using LC the separation of the thousands of molecules present in biofluids can reduce ion suppression (Matuszewski et al., 1998; Gustavsson et al., 2001) by decreasing the number of competing 5

Chapter # 1 Introduction

analytes entering the mass spectrometer ion source at a time. This results in a selective approach which allows quantification and structural information, where sensitivities in the pg/mL range can be achieved readily (Plumb et al., 2004). LC/MS technique has replaced some of the specialized methods which have been practicing in traditional clinical laboratories (Hommes, 1991) that used immunological, fluorometric, and biological techniques (Niwa, 1995). Manufacturers’ software is usually used to detect component peaks located in mass chromatograms and integration of selected ion currents is used to quantify the detected components relative to one or more internal standards. Then these integrated values are added in a table of peaks against each sample chromatogram. The systems of mass spectrometry are usually designed for “target compound analysis” where preselected peaks or components can be identified using patterns of their mass spectra or qualifier ions and retention data of chromatography such as retention index or retention time. High sensitivity and selectivity are tha main advantages of LC/MS that allow quantitative analysis of secondary metabolites in complex biological matrices at very low concentrations (Halket et al., 2005).

Followed by mass spectrometer (MS), LC has been used often prior to Electrospray Ionization (ESI) or less often atmospheric pressure chemical ionization (APCI). In electrospray ionization (ESI) a small needle is used to spray sample in an appropriate solvent at atmospheric pressure. A high voltage is applied to the needle which results in the production of small charged droplets followed by a quick solvent evaporation. These charged droplets are swept into the MS where the mass and intensity of these ions are measured by time of flight (TOF) analyzer (Gaskell, 1997). The quantification may be achieved through LC-MS by using chemical standards through either response or external calibration or by the ratios of peak areas (Gross, 2004). The column plays a very important role in the levels of resolution of peaks in LC-MS. The chemistry and size of LC column influence the levels of peaks resolution directly and the sensitivity levels are controlled by column and the technique used for MS. LC column generally, do not show resolving power necessary for the separation of complex biological mixtures (Tolstikov and Fiehn, 2002).

In spite of being an agricultural country and having different ecological regions, the medicinal plants of Pakistan have not been explored for their secondary metabolites which are responsible for treating different diseases. Although, huge importance of different 6

Chapter # 1 Introduction

extracts of medicinal plants from Pakistan have been reported for their different activities such as antimicrobial, anti-cancerouse, antiviral and antioxidant but complete biochemical profiling of these medicinal plants is lacking. LC-MS and GC-MS techniques have been applied in the field of drug discovery from medicinal plants but in Pakistan its success rate is very low in the subject of biochemical profiling. These techniques have been found very efficient as compared to traditional methods. 1.4. Importance of microbial secondary metabolites For the development of new medicines the microbial secondary metabolites offer great potential and they belong to a wide variety of chemical classes as many of them possess cholesterol-lowering, anti-tumor and antibiotic properties (Newman and Cragg, 2007). The exciting new sources of pharmacologically active natural products are constituted by the recently discovered marine environment and symbiont microorganisms (Olano et al., 2009), and the observed novel structures in all these sources allowed scientists to gain new perception into the active compounds for their structural and functional relationships. Considering that the primary source of therapeutic agents are natural products (Baker et al., 2007; Newman and Cragg, 2007), prior to chemical analysis the sequence analysis of bacterial genes provides opportunities to identify strains having the greatest genetic potential for yielding novel secondary metabolites, thus increaseing the efficiency and rate with which new drug leads can be discovered. Over the last two decades, natural product research has been declined by pharmaceutical companies, which is in part a result of increased rediscovery rates came across with traditional screening methodologies (Zerikly and Challis, 2009; Winter et al., 2011). However, it has been recognized with beginning of genomic era that a substantial proportion of the metabolic gene repertoire is expressed at very low levels only or under standard cultivation conditions is inactive (Winter et al., 2011). This insight has prompted the development of increasingly sophisticated genetic, bioinformatics and analytical tools which provide exciting new approaches for the discovery of natural products (Helfrich et al., 2014). In silico screening of already sequenced genomes is an integral step of this process for secondary metabolite biosynthetic gene clusters which is followed by gene analysis biosynthetic product prediction (Zerikly and Challis, 2009). Experiments can be designed on the basis of this information for targeted discovery or activation of a pathway (Winter et al., 2011). In this way to interpret the biosynthetic potential of microorganisms is 7

Chapter # 1 Introduction

now also possible which was previously considered unproductive or inaccessible by the scientific community (Letzel et al., 2013). To address ecological questions related to secondary metabolism and to identify environments having the greatest secondary metabolite potential, metagenomic or community analyses can be used. In addition, it is also critical to capitalize on these opportunities and to handle the massive influx of bacterial sequence data generated through next generated sequencing technologies that new bioinformatics tools should be developed. 1.5. Objectives of the study This project was conceived as a first step towards isolation of methanol extracts from indigenously selected medicinal plants of Pakistan from Swat and Cholistan areas to perform biochemical profiling, antibacterial and anticancerous activities and bioinformatics analysis. To study relationships among different polyketide synthases (PKS) of Type-II involved in antibiotics synthesis from bacteria, their phylogenetic and gene cluster analyses are necessary.

The aims of the study were:

1. Biochemical profiling of twelve indigenous medicinal plants to provide clues for active secondary compounds 2. Antibacterial and anticancerous activities of methanol extracts from these plants 3. Gene cluster and phylogenetic analyses of bacterial KSα domain of type-II polyketide synthase involved in polyketides synthesis 4. Upgradation of NaPDoS with better resolution of type II PKS and to find more phylogenetic groups

CHAPTER # 2 REVIEW OF LITERATURE

Natural products are the chemical compounds found in nature that usually has a pharmacological or biological activity for use in pharmaceutical drug discovery and drug design. Drugs of natural origin have been classified as original natural products, products derived semi-synthetically from natural products, or synthetic products based on natural product models. Collectively, plants produce a remarkably diverse array of over 100,000 low-molecular-mass natural products, also known as secondary metabolites. Secondary metabolites are distinct from the components of intermediary (primary) metabolism in that they are generally nonessential for the basic metabolic processes of the plant. Many secondary metabolites have been isolated and characterized from a variety of natural sources, such as bacteria, fungi, and plants. They are of high interest and importance because they often exhibit a broad spectrum of biological activities. Their remarkable properties can be attributed to their structural complexity and diversity. Each biosynthetic enzyme catalyzes a reaction corresponding to its structure, providing an important compound upon completion of the biosynthetic pathway (Crawford et al., 2008). 2.1. History of medicinal plants Botanical medicine or phytomedicine, also called herbal medicine is the use of plants’ seeds, roots, berries, leaves, flowers or bark for healthcare and they have been used since the prehistoric times by the people worldwide to treat, control and manage a variety of diseases (Philipeon, 2001; Kong et al., 2003). Today, the infectious diseases have become worldwide a leading cause of death, therefore, their study has become a global concern (Westh et al., 2004). The emergence of multidrug-resistance in the pathogens is threatening the clinical efficiency of many existing antibiotics (Bandow et al., 2003). It is a matter of fact that a number of infectious diseases have been treated with herbal medicines throughout the history of mankind. Due to incomparable availability of the chemical diversity, the plant extracts either as standardized natural products or as pure compounds have been providing unlimited prospects for new drugs. It is an urgent and continuous need that new antimicrobial compounds should be discovered having novel mechanisms of action and diverse chemical structures for re-emerging and new infectious diseases (Rojas et al., 2003). Therefore, the attention of a number of researchers towards folk medicines is increasing continuously and

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they are trying to develop better drugs with antimicrobial activities (Benkeblia, 2004). A continuous increase in the failure of antibiotic resistance and chemotherapeutics exhibited by the pathogenic microbial infectious agents has enhanced the importance of medicinal plants and they have been screening out for their potential antimicrobial activity (Colombo and Bosisio, 1996; Iwu et al., 1999). Scientists began to isolate, purify and identify active constituents (principles) from medicinal plant extracts during the late nineteenth century and these efforts led them to find some of the vital drugs from medicinal plants which are still broadly used in the field of modern medicine (Gupta et al, 2005). Table 2.1. Medicinal plants which laid the foundation of drug discovery Drug Plant Activity Morphine Papaver somniferum powerful pain reliever and narcortic Quinine Cinchona sp. anti-malarial Taxol Taxus brevifollis Anticancerous Vincristine Catharanthus rosesus Anticancerous Serpentine Rauwolfia serpentia hypertension Source: Gupta et al., 2005; Gurib-Fakin, 2006 Other than the biologically active natural products derived from medicinal plants stated above, a great number of natural products derived from medicinal plants have also served as “lead compounds” to design, synthesize and develop novel drug compounds (Lesney, 2004). In this perspective, to prepare so called “semi-synthetic drugs” some natural products derived from plants have been modified marginally to make them more effective or less toxic (Kong et al., 2003). In 1953 aspirin was developed as an example to such type of tactic with the help of structural modification of salicylic acid that was observed as an active constituent in many medicinal plants known for having pain-relieving effects (Lesney, 2004). Guanidine- type of alkaloid, galegine in G. officinalis has blood glucose lowering property and because the alkaloid was found to be very toxic for human use therefore, a number of structural analogs of this alkaloid were made and tested clinically. These efforts resulted in the development and marketing of metformin which is an effective antidiabetic drug (Gupta et al., 2005).

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2.1.1. Bioactive compounds from medicinal plants The extracts of several medicinal plants are very effective against microbial as well as parasitic infections (Haider et al., 2001). For example, several groups of antifungal proteins like glucanase, chitinase and proteins which are of low molecular weight and non-enzymatic in nature are present in the seeds of many medicinal plants and these proteins are being used for the protection of a developing embryo from many infections (Wu et al., 2003). Shoemaker et al. (2005) has reported that there are over 400,000 species of plants on earth which have a huge reservoir of bioactive compounds, but only a small percentage of these have been examined in the research studies. When the bioactive compounds from traditional medicinal plants were investigated through screening programs, it resulted that these compounds possessed a considerable number of therapeutic properties. As a consequence a number of antitumoral drugs (Pezzuto, 1997) and antifungal agents (Rai and Mares, 2003) are available for clinical uses and have been derived from plants. In another study (Newman et al., 2003), it has also been reported that plants are an important and continuous source of anticancer agents. During last 10-15 years, the fungal pathogens have gained resistance against presently engaged antifungal drugs and the adverse reactions or toxicity of the anti- infective. Due to this reason the importance of medicinal plants has been increased because they possess antimicrobial and antifungal activities (Lucca and Walsh, 2000). Several epidemiological studies have shown that certain dietary elements play an important role in the prevention as well as in the etiology of different types of human cancers. The people who use plant-derived foods in great amounts such as vegetables, fruits and soybeans have less chances of cancer (Steinmetz and Potter 1991; Block et al., 1992). Although documentation was limited but it was observed experimentally that the preparations of certain plants may cure many diseases (Minja, 1994). Stem parts of Euphorbia candelabrum plant has been used against Newcastle Disease (ND) in poultry while the leaves of Iboza multiflora in combination with Capsicum annuum fruits have been used to cure ND as well (Minja, 1994). Mtambo et al. (1999) reported that in a local preparation in Northern Tanzania consisting of three plants, namely Capsicum frutescens, Citrus limon and Opuntia vulgaris possess a therapeutic efficiency against ND in commercial chickens. In parasites and pathogenic microbes, the development of multi-drug resistance and for systemic mycoses the non-availability of safe antifungal drugs has forced the researchers to look for new

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antimicrobial substances from some other sources, including plants. The medicinal plants which have been used traditionally produce a wide range of compounds with known therapeutic values (Bruneton, 1995). For the production of new antimicrobial drugs, those substances are considered the most which have little toxicity to host cells and can inhibit pathogens. The antimicrobial properties of medicinal plants from South Asia have been increasingly reported (Ahmad et al., 1998; Ahmad and Beg, 2001). In the local traditional systems of medicines, most of these medicinal plants have been used to cure different ailments including infectious diseases (Bruneton, 1995). For instance, Terminalia arjuna bark has been extensively used for a variety of purposes and particularly, the bark has been effectively used in cardiovascular therapy (Vaidya, 1994). Similarly, Andrographis lineate has been used for the treatment of snake bites (Vlietinck et al., 1995). 2.2. Herbal medicines today Various methods have been used to obtain compounds for drug discovery including isolation and purification of active compounds from medicinal plants and other natural sources, combinatorial chemistry, synthetic chemistry and bioinformatics approaches (e.g. molecular modeling) (Lombardino and Lowe, 2004). Although the pharmaceutical companies and funding organizations are getting interested towards combinatorial chemistry, molecular modeling and other synthetic chemistry techniques but natural products and particularly medicinal plants remain an important source of new drugs, new chemical entities (NCEs) and new drug leads (Butler, 2004). Mostly the plant medicines have been used in their crude forms before nineteenth century and administered as infusions (herbal teas), decoctions (boiled extracts of bark and root), tinctures (alcoholic extracts) and syrups (Griggs, 1981). Plants have also been applied externally as herbal washes and ointments (essential oils, poultices and balms) (Gurib-Fakin, 2006). Researchers in developing countries who work on medicinal plants often experience a comprehensive exercise for the learning of names, uses and preparations of native plants (Okigbo and Ajalie, 2006), and in a number of marketplaces of villages of such countries the medicinal plants are being sold along with vegetables and other goods. The World Health Organization (WHO) has also recognized that in developing countries the agenda for effective health can never be accomplished by western medicine alone therefore, it should be supplemented by other medicines which also include traditional herbal medicines of these

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countries (WHO, 2002). It has also urged and advised accordingly to utilize the resources of their medicinal plants and other systems of traditional medicines to accomplish primary healthcare goal. It is reported for developed countries that the patients of chronic diseases are turning towards herbal treatments as alternatives to modern synthetic drugs (Bader et al., 2015). In developed countries this interest in the use of herbal medicines is believed to be motivated by several factors which include: i. The effectiveness of herbal medicines: Medicinal plants are believed to be effective, gentle and most of the time specific in their function to organs or systems of human body, and the belief that herbal medicines can be used to treat certain diseases where conventional medicine fails (Iwu et al., 1999). ii. Side effects of synthetic drugs: Although synthetic or chemical drugs as compared to herbal medicines can have greater or quicker effects but they possess many adverse effects and risks. Herbal medicines are believed to be devoid of these adverse effects because millions of people around the world have been using herbal medicines against many diseases for thousands of years (Haq, 2004). iii. Synthetic drugs are highly costly: Herbal medicines are generally less expensive as compared to synthetic ones. Medicinal plants are continuously contributing to modern prescription drugs considerably by providing principal constituents which can be used to synthesize new drugs. From medicinal plants the search and use of drugs and dietary supplements have been hastened in the recent past. Biochemists, microbiologists, botanists, pharmacologists and chemists of natural products around the world are engaged to investigate medicinal plants for geting more and more phytochemicals and lead compounds which could be developed to treat different diseases. 2.3. Herbal medicine in Pakistan In developed countries although the direct use of medicinal plant extracts continued to decrease in the late nineteenth and early twentieth centuries but in many parts of the world the medicinal plants are still playing a very important role in healthcare systems (Vandavasi et al., 2015). According to World Health Organization (WHO, 2001) for primary healthcare needs, 60% of world’s population is dependant on traditional medicines and 80% population of developing countries is depending almost completely on traditional plants to get herbal

Chapter # 2 Review of Literature

medicines (Zhang and Moller, 2000). To the present day, the long tradition of herbal medicine continues in China, India, Pakistan and many other African and South American countries (Tariq et al., 2015; Zhang and Gilbert, 2015). Pakistan is very rich in botanical wealth and diversity of plants resources because it has different climatic and edaphic factors. Only a small percentage of plants have been investigated biochemically (Ahmad et al., 2007) and now an extraordinary importance and popularity is being received by green pharmaceuticals (Shinwari et al., 2015). Pakistan has four phytogeographical regions (Fig 2.1). Although the Saharo-Sindian region is the biggest area but the diversity of plant species confined to this area is lowest for any phytogeographical region (Ali and Qaiser, 1986).

Fig 2.1. Floristic regions of Pakistan (Source: Shinwari, 2010) In Pakistan, the major research activities on medicinal plants are on the level of documentation and the research works are being conducted mostly in universities as ethnobotanical listing of resources. There are a number of research institutes in Pakistan which are involved in survey to various kinds of analytical studies. In Table 2.2, a list of some known organizations is given which are involved in medicinal plants research. The 14

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knowledge of local communities of the country about traditional uses of medicinal plants occurring in their areas are centuries old which has been transferred from generation to generation. These indigenous plants are used for the treatment of almost any kind of disease including headache, stomachic, cut and wound (Bhardwaj and Gakhar, 2005). For the extraction of various types of active constituents, some of the important plants are commercially harvested. Table 2.2. Major organizations of Pakistan involved in medicinal plants research Name of Department Organization Interest Area Initiated since Dept. of Botany; Pharmacy; Peshawar University Documentation; analytical 1950’s Chemistry and Pak. Forest Inst work ICCS, HEJ Inst.; Botany Dept. Karachi University Chemical analysis 1960’s Hamdard Laboratories Hamdard, Karachi Herbal Medicine 1960’s Dept. of Botany and Baluchistan Univ., Quetta Documentation and 1970’s Biochemistry Analysis Qarshi Research Int. Qarshi Industries (Pvt) Ltd. Herbal Medicine; Bot. 1980’s Garden Dept. Plant Sciences and Quaid-i-Azam University Ethnobotanical studies 1980’s Chemistry and Chemical analysis Department of Biological and Agha Khan University, Karachi Pharmacognocy 1990’s Biomedical Sciences National Agric. Res. Center Pak. Agric. Res. Council, Cultivation and 1990’s Islamabad Documentation Dept. of Botany and Chemistry Kohat University of Sci. and Documentation; analytical 2004 Tech. work Dept. of Biochemistry University of Agriculture, Analytical work and 2009 Faisalabad molecular studies 2.4. Medicinal plants from Northern areas of Pakistan The northern most tracts of Pakistan cover an area of 72,486 sq. km, border the Indian- administered Jammu and Kashmir to the east, Central Asia and Afghanistan through the Wakhan Corridor to the west, Chinese province of Xinjiang to the north and Pakistan- administered Azad Jammu and Kashmir to the south. The Northern areas are divided into six districts. Gilgit region has four districts which include Astore, Ghizer, Diamer and Gilgit. Baltistan region has two districts which include Ghangche and Skardu (Fig 2.2). Being a multidisciplinary, ethnobotany has not been given much importance in Northern areas of

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Pakistan although they have ample scope in this field. However, recently these studies have started to gain momentum (Khan and Khatoon, 2008).

Fig 2.2. Map of Northern areas of Pakistan (internet source)

A great treasure of medicinal plants is present in northern areas of Pakistan. Leporatti and Lattanzi (1994) studied 27 medicinal plants ethenobotanically in Makran and discussed their traditional medicinal uses. Goodman and Ghafoor (1992) conducted ethenobotanical study in Balochistan province. It is the region where a heterogeneous cultural group known as Baloch lives. They collected information about 114 plant species used by nomads and village dwellers. Shinwari (2010) focused on information regarding traditional uses of plants of Kaghan valley. Dastagir (2001) reported the medicinal plants of Mai Dhani Hill, Muzaffarabad (AK). Bukhari (1996) reported that as many as 69 plant species are used as crude drugs by the local people and folk lore for treating various diseases in National Park Machayara Muzaffarabad (AK). Khan (1996) reported phytosociological study in Babusar valley and recorded five plant communities in Babusar valley, district Diamer. He also described the vegetation type, range management and medicinal plants of the area. Rasool

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(1998) studied the medicinal plants conservation status of Northern areas and recorded 60 medicinal plants from different locations of Northern areas. Gorsi and Shahzad (2002) reported the medicinal uses of plants by the local community in Dhir Kot, district Bagh (AK). Local people collect medicinal plants for use as home remedies at large. Information about the collection, quantities and uses of the plants are badly needed to be communicated.

