Burch.] DC Ex Meissn.: an ETHNO

IN VITRO ANTIMICROBIAL AND ANTIOXIDANT POTENTIAL OF

ENDOPHYTIC ACTINOBACTERIA ASSOCIATED WITH

HARPAGOPHYTUM PROCUMBENS [Burch.] DC ex Meissn.: AN ETHNO

MEDICINAL PLANT OF SOUTHERN AFRICA.

A THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF

MASTER OF SCIENCE BY THESIS IN MICROBIOLOGY

THE UNIVERSITY OF NAMIBIA

MAGDALENA ELIZABETH LANG (BLIGNAUT)

201201456

APRIL 2021

MAIN SUPERVISOR: DR JD UZABAKIRIHO (UNIVERSITY OF NAMIBIA)

CO-SUPERVISOR: DR. S LOUW (UNIVERSITY OF NAMIBIA)

ABSTRACT

The present study was designed to determine the taxonomic diversity, metabolic activity, structure elucidation, and screening of genes involved in antimicrobial and antioxidant activity of the endophytic actinobacteria associated with Harpagophytum procumbens. Six lateral tubers collected from the Hardap (A) and Khomas (B) regions were used. After primary screening, 23 of 140 isolate extracts of ethyl acetate, chloroform and methanol were tested for their antimicrobial potential against 8 microorganisms and their MIC was determined. The ethyl acetate extracts produced significantly better results in all tests (P = 0.000). Ethyl acetate extracts of isolate B44 (Curtobacterium sp.) demonstrated a significant broad-spectrum potential against 7 out of 8 of the test organisms. The 23 isolates were identified by using 16S rRNA sequencing and phylogenetic analyses and were taxonomically grouped into 6 families and 7 genera: Streptomyces (̴52%), Agromyces (̴4%), Nocardiopsis (̴4%), Rubrobacter (̴4%), Patulibacter (̴13%), Rhodococcus (̴4%), Curtobacterium (̴4%) and 3 unidentified strains (̴13%). PKS-I (found in 61% of isolates) and NRPS (found in 13% of isolates) gene clusters were also amplified. From the four antioxidant tests carried out, ethyl acetate extracts of A36 (Streptomyces sp.) had the highest phenolic content (1.993 ± 0.004) and total antioxidant activity (0.258±0.001), B12 (Streptomyces sp.) had the highest radical scavenging activity (95%), while B43 (unidentified) had the highest total reducing power (0.849 ± 0.003). Ethyl acetate solvent extracts tested for their ability to protect DNA from degradation found that 61% of the extracts had DNA damage protection potential. When testing for industrially important enzymes, 74% tested positive for urease, 83% for gelatin degradation, 74% for protease, 65% for starch degradation, 48% for indole-acetic acid, and 96% for catalase. Furthermore, optimal growth conditions for antimicrobial production of the best overall performing strains (B12, B44 and A65) were evaluated and a multiple regression analysis was carried out (F(6,1451) = 293.036, p = 0.000, R2 = 0.548). GC/MS analysis was carried out on extracts B12, B44 and A65 and compounds were tentatively identified as alkanes (56%) and unknown compounds (37%), with B12 and A65 also containing octadecenamide. From the present study, it is possible to conclude that these endophytic actinobacteria associated with H. procumbens could be a promising source of bioactive compounds and warrant further studies.

Keywords: actinobacteria, H. procumbens, antimicrobial, antioxidant, GC-MS

LIST OF PUBLICATION(S)/CONFERENCE(S) PROCEEDINGS

1. Lang, ME. and Uzabakiriho, JD. Endophytic actinomycetes associated with Harpagophytum procumbens’ antimicrobial potential. Poster presented at the National Students’ Research Symposium 2019. Held in Windhoek, Namibia October 2nd to October 3rd.

2. Lang, ME; Sibanda, T; Louw, S and Uzabakiriho, JD. Antioxidant and DNA damage protective activities of selected endophytic actinobacteria isolated from Harpagophytum procumbens: A Kalahari Desert adapted plant. Submitted for publication in the Archives of Microbiology in November 2020.

3. Lang, ME; Louw, S and Uzabakiriho, JD. Phylogenetic profiling and antimicrobial potential of the endophytic actinobacteria isolated from Harpagophytum procumbens: A Southern African medicinal plant. In preparation for publication in December 2020.

4. Lang, ME; Louw, S and Uzabakiriho, JD. Qualitative analysis of bioactive constituents from endophytic actinobacteria isolated from Harpagophytum procumbens using thin layer chromatography (TLC) and gas chromatography- mass spectrometry (GC-MS). In preparation for publication in December 2020.

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TABLE OF CONTENT ABSTRACT ...... ii LIST OF PUBLICATION(S)/CONFERENCE(S) PROCEEDINGS ...... iii TABLE OF CONTENT ...... iv LIST OF TABLES ...... vii LIST OF FIGURES ...... ix LIST OF ABBREVIATIONS AND/OR ACRONYMS ...... xiii ACKNOWLEDGEMENTS ...... xv DEDICATION ...... xvi DECLARATION ...... xvii CHAPTER 1: INTRODUCTION ...... 1 1.1 Background of the study ...... 1 1.2 Statement of the problem ...... 2 1.3 Objectives of the study ...... 3 1.4 Significance of the study ...... 4 1.5 Limitations of the study ...... 4 1.6 Delimitations of the study ...... 5 REFERENCES ...... 6 CHAPTER 2: LITERATURE REVIEW ...... 8 2.1 Endophytic actinobacteria as a promising source of secondary metabolites 8 2.1.1 Host plant interaction effect on secondary metabolite production...... 8 2.1.2 Diversity of secondary metabolites from endophytic actinobacteria and their antimicrobial and antioxidant properties...... 10 2.1.3 Enzymatic activity of actinobacteria and the production of important chemicals ...... 25 2.1.4 Biosynthesis of natural secondary metabolites (Non ribosomal peptides, Polyketides, hybrid non-ribosomal peptides/Polyketides) ...... 26 2.2 Harpagophytum procumbens: A Southern African endemic plant with therapeutic potential ...... 30 2.2.1 Botanical description and distribution ...... 30 2.2.2 Ethnomedicinal use of H. procumbens ...... 33 2.2.3 Bioactivity of H. procumbens extracts ...... 33 2.3 Rationale for plant selection ...... 36 REFERENCES ...... 37 CHAPTER 3: PHYLOGENETIC PROFILING AND ANTIMICROBIAL POTENTIAL OF THE ENDOPHYTIC ACTINOBACTERIA ISOLATED FROM HARPAGOPHYTUM PROCUMBENS: A SOUTHERN AFRICAN MEDICINAL PLANT ...... 45 ABSTRACT ...... 45

3.1 INTRODUCTION ...... 47 3.2 MATERIALS AND METHODS ...... 49 3.2.1 Secondary tuber sample collection...... 49 3.2.2 Isolation of endophytic actinobacteria ...... 49 3.2.3 Genomic DNA extraction and molecular identification of actinobacterial isolates ………………………………………………………………………...50 3.2.4 Phylogenetic analysis ...... 52 3.2.5 Active compound extraction and bioactivity evaluation...... 52 3.2.6 Media Optimization ...... 55 3.2.7 Statistical analysis ...... 56 3.3 RESULTS ...... 56 3.3.1 Morphological characterization, molecular identification, and phylogenetic analysis ...... 56 3.3.2 Antimicrobial potential of isolated Actinobacteria strains...... 63 3.3.3 Effect of Cultural Parameters on Antimicrobial Activity ...... 68 3.3.4 Minimum inhibitory concentrations (MIC) of the various extracts ..... 69 3.4 DISCUSSION ...... 71 3.5 CONCLUSION ...... 83 REFERENCES ...... 84 APPENDIX ...... 94 CHAPTER 4: ENZYMATIC, ANTIOXIDANT AND DNA DAMAGE PROTECTIVE ACTIVITIES OF SELECTED ENDOPHYTIC ACTINOBACTERIA ISOLATED FROM HARPAGOPHYTUM PROCUMBENS: A KALAHARI DESERT-ADAPTED PLANT ...... 98 ABSTRACT ...... 98 4.1 INTRODUCTION ...... 99 4.2 MATERIALS AND METHODS ...... 102 4.2.1 Plant sample collection ...... 102 4.2.2 Isolation of actinobacteria strains...... 102 4.2.3 Extraction of secondary metabolites ...... 103 4.2.4 Physiological characteristics ...... 103 4.2.5 Determination of total phenolics (TPC) ...... 105 4.2.6 Determination of total antioxidant activity (TAA) ...... 106 4.2.7 Determination of DPPH radical scavenging activity ...... 106 4.2.8 Determination of total reducing power ...... 107 4.2.9 Determination of DNA protecting potential ...... 108 4.2.10 Data analysis ...... 108 4.3 RESULTS ...... 109

4.3.1 Isolation of actinobacteria strains and their biochemical activities ... 109 4.3.2 Total Phenolic content...... 111 4.3.3 Total antioxidant activity ...... 112 4.3.4 Free radical scavenging activity using DPPH assay ...... 113 4.3.5 Total Reducing power ...... 115 4.3.6 DNA nicking assay ...... 116 4.4 DISCUSSION ...... 116 4.5 CONCLUSION ...... 120 REFERENCES ...... 122 APPENDIX ...... 126 CHAPTER 5: QUALITATIVE ANALYSIS OF BIOACTIVE CONSTITUENTS FROM ENDOPHYTIC ACTINOBACTERIA ISOLATED FROM HARPAGOPHYTUM PROCUMBENS USING THIN LAYER CHROMATOGRAPHY (TLC) AND GAS CHROMATOGRAPHY-MASS SPECTROMETRY (GC-MS) ...... 130 ABSTRACT ...... 130 5.1 INTRODUCTION ...... 131 5.2 MATERIALS AND METHODS ...... 132 5.2.1 Chemicals and materials ...... 132 5.2.2 Thin layer chromatography screening of phytochemicals ...... 133 5.2.3 GC-MS analysis ...... 134 5.3 RESULTS AND DISCUSSION ...... 135 5.3.1 TLC phytochemical screens for terpenoids, alkaloids, phenols, and flavonoids ...... 135 5.3.2 Identification of the volatile constituents ...... 141 5.4. CONCLUSION ...... 161 REFERENCES ...... 163 CHAPTER 6: GENERAL CONCLUSIONS AND RECOMMENDATIONS ...... 166

LIST OF TABLES

Table 2.1: Bioactivity types of microbial metabolites and numbers of discovered bioactivities (Bérdy, 2005; Raja and Prabakarana, 2011)...... 12 Table 2.2: Major ROS and RNS of physiological importance (Adapted from Sailaja et al., 2011 and Ore and Akinloye, 2019)...... 19 Table 2.3: An estimate of plant secondary metabolites (Colitti et al., 2019)...... 24 Table 2.4: Commercially relevant enzymes produced by actinobacteria (Adapted from Prakash et al., 2013; Kumar et al., 2014 and Shivlata and Satyanarayana, 2015)..... 26 Table 3.1: Morphological and Molecular Identification of Actinobacteria strains .. 58 Table 3.2: MIC in µg/mL of ethyl acetate extracts ...... 70 Table 3.3: MIC in µg/mL of chloroform extracts ...... 71 Appendix table 3.1: Primary screening zones of inhibition (mm) mean ± standard deviation ...... 94 Appendix table 3.2: Zones of inhibition of secondary screening (mm) mean ± standard deviation (Ethyl acetate) ...... 94 Appendix table 3.3: Zones of inhibition of secondary screening (mm) mean ± standard deviation (Chloroform) ...... 95 Appendix table 3.4: Zones of inhibition of secondary screening (mm) mean ± standard deviation (Methanol) ...... 95 Appendix table 3.5: Zones of inhibition of mixed extracts (mm) mean ± standard deviation (Ethyl acetate) ...... 96 Appendix table 3.6: Zones of inhibition of mixed extracts (mm) mean ± standard deviation (Chloroform) ...... 96 Appendix table 3.7: Zones of inhibition of mixed extracts (mm) mean ± standard deviation (Methanol) ...... 96 Appendix table 3.8: Effects of cultural parameters on antimicrobial activity (mm) mean ± standard deviation…………………………………………………………...97 Table 4.1: Biochemical characterization of isolates ...... 110 Appendix table 4.1: Free radical scavenging activity of ethyl acetate extracts at different concentrations ...... 126 Appendix table 4.2: Free radical scavenging activity of chloroform extracts at different concentrations ...... 127

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Appendix table 4.3: Free radical scavenging activity of methanol extracts at different concentrations ...... 128 Appendix table 4.4: IC 50 for free radical scavenging activity by DPPH assay .... 128 Appendix table 4.5: Absorbance of extracts at 700nm to show reducing power as compared to gallic acid at 0.1mg/mL………………………………………………129 Table 5.1: Phytochemicals detected in the ethyl acetate extracts of endophytic actinobacteria isolated from H. procumbens...... 139 Table 5.2: Constituents identified in the three ethyl acetate extracts from the actinobacteria isolates B12, B44 and A65...... 144 Table 5.3: Mass spectra of carboxylic acids and esters……………………………147

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LIST OF FIGURES

Figure 2.1: Chemical structures of compounds with antibacterial activity isolated from actinobacteria (Jakubiec-Krzesniak et al. 2018) ...... 15 Figure 2.2: Chemical structures of compounds with antifungal and antiviral activities isolated from actinobacteria (Jakubiec-Krzesniak et al. 2018)...... 16 Figure 2.3: Causes, targets, affected organs and antioxidants that ﬁght oxidative stress. Adapted from Carocho et al. (2018)...... 22 Figure 2.4: Genome size, isolation source and number of secondary metabolite gene clusters. (Adapted from Doroghazi and Metcalf, 2013)...... 28 Figure 2.5: A Venn diagram of PKS, NRPS, and hybrid gene-cluster numbers. The gene-cluster numbers of bacteria, archaea, and eukarya are shown in red, purple, and blue, respectively. The values in parentheses represent the numbers of hybrid enzymes that contain both NRPS and PKS core domains(Adapted from Wang et al., 2014). . 29 Figure 2.6: H. procumbens plant and its fruit (SANBI, 2017) ...... 31 Figure 2.7: Distribution of species and subspecies of Harpagophytum in southern Africa (Adapted from Ihlenfeldt and Hartmann, 1970)...... 32 Figure 3.1: Consensus of the most likely tree inferred using 16S rRNA sequences of endophytic actinobacteria associated with H. procumbens. The phylogenetic tree represents a Maximum Parsimony analysis of 12 isolates with their reference strains of Streptomyces sp…………………………………………………………………..60 Figure 3.2: Consensus of the most likely tree inferred using 16S rRNA sequences of endophytic actinobacteria associated with H. procumbens. The phylogenetic tree represents a Maximum Parsimony analysis of 11 isolates with their reference strains of non-Streptomyces sp...... 62 Figure 3.3: Zones of inhibition with standard deviation bars of isolates showing the best activity against the various test microorganisms during primary screening...... 64 Figure 3.4: Actinobacteria isolate ethyl acetate extracts that had the largest inhibition zones when tested against the various test microorganisms ...... 65 Figure 3.5: Actinobacteria isolate chloroform extracts that had the largest inhibition zones when tested against the various test microorganisms...... 66 Figure 3.6: Zones of inhibition and standard deviation of ethyl acetate extract mixtures that exhibited the best activity against the test microorganisms ...... 67

Figure 3.7: Zones of inhibition and standard deviation of chloroform extract mixtures that exhibited the best activity against the test microorganisms ...... 68 Figure 3.8: Best activity of the chosen isolates against test microorganisms after being subjected to various growth parameters on starch casein agar containing extracts of the host plant H. procumbens...... 69 Figure 4.1: mgGAE/g of strain extract in different solvents for TPC...... 111 Figure 4.2: mgGAE/g of strain extract in different solvents for total antioxidant activity ...... 112 Figure 4.3: Free radical scavenging activity of extracts at 0.1mg/mL of all three solvents compared to the gallic acid standard...... 113 Figure 4.4: IC50 of extracts in all three solvents as compared to the gallic acid standard for free radical scavenging activity by DPPH assay...... 114 Figure 4.5: Total reducing power of extracts at a concentration of 0.1mg/mL ...... 115 Figure 5.1: TLC screen for terpenoids. A brown spot is observed where a terpenoid is present (The positive control (+) is β-sitosterol (Rf = 0.32) and the negative control (- ) is ethyl acetate)...... 136 Figure 5.2: TLC screen for alkaloids. An orange spot is observed where an alkaloid is present (The positive control (+) is Quinine (Rf = 0.66) and the negative control (-) is ethyl acetate)...... 137 Figure 5.3: TLC screen for phenols. A blue spot is observed where a phenol is present (The positive control (+) is gallic acid (Rf = 0.73) and the negative control (-) is ethyl acetate)...... 137 Figure 5.4: TLC screen for flavonoids. A black spot is observed where a flavonoid is present (The positive control (+) is Quercetin (Rf = 0.39) and the negative control (-) is ethyl acetate)...... 138 Figure 5.5: Total ion chromatogram of the ethyl acetate extract from actinobacteria isolate B12...... 142 Figure 5.6: Total ion chromatogram of the ethyl acetate extract from actinobacteria isolate B44...... 142 Figure 5.7: Total ion chromatogram of the ethyl acetate extract from actinobacteria isolate A65...... 143

Figure 5.8: MS for compound 1, identified as 3-methyl-decane (branched C11 alkane) in the ethyl acetate extracts from isolates B12, B44 and A65...... 149

Figure 5.9: MS for compound 2, identified as tridecane in the ethyl acetate extracts from isolates B12, B44 and A65...... 150 Figure 5.10: MS for compound 3, identified as pentadecane in the ethyl acetate extracts from isolates B12 and A65...... 150 Figure 5.11: MS for compound 4, identified as heptadecane in the ethyl acetate extracts from isolates B12 and A65...... 151 Figure 5.12: MS for compound 5, identified as nonadecane in the ethyl acetate extracts from isolates B12 and A65...... 151 Figure 5.13: MS for compound 6, an unknown constituent in the ethyl acetate extracts from isolates B12 and A65...... 152 Figure 5.14: MS for compound 7, identified as an octadecenamide analogue in the ethyl acetate extracts from isolates B12 and A65...... 152 Figure 5.15: MS for compound 8, identified as 9-octadecenamide in the ethyl acetate extract from isolate B12...... 153 Figure 5.16: MS for compound 9, an unknown constituent (possible cyclohexane carboxylic acid ester) in the ethyl acetate extracts from isolates B12 and A65...... 153 Figure 5.17: MS for compound 10, an unknown constituent in the ethyl acetate extract from isolate B12...... 154 Figure 5.18: MS for compound 11, an unknown constituent in the ethyl acetate extract from isolate B44...... 154

Figure 5.19: MS for compound 12, an unknown constituent (possible C18 carboxylic acid/ester) in the ethyl acetate extract from isolate B44...... 155 Figure 5.20: MS for compound 13, identified as an unknown unsaturated acid or ester in the ethyl acetate extract from isolate B44...... 155 Figure 5.21: MS for compound 14, identified as an unknown ethyl octadecenoate in the ethyl acetate extract from isolate B44...... 156

Figure 5.22: MS for compound 15, identified as an unknown C20 carboxylic acid or ester in the ethyl acetate extract from isolate B44...... 156 Figure 5.23: MS for compound 16, an unknown constituent in the ethyl acetate extract from isolate B44...... 157

Figure 5.24: MS for compound 17, identified as a C24 alkene or a C21 alcohol in the ethyl acetate extract from isolate B44...... 157

Figure 5.25: MS for compound 18, identified as a C20 alkene or a C17 alcohol in the ethyl acetate extract from isolate A65...... 158

Figure 5.26: MS for compound 19, identified as a C22 alkene or a C19 alcohol in the ethyl acetate extract from isolate A65...... 158 Figure 5.27: MS for compound 20, identified as tricosane in the ethyl acetate extract from isolate A65...... 159 Figure 5.28: MS for compound 21, identified as tetracosane in the ethyl acetate extract from isolate A65...... 159 Figure 5.29: MS for compound 22, identified as pentacosane in the ethyl acetate extract from isolate A65...... 160 Figure 5.30: MS for compound 23, identified as hexacosane in the ethyl acetate extract from isolate A65...... 160

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LIST OF ABBREVIATIONS AND/OR ACRONYMS 8-OH-dG – 8-hydroxy-2’-deoxyguanosine 8-OH-G – 8-hydroxyguanine ANOVA – Analysis of variance AP – Activator protein BHT – Butylated hydroxytoluene BLAST – Basic local alignment search tool CNS – Central nervous system COX-2 – Cyclooxygenase 2 DCM – Dichloromethane DNA – Deoxyribonucleic acid DPPH – 1,1-diphenyl-2-picrylhydrazyl GAE – Gallic acid equivalents GC-MS – Gas chromatography-mass spectrometry GSH – Glutathione H· - Hydride IC50 – Half maximal inhibitory concentration IL – Interleukin iNOS – Inducible nitric oxide IZ – Inhibition zone LOX – Lipo-oxygenase LPS – Lipopolysaccharide-stimulated MCD – Monocyte chemoattractant protein MIC – Minimum inhibitory concentration ML – Maximum likelihood mRNA – Messenger ribonucleic acid NADPH – Nicotinamide adenine dinucleotide phosphate NCBI – National Centre of Biotechnology Information NIST – National Institute of Standards and Technology NRPS – Nonribosomal peptide synthase ·OH – Hydroxyl PAI – Plasminogen activator inhibitor PCR – Polymerase chain reaction PGE-2 – Prostaglandin E2

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PKS – Polyketide synthase RDP – Ribosomal Database Project Rf – Retention factor RI – Retention indices RNA – Ribonucleic acid RNS – Reactive nitrogen species ROS – Reactive oxygen species rRNA – Ribosomal ribonucleic acid Rpm – Revolutions per minute RS – Reactive species SOD – Superoxide dismutase SPSS – Statistical Product and Services Solutions TAA – Total antioxidant activity TBE – Tris-borate-EDTA TBHQ – Tiertiery-butylhydroquinone TCA – Trichloroacetic acid TLC – Thin layer chromatography TNFα – Tumour necrosis factor alpha TPC – Total phenolic content UV – Ultraviolet

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ACKNOWLEDGEMENTS

Alfred Whitehead, English mathematician and philosopher (1861-1947) once said “No one who achieves success does so without the help of others. The wise and confident acknowledge this help with gratitude”. Thus, I would like to take this opportunity to acknowledge all those who have aided me in my path to victory.