Table 2.3. Some medicinal plants from Northern areas with their traditional uses

S. # Plant Local name Parts used Local use/ effective against Amaranthus viridis Shoots and 1 Chalwai Cough and asthma L. leaves Coriandrum sativum 2 Dhanial Fruit Stomachache L. 3 Foeniculum vulgare Kaga Velanay Fruit Dysuria and as laxative Antispasmodic 4 Artimisia vulgaris L. Tarkha Young shoots and stomachache Aundice and 5 Cichorium intybus L. Han Root fever Leaves and 6 Taxaxacum officinale Ziarr Gulay Disorders of kidney and liver roots Rephorlogical complaints and 7 Berbiris lycium Kwaray Root jaundice. Capesella bursa Leaves and 8 Bambesa Diarrahea pastoris L. stem 9 Nasturtium officinale Talmira Young shoots Constipation and stomachache 10 Sarcococa saligna Ladanrr Herb Muscular pains and rheumatism Shoots and Wounds healing and anodyne 11 Cannabis sative L. Bhang leaves (Pain relieving agent) Vibernum Ghaz meva 12 Fruit Stomach disorders grandiflorum (Asos) Leaves and 13 Silene vulgaris Bashka Stomachache and as emollient shoots 14 Stellaria media Oulalai Whole plant As purgative Cuscuta reflexa 15 Niladaria Whole plant Diabetes Romb. Dysentery and 16 Diospyrus lotus L. Tor Amlook Fruit constipation Heart problem, cough and chest 17 Eleagnus umbellate Ghanam ranga Flowers heads pain Bowl complains and also used 18 Euphorbia wallichii Shangla Shoots for the removal of ring worms in children Jaundice and also used as blood 19 Fumaria indica Paprra Whole plant purifier Geranium Curing of kidney diseases, cough 20 Srazela Rhizome wallichianum and fever Source: Sher et al., 2010

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Importance has always been given to therapeutic plants as a mode of treatment for different diseases in local cultures. Plants have also played a vital role for the discovery of modern day medicines with novel chemical compounds (Devi et al., 2008; Shirin et al., 2010). Although the effectiveness of medicinal plants is often accounted for curative purposes in terms of organic constituents they possess such as vitamins, oils and glycosides but it is also an established fact now that the over dose or prolonged intake of some medicinal plants would lead to chronic accumulation of various elements that cause different health problems (Sharma et al., 2009). Traditional uses of some commonly used medicinal plants by local people of Northern areas are given in Table 2.3. 2.5. Medicinal plants from Cholistan desert of Pakistan In the southeastern part of the Indus plain from eastern Bahawalpur to southern Thar Parkar region there is a typical desert which is an extension of Thar Desert present between Pakistan and India. The desert is separated by dry bed of the river Ghaggar from central irrigated zone of plains in Bahawalpur and eastern Nara canal in Sindh. In Bahawalpur the desert in known as Cholistan or Rohi and in Sindh it is called as Thar or Pat desert. The surface of Cholistan desert is a wild maze of sand dunes and ridges. Along the south border of Punjab province Cholistan desert is stretched (Fig 2.3) and it a part of world’s seventh largest desert also known as the Great Desert (Rao et al., 1989) which lies at an altidue of 112 m above the sea level (Ali et al., 2009). Comprising an area in total about 25,000 km2 Cholistan desert lies between 27º 42’ and 29º 45’ North and 69º 52’ and 75º 24’ East (Arshad et al., 2007).

About 600 years ago the old Hakra River which was one of the important geological features of Cholistan desert was driend out. Between the two eco-regions of desert the riverbed created a dividing line and formed two parts i.e. the Lesser and the Greater part. To the south of the this riverbed is the Greater part while to the northern portion of desert margin is the Lesser part that includes areas north of the Hakra along the bank of river Sutluj. The Greater Cholistan extends to Indian border from Hakra River that is the most recent course of extinction (Akhter and Arshad, 2006). Hisotrically, Cholistan desert and world’s oldest civilizations which include Indus valley, Mohenjo Daro and Harappa received heavy monsoon downpours. The decline in precipitation was resulted because of a gradual change

Chapter # 2 Review of Literature in the climate that shifted the monsoon winds away from this area that eventually converted into a desert (Leopold, 1963).

Fig 2.3. Map of Cholistan desert of Pakistan (Source: Hameed et al., 2013) 2.5.1. Soil and climate of Cholistan desert Due to negligible amounts of organic matter in the soil of Cholistan desert it is rated as poor. The large compacted areas are the characteristic properties of Lesser Cholistan with alluvial clay in between dunes and low sandy ridges that are mostly less frequently shifting dunes, semi-stabilized or stabilized (Arshad et al., 2007). The soil of interdunal flats varies with respect of its structure, texture and extents of salinity and sodicity with pHs in the range of 8.2 to 9.6 (Arshad et al., 2008). The sand dunes in the Lesser part are much lower i.e. less than 100 meters than the dunes which are found in Greater part. Large wind-shifting sandy dunces and ridges are comprised by the Greater Cholistan interspaced with interdunal plains which are significantly reduced (Arshad et al., 2003). The climate of Cholistan desert is

Chapter # 2 Review of Literature harsh, arid, sub-tropical and hot that is influenced by the seasonal monsoons. Dry-years occure in clusters such as for 4-6 years recurrently and it is one of the most remarkable features of Cholistan therefore, temperature greatly varies annually and even daily. From May to June the mean temperature varies from 35 to 50 ºC where as in winter it varies from 15 to 20 ºC through December to February (Arshad et al., 2007). The annual rainfall has its maxima through July to September in monsoon seasons and in winter from January to March. Overall, the annual rainfall in Cholistan desert is very low unpredictable that ranges from 100-250 mm annually (Arshad et al., 2006). During summers the environment of Cholistan becomes extremely harsh and the desert has been transformed into a death-valley due to low humidity, high rate of evaporation, high temperature and strong winds (Akram et al., 1986).

2.5.2. Vegetation of Cholistan desert The vegetation of Cholistan includes xeromorphic species. Depending upon the nature of soil and environmental conditions of Cholistan desert the vegetation has adopted a variety of stresses such as high salinity, extreme aridity, high temperature and low amount of nutrients (Naz et al., 2010). A relatively deser vegetation is found in the eastern side of the desert as it is a zone of relatively high-rainfall that receive up to 200 mm of rainfall annually. Whereas, the southern region receives only 100 mm rainfall annually and therefore, it is called as hyper-arid region. The characterisitcs such as soil topography, composition and other physio- chemicals play vital roles in the distribution of plant species and their structures (Noureen et al., 2008). A number of studies on medicinal plants of Cholistan desert have been conducted such as Baig et al. (1975) reported that there are six main plant communities in desert. They identified these plant communities by dominant species i.e. Haloxylon stocksii, Tribulus longipetalus, Ochthochloa compressa, Calligonum polygonoides, Prosopis cineraria and Dipterygium glaucum. On the basis of adaptability potential to extreme aridity Khan (1992) classified vegetation of Cholistan and he reported that highly adapted grasses include Cenchrus ciliaris and Panicum turgidum, highly adapted shrubs include Ziziphus nummularia, Calligonum polygonoides and Haloxylon stocksii and highly adapted trees include Prosopis cineraria and Acacia jacquemontii. Along with dominant communites of plants, Arshad and Rao (1995) classified soil into four different groups and put Calligonum polygonoides community as a dominant of sand dunes, C. polygonoides, Prosopis cineraria

Chapter # 2 Review of Literature and Capparis decidua community as a dominant of sandy plains, and Haloxylon stocksii, Suaeda fruticosa, Tamarix dioica community as a dominant of saline areas. Although vegetation cover is tremendously low on the sand dunes but Cenchrus ciliaris, Lasiurus scindicus and Panicum turgidum are amongst the dominant grasses along with Cyperus conglomeratus. The dominant shurbs include Calligonum polygonoides, Aerva javanica and Leptadenia pyrotechnica, and as a dominant herb it comes Dipterygium glaucus (Arshad and Akbar, 2002).

Physical environmental variables, soil chemistry and anthropogenic disturbances and the availability of affecting water are three groups of factors which are mostly related to the distribution, abundance and pattern of different plant species and communities in desert environments. Rainfall (Kadmon and Danin, 1999), texture and water contents of soil (Kumar, 1996), depth of the ground-water (Cornelius and Schultka, 1997), altitude (Burke, 2001), slope, aspects, topographic positions and landforms (Vetaas, 1993), and the processes of aeolian and fluvial (Cornelius and Schultka, 1997) are termed as physical factors.

2.5.3. Use of medicinal plants by local inhabitants Medicinal plants from neighboring countries that share habitats similar to Cholistan especially from India have been explored for their medicinal properties and traditional uses. Although, a great number of medicinal plants from Cholistan desert have been frequently used the local people but unfortunately, the active constituents from these plants with their medicinal properties have still not documented (Hameed et al., 2011). Neurada procumbens is one of the most conspicuous examples and a great deal of mistreatment of this important medicinal plant has made its indigenous status endangered to a critical level.

The treasure of medicinal plants in Pakistan has never been preserved which causes loss of very important medicinal plants. Therefore, there is a need to take steps for the conservation of these important medicinal plants. Government of Pakistan should undertake the following actions in order to preserve the flora of Pakistan and to strengthen the health agenda through traditional medicine:

i. There should be a police, legal and regulatory frameworks to practice traditional medicines within the context of national health strategies and health legislation.

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ii. Relevant research on medicinal plants should be conducted and promoted in collaboration with traditional health physicians for the validation claims constructed on safety, quality and efficacy of herbal medicines.

iii. The indigenous knowledge of traditional herbal medicines should be protected through intellectual property rights.

iv. Establishment of an enabling economic and political and regulatory atmospheres to produce traditional medicines locally and development of industries for the production of standardized medicines to increase access.

v. If need, traditional medicines should be registered using guidelinces given by WHO on registration and regulation of herbal medicines in WHO Asian region.

vi. Publicize proper information about the uses of traditional medicines among general public to enable them with knowledge and skills about those herbal medicines.

In addition to Government of Pakistan, local people who are working on medicinal plants should also follow guidelines for the collection and harvesting of these important medicinal plants. N. procumbens has been extensively used as a strong stimulant and strong tonic against weakness and impotency besides as a cooling agent (Qureshi et al., 2010). The serious threat to the diversity of medicinal plants in Cholistan is from habitat degradation because of agricultural practices. The farmers cultivate their desirable crops and destroy or ignore other important plant sepeices. There is an urgent need for the conservation of medicinal plants in Cholistan by sustaining natural habitat. The existing knowledge and documentation of medicinally important plants should be promoted. The local communities of this region also exploit these plant sepcies for different perposes such as food, fodder and construction. One such example is of Prosopis cineraria whose seeds and fruits are used extensively in various dishes (Arshad et al., 2006). The herbal aqueous extract of Cymbopogon jwarancusa is used by the people of Cholistan in summer for relaxing and reducing thirst. Calotropis procera is another important medicinal plant whose each and every part is used by the local communities to cure various diseases and some part of this plant have other applications such as fruit floss are used in pillows and cushions for stuffing (Chaudhry et al., 2004).

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There are a great number of other examples of local medicinal plants from Cholistan desert whose applications along with their chemical constituents are not yet reported. Although there is a big list of medicinal plants which are traditionally used by the local people of Cholistan desert but applications of some commonly used medicinal plants by these people are given in table 2.4. Local names of these medicinal plants along with parts which are used to cure different diseases are also given in the table.

Table 2.4. Some medicinal plants from Cholistan desert with their traditional uses

S. # Plant Local name Parts used Local use/ effective against Asthma, cough, pneumonia, 1 Achyranthes aspera Ubat Kandri Roots joint pain 2 Aerva javanica Booh Whole plant Toothache Constipation, gall bladder 3 Amaranthus virdis Mariro Whole plant and kidney stones 4 Aristolochia bracteolata Kabar Leaves Ulcer, eczema, dermatitis 5 senna italica Ghorawal Leaflets Backache, 6 Chenopodium album L. Chill Whole plant Constipation 7 Citrullus colocynthis Trooh Roots, Fruits Toothache, Constipation Dhanar 8 Cleome brachycarpa Whole plant Joint pain and inflammation Khathuri 9 Cleome viscosa L. Kinni Buti Whole plant Ear infection, pain and deafness 10 Convolvulus arvensis L. Naaro Leaves Boils and inflammation 11 Desmostachya bipinnata Drabh Roots Carbuncle 12 Digera muricata Lulur Whole plant Constipation 13 Fumaria indica Shahatro Whole plant skin diseases 14 Gynandropsis gynandra Kinro Leaves Fever, boils, earache, otalgia 15 Kickxia ramosissima Wal Whole plant Diabetes 16 Leucas aspera Goomi Buti Whole plant Pain and inflammation 17 Neurada procumbens Kotak Fruits Sexual debility 18 Phyla nodiflora Bukkan Whole plant Micturition, dysuria Urinary calculi, spermatorrhoea, 19 Tribulus terrestris L. Bakhro Fruits general debility Wasanh/ 20 Zelya petandra Roots Influenza, phlegmatic cough Waaho Source: Qureshi and Bhatti, 2008 Ethnopharmacological applications of some medicinal plants of Pakistan along with knowledge of their phytochemicals are given in table 2.5.

Table 2.5. Ethnopharmacological applications of some medicinal plants along with their phytochemicals

Sr. Preparation and Plant/ Local name Parts used Investigation Phytochemcials found No. application Eye infection, toothache, abdominal Achyranthes aspera Root infusion is Alkaline ash containing potash, saponin 1 Root pain, dysentery, rheumatism and L/ Puth kanda taken orally (Nadkarni, 1982) skin infections (Jan et al., 2008) Astringent, diuretic, tonic, Flavonoids, terpenoids, tannins, mucilage, Adiantum capillus L/ Decoction of aerial antibiotic, emetic, expectorant, volatile oil, capillerine, mucin, gallic acid, 2 Aerial parts Sraj parts is taken orally. febrifuge, jaundice and hepatitis sugar, kaempferol, quercetol and luteol (Abbasi et al., 2009) (Prajapati et al., 2006) Ceryl alcohol, β-sitosterol, α-sitosterol, cerotic, Headache, pimples, measles, palmatic, oleic and linoleic acids, glucose, Juice of fresh aerial stomach acidity, internal colic, arabinose, rhamnose, phenolic acid, resins, Ajuga bracteosa/ 3 Aerial parts parts is taken orally jaundice, hypertension, sore throat iridoid, glycosides, alkaloids, phytol, Ratti booti before breakfast. and constipation (Qureshi et al., phytosterols, diterpenoids, triterpenoids, 2009) unidentified compound of formula C49H82O (Rehman et al., 1986) Slightly warm paste Volatile oil, sulphur, essential oil, of bulb in mustard Gastric trouble, anti diabetic organic sulphur, quercetin, moisture, ether, 4 Allium cepa L/ Piaz Bulb oil is tightening over (Ahmad et al., 2003) albuminoids, carbohydrates, fiber, ash and boils and warts for a sugar (Kirtikar and Basu, 1993) night. Chromanol, pteroyglutamic acid, aloe-emodin, quinone, d-glucitol, glucosamine, mono and Anthelmintic, colic, emmenagogue, penta saccharids, hexuronic acid, casanthranol I piles, purgative, rectal fissure, anti- Aloe vera/ Kunvar Fresh pulp is layered and II, aloetic acid, sapogenin, glucoside, 5 Leaf pulp diabetic, blisters, stomach ulcer, gandal for a day. hecogenin, 2-amino-2-deoxy glucose, pussy wounds and eruption chrysophanic acid, m-protocatechuic aldehyde, (Qureshi et al., 2009) cellulose, proteinase, resins, imidazole (Ahmad et al., 1993) Snake bite, scorpion sting, Extract of fresh abscesses, boils, urinary diseases, Argyrolobium leaves is taken Ether, albuminoside, carbohydrates (Nadkarni, 6 Leaves hair tonic, flu, fever and laxative, roseum/ Makhni booti orally before 1982) vision problem (Qureshi et al., breakfast. 2009) Berberis lyceum/ Infusion of fresh or Eye diseases, febrifuge, jaundice, Alkaloids umbellatine, barberin, barbamine, 7 Bark Sumbal dried bark is taken diarrhoea, menorrhagia, piles, starch grains and tannins (Tyler et al., 1981)

orally before backache, dysentery, earache, breakfast. fracture, eye ache (Abbasi et al., 2009) Antiseptic, aphrodisiac, astringent, Tannic acid, gallic acid, starch, mineral salts, Powder of dried boils, demulcent, diuretic, fever, Bergenia ciliate/ metarbin, albumen, glucose, mucilage, wax, 8 Rhizom rhizome is sprinkled ophthalmia, wound healing, colon Batpia ash, A catechine, (+)-afzelechin yield 2% (Haq on wounds. cancer, muscular pain, tonic (Shah and Rehman, 1990) and Khan, 2006) Fresh bark is crushed and is Bombax ceiba L/ Dug Alterative, astringent, restorative, Drying oil, tannic and gallic acids (Nadkarni, 9 Bark applied topically on sumbal tonic (Shinwari and Khan, 1998) 1976) pimples, carbuncles and boils. Seeds are grounded Antiscorbutic, stomachic, body Ocolaza, potash, fixed oil, glycosides, myrosin Brassica campestris with sulphur 10 Seeds weakness, gleets, leucorrhoea enzyme, erucic acid, volatile oil (Kirtikar and L/ Sarian powder. This paste (Abbasi et al., 2005) Basu, 1993) is applied topically. Crushed leaves are Calendula arvensis L/ Antispasmodic and conjunctivitis 11 Leaves topically applied on Sesquiterpene glycoside (Prajapati et al., 2006) Stbarga (Ahmad et al., 2007) wounds. Latex of Calotropis procera, seeds of Prunus armeniaca Voruscharin, calotoxin, calotropin, uscharidin, and horse nails are Purgative, skin infection, trypsin calcatin, uzarigenin, syriagenin, Calotropis procera/ 12 Latex grounded together expectorant, anthelmintic, proceroside, benzoyllineolone, Ak and mixed with diaphoretic (Hussain et al., 2008) benzoylisolineolone, cyanidin-3- mustard oil. This rhamnoglucoside (Rastogi and Mehrotra, 1993) paste is applied topically. Fresh leaves of Cannabis sativa and Narcotics, antispasmodic, boils, Volatile oil, cannabene, cannabine, alkaloids, Cannabis sativa L/ fresh scales of anticonvulsant, antidiarrhoeal, cannabinone, cannabine, cannabinol, pseudo 13 Leaves Bhang Allium cepa are sedative, tonic, refrigerant, cannabinol, cannabinin and terpenes (Hamid et crushed together and astringent (Qureshi et al., 2009) al., 1998) apply directly. Powder of dried Antiseptic, asthma, cardiac Carissa opaca/ Carissone, palmatic acid, benzyl salicylate, 14 Root roots is sprinkled on stimulant, fly repellent, jaundice, Granda benzyl benzoate, farnesene (Rai et al., 2005) wounds. hepatitis (Abbasi et al., 2009)