First and foremost, to my remarkable supervisors, Dr. Jean D. Uzabakiriho, Dr. S.

Louw and Dr. T. Sibanda, to whom I owe the deepest of gratitude. This work would not have been possible without their invaluable direction, support, patience, and motivation. They have not only helped me in my studies but have provided me with tools that will be useful throughout my career and have been an inspiration to me.

I also received substantial support from the HOD of Biological Sciences, Prof. John

Mfune and technical staff members, such as Mr. Mbangu, Ms. Kaitjizemine and Ms.

Johnson, who helped me gain access to the research facilities and were always just a call away when I wanted to enquire about various equipment or materials. Thank you to Dr. Kwembeya for his patience in assisting me with the statistical analyses and helping me master the use of SPSS. I am grateful for the company of my good friend,

Pandu Shipoh, who spend hours with me in the lab as we both did our research. To other staff members, such as Ms. Deelie, Mr. Mukuve and Ms. Morkel, that assisted me in ways such as helping with workloads and general guidance. Lastly to my family and friends whose love and support was integral during this time. Thank you to all!

DEDICATION

I would like to dedicate this work to my amazing husband, Horst Ralph Lang, who has been patient with my long hours working into the late evenings. He has stood by my side these past years through thick and thin and has always been my biggest supporter.

I thank him for being my rock and always motivating me to do and be better.

To my aunt, Letta De Klerk, and my grandparents, Lana, and Hugo De Klerk, who provided me with a loving home for a large duration of my studies. Who helped me in ways that I will never be able to fully repay, always being there for me at a moment’s notice. You will always be my second home.

To my parents, Magda and Allen Blignaut and Charlene and Horst Lang, my brothers,

Jean-Pierre Blignaut and Kevin Lang, my adorable little nephew and niece, Arthur and

Sky Blignaut, and my godchild, Hailey Simoes, for providing me with a strong family system and always being there to put a smile on my face when things were dire.

To the rest of my family and friends, thank you for your support without which I would not have made it to this point in my life. Each one of you has played a role in shaping the person I am today, and for that, I thank you.

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DECLARATION

I, Magdalena Elizabeth Lang, hereby declare that this study is a true reflection of my own work. I have not copied from other students’ work or from any other sources except where due to reference or acknowledgment is made explicitly in the text, nor has any part been written for me by another person.

I, Magdalena Elizabeth Lang, grant the University of Namibia the right to reproduce this thesis in whole, in part and/or in any part the University deems fit.

…………………………………. Date: 26/03/2021 Magdalena Elizabeth Lang

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CHAPTER 1: INTRODUCTION

1.1 Background of the study

The emergence of antimicrobial resistance coupled with the decline in the discovery of new antimicrobial compounds has necessitated the need to investigate novel and biologically active compounds in potentially important organisms (Tanvir et al.,

2016). Some of the most important and fairly ignored organisms are endophytic actinobacteria. Endophytic actinobacteria ubiquitously and asymptomatically dwell within healthy plants and confer enhanced fitness to the host by producing functional metabolites (Qui et al., 2015). They are the most economically and biotechnologically important prokaryotes capable of producing an arsenal of bioactive secondary metabolites, many of which have useful applications in medicine, agriculture, and industry such as enzymes, immuno-modulators, antibiotics, insecticides, herbicides and anticancer agents (Valli et al., 2012; Messaoudi et al., 2015). The endophytic actinobacteria are endowed with potent polyketide synthase (PKS) or nonribosomal peptide synthetase (NRPS) gene clusters responsible for secondary metabolite biosynthesis with antimicrobial, antioxidant and DNA damage protecting properties

(Ozcan, 2017).

Research showed that endophytic actinobacteria are prevalent and diverse in medicinal plants and are promising sources of biologically active natural compounds (Qui et al.,

2015). One such plant thriving in the harsh Namibian desert is Harpagophytum procumbens (Devil’s Claw) which is a herbaceous perennial plant that grows in the

Kalahari region of Southern Africa. It has reportedly been used as traditional medicine to treat various types of ailments (Mncwangi et al., 2012). Thus, H. procumbens might be a good reservoir for actinobacteria that harbour these compounds. The aim of this

1 present study was thus to recover the endophytic actinobacteria associated with secondary tubers of H. procumbens occurring in an unexplored biome in Namibia. In addition, we set out to determine the ability of these actinobacteria endophytes to produce antimicrobial, antioxidant and DNA damage protecting metabolites.

1.2 Statement of the problem

Drug resistance to known antimicrobials by pathogenic microorganisms has become a large problem as well as the decreasing discovery rate of novel antimicrobials

(Saravanakumar et al., 2010; Sharon et al, 2013). Additionally, the intensive use of medicinal plants, of which 20% are being threatened, for newer potential active metabolites is detrimental to biodiversity (Tanapichatsakul et al., 2017). As an alternative, endophytes can be isolated and cultured as many of the host plant bioactivities can be linked to their endophytes (Golinska et al, 2015). Furthermore, actinobacterial endophytes are acquiescent to genetic manipulations and can be scaled up for bioactive compound production (Xu et al., 2007). However, to date, there is no available information on the incidence of endophytic actinobacteria associated with H. procumbens and their antimicrobial potential.

Pathophysiological or environmental interferences are known to cause unregulated generation of Reactive Oxygen Species (ROS) (Dayem et al., 2017). ROS can cause oxidative damage to biomolecules including DNA. Synthetic antioxidants that are currently being used as treatments, such as tertiary-butylhydroquinone (TBHQ), butylated hydroxytoluene (BHT) and butylated hydroxyanisole (BHA), may have probable toxicity, carcinogenicity, and other adverse effects (Pavithra and

Vadivukkarasi, 2015). As a result, there is growing attention to obtain antioxidants from natural sources.

The endophytic actinobacteria of H. procumbens are yet to be isolated, identified and characterized and their active metabolites have not been studied and explored. The best conditions for cultures can also increase the production of secondary metabolites of endophytic actinobacteria harboured in the secondary roots of H. procumbens (Pudi et al., 2016). Furthermore, traditionally medication has been administered in the form of crude extracts which might be dangerous as it does not separate the medicinal compounds from the other compounds in the extract (Mensah et al, 2011). Thus, identifying these bioactive compounds will also help in the targeted upscaling of their production.

1.3 Objectives of the study

The objectives of the study were to:

a) Isolate, identify and characterize endophytic actinobacteria associated with H.

procumbens’ secondary tubers. b) Screen isolates for the production of bioactive compounds (antimicrobial,

antioxidant and DNA damage protection activity, free radical scavengers, and

enzymatic activity) and biosynthetic gene clusters (PKS and NRPS).

c) Investigate the synergistic antibacterial activities of selected crude extracts.

d) Explore the best culture conditions of endophytic actinobacteria associated with

H. procumbens to enhance the production of secondary metabolites.

e) Qualitatively analyze selected bioactive compounds extracted from the

endophytic actinobacteria associated with H. procumbens’ secondary tubers using

thin layer chromatography (TLC) and gas chromatography-mass spectrometry

(GC-MS).

1.4 Significance of the study

H. procumbens from Namibia has yet to be studied as per their actinobacteria endophytes, as some of their beneficial characteristics might be the results of the endophytic community that can lead to the discovery of new compounds. The diversity of these bioactive endophytic actinobacteria was determined and some of their bioactive compounds were identified. This study was a significant endeavor in providing novel sources of antimicrobial, antioxidant and DNA damage protecting compounds from an underexplored, natural source since synthetic antioxidants currently being used have been shown to have detrimental side effects (Pavithra and

Vadivukkarasi, 2015; Janardhan et al., 2014) and there is a need for novel antimicrobial compounds (Sharon et al, 2013). Furthermore, these endophytic actinobacteria harbour advantageous gene clusters synthesizing an array of structurally diverse secondary metabolites with potential biotechnological significance (Choi et al., 2015). In this study, the most conductive culture conditions to produce these metabolites were determined.

1.5 Limitations of the study

Age of the selected plant, media used and using the culture-dependent method could impact the actinobacteria isolated and metabolites produced as the lab environment might not be conducive. Standard procedures for actinobacteria isolation were carried out which might limit the diversity obtained. Some endophytic actinobacteria might function in conjunction with others in their natural habitat to produce the required metabolites but for the purpose of this study, actinobacteria strains will be evaluated separately.

1.6 Delimitations of the study

The scope of the present study only focused on antimicrobial, antioxidants, DNA damage protecting properties, biochemical pathways, diversity and certain biosynthetic gene sequences within solely endophytic actinobacteria associated with

H. procumbens. The results obtained might only apply to H. procumbens found within the specific regions of sampling.

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Pudi, N. et al., 2016. Studies on Optimization of Growth Parameters for Enhanced Production of Antibiotic Alkaloids by Isolated Marine Actinomycetes. Journal of Applied Pharmaceutical Science, 6(10), 181-188.

Qui, P., Feng, Z., Tian, J., Lei, Z., Wang, L., Zeng, Z., et al., 2015. Diversity, Bioactivities, and Metabolic Potentials of Endophytic Actinomycetes Isolated from Traditional Medicinal Plants in Sichuan, China. Chinese Journal of Natural Medicines, 13(12), 942-953.

Saravanakumar, R., Moomeen, S., Ronald, J., and Kannan, M., 2010. Control of Fish Bacterial Pathogens by Antagonistic Marine Actinomycetes Isolated from Gulf of Mannar coast. World Journal of Fish and Marine Sciences, 2(4), 275-279.

Sharon, S., Daniel, R., and Shenbagorathai, R., 2013. Screening of Marine Actinomycetes from Coastal Region of Tamil Nadu. Indian Journal of Applied Research, 3(10), 19-20.

Tanapichatsakul, C., Monggoot, S., Gentekaki, E. and Pripdeevech, P., 2017. Antibacterial and Antioxidant Metabolites of Diaporthe spp. Isolated from Flowers of Melodorum fruticosum. Current Microbiology, 75, 476-483.

Tanvir, R. et al., 2016. Rare Actinomycetes Nocardia caishijiensis and Pseudonocardia carboxydivorans as Endophytes, Their Bioactivity and Metabolites Evaluation. Microbiology Research, 185, 22-35. Valli, S. et al., 2012. Antimicrobial Potential of Actinomycetes Species Isolated from Marine Environment. Asian Pacific Journal of Tropical Biomedicine, 469-473.

Xu, L. et al., 2007. Fungal Endophytes from Dioscorea zingiberensis Rhizomes and Their Antibacterial Activity. Letters in Applied Microbiology, 46(1).

CHAPTER 2: LITERATURE REVIEW

2.1 Endophytic actinobacteria as a promising source of secondary metabolites

2.1.1 Host plant interaction effect on secondary metabolite production.

Plants have served as a supply of medicinal bioactive compounds against various forms of ailments for a long time. Ironically, in recent years it has been shown that in many cases, microorganisms associated with plants rather than plants themselves, produce products with high therapeutic potential (Gouda et al., 2016). Endophytes are an endosymbiotic group of microorganisms (often bacteria or fungi) that colonize the inter- and/or intracellular locations of plants and often confer extended nutrients and defensive mechanisms to the host (Gomes and Cleary, 2013). They are omnipresent in nature and exhibit multifaceted interactions with their hosts, which involve mutualism, antagonism and seldom parasitism (Gouda et al., 2016). Endophytic actinobacteria represent a potential depository of novel bioactive compounds as there are almost 300,000 plant species, each hosting one or more types of endophyte (Hug et al., 2018).

The extraction of metabolites from endophytes is affected by a variety of factors, such as the season of sample collection, climatic conditions, and geographical location

(Gouda et al., 2016). It should be noted, that since not all endophytes may be culturable, that endophytes can also be defined as a set of microbial genomes inside plant organs (Rout and Southworth, 2013). Plants in their environment are the result of the combined and coordinated expression of both plant and microbial genes and these interactions establish a highly effective phenomenon of adaptation. Since H. procumbens is a desert-adapted plant, endophytic microbial communities play an important role in shaping its survival, through perhaps promoting plant growth,

8 producing protective biofilms or antibiotics, and aiding in phytostimulation, etc (Nair and Padmavathy, 2014; Bacon and White, 2015).

Endophytes can colonize the stem, roots, petioles, leaf segments, inflorescences of weeds, fruit, buds, seeds, and dead and hollow hyaline cells of plants (Gouda et al.,

2016). Microbes can colonize the host plant horizontally via the environment, vertically from within the host transferred from parent to offspring, or by mixed modes

(Rosenberg and Zilber-Rosenberg, 2011). In many vertically transmitted symbioses, the microbe is obligate and cannot survive outside of the host (Foster and Wenseleers,

2006). Vertical transmission via seeds is well documented for certain groups of fungal endophytes (Schardl, 2001). However, most bacterial endophytes are more likely to be horizontally transmitted since the diversity of bacteria in seeds and seedlings grown under sterile conditions is usually poorer than in those grown in soil (Hardoim et al.,

2012). Furthermore, bacterial endophytes are often generalists and can typically transfer benefits to distantly related plants (Rajkumar et al., 2011). Thus, they are unlikely to be strictly vertically transmitted. The ability of a plant to acquire a diverse set of symbionts horizontally may be beneficial for plants in changing environments

(Frank et al., 2017). However, an endophyte that is beneficial to its host under a particular circumstance (e.g., biotic stress) may be passed down to the offspring vertically. A single plant species could possess thousands of microorganisms, categorized as epiphytes (microbial inhabitants of the rhizosphere and phyllosphere; those near or on plant tissue) or endophytes (microbes residing within plant tissues in leaves, roots, or stems) (Gouda et al., 2016).

Although plants are sessile, they make up an excellent ecosystem for microbes. They regularly encounter both abiotic stresses such as drought, salinity and metal toxicity and biotic stresses such as pathogenic bacteria, fungi, nematodes, and Oomycetes. The

9 plant microbiome is currently attracting a lot of research interest due to its ability to buffer plant hosts against abiotic and biotic stress, facilitate nutrient uptake and nutrient use efficiency, and promote growth (Frank et al., 2017). Associations between the two can provide beneficial outcomes to plant growth through a variety of mechanisms such as nitrogen fixation, protection against various biotic and abiotic stresses and through the production of growth-promoting metabolites. Endophytes can also interact with plants by producing protective bioﬁlm or antibiotics, protecting the host plant against other potential pathogenic infections and breaking down toxins present in the surrounding environment (Rout and Southworth, 2013). Endophytes also successfully compete with pathogens by occupying the space available to carry out activities (Fadiji and Babalola, 2020). Some endophytes can also aid the plant in phytostimulation, pigment production, enzyme production, siderophore production and nutrient cycling (Nair and Padmavathy, 2014). In return, the plant provides the endophytes with nutrients to produce a variety of organic compounds. Most plant phenotypes in nature include the extended phenotypes of one or more microbes and as a result express both plant and microbial genes (Partida-Martínez and Heil, 2011).

These associations institute a highly efficient technique of adaptation and greatly affect microbial ecological communities (Russo et al., 2012).

2.1.2 Diversity of secondary metabolites from endophytic actinobacteria and

their antimicrobial and antioxidant properties.

Evidence suggests that endophytic actinobacteria are prevalent in medicinal plants and are promising sources of biologically active natural compounds (Qui et al., 2015).

Actinobacteria (Phylum: Actinobacteria) are gram-positive, saprophytic bacteria that are extensively distributed in soil and other terrestrial environments (Himamana et al.,

2016). Furthermore, they generally have a high GC (guanine and cytosine) content of

55% or higher. Their fungal morphology led to them initially being misidentified as relatives to fungi (Doroghazi and Metcalf, 2013; Chakrabortya et al., 2015).

Actinobacteria produce about half of the discovered bioactive secondary metabolites such as antibiotics, antitumor agents, immunosuppressive agents, enzymes and about

75% of the known antibacterials (Oskay, Tamer and Azeri, 2004; Adegboye and

Babalola, 2013). They also produce a variety of secondary metabolites such as polyketides (constitute a large and structurally diverse family of natural products with many biological activities and pharmacological properties), peptides, quinones

(compounds having a fully conjugated cyclic dione structure), macrolides (cluster of drugs whose activity stems from the presence of a large macrocyclic lactone ring to which one or more deoxy sugars may be attached), terpenes (large and various class of hydrocarbons), alkaloids (class of naturally occurring organic nitrogen-containing bases), and many more, each with unique properties and uses in the medical field

(Manivasagan et al., 2014). Additionally, actinobacteria can produce plant growth promoters to augment plant growth especially under stressed circumstances

(Himamana et al., 2016). As early as the 1950s, many natural products were discovered and studied, predominantly from the genus Streptomyces, which is considered one of the most significant types of industrial bacteria due to its advanced capabilities in producing valuable secondary metabolites. Table 2.1 highlights the importance of microbial metabolites and their bioactivities.

Table 2.1: Bioactivity types of microbial metabolites and numbers of discovered bioactivities (Bérdy, 2005; Raja and Prabakarana, 2011).

Antibiotic activities (16 500 compounds) Number Antibacterial activity Gram-positive 11 000-12 000 Gram-negative 5 000-5 500 Mycobacteria 800-1 000

Antifungal activity Yeast 3 000-3 500 Phytopathogenic fungi 1 600-1 800 Other fungi 3 800-4 000

Antiprotozoal activity 1 000

Chemotherapeutic Antitumor(cytotoxic) 5 000-5 500 Antiviral 1 500-1 600 Other bioactivities (11 500 compounds) Pharmacological Enzyme inhibitor activity 3 000-3 200 Immunological (suppressive, modulatory) ~800 Biochemical (DNS, tubulin, mitotic, etc) ~1 000 Other (Antagonistic, modulatory, anti-inflammatory, etc) 2 000-2 500

Agricultural activity Pesticide (antiparasitic, algicide, amoebicide, etc) 900-1 000 Herbicide (phytotoxic, plant growth regulatory, etc) 1 800-1 900 Insecticide/Miticide/Larvicide/Deterrent 1 100-1 200 Feed additive, preservatives 300-400

Other activities Microbial regulators (growth factors, microbial hormones, ~500 morphogens) ~300 Biophysical effects (surfactants, etc)

However, recent reports have established that the detection of novel secondary metabolites from the Streptomyces species has considerably decreased and more new discoveries are coming from the non-Streptomyces actinobacteria, called rare actinobacteria, which consist of more than 200 genera (Choi et al., 2015). Furthermore, the rate at which new compounds are being discovered has decreased while the re-

12 isolation of already discovered compounds has increased (Saravanakumar et al.,

2010). Novel compounds from actinobacteria that have recently been discovered include some antibiotics (antimycin-A demonstrating antibacterial, antifungal, inhibition of enzymes and anti-cancer activity; salinosporamide A exhibiting strong cytotoxicity against various cancers; angucyclines that have antibacterial, antitumor, antiviral and enzyme inhibitory activities), pigments, enzymes (L-asparaginase and L- glutaminase exhibiting anticancer properties and xylanases), anti-inflammatory compounds (saphenic acid, lipomycin and cyclomarin A and C) and endophenazines

(redox-active molecules to aid survival in anoxic or anaerobic conditions) (Mohan and

Rajamanickam, 2018).

The genus Streptomyces produce over two-thirds of clinically useful antibiotics which include macrolide polyenes that have antifungal properties (such as nystatin, amphotericin B and natamycin), aminoglycosides (such as streptomycin, neomycin, and kanamycin), erythromycin, tetracycline, chloramphenicol, vancomycin and thienamycin (Kieser et al., 2000; Raja and Prabakarana, 2011). Whole-cell screening of broths from actinobacteria or fungi promptly leads to biologically active compounds because they are screened against real target microbes (Baltz, 2007). In a recent review by Jakubiec-Krzesniak et al. (2018), various secondary metabolites have been reportedly obtained from various actinobacteria including those with antibacterial

(spirotetronate compounds, β-diketones, tetracenediones, lactones, lactams, quinones, quinolones, xanthones, peptides, aminocoumarins, terpenoids, depsipeptides, lipopeptides, etc), antifungal and antiviral activity as shown in Figure 2.1 and Figure

2.2

Figure 2.1: Chemical structures of compounds with antibacterial activity isolated from actinobacteria (Jakubiec-Krzesniak et al. 2018)

Figure 2.2: Chemical structures of compounds with antifungal and antiviral activities isolated from actinobacteria (Jakubiec-Krzesniak et al. 2018).

Due to the rapidly increasing need for new medicines to fight off infections of various kinds and the fact that new antibiotic-resistant strains of bacteria are emerging at an alarming rate, it is pertinent to find new and stronger antibiotics (Sharon et al., 2013).

Furthermore, in mainstream medicine, conventional antimicrobial agents are amongst the most frequently prescribed drugs (Hübsch et al., 2014). It is thus crucial to explore underexplored habitats for novel actinobacteria strains that might produce novel biologically active compounds. It is also important to investigate combinations to identify possible alternatives to overcome resistance. Combination studies also provide valuable information for use in the clinical setting, where natural product– drug interactions can occur (Hübsch et al., 2014).

Oxidative stress refers to an imbalance between the production of reactive species (RS) and antioxidant defenses, favouring the oxidants and leading to a chemical imbalance or disruption of redox signaling and control which can lead to molecular damage (Ore and Akinloye, 2019). Certain chemical compounds such as reactive oxygen species

(ROS) and reactive nitrogen species (RNS) can generate free radicals (atoms or group of atoms with an unpaired electron) that are highly reactive and can start a chain reaction (Li et al., 2015). Oxidative stress is linked with many diseases, particularly those with an inflammatory mechanism (Ore and Akinloye, 2019). ROS, such as superoxide, hydroxyl radicals, and peroxyl radicals, with the addition of non-radicals, such as hydrogen peroxide, hypochlorous acid and ozone are generated during the metabolism process of oxygen. RNS, including nitrogen-based radicals and non- radicals, such as nitrogen dioxide, nitric oxide radicals and peroxynitrite, are derived from nitric oxide and superoxide via inducible nitric oxide synthase (iNOS) and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase, respectively (Li et al., 2015; Pavithra and Vadivukkarasi, 2015).

Furthermore, excess ROS and RNS in cells lead to oxidative stress, causing damage such as lipid peroxidation, breaking of DNA strands, and indiscriminate oxidation of virtually all molecules in biological membranes and tissues resulting in disruptions in membrane fluidity and ion transport, loss in enzyme activity and disruptions in protein synthesis (Nisha and Deshwal, 2011; Li et al., 2015; Ore and Akinloye, 2019).

Oxidative stress has been classified according to severity as “eustress” (physiological oxidative stress) and “distress” (toxic oxidative burden that can cause damage) since low exposure is useful for redox signaling (Ore and Akinloye, 2019). For example, preeclampsia is a multisystem disorder of pregnancy whose cause remains largely unknown. However, cumulated evidence points to a major role of oxidative stress as a factor underlying the mechanism of the development of the endothelial dysfunction accounting for the syndrome (Rodrigo et al., 2007). Table 2.2 lists the major ROS and

RNS, their sources and the human body’s natural defense mechanisms against them.

Table 2.2: Major ROS and RNS of physiological importance (Adapted from Sailaja et al., 2011 and Ore and Akinloye, 2019).

MAJOR SOURCES DEFENSE SYSTEM ROS Free Hydroxyl Decomposition of ONOO- or HOCl SOD, Mn-SOD, Cu, Zn- Radicals radical (푂퐻*). SOD, glutathione Electron transport systems, and one- electron reduction of O2 by respiratory Superoxide dismutase Superoxide burst via the action of membrane- *- radical (푂2 ) bound NADPH oxidase

Peroxyl radical Produced in the Fenton reaction Tocopherols, Ubiquinone (ROO*) Photoexcitation, enzymatic reactions catalyzed by dioxygenases, Singlet oxygen lactoperoxidases, myeloperoxidases, Carotenoid * (O2 ) cytochromes, tryptophan pyrrolase and lipoxygenases Non- Hydrogen Activated macrophages during Catalase, Se Glutathione Radicals peroxide (H2O2) inflammation peroxidase

Hypochlorous Combined activities of NADPH acid (HClO) oxidase and myeloperoxidase (MPO) in phagocytes Lipid peroxides (ROOH) Formed from oxidation of Glutathione peroxidase, polyunsaturated fatty acid via lipid- Glutathione reductase peroxyl radical reaction MAJOR SOURCE DEFENSE SYSTEM RNS Free Nitric oxide Nitric Oxide Synthase (NOS) Nitrate, Superoxide Radicals (NO*) dismutase, erythrocytic Nitrogen Activated neutrophils hemoglobin, cell-free * dioxide (푁푂2 ) (NO derivative) hemoglobin Non- Dinitrogen Produced in pathological conditions radicals trioxide (N2O3) where inducible nitric oxide (iNOS) is upregulated

Peroxynitrite Produced in pathological conditions (ONOO-), where iNOS is upregulated Myeloperoxidase Oxidation product from NO, formed - Nitrite (푁푂2 ) during NOS activation in inflammatory diseases

Nitryl ion Activated neutrophils + (푁푂2 ) OTHER SOURCE DEFENSE SYSTEM Transition Food and other environmental sources Chelators Metals (Fe+2, Cu+2)

DNA damage can be caused by sources such as radiation, ultraviolet light, and contaminants in our food and the environment, potentially leading to cancer and other diseases (Kang, 2002). Free radicals such as •OH (hydroxyl) and H• (hydride) react with DNA by addition to bases or elimination of hydrogen atoms from the sugar moiety, damaging DNA (Nisha and Deshwal 2011). 8-Hydroxy-2′-deoxyguanosine

(8-OH-dG) and 8-hydroxyguanine (8-OH-G) are the most commonly measured

DNA/RNA damage products (Nisha and Deshwal, 2011; Ore and Akinloye, 2019).

DNA damage also involves degradation of bases, single- or double-stranded DNA breaks, purine, pyrimidine or sugar-bound modifications, mutations, deletions or translocations, and cross-linking with proteins (Al-Dalaen and Al-Qtaitat, 2014). DNA damage can accumulate in the brain, muscle, liver, kidney, and in long-lived stem cells, likely leading to the decline in gene expression and loss of functional capability observed with increasing age.

Unusual arrangement in the membrane lipid bilayer can result in inactivation of the membrane-bound receptors and enzymes and causes an increase in tissue permeability

(Al-Dalaen and Al-Qtaitat, 2014). Lipid peroxidation is the destruction of double bonds of unsaturated lipids by ROS. Products of lipid peroxidation are capable of inactivating many cellular proteins by forming cross-linkages, leading to depletion of intracellular GSH, induce peroxide production, activate epidermal growth factor receptors and induce fibronectin production (Al-Dalaen and Al-Qtaitat, 2014). Nitric oxide inhibits several enzymes including complexes I and IV of the mitochondrial electron transport chain, leading to ROS generation. It also reacts with proteins to form

S-nitrosothiols thus altering their function, and in lipids causing their peroxidation

(Dias et al., 2013). Peroxynitrite can induce DNA fragmentation, lipid peroxidation, injury in dopamine synthesis independent of dopamine oxidation or cell death (Dias et

20 al., 2013). Some of the most important oxidative damage products of lipids that are frequently measured include malondialdehyde, lipid peroxides, 8-isoprostane, and 4- hydroxy-2-nonenal (4-HNE) (Ore and Akinloye, 2019).

Oxidation of proteins can result in protein cross-linkage, the formation of protein carbonyls, and modification of amino acids. Important products of oxidative modification of amino acids that are frequently measured include 3-nitrotyrosine (a product of ROS-mediated nitration of tyrosine), 2-oxohistidine and hydroxyproline

(Ore and Akinloye, 2019). Fragmentation of the peptide chain and aggregation of cross-linked reaction products result in an altered electrical charge and increased vulnerability to proteolysis (Al-Dalaen and Al-Qtaitat, 2014). Other detrimental effects caused by ROS include atherosclerosis, reperfusion injury, cataractogenesis, rheumatoid arthritis, inflammatory disorders, and cancer (Lee et al., 2014). Therefore, the toxicity of oxygen necessitates effective protection mechanisms to preserve oxidative homeostasis and guarantee the cell’s survival.

Figure 2.3 illustrates some of the causes, targets and organs affected by oxidative stress, as well as some antioxidants used to combat it.

Figure 2.3: Causes, targets, affected organs and antioxidants that ﬁght oxidative stress.

Adapted from Carocho et al. (2018).

As the body ages, its capacity to deal with external changes and/or environmental stresses reduces and ultimately leads to the development of chronic diseases, such as neurodegenerative diseases (e.g., Parkinson's disease and Alzheimer's disease), cardiovascular diseases and also cancer (Fischer and Maier, 2015; Leszek et al., 2016)

One of the main causes of the development of these chronic diseases is the accumulation of free radicals over time which ultimately overcomes the antioxidant defenses of the host, causing various deleterious effects on cell components and connective tissues (Ser et al., 2017). Most Streptomyces species produce melanin that has natural antioxidant activity, as well as Streptomyces lincolnensis reportedly produced Protocatechualdehyde and Streptomyces coelicoflavus reportedly produced

Surugapyrone A, both of which are also natural antioxidants (Rao and Rao, 2013).

Finding novel antioxidants could help combat various health problems.

Antioxidants considerably delay or thwart oxidation of oxidizable substrates when present at lower concentrations than the substrate. Antioxidants can be synthesized in vivo (e.g., reduced glutathione (GSH), superoxide dismutase (SOD), catalases and peroxidases), or taken as dietary supplements, such as vitamins and steroids, to combat or prevent oxidative stress (Kasote et al., 2015; Darbandi et al., 2018). Many synthetic antioxidants such as tertiary-butylhydroquinone (TBHQ), butylated hydroxytoluene

(BHT) and butylated hydroxyanisole (BHA) have been reported to cause liver damage and acting as carcinogens in laboratory animals, whereas natural antioxidants avoid these disadvantages (Lee et al., 2014; Pavithra and Vadivukkarasi, 2015).

Antioxidants from natural sources play a paramount role in helping endogenous antioxidants to neutralize oxidative stress. Antioxidants, therefore, are used to reverse the damaging effects of the free radicals by scavenging the free radicals and detoxifying the physiological system (Lee et al., 2014).

It has been reported that foods, beverages, and nutraceutical formulations containing antioxidants play an important role in the prevention of different diseases such as cancer, cardiovascular and neurodegenerative diseases (Mousumi and Dayanand,

2013). Plants have long been a source of exogenous antioxidants and considering the variety of medicinal properties that H. procumbens has; its endophytic actinobacteria might be a good reservoir for these metabolites. Table 2.3 demonstrates how significant plants have been in providing various secondary metabolites. Recent studies are focusing on the response of antioxidant systems in bacteria, which is an important aspect of biotechnology which as demonstrated in a study by Priya et al.

(2012). The study reported that Streptomyces sp. ABTRI 12 possess significant DPPH free radical scavenging activity.

Table 2.3: An estimate of plant secondary metabolites (Colitti et al., 2019) Nitrogen- Number of Non-Nitrogen Number of Containing Natural Containing Natural Compounds Compounds Compounds Compounds Alkaloids 12 000 Monoterpenes 1 000 Non-protein amino 600 Sesquiterpenes 3 000 acids Amines 100 Diterpenes 2 000 Cyanogenic 100 Triterpenes, 4 000 glycosides Saponins, Steroids Glucosinolates 100 Tetraterpenes 350 Flavonoids 2 000 Polyacetylenes 1 000 Polyketides 750 Phenylpropanes 1 000

Phenolic compounds, the most abundant antioxidant in the human diet and widely distributed in plant materials, have received much attention in recent years (Xiao et al., 2015). Lipid peroxidation can be halted by antioxidants, namely lipophilic ones like vitamin E (which is one of the most effective when working in synergy with vitamin C) and gallic acid (Carocho et al., 2018). There is also a possibility of using vitamins E and C to treat oxidative stress in preeclampsia, hypertension, and prevention of atherosclerosis (Rodrigo et al., 2007). A recent study in humans showed that supplementation with antioxidant compounds such as vitamins E and C, lycopene and ß-carotene can facilitate in reducing the levels of free-radical damage (Bub et al.,

2003). Ascorbic acid (vitamin C) and its monoanion, ascorbate, are very strong antioxidants, both within the human body by neutralization of free radicals, but also in foodstuffs, where they are used as antioxidants to avoid oxidation of the food and its eventual spoilage. Vitamin C protects against the oxidation of lipids, proteins, and

DNA (Rodrigo et al., 2007). Octyl gallate is used as an antioxidant, an antimicrobial, especially against gram-positive bacteria, but also as an antifungal agent (Carocho et al., 2018). Despite the enormous interest in antioxidants as potential protective agents

24 against the development of human disease, the real contributions of such compounds to health maintenance and the mechanisms whereby they act remain unclear (Rodrigo et al., 2007). Certain antioxidant secondary metabolites produced by H. procumbens might be linked to those produced by the endophytic actinobacteria within it.

2.1.3 Enzymatic activity of actinobacteria and the production of important

chemicals

Actinobacteria can synthesize extracellular enzymes that are able to hydrolyze complex macromolecules like proteins, starch, chitin, humus, cellulose, and lignocellulose in different habitats (Minotto et al., 2014). More than 4000 enzymes that are known today are of microbial origin (Mohan and Charya, 2012). Due to their application in clean, eco- friendly and cost-effective biotechnological processes, the demand for bacterial enzymes in industrial fields is increasing as shown in Table 2.4

(Prakash et al., 2013). Actinobacteria are the most significant among microbes due to their ability to produce copious bioactive molecules including antibiotics and enzymes

(Mohan and Charya, 2012).

Table 2.4: Commercially relevant enzymes produced by actinobacteria (Adapted from

Prakash et al., 2013; Kumar et al., 2014 and Shivlata and Satyanarayana, 2015).

Enzyme Actinobacterial strain Industrial applications Protease S. galbus Detergent, Food, Brewing, Saccharomonospora viridis Leather, Medicine Nocardiopsis prasina Cellulase S. actuosus Detergent, Textile, Paper, and pulp Lipase S. groseochromogenes Detergent, Baking, Diary, Textile Xylanase S. rameus Baking, Animal feed, Paper, and Thermomonospora fusca pulp Kocuria sp. Streptomyces sp. Pectinase S. fradzae Beverage, Textile

Amylase S. aureofasciculus Detergent, Baking, Paper and S. galilaeus pulp, Starch industry, Textile Thermomonospora viridis Thermomonospora curvata Glucose oxidase Streptomyces sp. Baking Lipoxygenase Streptomyces sp. Baking Phytase S. ambofaciens Animal feed S. leinomycini Peroxidase Thermomonospora fusca Textile S. viridosprus β-galatoxidase Streptomyces sp. Diary L-asparaginase S. aureofasciculus Food Industry S. canus S. chattanoogenesis S. hawaiiensis S. olivoviridid S. orientalis S. plicatus L-glutaminase S. rimosus Food industry S. galbus Keratinase Doretomycetes microspores Animal feed, Leather, Actinomadura keratinilytica Pharmaceutical Thermomonospora fusca Acetylxylan esterase Thermobifida fusca Paper and pulp Dextranase Streptomyces sp. Sugar mills Nitrite hydratase Pseudonocardia thermophila Acrylamide production Laccase Thermobifida fusca Waste treatment, Textile dye treatment Carbon monoxide Streptomyces sp. Bioenergy generation, Biofilters dehydrogenase

2.1.4 Biosynthesis of natural secondary metabolites (Non-ribosomal peptides,

Polyketides, hybrid non-ribosomal peptides/Polyketides)

Actinobacteria possess a large quantity of genes that encode for copious amounts of bioactive metabolites. PKS and NRPS genes are multi-domain megasynthases that synthesize secondary metabolites nonribosomal peptides and Polyketides (Ozcan,

2017). Nonribosomal peptides are biosynthesized by sequential condensation of amino acid monomers, whereas polyketides are made from repetitive addition of two carbon ketide units derived from thioesters of acetate or other short carboxylic acids (Ansari et al., 2004).

Examples of polyketides are various macrolides, ansamycins (anti-tumour), polyenes

(antifungal), polyethers (antibiotic monensin), tetracyclines, acetogenins and others.

Many mycotoxins produced by fungi are polyketides (Huffman et al., 2010).

Examples of nonribosomal peptides include various antibiotics, cytostatics, immunosuppressants, siderophores, pigments, toxins, phytotoxins and nitrogen storage polymers. They are diverse and have been detected in actinobacteria associated with marine corals and sponges (Martinez-Nunez and Lopez, 2016). Whatever their use, the genes that are responsible for the production of individual secondary metabolites are almost always located together in the genome and are referred to as biosynthetic gene clusters and can aid in the discovery, characterization, and comparison of the genes responsible for secondary metabolite biosynthesis (Doroghazi and Metcalf, 2013). Doroghazi and Metcalf (2013) compared the genomes of

Mycobacterium, Corynebacterium, Rhodococcus, Arthrobacter, Frankia and

Streptomyces in detail to determine the extent to which natural product gene clusters are conserved within each genus (Figure 2.4). They found that natural product gene clusters were conserved within Mycobacterium, Streptomyces and Frankia species which suggest vital roles for natural products in the biology of each genus.

Figure 2.4: Genome size, isolation source and number of secondary metabolite gene clusters (Adapted from Doroghazi and Metcalf, 2013).

Hybrid clusters containing both NRPS and PKS core domains have been shown to also occur in one-third of gene clusters by Wang et al. (2014) (Figure 2.5). The hybrid clusters tend to be larger and possess more domains, compared with stand-alone NRPS and PKS gene clusters and, therefore, they may produce more complex products than

NRPS and PKS clusters on their own (Wang et al., 2014).

Figure 2.5: A Venn diagram of PKS, NRPS, and hybrid gene-cluster numbers. The gene-cluster numbers of bacteria, archaea, and eukarya are shown in red, purple, and blue, respectively. The values in parentheses represent the numbers of hybrid enzymes that contain both NRPS and PKS core domains (Adapted from Wang et al., 2014).

Effective methods for assessing the presence of these biosynthetic pathways include the detection of PKS and NRPS genes by PCR, if primers are conserved, or whole- genome sequencing. Since these biosynthetic gene clusters are usually made of very long genes that encode for multi-modular enzymes, obtaining whole genome sequences can help to locate these gene clusters and accurately identify them as was done by Lee et al. (2020) with 30 Streptomyces strains. However, in a study by Ayuso-

Sacido and Genilloud (2005), 210 strains of actinobacteria from 33 genera were tested

29 with customized primer sets. They found that 79.5% of the strains contained NRPS gene clusters and 56.7% of strains contained PKSI gene clusters after PCR amplification. This study will focus on using customized primer sets designed for actinobacteria to target and amplify these areas of the genome.

2.2 Harpagophytum procumbens: A Southern African endemic plant with therapeutic potential

2.2.1 Botanical description and distribution

The genus Harpagophytum (Family: Pedaliaceae), also known as Devil’s Claw, is a perennial native and well-adapted plant to the arid conditions of the southern part of the African continent (McGregor, 2009; Muzila et al., 2014). As seen in Figure 2.6, fruits are woody, longitudinally dehiscent, almost flattened, generally elliptic and armed along the edges (Muzila et al., 2014). Inside, seeds are arranged in rows within each loculus and enclosed by 2 seed coats. The outer seed coat is brownish-black, imperfectly quadrilateral with sharp edges, rough textured and fibrous. The second coat is light brown, highly obstinate and virtually elastic when drenched in water

(Jordaan, 2011). Leaves are big, with 3 - 5 lobes which are petiole, with wavy scalloped margins and occur in opposite arrangement along the entire semi-woody branches. They are covered in white mucilaginous cells, making them appear a grayish-green colour (Muzila et al., 2014). Flowers are perigynous, hermaphroditic, perfect, zygomorphic, solitary, and non-sessile trumpets with colours including pink, red, or purple with a yellowish center (Muzila et al., 2014).

The Devil’s Claw is widely distributed in the Kalahari Sands of Namibia, Botswana,

South Africa, Angola, Zambia, and Zimbabwe (Figure 2.7). Common habitat characteristics of Harpagophytum are areas with annual rainfall 300 – 500 mm, minimum temperatures of 3.0 – 3.5 ºC, maximum temperatures of 32 – 36 ºC, variable

30 soil types but predominantly sand and altitudes of between 700–1400 m above sea level, but with some notable differences between taxa. It is comprised of two species:

Harpagophytum procumbens (with two subspecies, procumbens and transvaalensis) and Harpagophytum zeyheri (with three sub-species, zeyheri, sublobatum and schiiffii)

(Grote, 2003). These species consist of herbaceous, perennial, xerophytic herbs with multiple creeping stems, which survive unfavourable weather through its succulent underground tubers (Muzila et al., 2014). This underground food storage organ

(geophyte) has positive gravitropism in the tuberous main root. From this main root, plagiotropical thick secondary roots, which can reach a length of 5 – 25cm, develop

(Cole and Strohbach, 2007). H. procumbens ssp. procumbens is found mostly at 1000

– 1400 m, H. procumbens ssp. transvaalense at 700 – 1400 m, H. zeyheri ssp. zeyheri at 900 – 1000 m, H. zeyheri ssp. sublobatum at 700 – 1400 m, and H. zeyheri ssp. schijffii at 1000 – 1200 m specifically in Botswana (Surveys and Mapping. 2014).

Figure 2.6: H. procumbens plant and its fruit (SANBI, 2017)

Figure 2.7: Distribution of species and subspecies of Harpagophytum in southern

Africa (Adapted from Ihlenfeldt and Hartmann, 1970).

Despite the low survival rates of its seedlings, H. procumbens is considered a pioneer or even weedy species (Surveys and Mapping. 2014). It is frequently found growing in areas where the soil has been disturbed or where grazing demands are elevated (Cole and Strohbach, 2007). Annual shoot growth from the perennial tuber begins after the summer rain, after which the shoots die back into winter dormancy (Cole and

Strohbach, 2007).