Abscesses, snake bite, wounds, Cissampelos pareira Leaves are crushed Sterols, steroids, alkaloids and flavonoids 15 Leaves stomachic, malaria (Shinwari and L/ Ghoray summi and applied directly. (Ganguly et al., 2007) Khan, 1998) Methyl-phytosterol, amyrin, multiflorenol, Thin slices of fruit Cucumis sativus L/ Jaundice, stomachic, skin methylenecycloartenol, cycloartenol, tirucallol, 16 Fruit are placed on face at Khira preparation (Abbasi et al., 2009) protein, isopentenyl adenosine trialcohol night. (Prajapati et al., 2006) Aperient, astringent, cooling, Alanine, aspartic acid, glutamic acid, lysine, diuretic, fresh wounds, laxative, Emblica officinalis/ Leaves are crushed proline, protein, fat, carbohydrates fibers, 17 Leaves jaundice, hepatitis refrigerant, hair Amla and directly applied. minerals, iron, niacin, chromium and copper tonic, appetizer, gas trouble (Abbasi (Prajapati et al., 2006) et al., 2009) Glyxylic acid, oxalic acid, vitexin, isovitexin, Fresh leaves are Refrigerant, stomach trouble, Oxalis corniculata L/ neutral lipids, glycolipids, vitamin C, 18 Leaves crushed and applied antiscorbutic, scurvy, jaundice Jandora phospholipids, fatty acids and tocopherols topically. (Qureshi et al., 2009) (Prajapati et al., 2006) whooping cough, asthma, jaundice, Tannins, essential oil, resin, triterpenic acid, Pistacia integerrima Bark is crushed and dysentery, antidote to snake venom 19 Bark pistacienoic acid, triterpene alcohol and J.L./ Kangar topically applied. and scorpion sting, intestinal colic triterpenoic acid (Prajapati et al., 2006) (Shah and Khan, 2006) Dried fruit of Rhus chinensis, Foeniculum vulgare Jaundice, hepatitis (Abbasi et al., Gallotannins, gallotannic acid, gallic acid and 20 Rhus chinensis/ Tiater Fruit are grounded along 2009) m-digallic acid (Prajapati et al., 2006) with sugar. This powder is taken orally. Volatile oils, phenols, shogals, paradols, dihydroparadols, gingerols, gingerdiols, 1- Zingiber officinale/ Powder is sprinkled Indigestion, labour pain, urticarial dehydrogingerdiones, diarylheptanoids, methyl 21 Rhizom Haldi on wounds. (Ignacimuthu et al., 2008) ether, methyl [8]-paradol, methyl [6]- isogingerol (12) and [6]-isoshogaol (Ali et al., 2008)

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2.6. Secondary plant metabolites with medicinal properties The pharmacological and medicinal properties of medicinal plants are often attributed to the presence of so called secondary plant metabolites (Heinrich et al., 2004). Unlike the presence of universal macromolecules of primary metabolism (e.g. monosaccharides, polysaccharides, proteins, nucleic acids, lipids and amino acids) in all plants, the secondary metabolites which have medicinal properties are observed only in a few species of plants (Kayani et al., 2015). Against herbivores and pathogens some of these secondary metabolites play a role as defensive compounds while others function in attracting pollinators and fruit dispersers, in reducing the growth of nearby competing plants, in mechanical support for plants or in absorbing harmful ultraviolet radiation (Ahmed et al., 2015). Polysaccharides, waxes and fatty acids, terpenoids, phenolics (simple phenolics and flavonoids), alkaloids and glycosides and their derivatives are plant secondary metabolites which have reported medicinal properties but not limited to these compounds only. Some of these plants secondary metabolites are discussed here briefly: 2.6.1. Carbohydrates and related compounds Fibre, cellulose and its derivatives, dextrins, fructans, pectins, starch and its derivatives, mucillages (uronic acid containing polymers) and gums are carbohydrates and related compounds derived from plants (Bruneton, 1999). Carbohydrates and related compounds in addition to their use in pharmaceutical industry as bulking agents have also been shown to have immune-modulatory, hypoglycaemic, anticoagulant (e.g. heparin), anti-tumor and antiviral activities (Gurib-Fakim, 2005). 2.6.2. Alkaloids Alkaloids contain nitrogen in a heterocyclic ring are organic bases and many of them have pronounced pharmacological activities (Wyk et al., 2000). On the basis of either their basic ring system (e.g. atropine, quinoline, indole, isoquinoline, piperdine alkaloids or imidazole) or plant sources (e.g. opium, vinca, belladonna, ergot alkaloids or cinchona) or pharmacological properties (e.g. analgesic, anti-malarial alkaloids or stimulant) alkaloids can be classified into several groups (Heinrich et al., 2004). Mostly, alkaloids are strongly bitter in taste and are very toxic, for these reasons they are used by plants to defend them against herbivores, microbial pathogens and invertebrate pests attacks (Bruneton, 1999). Heinrich et

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al. (2004) reported that several medicinal plants which contain alkaloids have been used by the early man as pain relievers and as recreational purposes or in some religious ceremonies to achieve a psychological state in which they could communicate with their ancestors or god. Structure of reserpine is given in Fig 2.4 as an example of alkaloids. Reserpine was derived from Vinca rosea and Rauwolfia serpentine and it reduces the production of neurotransmitters which causes hypotension and sedation by interfering membrane of synaptic vesicles (Talapatra and Talapatra, 2015).

Fig 2.4. Structure of reserpine (an alkaloid) (Adopted from: Gupta et al., 2005) 2.6.3. Phenolics Another class of plant secondary metabolites are phenolics which are characterized by the presence of one or more hydroxyl (-OH) groups attached to an aromatic ring either benzene or some other complex aromatic ring structure (Heinrich et al., 2004). Phenolics plant secondary metabolites on the basis of their structure can be classified into two broad classes, flavonoid and non-flavonoids phenolic compounds and they are responsible for the development of different colors in plants and play a role in pollination also they protect plants from UV radiation and pathogens (Bruneton, 1999; Heinrich et al., 2004). A three ring structure with two aromatic centers (ring A and B) and a central oxygenated heterocyclic ring (C) are contained by flavonoids which are a large and complex group of phenolics compounds (Hollman and Katan, 1999) (Fig 2.5). Flavonoids are known to be present in garlic and they have been found effective in reducing atherosclerosis, coronary thrombosis, cholesterol level and many other serious as well as fatal ailments (Talapatra and Talapatra, 2015).

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Fig 2.5. Basic structure of flavonoids (Adopted from: Kumar and Pandey, 2013) On the other hand simple phenols (e.g. euginol, hydroquinone, catechol, phloroglucinol and p-anisaldehyde) (Jadhav et al., 2004), the C6-C3 phenyl propanoids and their derivatives (caffeic acid, cinnamic acid, ferulic acid myristicin and synapyl alcohol), the C6-C1 benzoic acids (gallic acid, vannilic acid and protocatechic acid), coumarins (warfarin, scopoletin and dicoumarol), hydrozable tannis (gallotannins and ellagitannins) and lignans and related compounds all are included in non-flavonoid phenolic compounds. 2.6.4. Terpenoids The largest group of plant secondary metabolites is terpenoids which are also known as isoprenoids (Bruneton, 1999). Terpenoids are classified on the basis of isoprene units into monoterpenes (C10), sesquiterpenes (C15), diterpenes (C20), triterpenes (C30) and tetraterpenes (C40) (Heinrich et al., 2004; Gurib-Fakim, 2005). They play different roles in plants such as in defense, thermotolerance, wound scaling and pollination of seed crops. Terpenoids also give flavors to fruits, fragrance to flowers and also responsible for the quality of agricultural products (Heinrich et al., 2004). Structure of bisabolol is given in fig

2.6 representing Sesquiterpenes (C15). Bisabolol is used as an anti-bacterial, antifungal, antimalarial and mulluscicidal drug (Heinrich et al., 2005) and isolated from different plant sources such as Salvia stenophylla (Musarurwa et al., 2010) and Plinia cerrocampanensis (Vila et al., 2010).

Fig 2.6. Structure of bisabolol (Adopted from: Heinrich et al., 2006)

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2.6.5. Glycosides Glycosides are plant secondary metabolites which are made up of two components including glycone (a carbohydrate component) and aglycone (a non-carbohydrate component). The former component usually consists of one or more glucose units and the latter component may be any one of the plant secondary metabolites from alkaloids, phenolics or terpenoids (Heinrich et al., 2004; Gurib-Fakim, 2005). Anthraquinone glycosides, steroidal (cardiac) glycosides and coumarin glycosides are medically important glycosides but the medicinal importance is not limited to these glycosides only. Structure of aloesin is shown in fig 2.7 that is an example of glycoside. Aloesin has been isolated from Aloe vera and reported for antioxidant activity, free radical scavenging and anti-inflammatory effects (Yagi et al., 2002).

Fig 2.7. Structure of aloesin (a glycoside) (Adopted from: Dell-Agli et al., 2007) 2.7. Bioactive compounds and defense mechanisms in plants Bioactive compounds (also known as defense bioactive compounds) are a wide variety of chemically diverse compounds produced by plants through complex mechanisms to respond the attacks of insect herbivores and microbial pathogens. Bioactive compounds from plants have been widely used in cosmetic, food and pharmaceutical industries (Gou et al., 2011). Microorganisms are causing diseases in a huge number of plant hosts and are responsible for big losses in economical crops and also preventing valuable food distribution worldwide (Donini et al., 2005; Ferre et al., 2006). The plants which are continuously exposed to a large

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number of pathogens are being attacked in both chemical and mechanical ways by these pathogens (Mee Do et al., 2004). It has also been found that against these pathogen attacks, plants show both inducible and constitutive defenses (Hwang, 2001). And these defenses are due to the transcriptional regulation of genes which plays a primary role in response against the pathogen infections in plants (Rushton and Somssich, 1998). The pathogen attacks induce a number of defense-related and pathogenesis related (PR) genes in plants and these genes are regulated transciptionally through different signal transduction pathways which are mediated by ethylene (Ecker, 1995), salicylic acid (Durner et al., 1997), jasmonic acid (Creelman and Mullet, 1997) and probably hydrogen peroxide (Lamb and Dixon, 1997). A wide range of mechanisms are involved in plants for defense against invading pathogens. These include the induction of those genes which encode pathogenesis-related (PR) proteins, the hypersensitive response (HR) which is necessary for restricting the pathogens from spreading at the primary site of infection and the production of those enzymes which are involved in the production of phytoalexins. In addition, those which are related to tissue repair, oxidative stress protection and cell wall lignification (Reymond and Farmer, 1998). Different active protective mechanisms and constitutive defense barriers which are accompanied by a variety of physical and biochemical changes are also involved in plants to play an important role in defense against different pathogens. Synthesis of a group of pathogenesis-related (PR) proteins which are host-encoded proteins is one of the most studied defense responses in plants. It has been suggested recently that thionins (Stotz et al., 2009), plant defensins (Terras et al., 1992) and lipid transfer proteins (Garcia-Olmedo et al., 1995) which are different groups of small, basic and cysteine-rich antimicrobial proteins they may play an important role in plant defense responses. In fact it has been found that some PR proteins have in vitro antifungal activity (Bol et al., 1990). Similarly, Alexander et al. (1993) has also reported that the genetically engineered and over-expressing PR proteins in plants have been found to be resistant against pathogen infections. Moreover, by the treatment of abiotic elicitors the PR proteins can also be induced in plant tissues. In addition to biotic elicitors, polyacrylic acid, benzoic acid, ethephon, 2,6-dichloroisonicotinic acid (INA), salicylic acid (SA), benzo (1,2,3) thiadiazole-7-carbothioic S-methyl ester (BTH) and DL-β- amino-n-butyric acid (BABA) are also some renowned chemical inducers of PR proteins (Alexander et al., 1993).

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2.7.1. Antimicrobial peptides (AMPs) Antimicrobial peptides (AMPs) provide resistance to plants against microbial infections and have been detected in many agricultural plant species (Broekaert et al., 1997; Marcus et al., 1997). In vitro strong antimicrobial activity of antimicrobial peptides and their localization in a wide range of plant tissues have indicated that they can play an important role for the protection of plants against pathogens. The role of these AMPs in plant protection is also supported by their high expression levels both systemically and locally during the attacks of different pathogens (Bohlmann et al., 1998). All these AMPs do have antimicrobial activity and they can be categorized into different types according to their structures and functions (Broekaert et al., 1997). In different plants two well-known subclasses of these AMPs are found which are called as thionins and plant defensins (Osborn et al., 1995; Elfstrand et al., 2001). Chitin-binding proteins (Broekaert et al., 1997), knottin-type peptides (Chagolla-Lopez et al., 1994) and protease inhibitors (Joshi et al., 1998) are some other AMPs which have also been isolated from medicinal plants and studied. Much attention has been given in recent years to the potential use of AMPs to design novel fungicides which should be environmentally friendly. To engineer genes of disease resistance in plants which can reduce the use of additional chemical fungicides, AMPs are also a possible source of these genes (Gaspar et al., 2014). 2.7.2. Anticancerous compounds Over the last century, the secondary metabolites of plants and their derivatives have acquired most new clinical applications as they are being applied to fight against cancers (Butler, 2004). Drug discovery from medicinal plants for the treatment of different cancers has played a vital role. In a study (Newman et al., 2003) it was shown that from all the available anticancer drugs, there were 40% natural products or their derivatives with another 8% were considered as a mimic of natural products. Many bioactive compounds comprising anticancerous activity have also been extracted and purified. The extracts of Pavetta crassipes showed potential toxicity against human cancer cells (Sanon et al., 2003). The leaves of Pavetta crassipes have also been reported to have indolomonoterpenic alkaloids, hydroxyl-elaeocarpidin and elaeocarpidin (Sanon et al., 2005). Balde et al. (2010) described the potential of indolomonoterpinic alkaloids as effective compound to cure cancer, malaria and bacterial infections.

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The anticancerours compounds from plants which are presently in clinical trials can be divided into four major classes of compounds: taxanes, vinca (or Catharanthus), camptothecins and epipodophyllotoxins. From Catharanthus roseus (L.) and Vinca rosea (L.) two anticancerous agents (i.e. vinblastine and vincristine) were isolated and for over 40 years both compounds were used clinically (van Der Heijden et al., 2004). The vinca alkaloids and their different semi-synthetic derivatives inhibit mitosis by blocking metaphase through binding specially to tubulin which results in its depolymerization (Okouneva et al., 2003). Tubulin binding was also showed by taxanes, including paclitaxel and derivatives without letting depolymerization or interference with tubulin assembly (Horwitz, 2004). From the resin Podophyllum peltatum L. another anticancerous agent (i.e. podophyllotoxin) was isolated but in mice it was found toxic and therefore, its derivatives were prepared with etoposide that was the first clinically approved drug (Gordaliza et al., 2004). Camptothecin was obtained from Camptotheca acuminate but it showed intolerable myelosuppression originally (Newman et al., 2003) and when its action was found by selective inhibition of topoisomerase I, the interest in camptothecin was revived (Cragg and Newman, 2004). Various derivatives of all these four compounds have been produced and some of which are still in their clinical uses. 2.8. Natural products from bacteria The study of microorganisms especially from unexplored habitats such as oceans gained so much attention as an effort to discover new natural products which can be used as novel drugs for the treatment of human diseases and other biotechnological applications. The secondary metabolites from microbial sources have long benefited human health and industry. According to Berdy (2005) more than twenty thousand biologically active natural products from microorganisms have been reported including important pharmaceutical agents such as antibiotic penicillin, the immunosuppressant rapamycin and the antibacterial agent vancomycin. Secondary metabolites also play vital ecological roles in microorganisms that produce them, particularly in terms of chemical communication, nutrient acquisition and defense (Wietz et al., 2013). It has come to known after two decades of research in marine microbiology that marine Actinobacteria are a productive source of secondary metabolites with immunosuppressive, antibacterial and antitumor activities (Fenical and Jensen 2006; Olano et al. 2009). The

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Actinobacteria derived from marine sources include new genera as demonstrated by the descriptions of Salinispora, Serinicossus, Salinibacterium, Sciscionella and Marinactinospora (Tian et al. 2009a) and also new species which belong to this genera also occur on land (Liu et al., 2010). The potential of the marine environment to yield new secondary metabolites and Actinobacterial taxa is clear from these discoveries. According to Fenical and Jensen (2006) the genus Salinispora which belongs to marine actinomycete has been an important source of bioactive secondary metabolites and two species i.e. Salinispora tropica and Salinispora arenicola have been formally described (Maldonado et al., 2005) while Salinispora pacifica has been proposed (Jensen and Mafnas, 2006). Biogeographical studies have revealed that Salinispora pacifica occurs worldwide except for the Caribbean, Salinispora tropica is restricted to Caribbean only while Salinispora arenicola is broadly distributed and co-occurs with both species (Freel et al., 2012). A relationship between Salinispora taxonomy and secondary metabolites production has also been revealed previously (Jensen et al., 2007). Correlations were also found between where these microbial strains were derived and the biosynthetic genes they maintain (Edlund et al., 2011). These findings suggest that culturing new Salinispora species or already known species but from new and different locations as reported previously is a potentially productive approach for the discovery of novel natural products. 2.8.1. Polyketides Polyketides represent one of the major classes of natural products and comprise a diverse and large class of secondary metabolites which are produced by plants, fungi and bacteria (Walsh, 2004; McDaniel et al., 2005). A heterogeneous group of compounds are covered by polyketide class such as macrolides, anthracyclines, enedyines, angucyclines, macrolactams, polyenes and polyethers (Hertweck, 2009). Polyketides are ubiquitous in nature and found in prokaryotes such as bacteria to eukaryotes such as mollusks, insects and plants. The exact roles of polyketides in the context of original biological system are not fully understood yet, however these secondary metabolites are believed to serve as virulence factors, infochemicals and pigments or as defense weapons. In addition to infamous toxins or virulence factors many of these compounds or their derivatives have become clinically important pharmaceutics such as immunosuppressants, cholesterol-lowering agents, antibiotics and antitumor agents (Hutchinson and McDaniel, 2001). The immunosuppressant