2.2.2 Ethnomedicinal use of H. procumbens

H. procumbens has been used medicinally for centuries by the indigenous people of

Southern Africa, mainly the San (Matlahare, 2002; Stewart and Cole, 2005). H. procumbens is used traditionally for a wide variety of health conditions such as fever relief, blood diseases, muscular aches and pains, and as an analgesic during pregnancy in the form of infusions, decoctions, tinctures, powders and extracts (Van Wyk et al.,

2002). Dried, powdered secondary tubers have been used directly as a wound dressing or mixed with animal fat or Vaselines to make a wound- and burn-healing ointment

(Van Wyk et al., 2002). It has also been administered to pregnant women to relieve pain, and in a lower dose after delivery (Watt and Breyer-Brandwijk, 1962).

Decoctions of the secondary tubers have been used to relieve stomach and postpartum pains. An infusion is taken for the relief of fevers, as a bitter tonic, and for unspecified

‘blood diseases’, rheumatism, and for treating liver, kidney, pancreas and stomach ailments. The ointment is also applied to various skin lesions including sores, ulcers, boils, and cancerous growths (Watt and Breyer-Brandwijk, 1962; Von Koenen, 2001;

Grote, 2003). Von Koenen (2001) also reported it being used to treat syphilis and gonorrhea by the Herero people. When taken regularly, H. procumbens has a subtle laxative effect and minute doses of the plant extract are used to alleviate menstrual cramps, whereas higher doses aid in expelling retained placentas (Van Wyk and

Gericke, 2000). H. zeyheri is also used traditionally to prevent witchcraft, while the

Bushmen eat raw tubers, as they believe in their medicinal power only when they are taken orally (Grote, 2003).

2.2.3 Bioactivity of H. procumbens extracts

In western medicine, the secondary tubers are harvested for medicinal purposes due to the active ingredients that have analgesic effects (a remedy for fevers and allergies),

33 including harpagoside, and anti-inflammatory properties (Cole and Strohbach, 2007).

The medicinally most significant ingredients are iridoid glycosides (Wegener, 2000).

Other iridoids that are present in extracts of Devil’s Claw root are procumbide and harpagide (Brien et al., 2006). Iridoids represent an archetypal chemical constituent evident in the entire Pedaliaceae family, are characteristic for the order Lamiales, present in numerous traditional herbal medicines, and display a wide array of bioactivity (Wegener, 2000). Phenol derivatives, such as acetoside, and flavonoids, such as kaempferol and luteolin, may also contribute to the pharmacologic properties of the extract (Brien et al., 2006). Numerous phytochemical investigations have led to the isolation of iridoids and other substances including harpagoquinones, amino acids, flavonoids, phytosterols and carbohydrates from H. procumbens (Gruenwald, 2002).

Recent scientific studies illustrate that extracts of the secondary tubers of H. procumbens are effective in the treatment of degenerative rheumatoid arthritis, osteoarthritis, tendonitis, kidney inflammation, heart disease, dyspepsia and loss of appetite (Wichtl and Bisset, 2000; Stewart and Cole, 2005). For example, Warnock et al. (2007) conducted a clinical study with more than 200 patients suffering from rheumatic disorders that showed significant improvement based on patient assessments of global pain, stiffness, and function after 8 weeks of ingesting

Harpagophytum tablets. Compounds like harpagoside, 8-coumaroylharpagide and verbascoside found in the tubers of Harpagophytum are well-known to inhibit the arachidonic, cyclooxygenase 2 (COX-2), and lipo-oxygenase (LOX) pathways

(McGregor et al., 2005; Abdelouahab and Heard, 2008). Ex-vivo application of H. procumbens to porcine skin suppressed the COX-2 products, prostaglandin E2 (PGE-

2) and lipoxygenase (5-LOX), suggesting a capacity to cure inflammation in deeper subcutaneous tissues as in arthritis (Ouitas and Heard, 2009).

Additionally, extracts from tubers of H. procumbens have also been shown to suppress lipopolysaccharide-stimulated (LPS) expression of COX-2, and inducible nitric oxide synthase (iNOS) in cell lines (Jang et al. 2003). It also inhibits the release of tumour necrosis factor-alpha (TNFα), interleukin (IL)-6, IL-1β and prostaglandin E2 (PGE-

2), which prevents gene expression of TNFα and IL-6 mRNA in human monocytes, and COX-2 in RAW 264.7 cells (Inaba et al., 2010). Similarly, effects were noted on

TNFα-induced mRNA synthesis and protein production of the atherogenic adipokines including IL-6, PAI-1, and MCP-1, suggesting that harpagoside may prevent obesity- induced atherosclerosis (Kim and Park 2015).

Furthermore, extracts from H. procumbens also block the AP-1 pathway via inhibition of the transcription of AP1 genes that are stimulated by the LPS (Fiebich et al., 2012).

Antimutagenic properties of harpagoside have been indicated in in vitro tests of H. procumbens against the mutagenic and carcinogenic 1-nitropyrene (Luigi et al., 2015).

For evaluation of the potential to counteract osteoporosis, in vitro analyses were conducted using mice osteoblastic cells together with the evaluation of in vivo bone status of mice (Chung et al., 2016). The results indicated that harpagoside can stimulate osteoblast differentiation and maturation, as well as inhibit osteoclast formation. An anti-Alzheimer effect has also been indicated, with verbascoside apparently being the crucial component for inhibition of cholinesterases (Bae et al.,

2014). Even an anti-obesity effect has been indicated; due to suppression of the hunger hormone ghrelin when mice lost their appetite when treated with an H. procumbens extract (Torres-Fuentes et al. 2014).

Multiple toxicity studies in mice revealed low toxicity, however toxicology data available for H. procumbens extracts is unsatisfactory, does not assure safety for human use, and that repeated-dose and chronic toxicity studies, as well as

35 reproductive, genotoxicity, mutagenicity and carcinogenicity studies, are urgently required (Mncwangi et al., 2012). Adverse effects reported have been few, but Cuspidi et al. (2015) described one case where a healthy postmenopausal woman developed hypertension after self-medication with two daily tablets of H. procumbens for two weeks. Another study conducted by Al-Harbi et al. (2013) noted that during acute toxicity studies, there were no external alarming toxicity symptoms in animals except a slight decrease in locomotor activity in the animals treated with a higher dose of the

H. procumbens capsule contents. In addition, it was reported to induce additive analgesic activity when combined with other analgesics and anesthetics and might cause some central nervous system (CNS) depressant effect. However, Al-Harbi et al.

(2013) concluded that treatment with Devil's claw capsule contents in the given dose for a prolonged period of time, to be safe. Thus, H. procumbens is a known source for various biologically active compounds which could possibly be produced by its endophytic actinobacteria.

2.3 Rationale for plant selection

Actinobacteria from hot and highly thermophilic environments provide products that could endure extremely high temperatures and still show reasonably good activity

(Agarwal and Mathur, 2016). In semi-arid areas such as Namibia, many extremophiles might form plant-microbe associations for both the plants’ and microorganisms’ mutual benefit to adapt to this unpredictable and harsh environment. H. procumbens has been used medicinally for centuries and some of its medicinal qualities might be attributed to endophytic actinobacteria.

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CHAPTER 3: PHYLOGENETIC PROFILING AND ANTIMICROBIAL POTENTIAL OF THE ENDOPHYTIC ACTINOBACTERIA ISOLATED FROM HARPAGOPHYTUM PROCUMBENS: A SOUTHERN AFRICAN MEDICINAL PLANT M.E. Lang1, S. Louw2 and J.D. Uzabakiriho1 1Department of Biological Sciences, University of Namibia, Namibia 2Department of Chemistry and Biochemistry, University of Namibia, Namibia ABSTRACT

Endophytic actinobacteria associated with ethnobotanical medicinal plants are key reservoirs for the discovery of novel biomolecules and enzyme activities. The knowledge of such endophytic actinobacteria in the Southern Africa arid regions remains scanty. This study was designed to isolate and investigate the antimicrobial activity and determine the taxonomic diversity of endophytic actinobacteria from the

Devil’s claw (Harpagophytum procumbens), a well-known Kalahari Desert plant with indigenous pharmaceutical uses. The antimicrobial activity was evaluated using perpendicular screening, culture filtrate extracts disk diffusion and minimum inhibitory concentration (MIC) methods. From a total of 140 isolates, only 23 were selected based on their antimicrobial activity against an array of human pathogens.

Amongst the various extracts (ethyl acetate, chloroform and methanol) tested, ethyl acetate disc diffusion fraction exhibited a broad-spectrum antimicrobial activity against test organisms and significantly higher zone of inhibition and the lower MIC values (p = 0.000) as compared to other extracts, for instance, extracts from isolate

B44 (Curtobacterium sp.) demonstrated a significant broad-spectrum potential against

L. monocytogenes (IZ: 29.00 ± 2.65 mm, MIC 2.5 µg/ml) followed by M. avium (IZ:

27.6 ± 2.25 mm, MIC 2.5 µg/ml) and S. enterica (IZ: 25.33 ± 1.15 mm, MIC 3 µg/ml).

The lowest results were obtained against B. cereus (IZ: 21.33 ± 1.15 mm, MIC 3

µg/ml), E. coli (IZ: 23.00 ± 1.00 mm, MIC 3 µg/ml) and S. aureus (IZ: 23.00 ± 2.65 mm, MIC 3 µg/ml). Nevertheless, it showed no activity against C. albicans. Further, greater inhibitory activities against gram-negative than gram-positive bacteria were observed. Antimicrobial analysis coupled with the results of amplifying gene clusters coding for polyketide synthetase (PKS-I) and nonribosomal peptide synthetase

(NRPS) demonstrated a significant broad-spectrum potential against all the test organisms except C. albicans. The subsequent 16S rRNA gene partial sequence analysis of the 23 isolates revealed 6 families affiliated to 7 genera that included the dominant Streptomyces genus (53%) whereas rare genera (Agromyces, Nocardiopsis,

Rubrobacter, Patulibacter, Rhodococcus, Curtobacterium) and 3 unidentified strains accounted for 43%. The phylogenetic analysis suggested Streptomyces, Patulibacter,

Rhodococcus, and Rubrobacter are potentially new species. The highest synergistic effect was tested for A3, A63, A65, B12 and B44 by the lowest MIC and the highest zones of inhibition. All extract mixtures showed synergistic effects against all test microorganisms except for the mixture of extracts from isolates A3 and A63 that showed antagonistic effects on their zones of inhibition. Furthermore, 74% of the actinomycete isolates tested positive for urease production, 83% for gelatin degradation, 74% for protease production, 65% for starch degradation, 48% for indole- acetic acid production and 96% for catalase production. Finally, for the best performing isolates (A65, B12 and B44) secondary metabolite biosynthesis was optimized as depicted by zones of inhibition that increased on starch casein media supplemented with H. procumbens extract at optimal temperatures and pH ranging between 34 °C - 38 °C and 6.4 - 6.8, respectively. This study suggests that the endophytic actinobacteria isolated from H. procumbens are diverse and promising sources of bioactive antimicrobial compounds.

Keywords: H. procumbens, actinobacteria, antimicrobial, endophytes, medicinal plants.

3.1 INTRODUCTION

Harpagophytum procumbens (Family: Pedaliaceae) popularly known as Devil’s Claw is a native herbaceous, perennial plant that thrives in the Kalahari Desert of Southern

Africa (Muzila et al., 2014). It has been used by the indigenous San people (Matlahare,

2002; Stewart and Cole, 2005) for a wide variety of health conditions such as fever relief, blood diseases, muscular aches and pains, an analgesic during pregnancy, rheumatism, liver, kidney and pancreatic ailments, osteoarthritis, tendonitis, heart disease, dyspepsia, and loss of appetite (Watt and Breyer-Brandwijk, 1962; Van Wyk and Gericke, 2000; Wichtl and Bisset, 2000; Von Koenen, 2001; Grote, 2003; Stewart and Cole, 2005). In modern medicine, the secondary tubers are harvested for medicinal purposes due to the active ingredients that have analgesic effects including harpagoside, and anti-inflammatory properties (Wichtl and Bisset, 2000; Stewart and

Cole, 2005; Cole and Strohbach, 2007). All medicinal plants surveyed to date have exhibited an inherent association with a wide range of microorganisms (Singh and

Dubey, 2018).

Endophytes colonize the inter- and/or intracellular plant tissues, for all or part of their life cycle, without causing any apparent symptoms of disease (Bulgarelli et al., 2013;

Rout and Southworth, 2013; Gouda et al., 2016; Gos et al., 2017; Kandel et al., 2017;

Singh and Dubey, 2018). The continual metabolic interactions between endophytic microorganisms and their host plant seem to serve as a strong evolutionary pressure for the endophytes to synthesize secondary metabolites (Kaul et al., 2012;

Vigneshwari et al., 2019). Endophytes associated with medicinal plants, rather than the plants themselves, represent a huge and largely untapped reservoir of bioactive

47 compounds (Qin et al., 2010; Selvam, Vishnupriya and Bose, 2011; Gouda et al.,

2016; Matsumoto and Takahashi, 2017). These naturally occurring molecules offer prospects for a vast assortment of applications and the basis for the synthesis of effective molecules in medical, pharmaceutical, agricultural and other industrial sectors (Gouda et al., 2016; Noriler et al., 2018; Arora et al., 2019). Endophytic actinobacteria are prevalent in medicinal plants and are promising sources of biologically active natural compounds (Qui et al., 2015).

In addition, the escalating levels of infectious diseases and multidrug-resistant human pathogenic microorganisms have become a worldwide health concern (Sharon et al.,

2013; Subramani and Aalbersberg, 2013; Subramani and Sipkema, 2019). Moreover, the discovery rate of active novel chemical products is decreasing (Saravanakumar et al., 2010). This situation clearly dictates the need for identifying new bioactive compounds for novel drugs. The prospect of discover of new drug molecules could be improved by moving research to unexplored and stressed environments (Tiwari and

Gupta, 2013; Tiwari, Upadhyay and Mösker, 2015). One such habitat could be the desert ecosystems where the combined effects of temperature fluctuations and aridity could lead to unique species adaptations (Makhalanyane et al., 2015). The purpose of this study was to provide the first evidence of endophytic actinobacteria associated with the secondary tubers of medicinal plant H. procumbens and investigate their potential antimicrobial activity against selected human pathogens and evaluate the phylogenetic relatedness among the compelling antimicrobial actinobacteria.

3.2 MATERIALS AND METHODS

3.2.1 Secondary tuber sample collection

H. procumbens secondary tubers were collected from the Khomas region (22º37’4.7”

S, 17º5’44.7” E) and Hardap region (22º51’34” S, 17º6’35.5” E) in May of 2018. The plant was identified in the field by Dr. Uzabakiriho and authenticated through the

National Botanical Research Institute. Three lateral tubers were collected from each location and stored in sterile plastic bags at -4 ˚C until use.

3.2.2 Isolation of endophytic actinobacteria

H. procumbens secondary tubers were cut into pieces of about 2 to 5 cm in length and washed under running water for 3 to 5 min to remove soil and organic debris. They were surface sterilized with 70% ethanol for 5min followed by rinsing 5 times in deionized water. To validate the effectiveness of surface sterilization, water from the last rinse was cultured onto starch casein media (Ramalashmi et al., 2018).

Five grams of tuber were dried with sterile filter paper and subsequently crushed using a sterile mortar and pestle and serial diluted to 10-6 using sterile water. Then 100 µl of each serial dilution was spread onto starch casein media using the spread plate technique in triplicate amended with nystatin and cycloheximide at 10 mg/ml to suppress fungal and bacterial growth, respectively (Janardhan et al.,2014). Plates were incubated at 30 ºC for 28 days and were examined daily.

A total of 140 pure cultures were obtained using the perpendicular streak method of which 23 were chosen for further study after showing antimicrobial activity during perpendicular screening. For preservation, all isolates were kept in 20% glycerol and stored at -20 ºC.

Morphological identification of actinobacteria was carried out according to a method outlined by Khanna, Solanki and Lal (2011) on ISP5 media incubated at 30 ºC for 2 weeks. Briefly, substrate mycelium colour was determined by cutting a piece of the agar containing growth, out, and removing most of the agar with a scalpel blade. A stereo light microscope was used to determine the aerial mass colour. Diffusible pigments were observed on the growth media.

3.2.3 Genomic DNA extraction and molecular identification of actinobacterial

isolates

Stored isolates were washed with double distilled water and centrifuged at 21913 x g for 5 min. The washing step was repeated 3 times. DNA was extracted using a ZR

Fungal/Bacterial DNA kit (Zymo Research, California, USA) according to the manufacturer’s protocol. The extracted DNA was analyzed by gel electrophoresis (1% agarose gel, 5 µl ethidium bromide, 120 V for 45 min, 10 µl DNA, 2 µl 6X loading dye and 12 µl 1 kb ladder) and viewed under UV light. The extracted DNA was subjected to PCR amplification (ESCO Swift MaxPro Thermal Cycler, Canada) targeting the 16S rRNA gene using the 27F (5 ' -GAGTTTGATCCTGGCTCAG-3') and 1492R (5'-GGTTACCTTGTTACGACT-3') primers.

DNA amplification was carried out in 50 µl reaction volumes (2.0 µl of each of the respective primers at final concentrations of 10 µM/µl, 25 µl master mix (containing

Taq polymerase, nucleotide bases and buffer obtained from Inqaba, South Africa), 3

µl template DNA, 18 µl nuclease-free water). The PCR cycling for 16S rRNA was done as follows: 95 ºC hot start for 4 min; 30 cycles of 95 ºC for 55 s (denaturation),

52 ºC for 1 min (annealing), 72 ºC for 1.5 min (elongation) and a final elongation step at 72 ºC for 5 min. Amplified DNA was again analyzed by gel electrophoresis as above

50 and compared to the ladder to confirm that the amplicons contained the correct number of base pairs of about 1500 for 16S rRNA amplification. PCR amplicons were commercially sequenced at Inqaba Biotechnical Industries (South Africa). Sequence results were analyzed and aligned using Chromas lite

(http://technelysium.com.au/wp/chromas/) and Bioedit

(https://bioedit.software.informer.com/7.2/, version 7.2). Consensus sequences were generated and compared with the nucleotide available in RDP

(https://rdp.cme.msu.edu/index.jsp) and NCBI

(http://www.ncbi.nlm.nih.gov/BLAST/) databases to identify the closest match.

The presence of the Polyketide synthase I (PKSI) and Nonribosomal peptide synthetase (NRPS) genes clusters were determined according to the method outlined by Ozcan (2017) with some modifications using primers K1F (5'-

TSAAGTCSAACATCGGBCA-3') and M6R (5 ' -CGCAGGTTSCSGTACCAGTA-

3'), and primers A3F (5'-CSTACSYSATSTACACSTCSGG-3') and A7R (5'-

SASGTCVCCSGTSCGGTAS-3'), respectively. PCR was carried out in 50 µl reaction volumes (2.0 µl of each of the respective primers at final concentrations of 10 µM/µl,

25 µl master mix (containing Taq polymerase, nucleotide bases and buffer obtained from Inqaba, South Africa), 3 µl template DNA, 18 µl nuclease-free water). The PCR cycling for PKSI gene clusters was done as follows: 95ºC hot start for 5 min; 35 cycles of 96 ºC for 45 s (denaturation), 55 ºC for 30 s (annealing), 72 ºC for 45 s (elongation) and a final elongation step at 72 ºC for 10 min. The PCR cycling for NRPS gene clusters was done as follows: 95 ºC hot start for 5 min; 35 cycles of 96 ºC for 45 s

(denaturation), 59 ºC for 30 s (annealing), 72 ºC for 45 s (elongation) and a final elongation step at 72 ºC for 10 min. The amplicons were then analyzed on 1% agarose

51 gel as above to determine the presence or absence of genes by comparing the bands to a positive control.

3.2.4 Phylogenetic analysis

Phylogenetic analysis was carried out according to the protocol outlined by Hall

(2013). A Maximum Parsimony (MP) phylogenetic tree was constructed using generated consensus sequences and aligned using Mega X

(https://www.megasoftware.net/) and ClustalW (http://www.clustal.org/clustal2/) and compared to sequences available in the GenBank database

(http://www.ncbi.nlm.nih.gov/BLAST/). Gaps and missing data were eliminated

(complete deletion option) (Kumar et al., 2018). Branches corresponding to partitions reproduced in less than 50% bootstrap replicates were collapsed.

3.2.5 Active compound extraction and bioactivity evaluation.

3.2.5.1 Screening for antibacterial activity of crude metabolites

The perpendicular screening method as described by Ara et al. (2012) was used against the following test organisms: Enterococcus durans ATCC 6056, Staphylococcus aureus ATCC 25923, Listeria monocytogenes ATCC 13932 and Bacillus cereus

ATCC 10876 which are gram-positive bacteria; Escherichia coli ATCC 25922 and

Salmonella enterica ATCC 35664 that are gram-negative bacteria; Mycobacterium avium ATCC 25291 which is an actinobacterium and Candida albicans ATCC 10231 which is a yeast. Test organisms were each grown in nutrient broth at 37 ºC for 24 h and diluted to make a 0.5 McFarland’s solution. Each isolate was streaked in the center of Mueller-Hinton agar and test organisms were streaked perpendicular to the isolate.

Zones of inhibition were measured using a ruler and recorded.

Of the 140 isolates, the 23 isolates that showed antimicrobial potential were then grown in broth to perform the Kirby Bauer disk diffusion antibiotic susceptibility method as described by Saravanakumar et al. (2010) with modifications. A hundred microliters of 24 h test microorganisms (E. durans ATCC 6056, S. aureus ATCC

25923, L. monocytogenes ATCC 13932, B. cereus ATCC 10876 E. coli ATCC 25922,

S. enterica ATCC 35664, M. avium ATCC 25291 and C. albicans ATCC 10231) were inoculated onto Mueller-Hinton agar. About 100 mL of broth from each isolate was poured into falcon tubes and centrifuged at 1789 x g for 15 min. Sterile paper disks with a diameter of 5 mm were soaked in each supernatant for about 10 min while shaking. These disks were then placed onto the inoculated agar plates in triplicate for each extract within each solvent and each of the test organisms. Penicillin (20 µg/disk) was used as the positive control and sterile broth as the negative control. Plates were placed in the fridge for 30 min to allow diffusion of the extracts and then incubated at

30 ºC for 24 h. After 24 h, plates were removed, and zones of inhibition were measured using a ruler.