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FK506 (Smith and Tsai, 2007), antifungal agent amphotericin B (Rawlings, 2001a), antibacterial agents such as erythromycin A (Hopwood, 1997), oxytetracycline (Hertweck, 2009) and rifamycin derivative rifampicin (Cheng et al., 2003), monensin (Sattely et al., 2008), the cholesterol-lowering agent lovastatin (Kennedy et al., 1999), the antitumor agents mithramycin (Donadio et al., 1991) and doxorubicin (Hutchinson and McDaniel, 2001) represent some of the clinically used microbial polyketides. Much attention has been paid to these polyketides in last few decades to access synthetic routes for these natural products or derivatives because of their tremendous structural diversities and pharmacological relevance. Although microbial polyketides are assembled from the simplest building block acetate or propionate (Hertweck, 2009), the total synthesis of many polyketides is still very challenging because of vast structural complexities and diversities of these compounds. This led to the emergence of “Combinatorial Biosynthesis” which is a new research area and utilizes the synthesis of natural products or their derivatives thereof modifying the original synthetic strategies and tools of nature. The biosynthetic routes of different types of polyketides have been studied and aromatic polyketides such as actinorhodins, angucyclines, anthracyclines and tetracyclines are amongst these metabolites. From this class of compounds several of the most commonly used antibiotics and anti-cancer drugs are employed today, such as the antibiotics tetracenomycin and oxytetracycline, the anthracyclines such as doxorubicin and aclacinomycin are employed in cancer chemotherapy. The usefulness of presently available polyketide drugs is limited due to unfavourable toxicity profiles which lead to serious adverse effects during chemotherapy and increasing antibiotic resistance. Due to chemical complexity of polyketides their chemical synthesis is difficult and for the production of non- natural polyketides the alternative routes have been explored. Based on gene transfer between various antibiotic producing species the “hybrid antibiotic” approach has been rather successful in producing novel microbial polyketides. 2.8.2. Biosynthesis of polyketides The biosynthesis of polyketides is catalyzed by mono- or multi-functional enzymes complexes called as polyketide synthases (PKSs). The genes encoding PKSs are usually organized in clusters, apparently to facilitate a coordinated expression regulation of multiple enzymes which are required for many steps in these specialized biosynthetic pathways (Walsh, 2004). The producer organisms protect them from self-intoxication of their own

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products with the help of biosynthetic genes which are also associated with resistance genes and their export. The chemistry associated with PKSs and well-studied fatty acid synthases (FASs) is closely related as both pathways share common biosynthetic logic and common building blocks i.e. acetyl-coenzyme A (acetyl-CoA) and malonyl-CoA (Smith and Tsai, 2007). Some representative examples of bacterial polyketides with their uses are given in table 2.6 and their structures are given in fig 2.8. Table 2.6. Some bacterial polyketides with their activities Sr. Polyketide Source organism Activity References No. 1 Oxytetracycline Streptomyces rimosus Antibacterial Hertweck, 2009 2 Monensin Streptomyces Antibacterial, Sattely et al., 2008 cinnamonensis Ionophore, Antiprotozoal 3 Rifampicin Amycolatopsis Antibacterial Cheng et al., 2003 mediterranei 4 Amphotericin B Streptomyces nodosus Antifungal Rawlings, 2001a 5 Erythromycin A Streptomyces erythreus Antibacterial Hopwood, 1997 6 Jadomycin B Streptomyces venezuelae Antibacterial Robertson et al., 2015 7 Mithramycin Streptomyces Antibacterial, Donadio et al., argillaceus Antitumor 1991 8 Doxorubicin Streptomyces peucetius Antitumor Hutchinson and McDaniel, 2001

β-ketoester intermediates are generated through decarboxylative Claisen thioester condensations of activated starter unit with extender units such as maloyl-CoA or malonyl- CoA-derived. The biosynthetic process also requires β-ketoacy synthase (KS), acylcarrier protein (ACP) and malonyl or acyltransferase (MAT/AT) as an optional enzyme. β- ketoreduction by ketoreductase (KR), dehydration by dehydratase (DH) and enoyl reduction by enoyl reductase (ER) are followed after every elongation step during fatty acid biosynthesis to yield a fully saturated acyl backbone. Each polyketide chain extension cycle in contrast, is followed by partial, full or no reduction steps giving rise to a complex functionalization pattern (Fig 2.9).

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Oxytetracycline Monensin

Rifampicin Amphotericin B

Erythromycin A Jadomycin B

Mithramycin Doxorubicin Fig 2.8. Representative examples of some polyketide drugs

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Unlike FASs, PKSs use a variety of building blocks and are more promiscuous as they can generate products with varying chain lengths. The carbon backbone in both pathways continues to grow to a defined length and the fully grown products then cleave off from the thioester-bound substrates of enzyme complexes. These newly synthesized primary products may then be subjected to further modifications. In chain propagation, PKSs and FASs even though have striking similarities in their enzymology (Rawlings, 1998), still they are different and constitute a metabolic branch point between primary and secondary metabolism. During evolution both pathways might have diverged at an early stage. PKSs in this context are involved in microbial polyunsaturated fatty acids biosynthesis (Metz et al., 2002) as well as lipids of mycobacterial cell wall (Gokhale et al., 2007).

2.8.3. Types of Polyketide synthases (PKSs) PKSs are divided into three major categories i.e. type I, type II and type III based on the assembly line, mode of actions and architectures (Table 2.7) (Hopwood, 1997). Table 2.7. Survey of PKSs types (modified from: Hertweck, 2009) PKS type Building blocks Organisms Modular type I ACP, various extender units; (in situ Bacteria, (protists) (non-iterative); sub-types: cis- methylation possible) AT, trans-AT Iterative type I ACP, only malonyl-CoA extenders (in Mainly fungi, some bacteria Subtypes: NR-, PR-, HR-PKS situ methylation possible) (Iterative) type II ACP, only malonyl-CoA extenders Exclusively bacteria (Iterative) type III Acyl-CoA, only malonyl-CoA Mainly plants, some extenders (stilbenes and bacteria and fungi tetrahydroxynaphthol are exceptions) PKS-NRPS hybrid ACP, malonyl-CoA, amino acids Bacteria (modular), fungi (iterative)

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Fig 2.9. Fatty acids (A) and polyketide (B) biosyntheses. Route A and route B represent biosynthesis of unreduced and partially or fully reduced polyketides Enz=Enzyme (modified from: Hertweck, 2009)

Chapter # 2 Review of Literature i. Type I PKSs They consist of large multifunctional enzyme complexes where each enzyme contains carrier protein and catalytic domains which are organized like beads on a string (Sattely et al., 2008). The assembly lines are further divided into two different systems i.e. modular and iterative. a. Modular type I In the modular type of system, in addition to a set of KS, AT and ACP domains each module also consists of optional β-keto processing domains such as KR, DH and ER (Fig 2.10). As the growing chain passes from N-terminal to C-terminal the catalytic and carrier domains are used only once. Thus the degree of β-keto reduction in each module is determined by the presence of KR, DH and ER domains, and also the number of modules reflects the number of cycles catalyzed by a particular type I PKS. In general, the number of catalytic domains in each module and the number of modules corresponds to the overall architecture of PKSs product and in this way making the prediction of product structure possible through the analysis of catalytic domains of PKSs or vice versa (Hertweck, 2009). The biosynthesis of erythromycin A is an example of modular type I PKS (Fig 2.10).

Fig 2.10. Biosynthesis of erythromycin A. PKS identifies the loading module (LM) and six modules from M1 to M6 (Source: Chan et al., 2009)

Chapter # 2 Review of Literature b. Iterative type I Iterative type I PKSs also utilize same core catalytic domains like modular type I PKSs, but as a difference between both types these domains occur on a single polypeptide which is used repetitively to generate the complete polyketide backbone. Lovastatin PKS is an example of iterative type I PKS in which one starter unit is condensed with eight extender units and Sadenosylmethionine (SAM) by iteratively acting multidomain polypeptide to generate the lovastatin intermediate dihydromonacolin L (Ma and Tang, 2007) (Fig 2.11). Initially, iterative type I PKSs had thought to be limited to fungal systems only, but now they have also been found in many bacteria. In addition, within modular PKSs the single modules have been found to play role iteratively for the incorporation of multiple extender units per polyketide synthesized.

Fig 2.11. Iterative PKS involved in the biosynthesis of lovastatin (fungal iterative type I PKS) (KS = ketosynthase, AT = acyltransferase, DH = dehydratase, MT = methyltransferase, KR = ketoreductase, ACP = acylcarrier protein, ER = enoyl reductase) (Source: Chan et al., 2009) ii. Type II PKSs Iterative type II PKSs are common in prokaryotes. These are different from type I PKSs as they use a minimal set of enzymes iteratively to generate poly β-keto thioester. Type II PKSs also contain similar core catalytic domains which were seen in type I PKSs but there are typically two domains of KS in type II PKSs i.e. KSα and KSβ (Fig 2.12). KSα is equivalent to the KS observed in type I PKSs while KSβ (known as chain length factor, CLF) controls

Chapter # 2 Review of Literature

the length of the polyketide. Ketoacyl synthases (KSα and KSβ) and ACP constitute the minimal PKS and the enzymatic activities are typically present on individual proteins (McDaniel et al., 1995). However, to control folding, cyclization and aromatization pattern of the newly synthesized polyketide chain some other enzymes i.e. ketoreductases (KRs), cyclases (CYCs) and aromatases (AROs) work with minimal PKS as an enzymatic complex. Actinorhodin (Schumann, 2006) biosynthesis is an example of type II PKS system reported first time from Streptomyces coelicolor (Malpartida and Hopwood, 1984) while doxorubicin (Hutchinson and McDaniel, 2001) (Fig 2.13), landomycin A (McDaniel et al., 1995), gilvocarcin V (Cox, 2007) and tetracycline (Malpartida and Hopwood, 1984) are other examples of type II PKS-derived antibiotics. In type II PKSs acetyle-CoA or propionyl-CoA are used as starter units while malonyl-CoA is used for polyketide chain elongation. Type II PKSs are mostly found in actinomycetes but some Gram-negative bacteria are exceptions (Joyce et al., 2008).

Fig 2.12. Schematic view of actinorhodin KSα and KSβ enzyme (type II PKS). The KSα subunit is shown in red and KSβ (CLF) subunit in green. The light blue region is showing the location which harbours the growing polyketide chain during elongation (Schneider, 2005)

Chapter # 2 Review of Literature

Fig 2.13. Biosynthesis of doxorubicin (bacterial type II PKS) (Chan et al., 2009) ii. Type III PKSs Type III PKSs for polyketide chain elongation do not require any ACP-bound extender units but they directly use acyl-CoA substrate. The biosynthesis of naringenin chalcone (Brachmann et al., 2007) that is a plant product represents a typical example of type III PKS catalysis through a sequential addition of 3 molecules of malonyl-CoA to a starter unit of pcoumaryl-CoA (Fig 2.14). These enzymes are found in bacteria, fungi and plants and are known as stilbene/chalcone synthases (CHS/STS) (Seshime et al., 2005). It has also been reported that the modules from type I PKSs are linked to nonribosomal peptide synthetase (NRPS) modules (Fischbach and Walsh, 2006) resulting in polyketide-peptide hybrid metabolite production. Furthermore, various mixed polyketide pathways such as type III/type I, type I/type II and FAS/PKS hybrids have also been found.

Fig 2.14. Biosynthesis of naringenin chalcone (plant type III PKS, chalcone synthase) (PKS = Polyketide synthase, MCoA = Malonyl CoA) (Chan et al., 2009)

Chapter # 2 Review of Literature

2.9. The Natural Product Domain Seeker (NaPDoS) NaPDoS is a web-based bioinformatic tool (http://napdos.ucsd.edu/) that is used to predict class and in some cases structure of natural products produced by bacterial PKS or NRPS genes (Ziemert et al., 2012). It uses phylogenetic information to detect and extract KS domains from both types of sequences i.e. DNA and amino acids derived from PCR products, genes, metagenomes, whole or draft genomic data. The present version of NaPDoS can classify these sequences on the bases of phylogenetic relationships of more than 200 KS and C references sequences. For the evaluation of biosynthetic richness and novelty of individual bacterial strains, environments or communities the web-tool provides a rapid method. The tool also offers a rational guide for the identification of known bacterial secondary metabolites (dereplicate) and facilitate the discovery of novel compounds and their mechanistic biochemistry. 2.9.1. NaPDoS working The NaPDoS web portal recognizes bacterial KS domains using a combination of basic local alignment search tool (BLAST) algorithm (Altschul et al., 1990) and hidden markov model (HMM) searches which have been optimized for query sequence(s) (Fig 2.15). The PCR products in nucleotide and amino acid formats as coding sequences (CDS) are investigated directly through BLASTX and BLASTP searches respectively against references database of KS domains which are manually curated and have been experimentally verified. For the detection of target domains in short sequences such as query sequences this BLAST-based approach has been proved more effective than HMM models. In the first step, NaPDoS detects and excises KS domains present in the query sequences conferring to the coordinates of their BLAST match through a custom Perl script. In next step, these sequences are BLASTed against a reference database of KS domains which have been experimentally characterized. An initial classification is being assigned to query sequence(s) which defines enzyme architecture or its biochemical function. In the third step, it generates a profile alignment by incorporating the query sequences into a cautiously curated reference alignment which has been created from all known biochemical classes of bacterial KS domains. The alignment is used to generate a phylogenetic tree using FastTree to estimate maximum likelihood (Guindon and Gascuel, 2003) which is interpreted manually for the establishment of a final classification of each query sequence. From FastTree the output i.e. Newick format

Chapter # 2 Review of Literature is changed to graphic images i.e. SVG format through Newick-Utilities program (Junier and Zdobnov, 2010). For subsequent analysis, the trimmed and aligned sequences can be downloaded then. For its operation, NaPDoS does not need any stand-alone tool or software but instead it employs preexisting programs which are publically available. 2.9.2. Domain classification The basis of NaPDoS classification system is formed by phylogenies of KS domains. The KS domains clade is based on enzyme architecture and its biochemical function and it clearly delineates PKSs of type I and II (Fig 2.16). In the reference tree of NaPDoS, the shared ancestry which is given between sequences of FAS and type II PKS (Jenke-Kodama et al., 2005) has been maintained clearly. A great number of reference sequences come in PKS type I clade which can be resolved further into seven groups or classes. Nevertheless, all these lineages are largely in accordance with the phylogenetic studies previously done (Jenke- Kodama and Dittmann, 2005) and therefore supported strongly in the tree with likelihood values 0.7–1.0.

NaPDoS 1.0 can identify and classify bacterial PKS genes and it can also identify KS domains in eukaryotes. It can also generate evolutionary history of KS domains from eukaryotes with prokaryotic homologs. The database of current version of this software is not well populated with KS sequences for a strong classification system. Therefore, an upgradation of software is required with more KS sequences in its database for better classification of KS domains, phylogenetic and pathways studies of different bacterial polyketides.

Chapter # 2 Review of Literature

Fig 2.15. NaPDoS bioinformatic pipeline (Ziemert et al., 2012)

Chapter # 2 Review of Literature

Fig 2.16. Phylogeny based KS domain classification. KS domain phylogeny in which polyphyletic groups are illustrated by letters (Ziemert et al., 2012)

CHAPTER # 3 MATERIALS AND METHODS

Section A: Phytochemical, antibacterial and cytotoxic studies of medicinal plants

This part of research work was conducted under IFPRI-USAID grant in the Molecular Biochemistry Lab., Department of Biochemistry, University of Agriculture, Faisalabad, Pakistan and Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California, San Diego, USA. 3.1. Study areas The study was conducted on medicinal plants of Swat valley and Cholistan desert of Pakistan. Swat is situated at the northwest corner of Pakistan. It lies from 34° 34' to 35° 55' north latitudes and 72° 08' to 72° 50' east longitudes. It is bounded by Indus Kohistan and Shangla on the east, Dir on the west, Chitral and Ghizer on the north and Buner and Malakand on the south. The total area of Swat is 5337 Km2 having a population of about 1.3 million. Swat is a part of the Malakand Division (Khan and Khan, 2015). Cholistan desert is an extension of the Great Indian Desert and is located in southern Punjab of Pakistan, between 27° 42' and 29° 45' north and 69° 52' and 73° 05' east (Akhter and Arshad, 2006). The climate of Cholistan desert is characterized by low and infrequent rainfall. The most striking feature of the Cholistan desert is drought with wet and dry years that occur in clusters (Akhter and Arshad, 2006). The vegetation of Cholistan desert comprises of xerophytic species due to adaptation of extreme seasonal temperature, a wide variety of edaphic conditions and moisture fluctuations (Naz et al., 2010). 3.2. Collection and identiﬁcation of plant species Twelve medicinal plant species used by local communities and herbalists of Swat valley and Cholistan desert were collected (Table 3.1) and carried to the Herbarium, University of Agriculture Faisalabad (Fig 3.1). For preservation, the plants were dried, pressed and

Chapter # 3 Materials and Methods

poisoned with 1% HgCl2 solution and mounted on the herbarium sheets. Herbarium specimens were identified by Dr. Mansoor Hameed (Plant Taxonomist), Department of Botany, University of Agriculture Faisalabad. After verifying plants identification by matching with the Flora of Pakistan (Ali and Nasir, 1989–1991; Ali and Qaiser, 1993–2011) voucher specimens were submitted in the herbarium. 3.3. Chemicals All chemicals were of analytical grade or HPLC grade and purchased from Sigma Chemical Co., Missouri USA, unless otherwise stated. 3.4. Preparation of plant extracts A representative amount (1 g) of whole plant samples collected was chopped into small pieces, shade dried, powdered and extracted at room temperature for 48 h with methanol (Fraser et al., 2012). The extracts were filtered through a Whatmann filter paper No. 42 (125

mm) and 5 g of Na2HSO4 was added to each solution and left for 10 h to absorb water. The extracts were filtered and concentrated on a rotary evaporator. 3.4.1. LC/MS analyses The plant extracts (1 mg/mL) were prepared and filtered from 0.2 µm filter and 10 µL of each solution were injected for LC-MS analysis (Oh et al., 2010) on Hewlett-Packard series 1100 LC-MS system with a reversed-phase C18 column (Phenomenex Luna, 4.6 mm 100

mm; pore size, 5 μm) using a solvent gradient from 5% to 100% CH3CN over 23 min, a flow rate of 0.7 mL/min, and UV detection. Low-resolution mass data were obtained in the positive mode; the following instrumental parameters were used: nitrogen gas temperature 350 °C, drying gas flow rate 11.0 l/min, capillary voltage was 4000 V, ESI voltage, 6.0 kV; capillary temperature, 200 °C; auxiliary and sheath gas pressure, 5 units and 70 lb/in2, respectively.