3.2.5.2 Secondary screening of antimicrobial activity

Extraction of secondary metabolites was carried out as described by Khanna, Solanki and Lal (2011). The 23 selected antagonistic actinobacteria were each inoculated into respective tubes containing 250 mL of starch casein broth and incubated at 30 °C in a shaker at 7 x g for 14 days. After incubation, the broths were centrifuged at 21913 x g for 10 min up to 3 times, and the cell-free supernatant was extracted with equal volumes of the three solvents including ethyl acetate, chloroform, and methanol. The solvent layers were removed aseptically with pipettes and placed into glass beakers.

Each organic extract was concentrated at 45 °C to dryness by using a rotary evaporator and then recuperated after weighing in 2 mL of the relevant solvent and tested for their

53 antimicrobial activities by using the Kirby–Bauer disc diffusion method (Hudzicki,

2009). The disks were deposited on the surface of Muller–Hinton medium, already containing 24 h grown test microorganisms (E. durans ATCC 6056, S. aureus ATCC

25923, L. monocytogenes ATCC 13932, B. cereus ATCC 10876 E. coli ATCC 25922,

S. enterica ATCC 35664, M. avium ATCC 25291 and C. albicans ATCC 10231).

Penicillin (20 µg/disk) was used as the positive control and the various solvents as the negative control. The plates were incubated at 4 °C for 2 h and later at 30 °C. The diameter of the aureoles of inhibition was measured with a ruler after 24 h.

3.2.5.3 Determination of Minimum Inhibitory Concentration

MIC was determined as illustrated by Wiegand et al. (2008) with modifications. Test microorganisms (E. durans ATCC 6056, S. aureus ATCC 25923, L. monocytogenes

ATCC 13932, B. cereus ATCC 10876 E. coli ATCC 25922, S. enterica ATCC 35664,

M. avium ATCC 25291 and C. albicans ATCC 10231) grown for 24 h in nutrient broth at 37 ˚C, were added to 5 mL of Mueller-Hinton broth, diluted to prepare 0.5

McFarland solutions, and incubated at room temperature for 24-48 h. Each test organism was streaked on a sterile Mueller-Hinton agar plate with a cotton swab and impregnated disks of extracts at various concentrations were placed on the plates and incubated at 37 °C. MIC was determined after 48 h of incubation by noting the concentration at which there was almost no zone of inhibition, similar to an E- test.

Penicillin at different concentrations was used as the positive control and the various solvents as the negative control.

3.2.5.4 Synergistic effects of mixing actinobacteria extracts

Five extracts from isolates A3, A63, A65, B12 and B44, with some of the best results after secondary screening, were selected. Each was mixed with another and again

54 tested for their activity against various test organisms. The same procedures were followed as were used during secondary screening.

3.2.6 Media Optimization

Three of the isolates with the best antimicrobial activities (A65, B12, B44) were selected to determine optimal media conditions for best inhibition against various test organisms. The following conditions were tested: pH (at 6.4, 6.8 and 7.2); incubation temperature (at 34 ºC, 38 ºC and 42 ºC); type of media (Starch casein, Glucose-yeast extract malt and actinobacteria isolation agar); presence and absence of host plant material and interactions between these conditions. Isolates were grown under these various conditions for 2 weeks in the various broth media in an incubating shaker at 7 x g. Secondary metabolites were then extracted using Ethyl acetate by liquid-liquid extraction as described by Khanna, Solanki and Lal (2011). Test organisms were incubated in nutrient broth and grown for 24 h and standardized using the 0.5

McFarland’s standard to adjust turbidity. Screening was carried out using the Kirby

Bauer antibiotic susceptibility method (Hudzicki, 2009). A hundred microliters of 24 h grown test organisms were inoculated onto Mueller-Hinton agar using the spread plate technique. Sterile paper disks with a diameter of 5 mm were soaked in each of the extracts from the supernatants for about 10 min while shaking. These disks were then placed onto the inoculated agar plates in triplicate. Penicillin (20 µg/disk) was used as the positive control and ethyl acetate as the negative control. Plates were incubated at 30 ºC for 24 h and zones of inhibition were measured in mm from the edge of the paper disk to the rim of the inhibition zone.

3.2.7 Statistical analysis

All results presented in this study are the means of three independent replicates. The data was presented as the mean of the three replicates ±standard deviation of the mean.

The normality tests followed the methodology of the Shapiro-Wilk test. The statistical analysis was performed using analysis of variance (ANOVA) to compare extract effects against various test organisms by using the statistical package SPSS 24. The mean difference comparison between the treatments was analyzed by the Tukey HSD test and Duncan multiple range test at a significance level of P ≤ 0.05. A correlation test was also done between secondary screening and MIC.

3.3 RESULTS

3.3.1 Morphological characterization, molecular identification, and

phylogenetic analysis

A total of 23 presumed endophytes were morphologically characterized on ISP5

(Table 3.1). The most common aerial mycelia colours were white (57% of the isolates) followed by grey (17% of the isolates), though isolate A39 had a pinkish colour, isolate

B43 and isolate B44 yellow and isolate B70 green. Approximately 52% of the isolates had fragmented mycelia growth, and 26% of isolates produced diffusible pigments.

PKSI gene clusters were detected in 74% of isolates while NRPS gene clusters were detected in 26% of isolates. Furthermore, 13% (A36, B12 and B44) of isolates showed the presence of both PKSI and NRPS gene clusters, while 13% had neither (Table 3.1).

To examine the relationship among the isolated endophytic actinobacteria isolated from H. procumbens occurring in Central Namibia, partial 16S rRNA gene sequences of the 23 isolates that exhibited potent antimicrobial activity were aligned along with type strains sequences retrieved from RDP and NCBI GenBank databases. Analysis of

56 their partial 16S rRNA gene sequences exhibited a high level of sequence similarity ranging from 91.2 to 100% with the existing strains in the database (Table 3.1). All sequences were deposited in the NCBI GenBank database, and accession numbers were provided (MT903973-MT903995).

The strains were divided into 6 families and 7 genera. Most of the isolates were grouped into Streptomyces (52%). Agromyces (4%), Norcadiopsis (4%), Rubrobacter

(4%), Patulibacter (13%), Rhodococcus (4%), Curtobacterium (4%) and 3 unidentified strains (15%). Tubers collected from location A (close to Rehoboth), contained all the genera except Curtobacterium, while tubers from location B

(Prosperita, Windhoek) only contained the genera Streptomyces, Patulibacter,

Curtobacterium and an unidentified actinobacterium. Eight isolates (35%) showed a high degree of similarities of 98% or above with known strains of Streptomyces misionensis, Agromyces flavus, Nocardiopsis dassonvillei, Rubrobacter aplysinae,

Streptomyces flaveus, Streptomyces virginiae, Curtobacterium pusillum and

Streptomyces spp. as indicated in Table 3.1. Three isolates had a 100% match to unidentified actinobacteria. The low sequence similarities of the other isolates suggest that they might belong to novel actinobacteria taxa.

Table 3.1: Morphological and Molecular Identification of Actinobacteria strains

Isolate Fragmented Aerial Substrate Diffusible PKSI NRPS Closest species % Similarity of colour colour pigment isolate to closest species

A3 (MT903983) - Grey Yellow - - + Streptomyces misionensis (NR0441381) 99.4% A7 (MT903994) - White Yellow - + - Unidentified actinobacteria 100% A29 (MT903973) - NA Yellow - + - Agromyces flavus (NR10833801) 99.5% A36 (MT903984) + Grey Light brown + + + Streptomyces sp. (LC435676.1) 95.72% A38 (MT903974) + White White - - - Nocardiopsis dassonvillei 99.4% A39 (MT903975) + Pinkish Grey - - - Rubrobacter aplysinae (NR0746351) 98.3% A57 (MT903995) - Grey Yellow - - + Streptomyces misionensis (NR0441381) 93.2% A63 (MT903976) - White Beige + + - Patulibacter brassicae (NR1536701) 97.5% A64 (MT903985) + White Grey - + - Streptomyces flaveus (NR 0434911) 98% A65 (MT903986) + White Grey/Black - + - Streptomyces flaveus (NR 0434911) 96.4% A66 (MT903977) - White Yellow - + - Unidentified actinobacteria 100% A67 (MT903978) - NA Pink - + - Rhodococcus agglutinans (NR1368601) 91.2% A68 (MT903987) + White Grey + - - Streptomyces virginiae (NR1156211) 100% A69 (MT903988) + White Grey - + - Streptomyces flaveus (NR 0434911) 97.4% A70 (MT903989) + White Grey - + - Streptomyces flaveus (NR 0434911) 95.5% B12 (MT903990) - Grey Grey + + + Streptomyces vietnamensis (NR0437101) 96.4% B21 (MT903991) + White Grey - + - Streptomyces flaveus (NR 0434911) 97.4% B23 (MT903979) - White Beige + + - Patulibacter brassicae (NR1536701) 97.6% B24 (MT903980) - White Beige + + - Patulibacter brassicae (NR1536701) 95.2% B43 (MT903981) - Yellow Yellow - + - Unidentified actinobacteria 100% B44 (MT903982) + Yellow White - + + Curtobacterium pusillum (NR1048391) 99.6% B69 (MT903992) + White Grey - + - Streptomyces flaveus (NR 0434911) 97.4% B70 (MT903993) + Green White - - + Streptomyces spp. 100%

The genus Streptomyces and non-Streptomyces genera were analyzed in separate phylogenetic trees (Figure 3.1 and Figure 3.2) The phylogenetic trees demonstrated that all endophytic actinobacteria were grouped into 7 different clades for actinobacteria, three for the Streptomyces genus tree in Figure 3.1 and four for the non-

Streptomyces genera tree in Figure 3.2. In both Figure 3.1 and Figure 3.2, most isolates did not cluster with the strains they showed high similarity to using BLASTn on NCBI and RDP.

Isolates A3 and A57 in clade 1 clustered with S. misionensis, S. vellosus and S. tendae with a bootstrap value of 100%, isolates B12 and A36 in clade 3 clustered with S vietnamensis with a bootstrap value of 96% and isolate B70 in clade 3 clustered with

S. griseoviridis with a bootstrap value of 98%. Isolate A68 in clade 3 clustered with S laurentii and not S. virginiae to which it showed the highest similarity after performing the BLASTn on NCBI and RDP, indicating that they might be novel species. These values indicate that the isolates are probably species of Streptomyces. The remaining isolates in clade 2 clustered together but not with any known strains. These isolates formed a separate monophyletic distinct cluster supported by a high bootstrap value

(99%) with recently described Streptomyces genus but not associated with any of the type strains, suggesting they might be novel species.

A68 53 Streptomyces laurentii DNA str B70 97 Clade 3 98 Streptomyces griseoviridis str B12

96 Streptomyces vietnamensis stra 64 94 A36 A69 100 A64 A70 Clade 2 A65 98 84 B21 100 B69 A57 Streptomyces vellosus strain H 100 100 Streptomyces tendae strain 174 Clade 1 100 A3 96 Streptomyces misionensis JCM 4 Streptomyces misionensis strai Streptomyces nodosus strain AT Streptomyces yerevanensis stra Streptomyces flaveus strain NR Streptomyces cinereus strain N Streptomyces bikiniensis strai

80 Streptomyces violaceorectus st

50 Streptomyces phaeochromogenes Streptomyces cinereoruber subs Streptomyces olivoreticuli sub

100 93 Streptomyces sporoverrucosus S 97 Streptomyces virginiae strain Streptomyces lavendulae strain Streptomyces plumbiresistens s

60 Streptomyces rochei strain Q1 66 Streptomyces sp. strain PEC119 Streptomyces coelicoflavus str Streptomyces levis strain NGA2 94 Streptomyces pseudogriseolus s 71 Streptomyces flaveolus strain Streptomyces parvulus strain K Bacillus cereus strain 9620

Figure 3.1: Consensus of the most likely tree inferred using 16S rRNA sequences of endophytic actinobacteria associated with H. procumbens. The phylogenetic tree represents a Maximum Parsimony analysis of 12 isolates with their reference strains of Streptomyces sp.

The phylogenetic tree of rare actinobacteria is shown in Figure 3.2. It indicated that rare actinobacteria were diversely distributed within 4 clusters. In the first clade, isolate A29 clustered with A. flavus, A subtropicus and A. indicus with a bootstrap value of 93% and is thus likely a species of Agromyces. Isolates A7, A66 and B43 in clade 3 clustered with an unidentified actinobacterium strain with a bootstrap value of

86%, while isolate A38 in clade 4 clustered with an Actinomycetelas bacterium and

N. dassonvillei with a bootstrap value of 86% and thus might be a species of

Nocardiopsis. The remaining isolates (A39, A67, B44, B24, B23 and A63) formed clade 3 and clustered together but not with other known strains or the strains they showed the highest similarity to when performing the BLASTn on NCBI and RDP, indicating that they might be novel species.

98 A38 86 Actinomycetales bacterium JAMS Clade 4 100 Nocardiopsis dassonvillei stra Nocardiopsis synnemataformans 100 100 Unidentified Actinomycete OPT2 B43 Clade 3 100 86 A66 91 A7 A39

97 A67 100 B44 Clade 2 68 B24

100 B23 52 A63 52 Patulibacter americanus strain

99 Patulibacter medicamentivorans 84 Patulibacter brassicae strain

97 Rhodococcus equi straiN GMA339 98 Rhodococcus olei strain Ktm 20 100 Rhodococcus hoagii strain Cr35 Rhodococcus agglutinans strain

84 Agromyces flavus strain CPCC 2 96 90 A29 93 Clade 1 Agromyces subtropicus Agromyces indicus strain ST20 73 Curtobacterium citreum strain Curtobacterium oceanosedimentu 99 Microbacteriaceae bacterium SA 98 98 Uncultured Curtobacterium sp. 97 Curtobacterium flaccumfaciens Rubrobacter bracarensis strain 100 Rubrobacter aplysinae strain R Bacillus cereus strain 9620

Figure 3.2: Consensus of the most likely tree inferred using 16S rRNA sequences of endophytic actinobacteria associated with H. procumbens. The phylogenetic tree represents a Maximum Parsimony analysis of 11 isolates with their reference strains of non-Streptomyces sp.

3.3.2 Antimicrobial potential of isolated Actinobacteria strains

Of the 140 isolates, 23 displayed antimicrobial activity during primary screening to various degrees with inhibition zones that ranged from 0.33 mm - 16.33 mm

(Appendix table 3.1). Hence, they were chosen for further studies. The extracts from the 23 isolates displayed broad-spectrum activity with most having activity against all the test microorganisms except for extracts from isolates A65, A66, A69, B43 and B70 not displaying activity against C. albicans ATCC 10231. This is to be expected as C. albicans is a yeast. The isolates with the highest zones of inhibition against each of the test microorganisms are displayed in Figure 3.3 as compared to the positive control of penicillin. All measurements not displayed in the figure can be found in Appendix

Table 3.1. There was a statistically significant two-way interaction between the test organisms and actinobacteria extracts, p = 0.00 by two-way ANOVA, though their activity did differ against different bacterial species. The isolates with the best activity overall were A57 (closest match Streptomyces misionensis), B12 (closest match

Streptomyces vietnamensis) and A3 (closest match Streptomyces misionensis), as determined by the post hoc Tukey HSD test.

Isolates with highest activity against test organisms during primary screening 30.00 25.00

20.00 a a a aa a a 15.00 a a a 10.00 a 5.00

0.00 Zone of inhibition inhibition of (cm) Zone

Test microorganisms

Penicillin A66 A3 B70 A57 A67 A39 A3 B12

Figure 3.3: Zones of inhibition with standard deviation bars of isolates showing the best activity against the various test microorganisms during primary screening. a= statistically significant compared to the positive control of penicillin after a Duncan multiple range test at P<0.05.

All 23 actinobacteria isolates were subjected to antimicrobial compound extraction using ethyl acetate, chloroform, and methanol by liquid-liquid extraction method. The extracts obtained from ethyl acetate and chloroform produced the maximum inhibitory zones when compared with the extracts obtained from methanol. They displayed antimicrobial activity during secondary screening against at least one test microorganism with zones of inhibition that ranged from 1 mm - 33 mm for ethyl acetate extracts, 1 mm - 19 mm for chloroform extracts and 1 mm - 8 mm for methanol extracts (Appendix table 3.2-Appendix table 3.4). For ethyl acetate and chloroform extracts, approximately 65% and 57%, respectively, showed activity against all test microorganisms. Methanol extracts had the lowest activity with none showing activity against C. albicans ATCC 10231. The top-performing ethyl acetate and chloroform

64 extract results can be seen in Figures 3.4 and 3.5 compared to the positive control, penicillin. All zones of inhibition for methanol extracts were 8 mm or lower.

Inhibition zones of top perfoming Ethyl acetate extracts against the test microorganisms

35.00 a a a 30.00 a a a a a a 25.00 aa a a a a a a a b bb a b aa aa 20.00 b b bbbb b b 15.00 b 10.00 c 5.00 c cc

0.00 Zones Zones inhibition of (mm)

Test microorganisms

Penicillin B44 A63 B23 B24 B12 A57 A39 A67

Figure 3.4: Actinobacteria isolate ethyl acetate extracts that had the largest inhibition zones when tested against the various test microorganisms. a =High activity (20+ mm), b = Medium activity (10-19.9 mm), c =Low activity (0-9.9 mm). All zones of inhibition were statistically significant when compared to the positive control, penicillin, with a Duncan multiple range test at P<0.05.

Inhibition zones of top performing Chloroform extracts against the test microorganisms

30.00 25.00 20.00 b b b b b b b b 15.00 b b b cb b b b b b b b b b b b b cc c b bb b b 10.00 b c c 5.00 c c cc c

0.00 Zones of inhibition (mm) inhibition of Zones -5.00

Test microorganisms Penicillin B44 A63 B23 B24 B12 A29 A69

Figure 3.5: Actinobacteria isolate chloroform extracts that had the largest inhibition zones when tested against the various test microorganisms. b = Medium activity (10-

19.9 mm), c =Low activity (0-9.9 mm). All zones of inhibition were statistically significant when compared to the positive control, penicillin, with a Duncan multiple range test at P<0.05.

Five of the extracts exhibiting broad-spectrum activity were selected and mixed one by one to determine if there were any synergistic or antagonistic effects between them on the zones of inhibition (Appendix tables 3.5-3.7). Figures 3.6 and 3.7 show the mixtures of ethyl acetate extract and chloroform extracts, respectively, with the best activity against the test microorganisms as compared to the positive control, penicillin.

Ethyl acetate extracts (IZ ranges of 1.33 mm – 38 mm) had the best results, followed by chloroform (IZ ranges of 0.33 mm – 26 mm) and then methanol (IZ ranges of 1.67 mm – 12.67 mm) with statistically significant differences among all 3 (p=0.000). All but one mixture showed synergistic effects as zones of inhibition were higher in the mixtures than they were for each separate extract. However, extracts from isolate A3

(closest match Streptomyces misionensis) mixed with those from A63 (closest match

Patulibacter brassicae) seem to have an antagonistic effect as the zones of inhibition were lower for the mixture than it was for each extract separately. There is a trend of all extracts performing poorly against the fungal strain C. albicans ATCC 10231.

Ethyl acetate extract mixtures with the best activity against the test microorganism

45.00 40.00 a a a a 35.00 a a a a b b b b 30.00 b b b b b b b b b b b b b b b b 25.00 b b b b b b b 20.00 15.00 10.00 c c 5.00 c c c

0.00 Zones of inhibition (mm) inhibition of Zones

Test microorganisms

Penicillin A64+B12 A63+B44 B12+B44 A64+B44 A3+B12

Figure 3.6: Zones of inhibition and standard deviation of ethyl acetate extract mixtures that exhibited the best activity against the test microorganisms. a = Very high activity

(30+ mm), b = High activity (20-29.9 mm), c =Low activity (0-9.9 mm). All zones of inhibition were statistically significant when compared to the positive control, penicillin, with a Duncan multiple range test at P<0.05.

Chloroform extract mixtures with the best activity against the test microorganisms

30.00 a 25.00 a a a a b b b a b 20.00 b b b b b b b b b b b b b 15.00 b b b b 10.00 c 5.00 c c c c

Zones of Inhibition (mm) Inhibition of Zones 0.00

Test Microorganisms

Penicillin A63+B44 A63+B12 B12+B44 A3+B44

Figure 3.7: Zones of inhibition and standard deviation of chloroform extract mixtures that exhibited the best activity against the test microorganisms. a =High activity (20+ mm), b = Medium activity (10-19.9 mm), c =Low activity (0-9.9 mm). All zones of inhibition were statistically significant when compared to the positive control, penicillin, with a Duncan multiple range test at P<0.05.

3.3.3 Effect of Cultural Parameters on Antimicrobial Activity

Three of the top-performing isolates with broad-spectrum activity were selected, namely B12 (closest match Streptomyces vietnamensis), B44 (closest match

Curtobacterium pusillum) and A65 (closest match Streptomyces flaveus) to carry out media optimization and test the effects of cultural parameters on antimicrobial activity against three test organisms (Appendix table 3.8). A multiple regression was done to predict inhibition zones in relation to differences in temperature, media, pH, host plant extract, actinobacteria extract and test organisms. These variables statistically significantly predicted inhibition, F (6,1451) =293.036, p=0.000, R2=0.548. The general form of the equation to predict inhibition as produced by SPSS is: Inhibition=

25.082-(0.986 x temperature)-(3.040 x actinobacteria extract)-(1.751 x Test organism)-(4.066 x media)-(0.669 x pH)+(1.934 x host plant extract). Figure 3.8 shows the best zones of inhibition obtained for the 3 isolates, displaying the best cultural parameters for these isolates.

Largest zones of inhibition of chosen isolates after different growth parameters

35 a 30 b b b 25 b

20 c c c 15 c

Zones of inhibition (mm) inhibition of Zones 5

0 E. durans E.coli M.avium E. durans E.coli M.avium E. durans E.coli M.avium pH6.4 pH6.8 pH6.8 38°C 38°C 34°C A65 B12 B44 Different growh parameters and test microorganisms

Figure 3.8: Best activity of the chosen isolates against test microorganisms after being subjected to various growth parameters on starch casein agar containing extracts of the host plant H. procumbens. a = Very high activity (30+ mm), b = High activity (20-29.9 mm), c = Medium activity (10-19.9 mm). All zones of inhibition were statistically significant when compared to the positive control, penicillin, with a Duncan multiple range test at P<0.05.

3.3.4 Minimum inhibitory concentrations (MIC) of the various extracts

The lowest MIC values were obtained from ethyl acetate extracts against all test organisms (Table 3.2 and Table 3.3). Extracts from isolates with the highest sequence similarity to Streptomyces species (A3, A57, B12 and A64) had some of the lowest

MIC values. Extracts from isolate B44 (closest match Curtobacterium pusillum) had

69 the lowest MIC values against most of the test microorganisms. MIC values against C. albicans ATCC 10231 were all above 100 µg/mL. A Pearson correlation was carried out between the MIC and zones of inhibition of secondary screening and a significant

(p = 0.00) negative correlation of -0.548 was obtained, meaning as the zones of inhibition increase, MIC tends to decrease. All MICs for methanol extracts were above

100 µg/mL.

Table 3.2: MIC in µg/mL of ethyl acetate extracts

Test microorganisms Isolate B. E. M. S. L. E. C. S. cereus coli avium aureus monocytogenes durans albicans enterica Penicillin ˃2 >3 >6.5 >2.5 >2.5 >2 - >3 A3 >9.5 >3 >9.5 >7.5 >6.5 >1 - >5.5 A7 >8.5 >4 >8 >7.5 >7 >7.5 - >5 A29 - >6 >9.5 - >8.5 >4 - >5.5 A36 - >7.5 >15 >15 >15 >7.5 - >15 A38 >25 >20 >20 >10 >15 >10 - >25 A39 >30 >15 >15 >20 >25 >15 - >25 A57 >9.5 >3 >9.5 >7.5 >6.5 >1 - >5.5 A63 >3 >3 >6.5 >7.5 >3 >3 - >5 A64 >4.5 >3.5 >5.5 >7.5 >3.5 >5.5 - >4 A65 >4.5 >3.5 >5.5 >7.5 >3.5 >5.5 - >4 A66 >8.5 >4 >8 >7.5 >7 >7.5 - >5 A67 >15 >20 >20 >20 >15 >5.5 - >30 A68 >10 >9.5 - >10 >10 >6 - >7.5 A69 >4.5 >3.5 >5.5 >7.5 >3.5 >5.5 - >4 A70 >5 >3.5 >5.5 >7.5 >3.5 >5.5 - >4 B12 >2 >3 >7 >5.5 >2 >2 - >4.5 B21 >5 >3.5 >5.5 >7.5 >3.5 >6 - >4 B23 >3 >3 >6.5 >7.5 >3 >3 - >4.5 B24 >3 >3 >7 >7.5 >3 >3 - >4.5 B43 >7.5 >4 >9 >6.5 >6.5 >7.5 - >4 B44 >3 >3 >2.5 >3 >2.5 >2.5 - >3 B69 >5 >3.5 >5.5 >7.5 >3.5 >5.5 - >4 B70 >15 >6.5 >3.5 >3.5 >4 >7.5 - >15 -Ethyl acetate used as the negative control had readings of >100µg/mL for all test organisms

Table 3.3: MIC in µg/mL of chloroform extracts

Test microorganisms Isolate B. E. M. S. L. E. C. S. cereus coli avium aureus monocytogenes durans albicans enterica Penicillin ˃2 >3 >6.5 >2.5 >2.5 >2 - >3 A3 >9.5 >7.5 - >30 - >50 _ >30 A7 >70 >50 >80 >30 >30 - - >50 A29 >7.5 >35 - >50 >35 >30 - >45 A36 >20 >20 >35 >40 >25 >15 - >40 A38 - - - >70 >80 >70 - >80 A39 ------A57 >9.5 >7.5 - >30 - >50 _ >30 A63 >5.5 >4.5 >20 >15 >5 >5 - >8 A64 >20 >15 >25 >25 >20 >20 - >30 A65 >20 >15 >25 >25 >20 >20 - >30 A66 >70 >50 >80 >30 >30 - - >50 A67 ------A68 >80 - >70 >60 >60 >60 - >70 A69 >20 >15 >25 >25 >20 >20 - >30 A70 >20 >15 >25 >25 >20 >20 - >30 B12 >8 >15 >20 >9 >4.5 >6.5 - >10 B21 >20 >15 >25 >25 >20 >20 - >30 B23 >5.5 >4.5 >20 >15 >5 >5 - >8 B24 >5.5 >4.5 >20 >15 >5 >5 - >8 B43 >70 >50 >80 >30 >30 - - >50 B44 >15 >20 >20 >9.5 >10 >10 - >15 B69 >20 >15 >25 >25 >20 >20 - >30 B70 - - >90 >60 >35 - - - -Chloroform used as the negative control had readings of >100µg/mL for all test organisms

3.4 DISCUSSION

Revealing the unexplored endophytic actinobacteria from a medicinal plant in arid environments is a promising source for bioprospecting novel bioactive compounds and yet these plants are poorly investigated (Zhao et al., 2012; Tiwari, Upadhyay and Mösker,

2015; Das et al., 2018; Gohain et al., 2019; Subramani and Sipkema, 2019; Musa et al.,

2020). To our knowledge, no scientific attempt has been made to isolate endophytic actinobacteria from H. procumbens a Namibian desert-adapted plant.

Based on 16S rRNA sequence analysis, 20 (87%) of the 23 endophytic actinobacteria were identified at genus level and 3 were unknown taxa. They were taxonomically assigned into 6 families and 7 genera with a high proportion (53%) of Streptomyces species. This predominance of Streptomyces spp. was earlier reported from a wide range of medicinal plants (Qin et al., 2009, 2010; Li et al., 2012; Kaewkla and Franco, 2013; Lee et al., 2014;

Passari et al., 2015; Rajivgandhi et al., 2016; Shan et al., 2018; Gohain et al., 2019).

Isolates A3, A57, B12, A36, and B70 clustered with the species they showed the highest similarity to after performing the BLASTn on NCBI and RDP. The remaining isolates did not cluster with strains they had the highest sequence similarity to. Therefore, more data will be required to determine the relationship between the isolates and the reference strains. Isolates B21 and B69 had a 100% bootstrap value indicating that they might be the same species. These figures indicate that most Streptomyces isolates might be novel species or subspecies.

There were no selective techniques used to target rare actinobacteria as this study focused on isolation techniques that would isolate a broad spectrum of actinobacteria. However, isolates belonging to 6 (47%) rare genera of actinobacteria namely, Patulibacter,

Agromyces, Norcadiopsis, Rubrobacter, Rhodococcus and Curtobacterium were isolated based on their sequence similarities. The ubiquitous occurrence of rare actinobacteria has been documented (Subramani and Aalbersberg, 2013; Tiwari and Gupta, 2013;

Matsumoto and Takahashi, 2017; Subramani and Sipkema, 2019). It is worth noting that

72 the current study is the first to report the presence of these rare endophytic bacteria in the tubers of H. procumbens.

Isolate B43 (Unidentified actinobacteria), A66 (Unidentified actinobacteria) and A7

(Unidentified actinobacteria) clustered together in a monophyletic clade with other unidentified actinobacterial strains with a bootstrap value of 86%. Thus, these three isolates might be closely related and be novel actinobacteria species. Isolate A29 (closest match Agromyces flavus) clustered with other Agromyces sp. with a bootstrap value of

93%. Isolate A38 (closest match N. dassonvillei) clustered with N. dassonvillei with a bootstrap value of 86%. Isolates B24 (closest match P. brassicae), B23 (closest match P. brassicae), A67 (closest match R. agglutinans), B44 (closest match C. pusillum), A63

(closest match P. brassicae) and A39 (closest match R. aplysinae) clustered together with a bootstrap value of 100%. None of these clustered with the strains they showed the highest sequence similarity to. These might thus all constitute novel species within the genera, though genome sequencing data will be required to make that determination.

The genus Patulibacter is rarely isolated and comprises 5 species predominantly soil dwellers (Tiwari and Gupta, 2013). It has been isolated from the rhizosphere of Chinese cabbage (Brassica campestris) (Jin et al., 2016) and Thymus zygis, a wild Mediterranean medicinal plant (Pascual et al., 2016) and soil from a ginseng field (Kim, Lee and Lee,

2012). Endophytic Patulibactor has been isolated from selected medicinal plants from

Southern India (Akshatha, Prakash and Nalini, 2016).

The genera Agromyces, Nocardiopsis, Rhodococcus have been isolated from various environments such as soils (Li et al., 2006; Zhang et al., 2008; Lee et al., 2011), rhizosphere (Jung et al., 2007; Zhang et al., 2008; Hamada, Saitou and Tamura, 2018) and

73 different animal forms (Bennur et al., 2015). Agromyces flavus has mostly been isolated from soil samples in China (Chen et al., 2011), but other Agromyces species like A. arachidis, have been isolated from plants such as Arachis hypogaea (Kaur et al., 2013) and A. aureus from Salix caprea (Corretto et al., 2016).

The genus Rhodococcus currently includes 69 species with validly published names

(https://www.bacterio.net/genus/rhodococcus), but none with correct names as this genus has been highly debated (Gou et al., 2015). Rhodococci species have various properties that make them suitable for bioremediation and degradation of organic pollutants (Fuller et al., 2010; Laczi et al., 2015). Two of its species have been reported to be pathogenic, namely R. fascians and R. equi, the former being a plant pathogen and the latter being a causative agent of pneumonia in various hosts, including immunocompromised humans

(Goethals et al., 2001; Muscatella et al., 2010).

Little is known about the ecology of Rubrobacter strains (Castro et al., 2019). Database- searching revealed ‘Rubrobacteria’ were relatively abundant in several published soil and plant rDNA libraries, but few have been cultured (Holmes et al., 2000) mainly from extreme biomes, particularly high-temperature environments (Castro et al., 2019). Eight species in the genus Rubrobacter have been isolated from varieties of habitats, while three thermophilic Rubrobacter species have been reported to be extremely ionizing radiation resistant (Shivlata and Satyanarayana, 2015; Chen et al., 2018). Though the resistance mechanism has not been satisfactorily deciphered, the complete whole-genome analysis of R. radiotolerans RSPS-4 unveiled the occurrence of genes encoding proteins involved in DNA repair systems, oxidative stress response, and biosynthetic pathways of compatible solute production. They are believed to play a role in alleviating the damage

74 caused by radiation (Castro et al., 2019). Only R. aplysinae is an endophytic species inhabiting marine sponges (Chen et al., 2018).

Members of the genus Nocardiopsis are known to produce a large variety of bioactive compounds (antimicrobial agents, anticancer substances, tumor inducers, toxins and immunomodulators) and novel extracellular enzymes (amylases, chitinases, cellulases, β- glucanases, inulinases, xylanases and proteases), making them ecologically versatile and biotechnologically important (Bennur et al., 2015). The genus consists of 44 reported species (https://www.bacterio.net/genus/Nocardiopsis), two of which are opportunistic human pathogens (N. dassonvillei and N. synnemataformans) and some species are plant endophytes (Bennur et al., 2015). N. dassonvillei has seldomly also been isolated in cutaneous and pulmonary infections (Beau et al., 1999)

Finally, the genus Curtobacterium has been isolated mainly from plants as beneficial endophytes and soil habitats, with C. flaccumfaciens being an important plant pathogen

(Chase et al., 2016). C. pusillum has been isolated from oil-brine fields, human clinical specimens and leaves of rice plants, soybean and corn and can inhibit plant pathogens such as Rhizoctonia solani (Zawadzka et al., 2013). The genus Curtobacterium currently has 8 known species (https://www.bacterio.net/genus/curtobacterium) and was isolated from a human clinical specimen by Funke et al. (2005) for the first time.

Contrasting degrees of diversity among endophytic actinobacteria communities associated with medicinal plants from different regions have been observed. In their study, Qin et al.

(2009) identified 32 genera including Streptomyces, Rhodococcus and Norcadiopsis from over 90 selected medicinal plants. Later, Nocardiopsis and Rhodococcus genera were isolated from the medicinal plant Dracaena cochinchinensis (Salam et al., 2017). In

75 addition, a study done on Camellia sinensis (tea plants) by Shan et al. (2018) from 15 tea cultivars, found 13 different genera including Streptomyces, and Nocardiopsis. Lately,

Jiang et al. (2018) reported 28 genera including Streptomyces, Curtobacterium and

Norcadiopsis isolated from 19 tissues from 5 mangrove plants. Rubrobacter from the rhizosphere of Boswellia sacra (Khan et al., 2017) and Curtobactrium, Nocardiopsis and

Rhodococcus from the medicinal plant Ferula songorica (Liu et al., 2016) were isolated.

None of these studies, however, found actinobacteria of the genera Agromyces and

Rubrobacter.

These differences in actinobacteria diversity could be explained by the fact that each plant thrives in a completely different environment that would prompt adjustments in plant and actinobacteria physiological properties and differences in chemo-attractant compounds

(Singh and Dubey, 2018). In addition to the age and the tissue studied, the sampling season and the isolation methods could have an impact on the diversity of the isolated endophytic actinobacteria (Golinska et al., 2015). The results of this current study confirmed the existence of rich microbial diversity associated with H. procumbens secondary tubers.

Furthermore, endophytic actinobacteria from desert-adapted plants, marine environments and other plants from extreme environments possess noteworthy gene clusters to produce bioactive compounds (Dorofeeva et al., 2003; Kaur et al., 2013; Subramani and

Aalbersberg, 2013; Singh and Dubey, 2018; Subramani and Sipkema, 2019; Sayed et al.,

2020). Reports of endophytic actinobacteria as a source of novel secondary metabolites have been recognized.

Most isolates that had high similarities to Streptomyces species had aerial mycelia colours that were white and grey, with isolate B70 (closest match Streptomyces sp.) being green

76 which are all in the range of colours for Streptomyces (Li et al., 2016). Streptomyces vietnamensis was isolated from the soil in Vietnam that produced white aerial mycelia and a violet-blue diffusible pigment on ISP5 agar (Zhu et al., 2007) as compared to this study, isolate B12 did have a rather purple diffusible pigment but grey aerial mycelia on ISP5.

The genus Agromyces is chemotaxonomically characterized by having MK-12 as the dominant menaquinone and the main peptidoglycan cell wall amino acid 2,4-diamino-n- butyric acid (Chen et al., 2011). They also described it as forming yellow colonies and having no diffusible pigment. Furthermore, Isolate A39 (closest match R. aplysinae) had a pinkish colony morphology which corresponds to a study done by Kampfer et al. (2014).

Jin et al. (2016) describes the species P. brassicae as having white colonies. Isolate A67

(closest match R. agglutinans) was described as a pink coloured non-spore-forming actinobacteria (Gou et al., 2015). Bennur et al. (2015) showed that N. dassonvillei has white aerial and substrate mycelia as well as no diffusible pigment. Curtobacterium species tend to have creamy, yellow or orange pigmented colonies with C. pusillum having glistening and mucoid colonies (Funke et al., 2005). This all corresponds to the morphology of the various isolates within this study as compared to those they had the highest sequence similarity to.

PCR detection of PKSI and NRPS gene clusters indicates their involvement in the regulation of antimicrobial activities in the various isolates (Jackson et al., 2018). The frequency of occurrence of these genes was reported to be 55% and 90% by Qui et al.

(2015), respectively, which is higher when compared to an occurrence of PKS-I of 74% and NRPS of 26% recorded in this current study. The results of this study are comparable with the studies of Ding et al. (2013) and Passari et al. (2015). The high occurrence of

PKSI could be correlated to the production of Siderophores to scavenge iron from nutrient-poor soils (Janso and Carter, 2010) In the current study, only isolates A36

(Streptomyces sp.), B12 (S. vietnamensis) and B44 (C. pusillum) had both these gene clusters of which B12 and B44 expressed excellent antagonistic activity against all test microorganisms except C. albicans.

All the isolates containing at least one of these biosynthetic genes had broad-spectrum activity against the gram-positive, gram-negative and Mycobacterium species, with insignificant activity against C. albicans. This agrees with the findings from other studies such as one by Hernandez-Macedo et al. (2014) that showed that 75% of the isolates containing either NRPS or PKSI gene clusters showed activity against at least one of the pathogens evaluated. In the study by Qui et al. (2015), it was reported that all the 80 bioactive isolates possessed at least one of the four biosynthetic gene clusters they were testing for. However, 3 bioactive strains in this study, namely isolates A38, A39 and A68, had neither of the gene clusters tested for, or the primers did not bind, but still had relatively high antimicrobial activity against some of the test microorganisms. It might be that these isolates contain gene clusters not tested for.

Among 140 isolates were obtained in this study, but only 23 (16%) demonstrated potential antimicrobial activities against at least one of the various test organisms during primary screening. This activity rate is lower compared to Janso and Carter (2010), Gohain et al.

(2019) and Shan et al. (2018) who reported a much higher rate of 46%, 27%; and 23% respectively. According to Kurosawa et al. (2008), Subramani and Aalbersberg (2013) and Silva-Lacerda et al. (2016), to stimulate regulatory pathways to produce secondary metabolites, several techniques can be used including varying culture conditions, and co-

78 culturing two or more organisms together. Hence, the isolates that did not show any antimicrobial activities cannot be firmly indicated as non-antimicrobial producers.

Of the three solvents used, ethyl acetate extracts had the best antimicrobial activity. In a study done by Arasu et al. (2014), they found that their ethyl acetate extracts showed significant antibacterial and antifungal activity compared to the methanol and chloroform extracts. In contrast, Alimuddin et al. (2011) found that methanol extracts showed activity against a higher total number of antifungal strains as compared to ethyl acetate and chloroform. These differences could be due to different polarities of the compounds in the study, and thus different solvents were more effective (Eloff, 2019). Out of the three solvents used in this study, methanol is the most polar, followed by ethyl acetate and chloroform is non-polar. Thus if the compounds are more non-polar, methanol would not be an effective solvent for extraction as a solvent needs to have a similar polarity to the solute in order for the solute to dissolve (Altemimi et al., 2017).

Comparing zones of inhibition of crude extracts to those after extracting compounds with various solvents, some zones of inhibitions are larger before extraction. For example, the zone of inhibition of isolate A7 (Unidentified actinobacteria) against B. cereus ATTC

10876 before extraction with ethyl acetate was 14.00 mm ± 1.00 and after extraction was

2.67 mm ± 0.58mm. These differences could be because solid (used in primary screening) and liquid (used after extraction) media may cause the microbes to produce different metabolites or that some compounds are lost during the extraction process (Charousova et al., 2019).

About 65% of the 23 crude extracts showed broad-spectrum antagonistic activity against the gram-positive and gram-negative test microorganisms as well as Mycobacterium

79 avium, with B12 (closest match S. vietnamensis) and A64, A65, A69, A70, B21 and B69

(isolates closely related to S. flaveus) exhibiting the strongest activity (MIC ranging between 2 and 7 µg/ml) and (MIC between 3 µg/ml – 7.5 µg/ml), respectively. In earlier studies, S. vietnamensis and S. flaveus were reported to produce broad-spectrum antibacterial and antifungal metabolites (Hwang et al., 1996; Chung et al., 2011; Seipke et al., 2012; Deng et al., 2015). Surprisingly, in the current study, extremely low activity against C. albicans has been recorded. According to (Gohain et al., 2019), this discrepancy in antagonistic activities of the same strain confirms that complex chemical properties of the host plant could impact the production of endophytic secondary metabolites.

This study demonstrated that secondary metabolites from actinobacteria associated with

H. procumbens have stronger antibacterial activity against gram-negative than gram- positive bacteria. Furthermore, the predominant active strains and potentially new species were tentatively identified as Streptomyces. This is in line with previous reports (Hasani et al., 2014; Shivlata and Satyanarayana, 2015; Undabarrena et al., 2016). Our study suggests the Streptomyces genus to be active against all the test microorganisms used in this study with the exception of Candida. Streptomyces species are known to be fastidious and represent an enormous biosynthetic potential resource (Lee et al., 2014; Golinska et al., 2015). For instance, extracts from A3 and A57 closely related to S. misionensis, though endowed with broad-spectrum activity, have exhibited the strongest activity against E. coli (MIC: 3µg/ml) and E. durans (MIC: 1µg/ml). S. misionensis is known for the production of a trypsin inhibitor with a strong broad-spectrum antibacterial activity against B. cereus, Erwinia, Ralstonia, S. typhi, and E. coli with MIC of 0.06, 0.06, 0.015,

0.12, and 0.48 mg/mL, respectively (Heidarian et al., 2018).