Table 3.1. Indigenous medicinal plants used in the study with their reported medicinal uses

Sr. Plant species Vernacular Family Habit a Study Parts Preparation Therapeutic uses References # name area used 1 Dryopteris Pakha Dryopteridaceae Wd, Swat Leaves Leaves are Gastric ulcer, Abbasi et al., ramosa Hr, An cooked and constipation 2013 taken orally 2 Bergenia ciliata Zakhm-e- Saxifragaceae Wd, Swat Roots Powder, Antiseptic, Shah and Hayat Hr, An decoction aphrodisiac, Khan, 2006 astringent, boils, demulcent, diuretic, fever, ophthalmia, wound healing, colon cancer, muscular pain, tonic 3 Quercus baloot Tor Banj Fagaceae Wd, Swat Leaves Extract Antibacterial Khurram et Sh, An al., 2013 4 Isodon rugosus Sparkay Lamiaceae Wd, Swat Leaves Juice blood pressure, body Khan and Sh, An temperature, Khatoon, 2007 rheumatism and toothache 5 Fragaria Saanp Booti Rosaceae Juss. Wd, Swat Root, Powder, Powdered root useful Akhtar et al., bucharia Hr, An fruit in disease of urinary 2013 tract; fruits carminative and laxative 6 Valeriana Mushk-e- Valerianaceae Wd, Swat Roots, Powder Epilepsy, Sher and Al- jatamansi Bala Hr, An Rhizo antispasmodic. Yemeni, 2011 me Carminative 7 Trillium Matter Jerri Trilliaceae Wd, Swat Roots Dried Dysentery, Rani et al., govanianum Hr, An Reproductive disorder 2013 8 Solanum Kundiari, Solanaceae Wd, Cholistan Whole Pills Chest pain, vomiting, Mahmood et surattense Momoli Hr, An plant burning al., 2012 feet, cough, asthma, 50

expectorant, stomachache, diuretic, gonorrhea, urinary, gastro-intestinal diseases 9 Calligonum Phok Polygonaceae Wd, Cholistan Fruit, Decoction, Abortifacient, Ahmed et al., polygonoides Sh, An Stem, Juice, Antibacterial, 2014 Leaves, Infusion, Emollient, Epilepsy, Flower Powder Diuretic, Dysentery 10 Fagonia indica Dramaaho Zygophyllaceae Wd, Cholistan Whole Decoction, skin eruption, Cold, Sharma et al., Sh, An plant Juice, Cooling effect, 2009 Infusion, Cancer, Hypertension, Powder Pneumonia, Sedative, Analgesic Antimicrobial 11 Suaeda fruticosa boi booti/ Amaranthaceae Wd, Cholistan Stem, Decoction, Antibacterial, Ahmed et al., Khaari Sh, An Leaves Juice conjunctivitis, Blood 2014 purifier, Cancer, Skin diseases, Snake bites 12 Heliotropium Gorakh Pam Boraginaceae Wd, Cholistan Leaves Paste Wounds Qureshi and strigosum Hr, An Bhatti, 2008 a Wd, Wild; Cult,Cultivated; Hr, Herb; An, Annulus; Pr, Perennial; Tr, Tree; Sh, Shrub

Dryopteris ramose Bergenia ciliate Quercus baloot Isodon rugosus

Fragaria bucharia Valeriana jatamansi Trillium govanianum Solanum surattense

Calligonum polygonoides Fagonia indica Suaeda fruticosa Heliotropium strigosum Fig 3.1. Selected medicinal plants used in this study

Chapter # 3 Materials and Methods

3.4.2. Antibacterial activity Gram-negative, E. coli was used in this study as a reference strain of human pathogen. The agar disc diffusion method was employed for the determination of antibacterial activity of the plant extracts according to Qaralleh et al. (2010) with some modification. Briefly, nutrient agar (31 g/L) was dissolved in distilled water and autoclaved. Inoculum (1 mL/100 mL) was added to the medium and poured in sterilized Petri plates. Then using sterile forceps, 6 mm discs of Whatman filter paper were laid flat on growth medium containing 30 µL of crude plant extract (10 mg/mL). Sensi-Discs of Ciprofloxacin were used as a reference antibiotic (positive control) and dimethyl sulfoxide (DMSO) as negative control. Petri plates were incubated at 37 oC for 24 h for the growth of bacteria. The plants extracts having antibacterial activities inhibited bacterial growth and clear zones of inhibition were formed. The zones of inhibition were measured in millimeters using zone reader. 3.4.3. Cytotoxicity Bioassay The anticancerous activity of test samples towards HCT-116 colon adenocarcinoma cells was determined using an in vitro assay (Oh et al., 2010). Aliquot samples of HCT-116 human colon adenocarcinoma cells were transferred to 96-well plates and incubated overnight at 37

°C in 5% CO2/air. Test samples were added to the plates in DMSO and serially diluted. The plates were then further incubated for 72 h and a CellTiter 96 aqueous non-radioactive cell

proliferation assay (Promega) was used to assess cell viability. Inhibition concentration (IC50) values were deduced from the bioreduction of MTS/PMS by living cells into a formazan product. MTS/PMS was first applied to the sample wells, followed by incubation for 3 h.

Etoposide (Sigma; IC50 = 1.5–4.9 μM) and DMSO (solvent) were used as the positive and negative controls in this assay. The quantity of the formazan product (in proportion to the number of living cells) in each well was determined by the Molecular Devices Emax

microplate reader set to a wavelength of 490 nm. IC50 values were calculated using the analysis program, SOFTMax.

Chapter # 3 Materials and Methods (Continued) Section B: Phylogenetic and gene clusters analyses of bacterial Type-II polyketide synthase with upgradation of NaPDoS

Chapter # 3 Materials and Methods

This part of research work was conducted at Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California, San Diego, USA under IRSIP program of Higher Education Commission, Govt. of Pakistan. 3.5. Comparison of phylogenetic softwares To get the best software for phylogenetic analysis, a comparison between PHYLIP (Plotree and Plotgram, 1989) and MEGA softwares was made by generating phylogenetic trees using both tools. β-actin partial gene sequence was amplified from a filamentous fungus i.e. Trichoderma harzianum and retrieved five similar sequences from NCBI through BLAST for the construction of a phylogenetic tree by PHYLIP. β-actin partial gene sequences of Cleistogenes songorica, Trichoderma reesei, Phaeosphaeria nodorum, Aspergillus terreus and Aspergillus clavatus were added in the phylogenetic analysis. 3.6. Working with bacterial type II PKS sequence data 3.6.1. Retrieval/Collection of Type II PKS sequences (KSα) The general steps performed for phylogenetic analysis of α-subunit of bacterial type II PKS are outlined in Fig 3.2. The first step was to find sequences which were homologous to KSα domain of type II PKS gene. A database search was performed to find sequences of interest and various public sequence databases were gone through such as National Center for Biotechnology Information (NCBI) which allowed keyword and sequence similarity searches. Basic Local Alignment Search Tool (BLAST) (Altschul et al., 1997) is the most popular search algorithm and can accommodate nucleotide or protein sequences. BLAST was tried to identify local regions of similarity and statistical significance of bacterial type II PKS sequences. Sequences were also collected from Database Of BIoSynthesis clusters CUrated and InTegrated (DoBISCUIT) which is a literature-based, manually curated database of gene clusters for secondary metabolite biosynthesis (Ichikawa et al., 2013). In total, 61 sequences were retrieved from different databases and used for bioinformatics analyses along with one outgroup (see Table 4.3). 3.6.2. Creating alignment of KSα domains of type II PKS Before running a phylogenetic analysis, the comparison of homologous sites of α-subunit of bacterial type II PKS was important and it was accomplished by creating an alignment in which each α-subunit sequence was assigned a separate row and homologous positions in

Chapter # 3 Materials and Methods

Selection of Dataset BLAST

DoBISCUIT

Alignment ClustalX Muscle MAFFT

Editing the alignment

Gblocks Mesquite MEGA

Model-testing ProtTest

Generating phylogenetic tree PAUP MrBayes MEGA RAxML

Tree drawing Figtree Treeview MEGA

Fig 3.2. Phylogenetic workflow and softwares used in this study

Chapter # 3 Materials and Methods different sequences aligned in columns. Different software packages were used to perform multiple alignments including ClustalX (Thompson et al., 1997), MUSCLE (MUltiple Sequence Comparison by Log- Expectation) (Edgar, 2004) and MAFFT (Multiple Alignment using Fast Fourier Transform) (Katoh et al., 2002). 3.6.3. Editing the alignment The truncated sequences were deleted and longer sequences were shortened in the multiple sequence alignment to make them all equal in length. Highly variable regions in the sequences were masked as they were not phylogenetically informative. Likewise, gaps in the alignment increase the risk of misalignment which could result in inaccurate phylogenetic analyses. However, variable regions in the alignment could provide important information for phylogenetic analyses. Gblocks was also tried which provides an automated method to perform alignment sensitivity tests and eliminates poorly aligned and divergent regions in the alignment (Talavera and Castresana, 2007). Finally, the final alignment was manually inspected carefully as these methods could never replace it. Mesquite (Maddison and Maddison, 2014) and MEGA (Tamura et al., 2011) were used to edit and convert alignment into different formats which were needed for phylogenetic analyses.

3.6.4. Model tests Phylogenetic trees were generated with maximum likelihood (ML) and Bayesian methods which are based on statistical models. Although to determine the robustness of a phylogenetic tree it is important to test different parameters but at the same time we cannot deny the importance of model testing which tells about the best fit model for our data. ProtTest (Abascal et al., 2005) was used in the study to identify which model best fits our data. ProtTest estimates the optimal parameters for subsequent tree calculation by analyzing likelihood values through different models. Although for generating phylogenetic trees the model testing and alignment editing are not essential steps but they are recommended to improve the accuracy and branch support. 3.6.5. Generating a reference phylogenetic tree for NaPDoS Four major methods with different models (Table 3.2) were used to generate a number of phylogenetic trees which were compared to each other to test the consistency of the results

Chapter # 3 Materials and Methods

and robustness of the trees. The final tree generated in the study will be used as a reference phylogenetic tree in upcoming version of NaPDoS (NaPDoS v2.0) for type II PKS. 3.6.5.1. Neighbor-Joining (NJ) Neighbor-Joining method is the fastest method for most alignments (Saitou and Nei, 1987). NJ is a distance-based method used in the study and it calculates a distance matrix for all pairs of sequences present in the alignment. PAUP (Swofford, 2003) MEGA (Tamura et al., 2011) and PHYLIP (Felsenstein, 2005) softwares were used for NJ analysis.

Table 3.2. Methods with different models used to generate phylogenetic trees Method Models used Method Models used Neighbor joining Dayhoff Maximum Dayhoff matrix based (NJ) tree Jones-Taylor-Thornton Likelihood Tree Dayhoff w-freq. (JTT) No. of differences Equal input p distance Jones et al. w-freg. Poisson JTT matix-based Minimum Evolution Dayhoff Poisson Tree Jones-Taylor-Thornton Whelan and Goldman (JTT) + Freq. No. of differences Whelan and Goldman p distance Maximum Poisson Parismony Tree 3.6.5.2. Maximum parsimony (MP) Maximum parsimony also uses minimum-evolution criterion for phylogenetic tree construction. Commonly used softwares PAUP (Swofford, 2003), PHYLIP (Felsenstein, 2005) and MEGA (Tamura et al., 2011) were used to generate MP tree. 3.6.5.3. Maximum likelihood (ML) Maximum likelihood and Bayesian methods are based on specific models of evolution for statistical analysis. The probability of a phylogenetic tree is calculated by ML analysis with given certain parameters and generates a tree with the highest likelihood score. MrBayes (Huelsenbeck and Ronquist, 2001) is a program that is implemented by the Bayesian method was used for ML analysis along with MEGA (Tamura et al., 2011) and PhyML (Guindon and Gascuel, 2003). 3.6.5.4. Minimum evolution (ME) Minimum evolution is a time consuming method for phylogenetic analysis. In ME method, those distance measures are used which are correct for multiple hits at the same sites. As an

Chapter # 3 Materials and Methods

estimate of a correct tree, a topology is chosen which shows the smallest value of the sum of all branches (S). MEGA (Tamura et al., 2011) software was used to construct ME tree. The final tree was visualized in Treeview and Figtree programs. As the published trees need to display a scale bar and some methods of statistical support therefore, the final tree was edited in MEGA (Tamura et al., 2011). 3.7. Study of structural similarities The chemical structures of all the compounds i.e. antibiotics and spore pigments used in phylogenetic analysis were collected from literature and databases such as DoBISCUIT (Ichikawa et al., 2013). The collected compounds of type II PKS were studied and divided into different classes on the bases of their structural similarities and the results were compared with all the clades of the subsequent phylogenetic tree to explain incongruities in the tree. 3.8. Gene cluster analyses of type II PKS For gene cluster analyses, the web tool antiSMASH (antibiotics and Secondary Metabolite Analysis Shell) (Medema et al., 2011) was used which aligned the identified regions from the selected sequences at the gene cluster level to their nearest relatives. ClusterBlast comparative gene cluster analysis for KSα domain of type II PKS was also performed with antiSMASH. Gene cluster analysis was also done by ‘Mauve Genome’ available in the latest version of Geneious (Kearse et al., 2012). Like MEGA (Tamura et al., 2011), Geneious is also a multipurpose and more general bioinformatic software package however, it must be purchased. Mauve application, v 2.3.1 was used for further visualisation (Darling et al., 2004) of biosynthetic gene clusters of bacterial type II polyketide synthases.

CHAPTER # 4 RESULTS AND DISCUSSION

Part A: Bioactive potential of medicinal plants from Northern areas and Cholistan desert of Pakistan

4.1. Biochemical profiling of selected medicinal plants In the present work the usage of LC-MS analysis of the methanolic extracts of twelve selected medicinal plants was explored for the separation and identification of the compounds rapidly. LC-MS chromatograms of methanolic extracts of selected medicinal plants are shown in Figures 4.1-4.12. Library search was conducted to find out active ingredients from each extract. The most potent compounds were compared with those reported in literature. LC-MS analysis revealed that the active constituents from plants had strong activities against a broad range of diseases (Table 4.1). The search was made for each of the compound detected in the medicinal plants for its potential use as medicine or drug in literature. It was found that the selected medicinal plant species had a great potential to be used against the reported diseases. Further research is needed to explore possibility of isolation of such active ingredients from the plant species. Maximum compounds were detected in Quercus baloot and Dryopteris ramosa. Although the study yielded very valuable information regarding potential bioactive compounds from the selected plants, further in-depth analysis is needed on extraction of the bioactive compounds followed by their efficacy test against different diseases. Selected medicinal plants for LCMS were those having vital bioactivities against a wide range of diseases according to local people of northern and desert areas. Due to the presence of potent bioactivity, these are also exported. Phytochemicals are non-nutritive chemicals and responsible for medicinal properties of plants (Savithramma et al., 2011). Bases on the functions they perform in plants’ metabolisms, phytochemicals are divided into two groups i.e. primary and secondary metabolites.

Chapter # 4 Results and Discussion

) Intensity (mAU

Time (min) Fig 4.1. LC-MS Chromatogram of methanolic extract of Dryopteris ramosa

) Intensity (mAU

Time (min) Fig 4.2. LC-MS Chromatogram of methanolic extract of Bergenia ciliata

Chapter # 4 Results and Discussion

) Intensity (mAU

Time (min) Fig 4.3. LC-MS Chromatogram of methanolic extract of Quercus baloot

) Intensity (mAU

Time (min) Fig 4.4. LC-MS Chromatogram of methanolic extract of Isodon rugosus

Chapter # 4 Results and Discussion

) Intensity (mAU

Time (min) Fig 4.5. LC-MS Chromatogram of methanolic extract of Fragaria bucharia

) Intensity (mAU

Time (min) Fig 4.6. LC-MS Chromatogram of methanolic extract of Valeriana jatamansi

Chapter # 4 Results and Discussion

) Intensity (mAU

Time (min) Fig 4.7. LC-MS Chromatogram of methanolic extract of Trillium govanianum

) Intensity (mAU

Time (min) Fig 4.8. LC-MS Chromatogram of methanolic extract of Solanum surattense

Chapter # 4 Results and Discussion

) Intensity (mAU

Time (min) Fig 4.9. LC-MS Chromatogram of methanolic extract of Calligonum polygonoides

) Intensity (mAU

Time (min) Fig 4.10. LC-MS Chromatogram of methanolic extract of Fagonia indica

Chapter # 4 Results and Discussion

) Intensity (mAU

Time (min) Fig 4.11. LC-MS Chromatogram of methanolic extract of Suaeda fruticosa

) Intensity (mAU

Time (min) Fig 4.12. LC-MS Chromatogram of methanolic extract of Heliotropium strigosum

Chapter # 4 Results and Discussion

Table 4.1. List of compounds (by Library matching) present in each medicinal plant with their medicinal use

Dryopteris ramosa Bergenia ciliata Quercus baloot Isodon rugosus bucharia Fragaria Valeriana jatamansi govanianum Trillium Solanum surattense polygonoides Calligonum indica Fagonia Suaeda fruticosa strigosum Heliotropium Medicinal Plant Species

Compounds with Classification

Reported Activities Phenylacetic Auxins + + + + + + + + + + + + acid Anticancer Activity (Neish, 1971) Indole-3- Auxins + + + + + + + + + + carboxylic acid Antiinflammatory activity (Rapolu et al., 2011) Genistein Isoflavones + + + + + + Against genetic diseases (Wegrzyn et al., 2010) Genistin Isoflavones + + Anticancer Activity (Hamdy et al., 2011) L-Tryptophan Free amino + + + + + + + + + + + Antidepressent acid (Thomson et al., 1982) Indole-3-acetic Auxins + + + + + + + + + + acid Treatment of Acne (Huh et al., 2012) Enhydrin Sesquiterpene + + + + + + + + + Antibacterial lactones Activity

Chapter # 4 Results and Discussion

Compounds with Classification

Reported Activities (Choi et al., 2010) Maytansin Nonalkaloids + + + + + + + + + + + + Anticancer Activity (Bell-McGuinn et al., 2011) Dihydro- Sesquiterpene + + + + + + + + + + + Parthenolide lactones Anti- inflammatory activity (Feltenstein et al., 2004) 4- Phenolics + + + + Hydroxybenzoic acid Vasodilative Compounds (Seki et al., 2010) Quercetin Flavonoids + + + + + + + Against Interstitial Cystitis (Katske et al., 2001) Protocatechuic Phenolics + + acid Cancer Chemo- preventive Activity (Tanaka et al., 2011) Myricetin Flavonoids + + + + + + Antioxidant Larson, 1988

Chapter # 4 Results and Discussion

Common carbohydrates, amino acids, proteins and chlorophylls belong to primary metabolites while alkaloids, terpenoids, flavonoids, glycosides, saponins, tannins, steroids etc are examples of plants secondary metabolites (Kumar et al., 2009). Hence in the present study biochemical profiling of twelve selected medicinal plants from Swat valley and Cholistan desert was carried out. The qualitative phytochemical analysis of these medicinal plants confirms the presence of various important secondary metabolites discussed here. 4.1.1. Flavonoids Two flavonoids i.e. Quercetin and Myricetin were detected in four medicinal plants. Quercetin is responsible to inhibit cytotoxicity of in vitro low-density lipoprotein and oxidation (De Whaley et al., 1990) and can decrease coronary heart disease or cancer risks (Yoshida et al., 1990). Myricetin is one of the most active antioxidant and responsible for free radical scavenging activity in foods and also have significant activity of vitamin C sparing (Larson, 1988). Plants flavonoids are responsible for a wide range of biochemical and pharmacological properties including anti-inflammation, anti-thrombotic action, anti- oxidation, anti-platelet and anti-allergic effects (Cooks and Samman, 1996). The mechanism of action of flavonoids is through chelating or scavenging process (Kessler et al., 2003) and also show anti-microbial activity through inhibiting those microbes which are resistant to antibiotics (Linuma et al., 1994b). 4.1.2. Sesquiterpene lactones Two different sesquiterpene lactones were found in selected plants. Enhydrin was found in four whereas dihydro-parthenolide was detected in all five medicinal plants. The primary sesquiterpene lactone, dihydro-parthenolide was also studied by Heptinstall and Awang (1998) in Tanacetum parthenium. The plant has well-established effects to cure migraine, inflammation and pain (Jain and Kulkarni, 1999). The other sesquiterpene lactone, enhydrin also showed similar activity and significantly blocked the hyperalgesic response and attenuated edema response significantly (Feltenstein et al., 2004). Sesquiterpene lactones which belong to class of lactones are known to possess anti-inflammatory properties (Hall et al., 1980) and the mechanism of action of these lactones has been found to inhibit both cyclooxygenases (COX-2) and pro-inflammatory cytokines in macrophages (Hwang et al., 1996).