Rare actinobacteria are an important source of a plethora of bioactive metabolites (Li et al., 2006; Tiwari and Gupta, 2013; Tiwari, Upadhyay and Mösker, 2015; Undabarrena et al., 2016; Matsumoto and Takahashi, 2017). Isolates belonging to Agromyces and

Patulibacter (A63, B23 and B24), Curtobacterium (B44) and Rhodococcus (A39, A67) species in this report have shown broad-spectrum activities against a variety of test organisms. These genera have been isolated from rhizospheres, marine sediments, or as endophytes in previous culture-dependent and independent studies (Jung et al., 2007;

Kurosawa et al., 2008; Kim, Lee and Lee, 2012; Tiwari and Gupta, 2013; Corretto et al.,

2016; Jin et al., 2016; Hamada, Saitou and Tamura, 2018). However, it is worth noting that to the best of our knowledge, this is the first report of antibacterial activity associated with endophytic Agromyces, Patulibacter, Curtobacterium and Rhodococcus species.

This study also showed that many of the extracts had synergistic effects when mixed.

However, extracts from isolates A3 (closest match S. misionensis) and A63 (closest match

P. brassicae) seem to have antagonistic effects. These strong inhibitory activities of these strains against an array of test pathogens confirmed that endophytic actinobacteria associated with H. procumbens may be potential candidates for the production of a variety of antimicrobial metabolites.

Variable parameters involved in the bioactive metabolite process such as media nutrient composition, pH, temperature, and fermentation time were optimized to increase the production of secondary metabolites with antimicrobial activities (Pfefferle et al., 2000).

Most Streptomyces species are mesophilic growing optimally between 10-37 ˚C (Hasani et al., 2014). This corroborates the optimum growth temperature (38 ˚C) for the isolates

A65 (closest match Streptomyces flaveus) and B12 (closest match Streptomyces

81 vietnamensis). Similarly, the same genus also grows optimally in pH 6.8 which in line with pH 6.5-8.0 as indicated by (Hasani et al., 2014). Species of the genus Curtobacteria

(B44), have optimal temperatures from 30 to 37 ˚C (Funke et al., 2005), but further growth conditions for this genus have not been determined.

Using different media with different carbon and nitrogen sources can also affect the growth of actinobacteria and the production of secondary metabolites. Though there are no studies on the best carbon and nitrogen source for S. flaveus (A65) and S. vietnamensis

(B12) specifically, a study done showed dextrose and ammonium phosphate as the best substrate for S. kanamyceticus (Pandey et al., 2005). In addition, literature shows that

Streptomyces sp. grows well in lactose and a nitrogen source of glycine-rich medium

(Almalki, 2020). Finally, Chase et al. (2016) found that the genus Curtobacterium most commonly degrades starch which is consistent with what was found in this study. We only looked at three different media containing starch, glycerol and dextrose as carbon sources and casein, sodium caseinate and yeast as nitrogen sources, and all three isolates tested performed best when grown on starch casein agar which has a carbon source of starch and a nitrogen source of casein.

More sources should be looked at before deciding the optimum growth media for these three strains. It was also found that all three had higher zones of inhibition when their growth media was supplemented with plant extract. This could be because the plant may contain some substrates used by the endophytes to produce the secondary metabolites

(Golinska et al., 2015).

3.5 CONCLUSION

This study provides the first comprehensive investigation into potential bioactive endophytic actinobacteria from H. procumbens: a desert-adapted medicinal plant. Based on phenotypic and molecular characteristics, 20 isolates were identified down to the genus level, many of which may merit new species status, with 3 being unidentified actinobacteria. Streptomyces was found to be the most dominant genus with 8 isolates being from rare actinobacteria genera, namely Agromyces, Nocardiopsis, Rubrobacter,

Patulibacter, Rhodococcus and Curtobacterium. Extracellular metabolites produced by the 11 isolates exhibited greater inhibitory activities against gram-negative than gram- positive bacteria. The antimicrobial potential of the isolates was positively influenced by appropriate carbon and nitrogen supplements in starch casein culture media along with the optimum cultural conditions and the presence of either PKSI genes, NRPS genes or both.

Therefore, the Devil’s claw is a reservoir of a diversity of bioactive and antagonistic endophytic actinobacteria.

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APPENDIX Appendix table 3.1: Primary screening zones of inhibition (mm) mean ± standard deviation

Test microorganisms Isolate B. cereus E. coli M. avium S. aureus L. E. durans C. albicans S. enterica monocytoge nes Penicillin 24.00±1.00 20.67±2.10 21.67±1.53 23.00±2.00 21.33±1.53 22.00±1.00 2.67±1.15 20.00±1.00 A3 12.33±0.58 13.33±1.15 3.67±0.58 16.33±0.58 9.00±1.00 1.33±0.58 9.67±0.58 10.33±2.08 A7 14.00±1.00 10.67±0.58 8.33±0.58 8.67±0.58 11.00±0.00 11.00±0.00 1.33±0.58 8.00±0.00 A29 9.00±0.00 9.33±0.58 3.33±0.58 6.33±1.53 9.67±0.58 2.33±1.15 0.33±0.58 8.00±1.00 A36 2.67±0.58 11.33±0.58 8.00±0.00 4.00±0.00 10.00±0.00 4.67±0.58 1.00±0.00 13.00±0.00 A38 8.33±0.58 4.00±0.00 8.67±1.53 9.33±1.15 9.00±0.00 1.67±1.15 - 3.33±0.58 A39 13.67±2.08 12.00±1.73 9.00±2.65 6.00±1.00 12.33±0.58 11.33±0.58 1.00±0.00 8.33±0.58 A57 8.33±0.58 11.00±1.00 6.33±0.58 16.33±1.53 4.67±1.53 2.00±2.00 1.00±1.00 8.00±1.00 A63 11.33±0.58 9.67±0.58 11.00±0.00 7.00±0.00 8.67±0.58 6.00±1.00 1.00±0.00 8.00±1.00 A64 11.00±1.73 11.00±0.00 10.67±0.58 8.00±0.00 9.00±1.00 5.67±0.58 1.00±0.00 9.00±0.00 A65 9.00±1.00 9.33±0.58 6.33±0.58 9.33±0.58 9.67±1.15 8.00±1.00 - 7.67±0.58 A66 14.33±0.58 13.33±2.31 5.00±1.00 8.33±0.58 5.67±0.58 4.67±0.58 - 11±1.73 A67 15.33±1.53 10.67±0.58 4.00±1.00 9.00±0.00 12.33±0.58 10.33±0.58 2.00±0.00 11.33±0.58 A68 12.00±0.00 9.67±0.58 9.67±1.15 4.67±1.53 8.00±0.00 5.00±1.00 0.33±0.58 9.67±0.58 A69 8.00±1.00 8.67±0.58 4.00±1.00 9.33±0.58 10.67±0.58 8.67±0.58 - 9.00±0.00 A70 13.33±0.58 10.00±1.00 9.00±0.00 9.00±1.00 9.00±0.00 5.33±1.15 0.33±0.58 8.67±0.58 B12 11.67±1.15 13.00±1.00 12.33±2.31 11.00±1.00 9.67±0.58 8.33±0.58 3.67±0.58 13.67±0.58 B21 11.00±1.00 9.67±1.53 9.00±0.00 9.00±1.00 8.67±0.58 6.00±1.00 0.67±0.58 8.00±0.00 B23 8.67±0.58 11.00±0.00 8.00±0.00 5.67±1.15 4.67±0.58 2.33±0.58 0.67±0.58 7.67±1.15 B24 9.33±0.58 11.00±0.00 6.67±0.58 7.33±1.15 5.33±1.53 2.00±1.00 1.00±0.00 6.67±1.15 B43 8.33±0.58 9.33±0.58 7.00±1.73 10.00±2.65 11.33±0.58 7.67±0.58 - 9.00±0.00 B44 13.67±1.15 8.33±0.58 3.67±0.58 8.33±0.58 4.33±0.58 5.00±0.00 1.33±0.58 5.67±0.58 B69 11.33±0.58 9.67±0.58 8.33±0.58 8.67±0.58 7.33±0.58 5.33±0.58 1.00±0.00 9.00±1.00 B70 13.33±0.58 8.33±2.31 14.00±0.00 9.00±0.00 10.33±0.58 2.00±0.00 - 9.33±0.58

Appendix table 3.2: Zones of inhibition of secondary screening (mm) mean ± standard deviation (Ethyl acetate)

Test microorganisms Isolate B. cereus E. coli M. avium S. aureus L. E. durans C. albicans S. enterica monocytoge nes Penicillin 22.33±2.51 20.33±0.58 19.00±1.00 21.33±1.53 21.00±1.00 22.33±2.10 2.33±0.58 19.67±0.58 A3 17.00±1.00 16.67±0.58 10.00±0.00 9.00±0.00 9.00±1.00 31±3.46 0.33±0.58 14.00±0.00 A7 2.67±0.58 12.00±2.00 5.33±1.53 14.67±2.08 12.67±1.53 12.00±.1.00 - 10.00±.1.00 A29 6.67±1.15 15.67±0.58 11.67±0.58 8.67±0.58 13.33±0.58 20.00±1.00 - 18.00±2.00 A36 17.67±0.58 12.67±0.58 8.33±1.53 11.33±0.58 10.33±1.15 17.33±1.15 0.67±0.58 10.67±0.58 A38 8.67±0.58 10.00±1.00 10.00±1.00 14.67±0.58 11.33±0.58 20.67±0.58 - 11.00±1.73 A39 8.33±0.58 12.67±0.58 12.67±0.58 8.67±0.58 9.00±1.00 14.67±0.58 3.00±0.00 10.33±0.58 A57 16.00±0.00 17.33±1.15 10.00±1.00 10.33±0.58 9.00±0.00 31.33±1.15 1.33±1.15 16.33±0.58 A63 19.33±0.58 22.33±2.08 15.00±1.00 14.67±0.58 24.00±1.73 23.33±0.58 - 20.00±0.00 A64 18.00±0.00 13.67±0.58 12.00±1.00 13.00±1.00 11.33±0.58 15.67±0.58 2.33±1.53 10.33±1.53 A65 17.67±0.58 13.33±1.15 12.33±0.58 11.67±0.58 10.67±0.58 14.67±1.53 1.00±0.00 11.00±0.00 A66 4.67±0.58 10.33±1.15 4.00±1.00 15.00±0.00 13.00±1.73 11.00±2.65 - 10.67±1.15 A67 9.00±0.00 10.33±0.58 8.00±1.00 9.33±1.15 10.00±1.00 18.33±1.15 3.00±0.00 8.33±0.58 A68 9.67±0.58 11.00±1.00 4.33±0.58 9.67±0.58 9.67±0.58 14.33±0.58 0.33±0.58 12.67±1.15 A69 17.00±0.00 12.33±0.58 11.00±1.00 12.67±0.58 10.67±1.53 14.67±0.58 2.33±0.58 12.67±1.53 A70 16.00±1.00 13.33±1.15 11.67±2.52 12.67±0.58 11.33±1.53 15.67±0.58 2.00±1.00 12.00±0.00 B12 19.00±1.00 21.33±2.31 14.00±1.00 17.67±0.58 18.67±1.15 24.00±1.73 1.00±1.00 20.33±0.58 B21 18.33±0.58 13.33±0.58 10.67±2.08 13.00±1.00 12.67±1.53 16.00±1.00 1.67±0.58 13.00±1.00 B23 19.00±0.00 20.00±1.73 14.33±0.58 13.00±0.00 23.67±0.58 22.67±1.15 - 20.00±1.00 B24 19.33±0.58 20.67±0.58 14.33±0.58 14.33±1.53 23.67±1.53 21.33±0.58 - 20.00±0.00 B43 2.67±1.53 9.67±1.53 4.67±1.15 12.33±1.15 13.33±1.53 12.00±1.00 - 11.33±0.58 B44 21.33±1.15 23.00±1.00 27.67±2.52 23.00±2.65 29.00±2.65 29.33±1.15 2.67±0.58 25.33±1.15 B69 17.33±0.58 15.00±1.73 10.67±3.21 13.00±1.00 12.00±1.73 16.00±0.00 2.33±0.58 10.00±1.00 B70 8.00±0.00 14.33±0.58 22.00±0.00 21.67±1.15 19.00±1.73 9.67±0.58 1.33±0.58 13.00±0.00

Appendix table 3.3: Zones of inhibition of secondary screening (mm) mean ± standard deviation (Chloroform)

Test microorganisms Isolate B. cereus E. coli M. avium S. aureus L. E. durans C. albicans S. enterica monocytoge nes Penicillin 22.33±2.51 20.33±0.58 19.00±1.00 21.33±1.53 21.00±1.00 22.33±2.10 2.33±0.58 19.67±0.58 A3 10.67±1.15 11.00±1.00 5.00±2.65 8.00±0.00 2.33±0.58 9.67±1.53 - 10.00±2.65 A7 6.33±1.53 4.67±0.58 7.00±0.00 7.00±1.00 4.33±0.58 2.33±1.53 1.33±0.58 11.00±1.00 A29 12.67±2.08 8.33±0.58 3.33±0.58 9.00±1.00 8.33±0.58 10.67±1.15 - 8.67±1.15 A36 9.00±0.00 6.67±0.58 7.00±0.00 8.33±1.53 9.67±1.15 10.00±1.00 - 8.00±1.00 A38 6.00±0.00 2.33±1.53 7.00±0.00 7.33±0.58 6.67±1.53 8.67±0.58 0.33±0.58 8.00±1.00 A39 - 2.67±0.58 3.33±1.15 - - 6.00±0.00 - 5.00±1.00 A57 10.00±1.00 9.67±0.58 3.67±0.58 6.00±1.73 1.67±0.58 10.33±0.58 - 9.67±0.58 A63 9.33±3.21 12.33±3.51 8.67±2.31 10.00±1.00 16.00±0.00 16.67±2.08 0.67±0.58 14.00±0.00 A64 8.67±1.53 9.33±0.58 5.67±1.15 8.00±0.00 9.33±1.15 11.33±1.15 0.67±0.58 7.33±0.58 A65 6.67±0.58 9.67±0.58 6.33±1.53 8.00±1.00 9.67±0.58 10.67±0.58 - 7.33±1.15 A66 6.00±1.00 3.67±0.58 7.33±0.58 8.00±1.00 3.67±0.58 5.33±1.15 1.33±1.15 11.00±1.00 A67 - 3.00±1.00 1.33±0.58 3.33±0.58 3.00±1.00 3.33±0.58 - 1.00±1.00 A68 6.33±0.58 4.33±0.58 6.33±0.58 5.33±0.58 6.67±0.58 5.00±1.00 - 5.67±2.52 A69 6.67±1.15 9.33±0.58 9.33±0.58 8.00±0.00 10.33±1.15 10.00±1.00 2.00±1.00 7.67±0.58 A70 8.00±1.00 9.33±0.58 8.00±1.00 9.00±0.00 9.67±0.58 10.33±0.58 0.67±0.58 8.67±1.15 B12 10.00±.0.00 10.33±0.58 8.33±1.15 11.33±1.15 15.00±2.65 14.00±3.00 - 11.33±1.15 B21 7.33±0.58 10.33±1.15 6.33±1.53 7.33±1.15 9.33±0.58 10.00±1.73 1.00±0.00 8.00±1.00 B23 11.67±1.15 12.67±1.15 8.00±2.00 10.33±0.58 16.33±0.58 15.00±1.73 1.33±1.15 12.33±1.15 B24 10.33±0.58 12.33±0.58 9.33±0.58 12.00±0.00 17.00±1.73 16.67±2.52 1.00±1.00 12.67±0.58 B43 6.67±0.58 9.00±4.00 7.67±0.58 4.67±0.58 4.33±2.08 4.67±2.08 0.67±0.58 9.00±1.00 B44 11.00±1.00 11.33±0.58 8.67±0.58 10.33±0.58 11.33±0.58 10.33±2.52 0.33±0.58 11.00±0.00 B69 7.00±1.00 11.67±2.31 7.00±0.00 8.67±0.58 8.33±0.58 10.33±0.58 0.67±1.15 7.00±1.00 B70 7.00±0.00 8.00±1.00 6.00±0.00 5.67±1.15 8.33±0.58 7.00±1.00 - 10.00±1.00

Appendix table 3.4: Zones of inhibition of secondary screening (mm) mean ± standard deviation (Methanol)

Test microorganisms Isolate B. cereus E. coli M. avium S. aureus L. E. durans C. albicans S. enterica monocytoge nes Penicillin 22.33±2.51 20.33±0.58 19.00±1.00 21.33±1.53 21.00±1.00 22.33±2.10 2.33±0.58 19.67±0.58 A3 4.00±2.65 7.00±0.00 1.67±1.15 - - 3.00±1.00 - 5.00±1.00 A7 2.33±0.58 1.00±0.00 2.33±0.58 2.67±0.58 - - - 3.33±0.58 A29 7.00±1.00 3.33±0.58 - 3.33±0.58 5.00±0.00 4.67±0.58 - 2.33±1.15 A36 3.00±1.73 - 4.33±1.53 3.67±0.58 4.00±1.00 4.33±0.58 - - A38 1.33±0.58 - 3.67±0.58 2.67±1.15 3.00±0.00 3.00±0.00 - - A39 ------1.33±0.58 A57 4.00±0.00 6.33±0.58 2.67±0.58 - - 2.00±0.00 - 4.33±0.58 A63 5.67±0.58 8.00±1.00 4.67±1.53 4.67±0.58 6.67±0.58 7.67±0.58 - 6.00±0.00 A64 5.00±1.00 4.67±1.15 4.33±2.08 4.00±2.65 3.67±2.08 3.33±0.58 - 4.67±0.58 A65 6.00±1.00 3.00±1.00 5.00±1.00 5.67±1.53 3.33±0.58 3.00±1.00 - 4.00±3.00 A66 1.67±0.58 1.67±0.58 2.33±0.58 3.00±0.00 - - - 3.67±1.15 A67 - - - - - 0.67±0.58 - - A68 1.00±1.73 - 2.67±0.58 1.33±0.58 4.00±1.00 1.67±0.58 - - A69 7.33±1.15 4.00±0.00 5.00±1.00 4.00±1.00 3.00±1.00 3.00±1.00 - 4.00±1.00 A70 5.00±1.00 3.33±0.58 4.67±0.58 5.33±0.58 4.00±0.00 3.33±1.15 - 5.00±0.00 B12 4.00±0.00 5.33±0.58 4.00±1.00 8.00±0.00 7.33±0.58 6.67±0.58 - 6.00±1.00 B21 6.67±0.58 5.33±0.58 5.00±1.73 3.67±0.58 3.00±1.73 3.67±0.58 - 5.00±0.00 B23 7.33±1.53 7.33±0.58 6.33±0.58 4.67±0.58 6.67±0.58 7.33±0.58 - 7.33±0.58 B24 5.67±0.58 6.67±1.15 6.00±0.00 5.00±0.00 6.33±0.58 6.33±1.15 - 6.67±0.58 B43 2.33±1.15 2.33±0.58 2.00±1.00 2.67±0.58 - - - 3.00±0.00 B44 4.67±1.15 6.33±0.58 6.00±0.00 4.33±0.58 6.67±1.53 6.33±0.58 - 5.00±0.00 B69 5.00±1.00 4.00±1.00 4.33±3.06 3.00±1.00 2.67±0.58 4.00±2.00 - 5.67±1.15 B70 - 1.67±0.58 - 1.33±1.15 3.00±1.00 - - 1.67±1.15

Appendix table 3.5: Zones of inhibition of mixed extracts (mm) mean ± standard deviation (Ethyl acetate)

Appendix table 3.6: Zones of inhibition of mixed extracts (mm) mean ± standard deviation (Chloroform)

Appendix table 3.7: Zones of inhibition of mixed extracts (mm) mean ± standard deviation (Methanol)

Appendix table 3.8: Effects of cultural parameters on antimicrobial activity (mm) mean ± standard deviation