Chapter # 4 Results and Discussion

4.1.3. Isoflavones Two isoflavones i.e. genistein and genistin were found in selected medicinal plants. Genistein was found in Suaeda fruticosa and Heliotropium strigosum, and genistin was found in Suaeda fruticosa only. Genistein belongs to the group of isoflavones, heterocyclic polyphenols which occur naturally in plants and it is also called 4′,5,7-trihydroxyisoflavone (Dixon and Ferreira, 2002). Genistein occurs naturally as a glycoside called genistin rather than as an aglycone (Nielsen and Williamson, 2007). A number of biological functions of genistein have been reported to date including phyto-oestrogenic, antioxidant and tyrosine kinase inhibitor activities (Szkudelska and Nogowski, 2007; Nielsen and Williamson, 2007). Wegrzyn et al. (2010) reported that genistein can also be used as a drug for as yet untreatable genetic diseases. Genistin was supplemented with selenium to provide antioxidant defense with high potential chemopreventive activity against tumors more than selenium alone (Hamdy et al., 2011). Isoflavones belong to phytoestrogen class and are naturally occurring plant chemicals. Currently, for a range of hormone dependent conditions including cancer, cardiovascular disease, menopausal symptoms and osteoporosis the isoflavones are heralded as offering potential alternative therapies (Setchell and Cassidy, 1999). 4.1.4. Phenolics In this study, 4-Hydroxybenzoic acid and protocatechuic acid were two phenolics observed in some selected plants. Protocatechuic acid (3,4-dihydroxybenzoic acid) is a simple phenolic which is widely distributed in nature and found in almost all plants like many other simple phenolic acids therefore, it is a common constituent of human diet (Liu, 2004). Tanaka et al. (2011) indicated that protocatechuic acid could be protective against epithelial malignancy development in different tissues and cardiovascular diseases also. The phenolic compounds are one of the largest group of plant secondary metabolites. A number of studies have been done on phenolics to focus their biological properties including anti-apoptosis, anti- carcinogen, anti-artherosclerosis, anti-ageing, anti-inflammation, cell proliferation activity, cardiovascular protection as well as improvement of the endothelial function and inhibition of angiogenesis (Han et al., 2007). Phenolic compounds remain the standards with which other bacteriocides are compared and also extensively used in disinfections (Okwu, 2001). The mechanism of action of this simple phenolic is mostly associated with antioxidant

Chapter # 4 Results and Discussion

activity including scavenging as well as inhibition of generation of free radicals and upregulating antioxidant enzymes Tanaka et al., 2011). 4.1.5. Non-alkaloids Maytansin is the only nonalkaloid found in all five studied medicinal plants. Maytansinoid toxins result in the disruption of microtubule activity and cell division and ultimately cell death through their binding to tubulin and inhibition of tubulin polymerization and microtubule assembly (Bell-McGuinn et al., 2011). 4.2. Antibacterial study of selected plants Antibacterial activities of indigenously selected medicinal plants were studied by agar diffusion assay which is also called disc diffusion antibiotic sensitivity testing or Kirby- Bauer antibiotic testing (KB testing) (Bauer et al., 1966). In this method a well is cut into the agar and the test compound is applied to this well. Water-soluble molecules diffuse through the agar and show their activities. Alternatively, a disk made of cellulosic material with test compound applied on it is used to place on the agar. Depending on the solubility the compound tends to spread into the agar. A bacterial test strain without antibiotic resistance against whom the antibacterial activity is to be determined is spread on the agar plate before placing the test substance. Then after overnight incubation the growth inhibition of the test strain is observed. The principle of this assay is that the test substance diffuses out of the disk into the agar and in its surrounding area and generating a zone with no bacterial growth. The radius or diameter of the area is measured in mm or cm which serves as zone of inhibition of the test compound against the selected bacterial strain. Solvent type is very important in extraction procedures for successful predictions of botanical compounds from medicinal plants. Usually, water is used as a solvent by traditional healers but in our study we used organic solvent i.e. methanol as it provides more consistent antibacterial activity compared to water (Parekh et al., 2005). In addition to the intrinsic bioactivity of different solvents by the ability to dissolve or diffuse in different media, these observations can be rationalized in terms of polarity of the compounds being extracted by these solvents. In this study, inhibition of E. coli growth was observed with most of the plant extracts tested (Fig 4.13). The negative control, DMSO, did not affect E. coli growth. The methanol extracts of Suaeda fruticosa showed significant antibacterial activity while of

Chapter # 4 Results and Discussion

Isodon rugosus, Solanum surattense, Fragaria bucharia, Trillium govanianum and Dryopteris ramosa showed substantial inhibition (Table 4.13).

Fig 4.13. Antibacterial activities (zones of inhibition) of selected medicinal plants against E. coli (with positive and negative controls) The results were found to be highly significantly differently from the controls in each case (P<0.01) (Table 4.2). The results demonstrate that these extracts have strong antibacterial activities towards E. coli. Biochemical profiling results showed that the antibacterial agent enhydrin (Choi et al., 2010) was present in tested medicinal plants with higher antibacterial activity, but the optimal effectiveness of a medicinal plant might not be due to only one main

Chapter # 4 Results and Discussion

active compound. The combined action of different constituents originally in the plant would be the cause of optimal effectiveness against a particular disease (Chang et al., 2001). In antibacterial studies, the observed in vitro minor interactions might not only result in significant synergism in vivo but they also made a difference to the in vivo durations for an effective drug level (Berenbaum, 1987). Herbal remedies have been used to treat infectious diseases throughout human history (Ozturk and Ercisli, 2006), but to study the potential antibacterial properties of plant-derived phytochemicals reliable and standardized antibacterial methods are needed. In the past few years many studies have been conducted in different countries to prove such efficiency (Tabuti et al., 2010; Zakaria et al., 2010) and antimicrobial activity from medicinal plants (Khanna and Kannabiran, 2008). The results obtained from present investigation of screening indigenously collected medicinal plants confirmed the therapeutic potency of some plants used in traditional medicines in Pakistan. The results also form a good basis for the selection of candidate plant species for further pharmacological and phytochemical investigations. The findings of this study support the folkloric usage of these studied medicinal plants and confirm the antibacterial properties possessed by some of the plant extracts which can be used as antibacterial agents in new drugs to combat infectious diseases caused by bacteria. The most active extracts from this study can be subjected to further pharmacological evaluation to isolate therapeutic antibacterial agents. 4.3. Cytotoxic study of selected medicinal plants The products obtained from medicinal plants have a long history of use in the treatment of cancer. Hartwell listed more than 3000 plant species in his review of plants used against cancer (Kaur et al., 2011). Many anticancer drugs have been developed from plant based drug discovery which are currently in clinical use. In addition, the field of drug discovery from plants also provides a platform to design novel and safe drugs through proper knowledge and understanding of complex synergistic interactions of various compounds obtained from medicinal plants having anticancerous activities (Larkin, 1983; Saxe, 1987). In current research cancer cell cytotoxicities of twelve selected indigenous medicinal plants were evaluated against human colon carcinoma cell line HCT-116 (see Table 4.2).

Cytotoxicity was expressed as IC50 value which is the concentration of extract needed to inhibit cell growth by 50%. 73

Chapter # 4 Results and Discussion

Table 4.2. Antibacterial and cytotoxic activities of indigenous medicinal plants samples

Zone of inhibition HCT-116 Plant species (mm) IC50 (μM) Dryopteris ramosa 13.2 ± 0.6 11.57 Bergenia ciliata 9.2 ± 1.4 NSA Quercus baloot 9.6 ± 1.2 NSA Isodon rugosus 15.2 ± 0.4 5.568 Fragaria bucharia 13.3 ± 0.5 NSA Valeriana jatamansi 12.1 ± 0.8 NSA Trillium govanianum 13.4 ± 0.4 8.864 Solanum surattense 14.8 ± 0.5 NSA Calligonum polygonoides 10.5 ± 0.9 NSA Fagonia indica 12.3 ± 0.7 NSA Suaeda fruticosa 19.5 ± 0.3 NSA Heliotropium strigosum 9.3 ± 1.3 NSA Positive control (Ciprofloxacin) 42.5 ± 0.1 - Negative control (DMSO) 0.0 - NSA = Not Significantly Active (Inhibition observed only at >20 μg/mL) Values are the mean of three replicates±standard deviation

Against HCT-116 colon carcinoma, Isodon rugosus showed the highest activity with IC50 = 5.68 μM. Trillium govanianum and Dryopteris ramosa were found to exhibit in vitro cancer

cell cytotoxicity with an IC50 of 8.864 μM and 11.57 μM respectively. It also raised questions regarding the nature of the constituents responsible for this cytotoxic activity and therefore, further studies are needed to find out these active ingredients. There are many phytochemicals which are known as bioactive and are used to treat cancer. These include isothiocyanates and dithiolthiones, terpenoids, flavonoids, protease inhibitors, phytoestrogens, phytic acid, phenolic compounds, glucosinolates, saponins, allium compounds, plant sterols, indoles and chemical found in various botanicals (Simon, 2002). In particular, the derivatives of glucobrassicin and indole may be useful to inhibit the formation of tumors in the liver, breast and lungs (Wattenberg and Loub, 1978). Usually all flavonoids tend to act as antioxidants and they are useful in chelating metallic ions. In plants, flavonoids help protect them from fungi, viruses and as repellents to keep animals from feeding on

Chapter # 4 Results and Discussion them. Of the two flavonoids found in some plants, quercetin is considered to be helpful for the inhibition of proliferation of leukemia and tumor production. Like the relationship present between isoflavones and inhibition of breast tumor, a link between quercetin intake and the inhibition of general tumor is also evident (Birt and Bresnick, 1991). Phenolic compounds are also helpful to inhibit cancer through the induction of certain detoxification systems such as N-nitrostation reactions (Simon, 2002). Keeping in view the importance of medicinal plants from Northern and desert areas of Pakistan, it is recommended that the indigenous people should be educated regarding the medicinal importance of plants from these areas and pre and post-harvest methods. It was observed in Northern areas of Pakistan that an important medicinal plant Ferula narthex has been destroyed up to 94% as the local people cut these medicinal plants above the root only to collect the latex (Haidar and Qaiser, 2009). Therefore, the indigenous people from these areas should be trained regarding the cultivation of these important medicinal plants on commercial basis, their trade and marketing which would ultimately generate extra sources of income for these people and will also reduce pressure on the extraction of these valuable medicinal plants. Northern and desert areas of Pakistan are protected areas and all these destructive practices should be stopped immediately to ensure the survival of these valuable medicinal plants. Even though medicinal plants have widespread uses in traditional medicine, but the bioassay analysis of very few medicinal plants are being conducted to explore the medicinal properties they have. The present study therefore, has been carried out to fulfill this gap and methanolic extracts of twelve selected medicinal plants were tested for their antibacterial and cytotoxic activities, in addition to their biochemical profiling. These activities were proved to be significant in some plant extracts while other extracts showed variable responses for these activities. Pakistan is a good example of plants biodiversity with a rich tradition of herbal remedies, and most of its population relies mainly on these medicinal plants for their healthcare issues. The medicinal plants may not be as useful as claimed or they may have more therapeutic properties than are known traditionally by indigenous people. Therefore, there is a need for proper scientific investigation to explore the exact medicinal potentials of these local plants.

Chapter # 4 Results and Discussion (Continued) Part B: Phylogenetic and gene clusters analyses of bacterial Type-II polyketide synthase with up gradation of NaPDoS

Chapter # 4 Results and Discussion

4.4. Comparison between PHYLIP and MEGA The phylogenetic tree of fungal partial β-actin genes generated by PHYLIP is given in fig 4.14. The structural designs of introns are very useful to study phylogenetic relationships. From this study, it was observed that among selected fungi, A. clavatus, A. terreus and Phaeosphaeria nodorum actins are evolutionarily closest to the ancestral actins. T. reesei actin is evolutionarily closer to the ancestral actin among these fungi but T. harzianum and Cleistogenes songorica are thought to be more diverged forms of ancestral actin (Mustafa and Jamil, 2013).

Fig 4.14. Phylogenetic tree of fungal actins 4.4.1. Advantages of PHYLIP i. PHYLIP was found to be user-friendly software and it is freely available. ii. It is stand-alone software and can be used on any computer. iii. The latest versions of PHYLIP contain various programs which can be used for different types of data. iv. PHYLIP works on any type of computer such as Windows, Macintosh MacOS X, Mac OS, Macintosh and Linux. v. It can be used as a free ware and as a web server as well. vi. Different programs are available in PHYLIP for the analysis of DNA and amino acid sequences.

Chapter # 4 Results and Discussion

4.4.2. Disadvantages of PHYLIP i. The inflexible format of PHYLIP makes it hard to work smoothly because any deviance in providing the data results in an error message “Unable to allocate memory” and then the program terminates its job. ii. There is a sequential way to use PHYLIP and the output from one program is used as an input in the next one. iii. The input or output files in PHYLIP folder have every time to be named as “infile”, “outfile” or “outtree” respectively that replaces the existing files in the folder. Therefore, the user has to rename the files very carefully because there is no program based on Bayesian inference method in PHYLIP. PHYLIP generates the phylogenetic tree in image format which cannot be edited or labeled whereas the phylogenetic tree generated by MEGA can be edited and the clades can also be labeled. Therefore, MEGA software was used in this study for phylogenetic studies because PHYLIP was not found a good choice for this sort of analysis. 4.5. Up-gradation of Natural Product Domain Seeker (NaPDoS) NaPDoS is freely available online bioinformatic tool which is used for the rapid detection and analysis of bacterial secondary metabolite genes. The tool was designed for the detection and mining of bacterial C- and KS- domains from either DNA or amino acid sequence data, including PCR amplicon products, whole genomes or individual genes and metagenomic data sets. The tool identifies candidate secondary metabolite domains from well-characterized chemical pathways by their sequence comparisons to a broad set of manually curated genes working as a reference. To predict what putative products might be of candidate gene sequences, they are extracted, trimmed, translated (if necessary) and subjected to domain- specific phylogenetic clustering by NaPDoS (Fig 4.15). The tool can also predict whether the products of candidate genes will produce similar compounds or different than the biosynthetic pathways previously known (Ziemert et al., 2012).

Chapter # 4 Results and Discussion

Fig 4.15. Screen shot of the NaPDoS webpage showing working steps of tool (Ziemert et al., 2012)

In the current version of NaPDoS (v1.0), type II PKSs are not fully resolved therefore, for better resolution of type II PKSs, a reference phylogenetic tree for KSα domain was generated in this study with more phylogenetic groups. The reference tree will be used for upgradation of NaPDoS (v2.0). The steps followed for generating reference phylogenetic tree for KSα domain of type II PKS are discussed here.

4.5.1. Retrieval/Collection of Type II PKS sequences (KSα)

To generate a reference phylogenetic tree for KSα domain, homologous sequences were retrieved and collected from databases such as National Center for Biotechnology Information (NCBI) and Database of BIoSynthesis clusters CUrated and InTegrated (DoBISCUIT). Basic Local Alignment Search Tool (BLAST) (Altschul et al., 1997) available on NCBI web page has been considered the most popular search algorithm and can accommodate nucleotide or protein sequences. DoBISCUIT is a literature-based database

Chapter # 4 Results and Discussion

and gives information about gene clusters of known PKS and NRPS. Table 4.3 is showing the list of compounds whose sequences were collected to generate a reference phylogenetic tree for KSα domain of type II PKS along with their accession numbers, classes and organisms that synthesize these compounds.

Table 4.3. Compounds with their classes selected to generate a reference phylogenetic tree of KSα domain of type II PKS Sr. Accession Source organism Compound Class # # 1 CAG14965 Streptomyces antibioticus Oviedomycin 2 AAO65346 Streptomyces Kinamycin murayamaensis 3 AAB36562 Streptomyces venezuelae Jadomycin B 4 AAR30152 Streptomyces Angucycline-like ambofaciens antibiotic 5 AAO65362 Streptomyces sp. PD 116740 6 AAD13536 Streptomyces cyanogenus Landomycin 7 AAK57525 Streptomyces sp. Rubromycin Angucycline 8 ADI71443 Amycolatopsis orientalis BE-7585A 9 AGO50610 Streptomyces lusitanus Grincamycin 10 CAA60569 Streptomyces fradiae Urdamycin A 11 CAH10117 Streptomyces sp. Sch 47554 12 ADB02843 Streptomyces sahachiroi Azicemicin A 13 ACP19353 Micromonospora sp. Saquayamycin Z 14 CBH32088 Streptomyces albaduncus Chrysomycin 15 CAA54858 Streptomyces griseus Griseusin Naphthoquinone 16 AAC18107 Streptomyces roseofulvus Frenolicin 17 ACI88861 Streptomyces sp. Alnumycin 18 AAF81728 Streptomyces maritimus Wailupemycin B 19 BAC79044 Streptomyces sp. Medermycin 20 CAA45043 Streptomyces coelicolor Actinorhodin 21 AAD20267 Streptomyces arenae Naphthocyclinone 22 P16540 Streptomyces Granaticin violaceoruber 23 CAA61989 Streptomyces argillaceus Mithramycin Aureolic acid 24 CAE17527 Streptomyces griseus Chromomycin 25 ADG86315 Streptomyces sp. A-74528 26 ------Streptomyces griseus Fredericamycin 27 CAM58798 Streptomyces sp. Benastatin Pentangular 28 ADB23391 Micromonospora TLN-05220 Polyphenol echinospora 29 AAG03067 Streptomyces collinus Rubromycin 30 AAM33653 Streptomyces sp. Griseorhodin A 80

Chapter # 4 Results and Discussion

31 ADE22315 Streptomyces flavogriseus Xantholipin 32 CAM34345 Streptomyces tendae Lysolipin 33 BAA82309 Actinomadura Pradimicin A verrucosospora 34 AHF72794 Salinispora pacifica Lomaiviticin 35 ABC00726 Streptomyces olindensis Cosmomycin 36 AAA65206 Streptomyces peucetius Doxorubicin 37 AAA87618 Streptomyces sp. Daunorubicin 38 AAF70106 Streptomyces galilaeus Aclacinomycin A 39 AGZ78377 Streptomyces sp. Nivetetracyclate Anthracycline B 40 CAJ42320 Streptomyces Steffimycin steffisburgensis 41 AHA81977 uncultured bacterium Arimetamycin A 42 CAA12017 Streptomyces nogalater Nogalamycin 43 ABX71114 Streptomyces rishiriensis Lactonamycin 44 CAP12600 Streptomyces olivaceus Elloramycin Naphthacenequinone 45 AAA67515 Streptomyces glaucescens Tetracenomycin C 46 AFU65894 Dactylosporangium sp. Dactylocycline 47 ADE34518 Streptomyces sp. SF2575 48 P43678 Streptomyces rimosus Oxytetracycline Tetracycline 49 BAB12566 Streptomyces Chlortetracycline aureofaciens 50 AHD25926 Amycolatopsis sulphurea Chelocardin 51 AAP69573 Streptomyces griseoflavus Gilvocarcin Gilvocarcin like 52 ACN64834 Streptomyces Polyketomycin Tetracyclic quinone diastatochromogenes 53 AAP85362 Streptomyces griseoruber Hedamycin Pluramycin 54 CAE51174 Streptomyces Resistomycin Resistomycin like resistomycificus 55 AAA02833 Streptomyces halstedii ------56 CAA39408 Streptomyces coelicolor ------57 BAB69165 Streptomyces avermitilis Avermectin 58 AAA26726 Streptomyces curacoi Curamycin Spore pigment 59 AAR83903 Streptomyces ------aureofaciens 60 AAG26879 Streptomyces collinus ------61 NP_824014 Streptomyces avermitilis ------62 NP_416826 Escherichia coli fabB gene Outgroup 4.5.2. Creating and editing the alignment For phylogenetic analysis the alignment quality has as much impact as the phylogenetic methods used and in addition to alignment algorithm, the method used to deal with the

Chapter # 4 Results and Discussion

alignment with great number of problematic regions may have a critical effect on the final phylogenetic tree. Therefore, the selected amino acid sequences of KSα domain of type II PKS were aligned using different software packages including MUSCLE, ClustalX and MAFFT (Katoh et al., 2002). The multiple sequence alignments were compared to find out differences among them and to select the best alignment to be processed for phylogeny. ClustalX is a program of older class which aligns sequences progressively starting with the most similar ones (Thompson et al., 1997). MUSCLE is one of the newer programs to create multiple sequence alignment iteratively and has been considered as more accurate one as it can reoptimize the initial alignment (Edgar, 2004). MAFFT has reduced the CPU time drastically as compared to other existing methods and it has two novel techniques. In the first technique the homologous regions are identified rapidly by the fast Fourier transform (FFM) while the second technique has simplified the scoring system and increased the accuracy of alignments even for those sequences which have large insertions or extensions as well as the sequences of similar lengths but distantly related (Katoh et al., 2002). Once the alignment was created, manual curation was required to avoid artifacts and maximize accuracy for phylogenetic analysis. Different alignments are recommended to test by generating preliminary phylogenetic trees if it is not clear whether the regions in the alignments are important or not for the analysis. Some automated methods are also available such as AltAVisT (Morgenstern et al., 2003) and Gblocks (Talavera and Castresana, 2007) which can perform alignment sensitivity tests and also remove divergent or poorly aligned regions from the alignment but a careful manual inspection of the alignment can never be replaced by these methods. MUSCLE was found to be more accurate for multiple sequence alignment of the selected sequences as they work iteratively and have the ability to reoptimize the initial alignment (Fig 4.16). The cleaned alignments finally, produced better topologies although with lower bootstrap values paradoxically.

Chapter # 4 Results and Discussion

Fig 4.16. Multiple sequence alignment of the selected amino acid sequences of KSα domain of type II PKS using MUSCLE in MEGA 5.05 4.6. Generation and analysis of NaPDoS reference PKS tree The amino acid sequences of 54 α-subunits of type II polyketide antibiotic biosynthesis gene fragments along with 7 polyketide spore pigment gene fragments were used for generating a reference phylogenetic tree for NaPDoS. The reference phylogenetic tree will serve as a basis for the classification of unknown polyketide antibiotic biosynthesis genes. The sequences were obtained for different bacterial strains including 53 Streptomyces, 2 Micromonospora, 2 Amycolatopsis and 1 Actinomadura, Dactylosporangium, Salinispora and uncultured bacterium each (Fig 4.17). The fatty acid biosynthesis pathway gene FabB from E. coli was used as an outgroup (Kauppinen et al., 1988). Maximum Likelihood (ML) method was used

Chapter # 4 Results and Discussion to infer the evolutionary history based on the Dayhoff matrix model (Schwarz and Dayhoff, 1979). Bootstrap values greater than 50% are shown at the nodes (100 = 100%). Scale bar = 20% dissimilarity. The tree with the highest log likelihood (-18341.2674) is shown. Initial tree(s) for the heuristic search were obtained automatically as follows. When the number of common sites was < 100 or less than one fourth of the total number of sites, the maximum parsimony method was used; otherwise BIONJ method with MCL distance matrix was used. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 62 amino acid sequences. All positions containing gaps and missing data were eliminated. There were a total of 332 positions in the final dataset. Evolutionary analyses were conducted in MEGA5 (Tamura et al., 2011). The analysis of distance estimation with overall mean was done. Standard error estimate was obtained by a bootstrap procedure (100 replicates) and using p-distance model. The overall estimate (d) was found to be 0.348 and standard error (S.E) 0.014. The analysis for best protein model for Maximum Likelihood (ML) was also conducted (Table 4.4). Models with the lowest BIC scores (Bayesian Information Criterion) are considered to describe the substitution pattern the best and only 15 best models are listed. For each model, AICc value (Akaike Information Criterion, corrected), Maximum Likelihood value (lnL), and the number of parameters (including branch lengths) are also presented (Nei and Kumar, 2000).

Chapter # 4 Results and Discussion

Fig 4.17. Molecular phylogenetic analysis for KSα subunits of bacterial type II polyketide synthases

Chapter # 4 Results and Discussion

Non-uniformity of evolutionary rates among sites may be modeled by using a discrete Gamma distribution (+G) with 5 rate categories and by assuming that a certain fraction of sites are evolutionarily invariable (+I). Whenever applicable, estimates of gamma shape parameter and/or the estimated fraction of invariant sites are shown. Table 4.4. Maximum Likelihood fits of substitution models S. No. Model Parameters BIC AICc lnL Invariant Gamma 1 WAG+G+F 141 34860 33743 -16730 n/a 0.80378 2 WAG+G+I+F 142 34869 33744 -16729 0.016752 0.84311 3 rtREV+G+F 141 34904 33787 -16752 n/a 0.72867 4 rtREV+G+I+F 142 34913 33788 -16751 0.016071 0.76373 5 JTT+G+F 141 35129 34012 -16864 n/a 0.76808 6 JTT+G+I+F 142 35137 34013 -16863 0.022968 0.81738 7 WAG+G 122 35146 34180 -16967 n/a 0.83768 8 WAG+G+I 123 35155 34180 -16966 0.020937 0.89035 9 JTT+G 122 35266 34300 -17027 n/a 0.82523 10 cpREV+G+F 141 35271 34155 -16936 n/a 0.64735 11 JTT+G+I 123 35274 34300 -17026 0.025735 0.88515 12 cpREV+G+I+F 142 35276 34151 -16933 0.072289 0.71883 13 Dayhoff+G+F 141 35388 34271 -16994 n/a 0.69638 14 Dayhoff+G+I+F 142 35397 34273 -16993 0.014799 0.72389 15 mtREV24+G+F 141 35538 34421 -17069 n/a 0.60291 GTR: General Time Reversible; JTT: Jones-Taylor-Thornton; rtREV: General Reverse Transcriptase; cpREV: General Reversible Chloroplast; mtREV24: General Reversible Mitochondrial. It has been confirmed from molecular phylogenetic analysis that based on antibiotics produced by different bacteria the antibiotic biosynthesis genes occur in separate branches. It was found in another study that spore pigment and antibiotic biosynthesis genes could be separated using amplified fragment of KSα gene. The genes of antibiotic biosynthesis could be placed in different branches of phylogenetic tree on the basis of starter unit whic is used in their biosynthesis (Metsa-Ketela et al., 1999). These are discussed below along with organizations of their biosynthetic genes.

4.6.1. Angucyline Due to presence of an angularly cyclized third ring the benz [a] anthracenes are called angucyclines. With respect to the rest of the molecule the further ring is bended due to the presence of angularly cyclized third ring. Angucyline is the largest and the most clearly separated group of antibiotics and contains genes which are involved in its biosynthesis (Fig 4.18a). The clade includes 14 sequences from different species of bacteria consisting of

Chapter # 4 Results and Discussion

Streptomyces fradiae urdA to Streptomyces sp. strain B1 that contains all of the known genes responsible for angucyclines biosynthesis such as the gene fragments from Streptomyces fradiae, Streptomyces cyanogenus and Streptomyces venezuelae. Micromonospora sp. and amycolatopsis orientalis were also found having gene fragments for the biosynthesis of two different angucylines namely Saquayamycin Z and BE-7585A respectively. The gene cluster analyses of all polyketides of angycycline group showed same expected pattern for minimal PKS genes i.e. KSα, KSβ and ACP subunits (Fig 4.18b). The group of angucycline antibiotics belongs to a biologically active family of microbial natural products which is classified within polyketides of type II (Rohr and Thiericke, 1992). All antibiotics of angycycline group share many features such as aglycone system of tetracyclic benz(a)nthracene (Rohr, 2000). The folding pattern of newly synthesized β-polyketide chains of angucycline members is different from well studied actinorhodin and tetracinomycin C which are also type II polyketides (Rohr and Thiericke, 1992).

Fig 4.18. Phylogenetic and organization of gene clusters of angucyclines (a) clade of angucycline group of antibiotics, (b) organizations of the biosynthesis gene clusters (phylogenetic tree was constructed in MEGA 5.05 and gene cluster analysis was performed using antiSMASH)

Chapter # 4 Results and Discussion

A number of gene clusters have been cloned, sequenced and identified that encode related and biologically active angycyclines such as jadomycin B (Han et al., 1994), urdamycin A (Decker and Haag, 1995), landomycin A (Westrich et al., 1999) and oviedomycin (Lombo et al., 2004). Mauve alignment of all the members of angucycline group of polyketides is showing biosynthetic gene clusters in green blocks (Fig 4.19).

Fig 4.19. Mauve alignment of biosynthetic gene clusters of angucycline group of polyketides. Each colored block is representing different regions/ subclusters. Green colored blocks are representing the biosynthetic gene cluster of all naphthoquinones. The regions which are in reverse complement (inverse) oreientation are markded with red rectangles at

Chapter # 4 Results and Discussion

the centre lines. Completely white areas were not aligned and probably contain sequence elements those are explicit to a particular region in the biosynthetic gene cluster. The average degree of sequence similarity is represented by the height of colour bars. (The analysis was done by ‘Mauve Genome’ available in Geneious software). The length of the bars in green blocks are showing similarity among all the members and vertical line joining all these green blocks showing the similar regions falling beneath each other. It is evident from the length of the bars that the biosynthetic gene clusters are highly similar.

4.6.2. Naphthoquinone Another identifiable group in the phylogenetic tree is the naphthoquinone group which extends from Streptomyces violaceoruber to Streptomyces roseofulvus. This group contains seven strains that produce antibiotics of naphthoquinone class (Fig 4.20a) which are Streptomyces violaceoruber, Streptomyces arenae, Streptomyces coelicolor, Streptomyces sp. (Strain AM-7161), Streptomyces maritimus, Streptomyces sp. (Strain CM020) and Streptomyces roseofulvus. The other only strain that also produce naphthoquinone antibiotic, Streptomyces griseus forms its own branch on the molecular phylogenetic tree.

Fig 4.20. Phylogenetic and organization of gene clusters of naphthoquinones and pentangular polyphenoles I (a) phylogenetic analyses, (b) organizations of the biosynthesis

Chapter # 4 Results and Discussion

gene clusters (phylogenetic tree was constructed in MEGA 5.05 and gene cluster analysis was performed using antiSMASH)

However, the separation of both naphthoquinones is feasible in the sense that other naphthoquinones form a shorter polyketide backbone consisting of 18 carbons than the S. griseus which formed a longer polyketide chain of 20 carbons (Yu et al., 1994). The organizations of biosynthetic gene clusters for members of both naphthoquinone groups are not showing same pattern of minimal PKS as well as other genes (Fig 4.20b). Aromatase is found in most of the gene clusters of naphthoquinonce II group but not in naphthoquinone I.

Fig 4.21. Mauve alignment of biosynthetic gene clusters of napthoquinone group of polyketides. Each colored block is representing different regions/ subclusters. Purple colored blocks are representing the biosynthetic gene cluster of all naphthoquinones. Completely white areas were not aligned and probably contain sequence elements those are explicit to a particular region in the biosynthetic gene cluster. The average degree of sequence similarity is represented by the height of colour bars. (The analysis was done by ‘Mauve Genome’ available in Geneious software). Medermycin, actinorhodin and granaticin like aromatic antibiotics produced by Streptomyces are known as Benzoisochromanequinone (BIQs) (Ichinose et al., 1998a) however, Metsa- Ketela et al. (2002) named them as naphthoquinones. A number of biosynthetic problems have been studied in BIQs concerning the glycosylated BIQs for instance deoxysugar

Chapter # 4 Results and Discussion biosynthesis in granaticin and medermycin (Trefzer et al., 1999), PKS (Hopwood, 1997) and post-PKS modification (Rix et al., 2002). The bars in the purple blocks of Mauve alignment are showing that all the biosynthetic gene clusters for naphthoquinone group of antibiotics with the positions of all individual genes are highly similar (Fig 4.21).

4.6.3. Anthracycline Anthracycline is another group identified in the phylogenetic group and the producers of anthracycline have formed two different clades in the tree (Fig 4.22a). S. nogalater, S. steffisburgensis along with an uncultered bacterium migrated separately from other members of anthracycline. The other producers of anthracycline that are represented in the KS tree S. pecifica, S. olindensis, S. peucetius, S. galilaeus along with two Streptomyces sp. formed the second clade. In our KS tree the S. galilaeus that is aclacinomysin producer and S. peucetius which is a producer of another anthacycline are falling under the same clade which is in argument since the pathways of antibiotics biosynthesis by these organisms proceed through aklavinone (Strohl et al., 1997) that is a common intermediate compound. But it is somewhat surprising to find that both organsims of anthracycline producers were present in two separate clades studied by Metsa-Ketela et al. (2002).

From the bacterial aromatic polyketides anthracycline is another exceptionally important family which includes the most important chemotherapy agents such as doxorubicin and daunorubicin (Hutchinson, 1997). Steffimycin (Gullon et al., 2006) and aranciamycin (Luzhetskyy et al., 2007) are other members of anthracycline class whose biosynthetic gene clusters were reported. In the biosynthesis of anthracycline the tetracyclic aglycon is derived from a C9-reduced decaketide backbone while the cyclization of first three rings of anthracycline class of antibiotics is similar to that of tetracycline class in which cyclase- mediated cyclizations of C7-C12 and C5-C14 are followed by spontaneous C3-C16 cyclization and third ring dehydration. Quinone-forming monooxygenases are involved in the oxidation of second ring of anthracyclines to afford the anthraquinone portion that is present in all anthracyclines (Zhou et al., 2010). Organization studies for biosynthetic gene clusters of both anthracyclines groups showing some differences in their clusters (Fig 4.22b). Acyl transerases were observed in almost all members of anthracycline II but not in anthracycline I. In anthracycline I all polyketides have regular pattern for minimal PKS whereas in

Chapter # 4 Results and Discussion anthracycline II Aclacinomycin A and Nivetetracyclate B showing the regular pattern for minimal PKS. ACP is not falling right after KSβ subunit of minimal PKS in most of the members of anthracycline II. For example, in the biosynthetic gene cluster of daunomycin the ACP gene was observed about 7 kb upstream of the KSα and KSβ genes (Lomovskaya et al., 1999).

Fig 4.22. Phylogenetic and organization of gene clusters of anthracyclines, naphthoquinones, pentangular polyphenoles II, aureolic acid, tetracyclic quinones and anthracycline II (a) phylogentic analyses, (b) organizations of the biosynthesis gene clusters (phylogenetic tree was constructed in MEGA 5.05 and gene cluster analysis was performed using antiSMASH) Mauve alignment for anthracycline group is also showing that nogalamycin, arimetamycin A, nivetetracyclate B and aclacinomycin A have similar organizations for their polyketide biosynthetic gene clusters (Fig 4.23). It is also evident from the mauve alignment of biosynthetic gene clustets for daunorubicin, doxorubicin and cosmomycin that gene for acyl carrier protein (ACP) is not falling right after chain length factor (CLF). The bars are showing the similarity among the entire gene clusters which is endorsing that the unknown

Chapter # 4 Results and Discussion

gene falling right after chain length factor is actually encoding acyl carrier protein in the biosynthesis of lomaiviticin.

Fig 4.23. Mauve alignment of biosynthetic gene clusters of anthracycline group of polyketides. Each colored block is representing different regions/ subclusters. Red colored blocks are representing the biosynthetic gene cluster of all naphthoquinones. The regions which are in reverse complement (inverse) oreientation are markded with red rectangles at the centre lines. Completely white areas were not aligned and probably contain sequence elements those are explicit to a particular region in the biosynthetic gene cluster. The average degree of sequence similarity is represented by the height of colour bars. (The analysis was done by ‘Mauve Genome’ available in Geneious software). 4.6.4. Naphthacenequinone and tetracyclic quinone The antibiotics of naphthacenequinone and tetracyclic quinone producers (Fig 4.22a) were placed on separate branches by the phylogenetic analysis and only one clade of each class is there in the analysis. However, because there is only one reported sequence from Tetracyclic quinone producer S. diastatochromagenes that is producing polyketomycin (Daum et al., 2009) therefore, in making prediction with molecules of this group caution should be used. Elloramycin and tetracenomycin C from S. olivaceus and S. glaucescens respectively showed more similarity with each other than lactonamycin produced by S. rishiriensis which is also

Chapter # 4 Results and Discussion

apparent from the organizations of their PKS gene clusters. Elloramycin and tetracenomycin C are showing regular organizations for minimal PKS gene clusters whereas the organization of lactonamycin gene cluster is an unusual one as for as the position of ACP is concerned which is not present at its usual position right after chain length factore (Fig 4.22b). The presence of two genes which encode ACPs is another unique feature of lactonamycin gene cluster. Only the gene designated by Lct24 of these ACPs exhibits strong similarity with ACPs of other type II PKSs which suggests that Lct26 and other ACPs may have a function of lactonamycinone biosynthesis initiation with glycine derivative. The hypothesis is strengthened by the fact that gene clusters of R1128 and frenolicin polyketides contain an additional ACP domain which plays a role for the initiation of polyketide biosynthesis with a different starter unit (Tang et al., 2003). Hence, it is suggested that the activation of a gycine derivative by Lct28 mighty have involved by the initial stages of biosynthesis of lactonamycinone and the activated amino acid is attached to Lct 26 as a thioester. Furter, the amino acid is transered to Lct31 ketosynthase by thioester exchange.

Fig 4.24. Mauve alignment of biosynthetic gene clusters of naphthacenequinone group of polyketides. Each colored block is representing different regions/ subclusters. Green colored blocks are representing the biosynthetic gene cluster of all naphthacenequinone. Completely white areas were not aligned and probably contain sequence elements those are explicit to a particular region in the biosynthetic gene cluster. The average degree of sequence similarity is represented by the height of colour bars. (The analysis was done by ‘Mauve Genome’ available in Geneious software).

Chapter # 4 Results and Discussion

The presence of thioesterase (Lct34) is another unusal feature in the organization of biosynthetic gene cluster of lactonamycin. The domains of thioesterase and stand-alone thioesterases are mostly found with type I polyketide synthases in an association but the presence of these thioesterases with gene clusters of type II polyketide synthases is found to be very rare (Mochizuki et al., 2003). The bars in the green blocks of biosynthetic gene clusters of napththacenequinone are proving that gene cluster for lactonamycin is different from those of elloramycin and tetracenomycin C (Fig 4.24). Lactonamycin has wider region in white as compared to other two antibiotics that is showing that there is no similarity in this region.

4.6.5. Pentangular polyphenols and Aureolic acids Two separate clades of pentangular polyphenols were observed in the phylogenetic analysis i.e. pentangular polyphenol I and II. Three Streptomyces along with one Micromonospora sp. were placed in pentangular polyphenol I (Fig 4.19a) while four Streptomyces along with one Actinomadura sp. were falling in a separate clade pentangular polyphenol II (Fig 4.22a). Fredericamycin A produced by S. griseus is considered as the longest bacterial aromatic polyketide from the class pentangular polyphenol. Wendt-Pienkowski et al. (2005) reconstituted the entire pathway of fredericamycin A in Streptomyces albus. The biosynthetic gene cluster is showing some incongruity as ketosynthase gene contains two cysteines i.e. Cys170 and Cys171 at the active sites of presumed KSR. A highly conserved sequence STGCTSGLD is observed in all other KSRs around the active site of Cys amino acid in contrast to SSGCCAGID for ketosynthase gene of fredericamycin. Most of the biosynthetic gene clusters from pentangular polyphenol II (Fig 4.22b) are showing aromatases in their organizations whereas these are not observed in polyketides of pentangular polyphenol I (Fig 4.20b).

Aureolic acids are another group of polyketides and defined as linearly-fused and tricyclic aromatic polyketides. It has been revealed that the biosynthesis of compounds of aureolic acid family go through an intermediate of tetracycline and naphthacene (Zhou et al., 2010). In the phylogenetic analysis the two aureolic acids i.e. mithramycin produced by S. argillaceus and chromomycin from S. griseus are not falling in the same clade (Fig 4.22b). Mithramycin is showing more similarity with polyketomycin of tetracyclic quinone class.

Chapter # 4 Results and Discussion

Mithramycin is the best studied example among aureolic acids (Trefzer et al., 2002). It was first proposed that mithramycin is being derived from a tetracenomycin-like scaffold that is based on putative last-ring cyclase herertologous expression from biosynthetic pathway of mithramycin in S. glaucescens Tu49 (Kunzel et al., 1997).

Successively, from a genetically modified strain of S. argillaceus premithramycin B was isolated which is a key intermediate (Prado et al., 1999). This was concluded from the structural similarity between aglycon of premithramycin B and oxytetracycline that mithramycin was more likely to be derived from a cyclization pathway of tetracycline-like and infact a number of highly homologous enzymes are shared by the biosynthetic pathways of mithramycin and oxytetracycline such as cyclases and tailoring enzymes (Zhang et al., 2006). It was identified that premithramycin B was transformed into an aureolic acid structure by oxygenase MtmOIV through fourth ring Baeyer-Villiger oxidative cleavage (Beam et al., 2009).

Fig 4.25. Mauve alignment of biosynthetic gene clusters of pentangular polyphenols group of polyketides. Each colored block is representing different regions/ subclusters. Purple colored blocks are representing the biosynthetic gene cluster of all pentangular

Chapter # 4 Results and Discussion

polyphenols. The regions which are in reverse complement (inverse) oreientation are markded with red rectangles at the centre lines. Completely white areas were not aligned and probably contain sequence elements those are explicit to a particular region in the biosynthetic gene cluster. The average degree of sequence similarity is represented by the height of colour bars. (The analysis was done by ‘Mauve Genome’ available in Geneious software). The enzyme homologue to cyclase MtmOIV was also identified in the biosynthetic gene cluster of an aureolic acid i.e. chromomycin A3 (Menendez et al., 2004) derived from prechromomycin B which is a tetracylic intermediate (Menendez et al., 2006). Genes for ACP are not found right after CLF in genome alignment visualizations of griseorhodin A and xantholipin (Fig 4.25) where as bars are representing that all other gene clusters for pentangular polyphenols are highly similar and have regular patterns for iterative type II polyketide synthase.

4.6.6. Tetracyclines The importance of tetracylines is very clear from the fact that in the last century, the most important antibiotics discovered were of tetracycline class. Because of their broad-range activities these antibiotics were extensively used to treat infections caused by both Gram- positive and Gram-negative bacteria. Five antibiotics from tetracycline class were included in the phylogenetic analysis (Fig 4.26a). Chelocardin was isolated from A. sulphurea, dactylocycline from Dactylosporangium sp. and SF2575, oxytetracycline and chlortetracycline were produced by different Streptomyces sp. with chlortetracyclline and oxytetracycline as the best known examples. Biosynthetic gene clusters are showing different organizations for all antibiotics of tetracycline class (Fig 4.26b).

Chapter # 4 Results and Discussion

Fig 4.26. Phylogenetic and organization of gene clusters gilvocarcin-like, tetracyclines and pluramycin. (a) phylogentic analyses, (b) organizations of the biosynthesis gene clusters (phylogenetic tree was constructed in MEGA 5.05 and gene cluster analysis was performed using antiSMASH) When the biosynthetic steps were reconstitured systematically in S. coelicolor strain CH999 and the cyclization steps which lead to naphthacene core formation were studied it was observed that only two cyclases are necessary for the cyclization of all four rings in the presence of an amide as a starter unit (Zhang et al., 2008). Mauve alignment is also endorsing that chelocardin and chlortetracycline antibiotics have traditional pattern for iterative type II polyketide biosynthetic gene cluster. Genes encoding KSα subunit and ACP are found at their regular positions but CLF was not identified in the gene cluster of oxytetracycline. The gene encoding ACP is not falling right after CLF in the gene cluster of dactylocycline and there is a distance of about 7,000 bp between ACP and other subunits of type II KS (Fig 4.27).

Chapter # 4 Results and Discussion

Fig 4.27. Mauve alignment of biosynthetic gene clusters of tetracycline group of polyketides. Each colored block is representing different regions/ subclusters. Red colored blocks are representing the biosynthetic gene cluster of all pentangular polyphenols. Completely white areas were not aligned and probably contain sequence elements those are explicit to a particular region in the biosynthetic gene cluster. The average degree of sequence similarity is represented by the height of colour bars. (The analysis was done by ‘Mauve Genome’ available in Geneious software). 4.6.7. Resistomycin-like Resistomycin was also placed on unique branch (Fig 4.28a) by the phylogenetic analysis because it has a discoid structure that is exceptional to all other bacterial aromatic polyketides. In the pathway of resistomycin three putative cyclaes are present i.e. RemI, RemF and RemL (Jakobi and Hertweck, 2004) and all three cyclases were shown to be essential using genetic inactivation and heterologous reconstitution combination as they have to function collectively for the generation of unique discoid structure. The cyclases are proposed to form a multienzyme complex with the minimal PKS. This observation has been reported in the biosynthesis of pradimicin A along with synergistic actions of cyclases which suggests that multienzyme complexes would be a widely adopted strategy for bacterial PKSs to direct the reactive backbones regioselective cyclization (Fritzsche et al., 2008). The biosynthetic gene cluster of resistomycine is showing two methyltransferases (Fig 4.28b) while the organization of minimal PKS is a usual one.

Chapter # 4 Results and Discussion

(a)

(b)

Fig 4.28. Phylogenetic and organization of gene clusters of spore pigments and resistomycin-like. (a) phylogenetic analysis (b) organization of the biosynthesis gene clusters of resistomycine (phylogenetic tree was constructed in MEGA 5.05 and gene cluster analysis was performed using antiSMASH) 4.6.8. Spore pigment There is clearly a separable clade from those of antibiotic biosynthesis genes that belongs to sequences of spore pigments (Fig 4.28a). In the early parts of the routes of biosynthesis of these two different classes of compounds the major difference is due to the fact that spore pigments have longer size of polyketide backbone (C24) than most of the antibiotics which has evaded the chemical identification (Yu et al., 1998). The results for 10 distinct amino acids were reocognized the reason of great distance in the phylogenetic analysis of spore pigments and antibiotic biosynthesis genes. The sequence of amino acids in the spore pigment clade was found highly conserved upto 93 to 100% which was variable and dissimilar in antibiotic clades. Moreover, in two classes the structural and chemical nature of these amino acids was also found different in a number of cases. The sequences of two strains i.e. TA21 and TA83 of non-Streptomyces are considered to be migrated between spore pigment and antibiotic sequences and interestingly, the strains contain amino acid signature sequences for both groups but it is not clear to which group these signature sequences belong (Metsa-Ketela et al., 2002). In the current study, not only a phylogentic tree for KSα subunit of type II polyketide synthase was generated to use as a reference tree in the upcoming version of NaPDoS but the anomalies in the falling of antibiotics of same group in different clades were also discussed and justified through biosynthetic gene cluster analyses. The antibiotics of type II PKS have

100

Chapter # 4 Results and Discussion been resolved in different groups in the reference phylogenetic tree and the previous reference tree of NaPDoS 1.0 will be replaced with this tree in NaPDoS 2.0. 4.7. The Natural Product Domain Seeker (NaPDoS 2.0) NaPDos (http://npdomainseeker.ucsd.edu/) is a publically freely availabale web tool which was originally created to analyse, detect and classify different domains from KS and C families and data of amino acid sequences where the query data would be genes, PCR products, genomes, metagenomes or simple contigs. The current limits for query size in NaPDoS 1.0 are 30 MB and 50,000 individual sequences. For new users a comprehensive tutorial is also given on the website that helps how to use this tool which has been executed through a web interface (Fig 4.29) which follows the bioinformatic strategy (Fig 2.15).

In the current version of NaPDoS (NaPDoS 1.0) there are 459 and 190 sequences for KS and C domains respectively which are derived from different biosynthetic pathways i.e. 20 NRPS, 66 PKS, 8 PKS/NRPS hybrid and 5 fatty acid synthase (FAS). Query sequences are BLAST against these sequences present in the reference database of NaPDoS. The reference sequences can be obtained and downloaded from NaPDoS webpage and all the major classes of type I and II KS domains can be incorporated which have been reported in literature (Hertweck, 2009; Jenke-Kodama and Dittmann, 2009). The database which has been manually curated is updated periodically in the form of modular architectures and their biochemical features which would be revealed for each type of domain. The strategy of NaPDoS as primary output for all types of studies such as identification of query sequences, best match with reference database, identity percentage, length of alignment, e-value, product and biosynthetic pathway classification which is related to the best match.

The sequences of KS domain obtained from the input data will serve as output in raw format or aligned with the best sequences obtained from BLAST matches from the reference database. A NaPDoS independent BLAST for those output domain sequence(s) which are not matched with the reference database of NaPDoS is strongly suggested. A phylogenetic tree construction is higly recommended to get final classification for sequence of each domain particularly for the sequence(s) which show very low sequence identity percentage with the database. If that option is selected during the analysis, a profile alignment is created showing

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Chapter # 4 Results and Discussion

the query sequences combined with the sequences obtained from reference database which are carefully curated and aligned.

Query Type

PCR or CDS Protein Genomic (Nucleic acid) (Amino acid) (Nucleic acid)

6-frame translation BLASTS vs Database

Size filter

Select domain BLASTP vs HMM search matches Database

Trim amino Align amino Tree building acid sequences acid sequences

Fig 4.29. NaPDoS working strategy

A phylogenetic tree is then generated using this alinment and the tree needs to be interpreted manually for establishing final classification of each query sequence. In the perspective of a phylogenetic tree the interpretation of sequences is predominantly imperative given that strategy of NaPDoS is set to low stringency intentionally in an effort to discover all possible matches from KS and C domains. Therefore, the homologous sequences of KSs which are

102

Chapter # 4 Results and Discussion

associated with the biosynthesis of fatty acid can be detected and these sequences can be classified easily on the basis of phylogenetic analysis.

The incorporation of DNA sequence data due to rapid advances in the technologies of DNA sequencing is providing extraordinary opportunities for natural product discovery process. Bioinformatic tools are required for effective use of this information which can investigate large datasets rapidly in the perspective of an inclusive array of complex biosynthetic models. A number of outstanding bioinformatic tools are available to study secondary metabolism on exact gene and operon assembly (Bachmann and Ravel, 2009; Medema et al., 2011) and to get through the construction of modular and highly repetitive nature of many genes which are taking part in secondary metabolism (Udwary et al., 2007). In metagenomic investigates of complex microbial communities this challenge can become problematic.

For the biosynthetic genes the use of domain sequence tags as proxies in which they reside is basically established on highly informative and well recognized phylogenetic relationships that they maintain. Such relationships provide the basis for NaPDoS classification system and gave a prompt mechanism to define biosynthetic gene abundance of bacterial secondary metabolites and diversity within an environmental sample or a genome. NaPDoS can analyze short sequence tags (e.g. 600 bp) efficiently and hence next generation sequence assemblies, minimum converage are well appropriate for this tool. To direct more widespread sequencing exertions or targeted operon assembly the obtained estimates having biosynthetic potential can be used. In cases if the query sequences give close mataches having 90% sequence identity with the domains which have been derived experimentally from characterized biosynthetic pathways, the prediction about the structural class of bacterial secondary metabolite(s) has been shown possible (Freel et al., 2011). The ability to adjust internal parameters for BLAST and low stringency of Hidden Markov Model (HMM) searches in NaPDoS increase the chances of better detection of highly different KS and C domains which may or may not be related to secondary metabolism in bacteria (e.g. fatty acid biosynthesis) and hence there is a need that all results should be examined very carefully. When the number of experimentally identified and well characterized different bacterial biosynthetic pathways increases this methodology will certainly give an progressively effective method to de-replicate and identification of strains which possess the highest potential of producing known secondary metabolites. 103

Chapter # 4 Results and Discussion

It has been proven that the mechanistic variety of non-ribosomal peptide and polyketide assembly is far bigger than recongnized ones (Wenzel and Muller, 2005). Therefore, NaPDoS classification system can be expected to grow as new phylogenetic lineages connected to specific enzyme architectures and biochemical functions. Considerable preliminary evidences are there that the classes which have been defined here would be further explained whenever some more characterized sequence data will be collected experimentally. For example, deeply branching KS domains which were obtained from CurC and JamG are included in Type II clade in reference phylogenetic tree of NaPDoS 1.0. These domains were predicted that they are involved in decarboxylation reactions rather than condensation reactions (Edwards et al., 2004; Chang et al., 2004).

Even though oversimplification potential of current classification system of NaPDoS 1.0 it still gives a useful approach for the estimation of functional types and numbers of biosynthetic genes which are found in complex query data sets. In spite of poor assembly of NaPDoS 1.0 among four draft genome sequences of Salinispora a huge number and variety of KS domains were observed. From these domains, seventeen were not detected in any of two complete genomes of Salinispora which was an evident that the considerable biosynthetic variability might have occurred among closely related strains.

The paradigms of customary natural product discovery have become progressively ineffective (Li and Vederas, 2009) and methods which captilize on access to DNA sequence data are rapidly taking their places (Davies, 2011). NaPDoS capitalizes on phylogenetic relationships which are well-established for KS domains. It provides on the basis of small sequence tags a rapid approach for making good understandings of bacterial secondary metabolism. The sequence tags have been obtained from different types of data such as poorly assembled and next generation datasets. The investigation of sequence space and identification of new domain families are foremost applications of NaPDoS where these new domain families have great probability for being related to new techniques of biosynthesis of bacterial secondary metabolites. The discovery of new biochemistry will be facilitated through prioritizing these domain families for their experimental characterization and finally they will represent a rationale method for the discovery of bacterial secondary metabolites.

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Chapter # 4 Results and Discussion

At present, the current version of NaPDoS (NaPDoS 1.0) has been optimized to identify and classify bacterial PKS and NRPS genes. However, the tool can also identify KS and C domains from eukaryotes as well provided their common evolutionary history with those of prokaryotic homologs but it should be mentioned here that the results acquired for non- bacterial sequences need to be inferred with great care because the reference database of NaPDoS 1.0 is not properly populated with those sequences to give a strong system of classification. Therfore, there was a need that NaPDoS should be expanded (i.e. upgraded to NaPDoS 2.0) to comprise surplus eukaryotic sequences along with subgroups within PUFA and FAS families and to add more groups in KS to get better resolution. In future, the additional goals will be the addition of type III PKSs that are initially found in plants and are not well known for their occurance in bacteria in a broad range (Moore and Hopke, 2001). Type III PKSs are associated indistinctly to types I and II PKSs and therefore, a discrete alignment and study approach is required. It will also be a convincing approach if additional families of secondary metabolites such as terpenoids, alkaloids and ribosomal peptides will be included in the database of NaPDoS.

105

SUMMARY

Humans have relied on nature throughout their ages to cater for their basic needs including medicines to cure a wide spectrum of diseases. Plants have formed the basis for sophisticated systems of traditional medicines. The structurally diverse metabolites of microorganisms and medicinal plants have been the main sources of pigments, flavors, dyes, medicines and even poisons since the beginning of human civilization. For therapeutic agents many of the presently known lead compounds are natural products or their derivatives. Ethnomedicinal studies play a vital role to discover new drugs from indigenous medicinal plants. Green pharmaceuticals are getting popularity and extraordinary importance because vast opportunities for new drug discoveries are provided by the unmatched availability of chemical diversity and natural products either as pure compounds or as homogenous plant extracts. Therefore, in recent years the demand for herbal medicines and several natural products from a variety of plant species is consistently increasing.

In the present study biochemical profiling of crude methanolic extracts of twelve selected medicinal plants was done using liquid chromatography coupled with mass spectrometry. The qualitative phytochemical analysis of these medicinal plants confirmed the presence of various important secondary metabolites of different classes such as flavonoids, sesquiterpene lactones, isoflavones, phenolics and nonalkaloids. Antibacterial activities of these medicinal plants were also studied by agar diffusion assay and the activities were proved to be significant in some plant extracts against E. coli while other extracts showed variable responses. DMSO was used as a negative control which showed no effect on the growth of E. coli. Methanol extracts of Suaeda fruticosa showed significant antibacterial activity while of Isodon rugosus, Solanum surattense, Fragaria bucharia, Trillium govanianum and Dryopteris ramosa showed considerable inhibition. The results were found to be significantly different from the controls in each case (P<0.01). The results demonstrate that these extracts have strong antibacterial activities towards E. coli.

Cancer cell cytotoxicities of these medicinal plants were also studied against the human

colon carcinoma cell line HCT-116. Cytotoxicity was expressed as IC50 value which is the concentration of extract needed to inhibit cell growth by 50%. Trillium govanianum, Isodon rugosus and Dryopteris ramosa showed significant cytotoxic activities. The findings of this

106

Summary

study support the folkloric usage of these studied medicinal plants and confirmed the antibacterial and cytotoxic activities possessed by some of the plant extracts which can be used as active agents in new drugs to combat different diseases. Therefore, the indigenous peoples from these areas should be trained regarding the cultivation of these important medicinal plants on commercial basis, the trade and marketing of these medicinal plants which would ultimately generate extra sources of income for these people and will also reduce pressure on the extraction of these valuable medicinal plants.

In second part of this research, comparative study of bacterial polyketide synthases was done. In current version of NaPDoS, type II PKSs are not fully resolved therefore, for better resolution of type II PKSs, a reference phylogenetic tree for KSα domain was generated in this study with more phylogenetic groups. For phylogenetic analysis the alignment quality has as much impact as the phylogenetic methods used. In addition to alignment algorithm, the method used to deal with the alignment with great number of problematic regions may have a critical effect on the final phylogenetic tree. The amino acid sequences of 54 α- subunits of type II polyketide antibiotic biosynthesis gene fragments along with 7 polyketide spore pigment gene fragments were used for generating a reference phylogenetic tree for upcoming version of NaPDoS (NaPDoS 2.0). Organizations of biosynthetic gene clusters of KSα for selected polyketides were also studied and ambiguities among different clades of same antibiotic groups were found out. A number of new groups of type II PKS have been introduced in the reference phylogenetic tree such as angucycline, naphthoquinone, anthracycline, naphthacenequinone, tetracyclic quinone, pentangular polyphenols, aureolic acid, tetracycline,and resistomycin-like. This reference phylogenetic tree will serve as a basis for the classification of unknown polyketide antibiotic biosynthesis genes.

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