M edi a (C co Sa Tes nte m 5 t nt) Starch Casein Glucose-yeast extract malt Actinomycetes Isolation Agar pl org pH 6.4 6.8 7.2 6.4 6.8 7.2 6.4 6.8 7.2 e Pla nt ext rac with with with with with with with with with t out with out with out with out with out with out with out with out with out with E. 12.0 15.3 16.0 18.3 13.3 15.6 8.33 11.0 12.6 14.0 9.00 11.3 6.00 9.67 10.0 12.6 7.33 9.00 dur 0±1 3±0 0±1 3±0 3±0 7±1 ±0. 0±1 7±1 0±1 ±1. 3±0 ±1. ±1. 0±1 7±1 ±0. ±1. ans .15 .58 .00 .58 .58 .15 58 .00 .00 .00 00 .58 00 15 .00 .15 58 00 10.3 13.0 14.3 17.6 11.6 14.0 5.67 9.67 10.0 13.3 7.33 10.0 3.00 7.33 8.67 11.3 4.67 8.67 B1 E. 3±0 0±1 3±0 7±1 7±1 0±1 ±1. ±1. 0±1 3±0 ±0. 0±1 ±1. ±0. ±1. 3±0 ±1. ±1. 2 coli .58 .15 .58 .15 .15 .00 15 15 .15 .58 58 .00 15 58 00 .58 00 15 M. 7.00 9.00 10.3 11.0 8.33 9.33 3.67 5.33 6.67 7.67 4.67 5.67 1.33 3.00 4.00 5.00 2.33 3.00 avi ±1. ±1. 3±0 0±1 ±0. ±0. ±1. ±0. ±1. ±1. ±1. ±1. ±0. ±1. ±1. ±1. ±0. ±1. um 15 15 .58 .00 58 58 00 58 15 15 15 00 58 00 15 00 58 00 E. 15.6 18.3 25.6 31.0 14.0 17.0 5.33 8.00 15.0 21.6 4.67 6.67 1.33 8.67 15.0 0.33 dur 7±1 3±0 7±1 0±1 0±1 0±1 ±0. ±1. 0±1 7±1 ±1. ±1. ±0. ±1. 0±1 ±0. ans .00 .58 .00 .00 .00 .15 58 00 .15 .15 00 00 0 58 15 .00 0 58 3 10.0 12.6 19.6 24.6 9.67 11.3 0.67 2.33 9.33 15.3 0.33 1.33 3.00 10.6 4 B4 E. 0±1 7±1 7±1 7±1 ±1. 3±0 ±1. ±0. ±0. 3±0 ±0. ±0. ±1. 7±1 º 4 coli .15 .15 .00 .15 15 .58 00 58 58 .58 58 58 0 0 00 .00 0 0 C M. 12.0 13.6 20.3 28.0 12.6 12.0 2.33 3.00 10.6 19.3 3.00 2.33 4.33 12.6 avi 0±1 7±1 3±0 0±1 7±1 0±1 ±0. ±1. 7±1 3±0 ±1. ±0. ±0. 7±1 um .00 .15 .58 .15 .00 .00 58 15 .00 .58 00 58 0 0 58 .15 0 0 E. 11.6 12.0 8.67 10.0 7.00 9.33 9.33 7.33 3.00 4.67 2.33 4.00 4.00 1.67 dur 7±1 0±1 ±1. 0±1 ±1. ±0. ±0. ±0. ±1. ±1. ±0. ±1. ±1. ±1. ans .15 .00 15 .00 15 58 58 58 00 00 58 00 15 00 0 0 0 0 9.33 10.6 7.33 8.67 5.67 8.00 4.00 5.00 2.33 3.33 0.33 3.33 A E. ±0. 7±1 ±0. ±1. ±1. ±1. ±1. ±1. ±0. ±0. ±0. ±0. 65 coli 58 .15 58 15 15 00 00 15 58 58 58 58 0 0 0 0 0 0 M. 8.67 9.33 6.67 7.33 4.00 6.00 3.00 4.67 1.33 2.00 0.67 avi ±1. ±0. ±1. ±0. ±1. ±1. ±1. ±1. ±0. ±1. ±1. um 00 58 00 58 00 15 00 00 58 00 0 15 0 0 0 0 0 0 E. 19.6 22.0 23.0 25.3 16.0 19.3 15.3 18.6 19.6 21.0 12.3 15.0 12.0 15.6 17.3 19.3 10.0 13.3 dur 7±1 0±1 0±1 3±0 0±1 3±0 3±0 7±1 7±1 0±1 3±0 0±1 0±1 7±1 3±0 3±0 0±1 3±0 ans .00 .00 .00 .58 .00 .58 .58 .15 .00 .00 .58 .15 .00 .00 .58 .58 .15 .58 17.6 20.0 20.3 22.6 14.6 17.6 13.0 15.3 16.0 19.6 10.3 14.6 10.6 13.0 14.6 17.0 7.67 12.3 B1 E. 7±1 0±1 3±0 7±1 7±1 7±1 0±1 3±0 0±1 7±1 3±0 7±1 7±1 0±1 7±1 0±1 ±1. 3±0 2 coli .15 .00 .58 .15 .15 .00 .00 .58 .00 .15 .58 .00 .15 .15 .15 .00 00 .58 M. 14.3 16.3 17.6 15.3 10.6 12.0 10.0 12.3 14.3 13.6 6.00 8.33 8.67 10.0 12.0 11.0 4.67 6.00 avi 3±0 3±0 7±1 3±0 7±1 0±1 0±1 3±0 3±0 7±1 ±1. ±0. ±1. 0±1 0±1 0±1 ±1. ±1. um .58 .58 .15 .58 .00 .15 .15 .58 .58 .00 00 58 00 .00 .00 .15 00 00 E. 10.3 13.0 20.3 26.6 9.00 12.3 0.33 2.67 11.3 19.3 2.00 5.00 13.0 dur 3±0 0±1 3±0 7±1 ±1. 3±0 ±0. ±1. 3±0 3±0 ±1. ±1. 0±1 ans .58 .15 .58 .00 00 .58 58 15 .58 .58 0 00 0 0 00 .15 0 0 3 5.67 8.33 14.0 19.0 4.33 8.33 3.67 8.67 2.33 8 B4 E. ±1. ±0. 0±1 0±1 ±0. :0.5 ±1. ±1. ±0. º 4 coli 00 58 .00 .15 58 8 0 0 00 15 0 0 0 0 0 58 0 0 C M. 7.33 9.00 15.6 23.3 8.00 3.67 5.00 16.3 9.67 avi ±0. ±1. 7±1 3±0 ±1. ±1. ±1. 3±0 ±1. um 58 00 .15 .58 00 00 0 0 00 .58 0 0 0 0 0 15 0 0 E. 14.3 15.3 11.0 13.3 10.6 12.0 9.00 9.67 6.33 8.67 6.33 7.67 4.67 3.67 0.67 3.00 1.00 2.33 dur 3±0 3±0 0±1 3±0 7±1 0±1 ±1. ±1. ±0. ±1. ±0. ±1. ±1. ±1. ±1. ±1. ±1. ±0. ans .58 .58 .15 .58 .15 .00 15 00 58 15 58 15 00 00 00 00 00 58 12.0 14.6 9.67 12.3 8.33 10.6 7.67 10.3 4.00 7.33 3.67 5.00 2.33 6.00 2.33 A E. 0±1 7±1 ±1. 3±0 ±0. 7±1 ±1. 3±0 ±1. ±0. ±1. ±1. ±0. ±1. ±0. 65 coli .00 .15 00 .58 58 .00 00 .58 00 58 00 00 58 15 0 58 0 0 M. 11.3 13.0 9.00 10.0 7.33 9.67 6.00 8.33 3.33 5.33 2.00 4.33 1.00 4.00 avi 3±0 0±1 ±1. 0±1 ±0. ±1. ±1. ±0. ±0. ±0. ±1. ±0. ±1. ±1. um .58 .00 00 .00 58 00 00 58 58 58 00 58 00 00 0 0 0 0 E. 12.3 15.0 16.6 18.3 14.3 14.6 7.67 11.6 12.6 13.6 9.00 11.0 6.00 8.67 10.0 13.6 7.33 9.67 dur 3±0 0±1 7±1 3±0 3±0 7±1 ±1. 7±1 7±1 7±1 ±1. 0±1 ±1. ±1. 0±1 7±1 ±0. ±1. ans .58 .00 .00 .58 .58 .15 00 .00 .00 .00 00 .00 15 15 .15 .00 58 00 11.3 13.6 13.3 17.3 11.6 13.6 5.67 9.00 10.3 13.3 7.33 10.3 3.00 7.33 8.33 12.3 4.33 9.00 B1 E. 3±0 7±1 3±0 3±0 7±1 7±1 ±1. ±1. 3±0 3±0 ±0. 3±0 ±1. ±0. ±0. 3±0 ±0. ±1. 2 coli .58 .15 .58 .58 .00 .00 15 15 .58 .58 58 .58 00 58 58 .58 58 00 M. 6.67 9.00 10.6 11.6 8.33 9.33 2.67 5.00 6.00 7.33 5.00 5.67 1.33 3.67 4.00 5.67 2.67 2.67 avi ±1. ±1. 7±1 7±1 ±0. ±0. ±1. ±1. ±1. ±0. ±1. ±1. ±0. ±1. ±1. ±1. ±1. ±1. um 00 15 .15 .00 58 58 00 00 15 58 00 00 58 00 15 00 00 00 E. 5.00 9.33 15.0 21.0 4.33 8.00 3.00 12.0 0.67 6.67 dur ±1. ±0. 0±1 0±1 ±0. ±1. ±1. 0±1 ±1. ±1. ans 00 58 .00 .15 58 00 0 0 00 .15 0 0 0 0 00 00 0 0 4 0.33 3.00 10.3 15.0 3.00 1.00 2 B4 E. L0. ±1. 3±0 0±1 ±1. ±1. º 4 coli 58 00 .58 .00 0 15 0 0 0 00 0 0 0 0 0 0 0 0 C M. 1.67 4.67 11.6 18.6 3.67 8.67 2.33 avi ±1. ±1. 7±1 7±1 ±1. ±1. ±0. um 15 00 .00 .15 00 0 0 0 0 00 0 0 0 0 0 58 0 0 E. 11.6 13.0 8.33 10.3 7.00 8.33 8.33 7.33 3.33 4.67 2.67 4.67 3.33 1.00 dur 7±1 0±1 ±0. 3±0 ±1. ±0. ±0. ±0. ±0. ±1. ±1. ±1. ±0. ±1. ans .00 .00 58 .58 00 58 58 58 58 00 00 00 58 00 0 0 0 0 9.33 11.6 7.67 9.00 5.00 7.67 4.67 5.00 2.67 3.00 3.00 B6 E. ±0. 7±1 ±1. ±1. ±1. ±1. ±1. ±1. ±1. ±1. ±1. 5 coli 58 .00 00 00 15 00 00 00 00 00 0 15 0 0 0 0 0 0 M. 8.00 10.3 7.00 6.33 4.33 5.33 3.67 4.67 1.67 2.33 0.33 avi ±1. 3±0 ±1. ±0. ±0. ±0. ±1. ±1. ±1. ±0. ±0. um 15 .58 00 58 58 58 15 15 00 58 0 58 0 0 0 0 0 0

0=no inhibition zone Positive control = Penicillin (E. durans=23.33±0.58; E. coli=20.67±1.00; M. avium=19.33±0.58)

CHAPTER 4: ENZYMATIC, ANTIOXIDANT AND DNA DAMAGE PROTECTIVE ACTIVITIES OF SELECTED ENDOPHYTIC ACTINOBACTERIA ISOLATED FROM HARPAGOPHYTUM PROCUMBENS: A KALAHARI DESERT-ADAPTED PLANT M.E. Lang1, T. Sibanda1, S. Louw2 and J.D. Uzabakiriho1 1Department of Biological Sciences, University of Namibia, Namibia 2Department of Chemistry and Biochemistry, University of Namibia, Namibia ABSTRACT The present study aimed to determine the antioxidant and DNA damage protective properties of the secondary metabolites of endophytic actinobacteria isolated from

Harpagophytum procumbens, more commonly known as the Devil’s claw. This desert plant is a well-known source of medicinally important phytochemicals, some of which might be produced by endophytes. Secondary tubers of H. procumbens were collected from the Khomas and Hardap regions of Namibia from which a total of 23 isolated actinobacteria were selected. The identities of the actinobacterial isolates were previously determined by partially sequencing the 16S rRNA gene. The antioxidant results revealed that the ethyl acetate extracts of A36, a Streptomyces sp., had the highest phenolic content of 1.993 ± 0.004 and total antioxidant activity of 0.258 ± 0.001. Extracts from B12, another Streptomyces sp., had the highest radical scavenging activity of 95% at 0.1 mg/mL while B43, an unidentified actinobacterium, had the highest total reducing power of 0.849

± 0.003. Furthermore, 74% of the isolates tested positive for urease production, 83% for gelatin degradation, 74% for protease production, 65% for starch degradation, 48% for indole-acetic acid production and 96% for catalase production. In addition, 61% of the isolates showed the ability to protect DNA from damage when exposed to hydrogen

98 peroxide. The present study concludes that endophytic actinobacteria associated with H. procumbens are a potential source of bioactive compounds with antioxidant and DNA damage protecting properties.

Keywords: H. procumbens, actinobacteria, antioxidants, DNA damage protection, endophytes, bioactive compounds

4.1 INTRODUCTION

Actinobacteria are verified producers of bioactive secondary metabolites (Solecka et al.,

2012; Adegboye and Babalola, 2013; Janardhan et al., 2014), and are extensively distributed in both terrestrial and aquatic habitats (Thenmozhi and Kannabiran, 2012;

Mousumi and Dayanand, 2013). As much as 73% of known bioactive compounds of actinobacteria origin are produced by Streptomyces spp., with the other 27% being produced by rare actinobacteria (Mousumi and Dayanand, 2013). Known bioactivities of these secondary metabolites include, among others, antimicrobial, antitumor, immunosuppressive, antioxidant, and enzyme inhibitory activities (Manimaran and

Kannabiran, 2017). Apart from actinobacteria isolated from soil and water environments, endophytic actinobacteria have also been shown to be rich sources of bioactive natural products (Singh and Dubey, 2015). Endophytic microorganisms grow intra- or inter- cellularly in plant tissues without harming the host (Dhayanithy et al., 2019), and confer several vital bioactivities to the host plant including promoting plant growth, eliciting defense responses against pathogens, disease resistance, including acting as remediators of abiotic stresses (Sudha et al., 2016; Khare et al., 2018).

Since ancient times, plant parts and/or their extracts have been widely used for therapeutic purposes. The link between the bioactivities of medicinal plants and the bioactivities of their endophytes has been loosely studied to date (Passari et al., 2015; Singh and Dubey,

2018). However, several studies indicate that endophytic actinobacteria found in medicinal plants can produce secondary metabolites with a totally different set of bioactivities compared to those of host plants (Shan et al., 2018). In particular, plants growing under extreme environments are a prime target in the hunt for novel endophytic actinobacteria with enhanced bioactivities owing to their ability to produce rare products as a coping strategy under abiotic stressors (Gos et al., 2017; Singh and Dubey, 2018).

One such plant is Harpagophytum procumbens, also known as the Devil’s claw, a perennial herbaceous plant species that is native to the Kalahari Desert in Namibia. The plant has multiple medicinal uses in Southern Africa, notably in Botswana, Namibia,

South Africa, and Zimbabwe (Georgiev et al., 2010). It has been used in the treatment of fever, malaria, indigestion, pain, arthritis, osteoarthritis, tendonitis, kidney inflammation, heart disease and blood diseases, and has also been shown to have a beneficial effect on rheumatic diseases due to its anti-inflammatory properties (Abdulhussein et al., 2018). H. procumbens has been used for centuries to treat various ailments, most notably as an anti- inflammatory agent (Cole and Strohbach, 2007). Since there is a strong relationship between inflammation and oxidative stress (Schaffer et al., 2013), there are reasonable grounds to expect medicinal plants exhibiting anti-inflammatory activities to also have antioxidant properties, making H. procumbens a good source of antioxidants.

A limited number of studies have evaluated the antioxidant activity of the aerial parts of

H. procumbens with promising results such as the study by Georgriev et al. (2010). While

100 humans have an inherent capacity to produce their own antioxidants which protect their

DNA from the damaging effects of some metabolic by-products such as reactive nitrogen species (RNS) and reactive oxygen species (ROS), this ability tends to diminish with age.

Without adequate antioxidants, DNA/RNA oxidation can occur, leading to single or double-strand fragmentation or alteration of the nitrogenous bases (Ore and Akinloye,

2019). Although the cells implement compensatory mechanisms to overcome the harmful effects of oxidative stress, in some circumstances DNA damage cannot be prevented, resulting in various ailments such as cancer (Sabahi et al., 2018). There is, therefore, a need for extensive research directed at finding natural sources of antioxidants, especially since synthetic antioxidants are largely associated with toxicity (Golla and Bhimathati,

2014; Lee et al., 2014).

Actinobacteria are also capable of synthesizing extracellular enzymes, such as ureases, gelatinases, proteases, amylase and catalase that can break down complex macromolecules used in various industrial fields in a clean, eco-friendly and cost-effective manner (Prakash et al., 2013; Minotto et al., 2014). Some actinobacteria also produce plant growth promoters such as indole-3-acetic acid (Khamna et al., 2009). To date, no studies have been done to assess the enzyme production of H. procumbens and its endophytic actinobacteria. This study was, therefore, aimed at investigating the enzymatic, antioxidant and DNA protecting potential of the secondary metabolites of H. procumbens’ endophytic actinobacteria, as an alternative source of natural antioxidants and industrial enzymes which are currently in short supply.

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4.2 MATERIALS AND METHODS

4.2.1 Plant sample collection

Non-destructive methods were used to obtain six lateral H. procumbens’ secondary tubers from the Khomas (A: 22º51’34” S, 17º6’35.5” E) and Hardap (B: 22º37’4.7” S, 17º5’44.7”

E) regions in Namibia in May of 2018. The plant was identified in the field by Dr.

Uzabakiriho and authenticated through the National Botanical Research Institute. Briefly, a spade was used to dig a hole around the main tubers and lateral tubers were carefully cut off, leaving the main tuber in the ground, and closing the hole. In total, six tubers, three from each site were collected and transported to the laboratory at the University of

Namibia in sterile plastic bags where they were stored at -4 °C until further processing.

4.2.2 Isolation of actinobacteria strains

Endophytic actinobacteria were isolated following the methods earlier described by

Janardhan et al. (2014), with modifications. The surface of the plant tubers was sterilised and oven-dried at 35 °C for 24h. Five gram pieces of dried, surface sterilised secondary tubers were crushed into powder using a sterile mortar and pestle, and serially diluted from

10-1 to 10-6 using sterile deionized water. One hundred microliter aliquots of each tuber dilution were then plated onto starch casein media agar (Genmed, Windhoek) supplemented with nystatin and cycloheximide at 10 mg/mL (Genmed, Windhoek) each to suppress the growth of bacteria and fungi, respectively. The plates were incubated at

30 ºC for a maximum of 28 days or until actinobacteria growth was observed. Once growth was observed, axenic cultures were obtained using the perpendicular streak method over three to four rounds of subculturing onto freshly prepared starch casein agar plates. Lone- standing colonies of each axenic culture were then transferred into freshly prepared starch

102 casein broth in 250 mL Erlenmeyer flasks. The broth cultures were incubated with shaking at 30 ºC and 7 x g for 14 days to allow for the production and excretion of secondary metabolites. A total of 140 isolates were obtained but following primary screening, 23 isolates were chosen for further investigation.

4.2.3 Extraction of secondary metabolites

To extract secondary metabolites, a method described by Khanna, Solanki, and Lal (2011) was used with some modifications. The broth cultures prepared during isolation were centrifuged at 21913 x g for 10 min to sediment the cell mass. The supernatant portions were divided into aliquots, which were then separately mixed with different extraction solvents (ethyl acetate, chloroform and methanol) in a 1:1 ratio (v/v), vigorously shaken for 10 min followed by agitation on an orbital shaker at 6 x g for 30 min and left to stand at 4 ºC for 12 hr. After the incubation, the mixtures were vigorously shaken for 5 min and then left to stand at room temperature in a separating funnel until the solvent layer and aqueous layer were completely separated. The solvent layers were harvested by opening the tap on the separating funnel and discarding the aqueous layer. The solvent portions were then placed into pre-weighed, sterile glass beakers and left to evaporate under a fume hood. The beakers were then re-weighed to determine the weight of the precipitates, and then re-dissolved using calculated volumes of the same solvent to produce stock solutions with a concentration of 10 mg/mL. These were then placed in sterile microfuge tubes and stored at -20 ºC until use.

4.2.4 Physiological characteristics

Isolated strains were subjected to selected assays to evaluate their biochemical activity including protease production, catalase production, urease production, indole production 103 and the degradation of gelatin and starch according to a study done by Kaylani et al.

(2012). An uninoculated plate was kept as a control for each experiment.

Protease production: Each isolate was inoculated on skim milk agar plates. Plates were incubated at 37 ºC for 48 h. Clear zones of skim milk hydrolysis were recorded after 48 h as positive for protease production. Protease solution was used as a positive control.

Catalase production test: Each isolate was inoculated on tryptic soy agar slants in test tubes. The slants were incubated at 35 ºC for 7 days after which 4 drops of hydrogen peroxide were allowed to flow over the growth. The production of oxygen bubbles showed a positive result for catalase production. B. cereus was used as a positive control.

Urease production test: Each isolate was inoculated with an inoculating loop into urease broth in test tubes that were prepared according to the manufacturer’s protocol. The tubes were incubated at 30 ºC for 7-21 days. The development of a pink colour showed a positive result for urease production. Tubes were observed at intervals of 7 days. Proteus marabilis was used as a positive control.

Indole production test: Tryptophan broth was prepared and poured into tubes. Each isolate was inoculated into the broth and incubated at 30 ºC for 7 days. Kovac’s reagent was then added to each tube and the production of a dark red colour indicated a positive result for indole production. E. coli was used as a positive control.

Starch degradation and amylase production: Modified Bennette Medium was prepared

(10.0 mL glycerol, 2.0 mL pancreatic digest of casein, 1.0 g yeast extract, 1.0 g beef extract in 1 L distilled water). To this, 20.0 g of agar and 10.0 g of starch were added and the agar was poured onto sterile plates. Actinobacteria isolates were streaked on the plates

104 and incubated at 30 ºC for 7 days. After incubation, the plates were flooded with Gram’s iodine solution and observed for zones of clearing indicating positive for starch degradation. Bacillus subtilis was used as a positive control.

Gelatin degradation test: Again, the Modified Bennette Medium was prepared on agar plates. To this 20.0 g of agar and 4.0 g of gelatin were added. Actinobacteria isolates were streaked on the plates and incubated at 30 ºC for 7 days. After incubation, the plates were flooded with saturated ammonium sulfate solution and left for 15-30 min to allow unhydrolyzed gelatin to precipitate. The plates were then checked for zones of clearing against a dark background indicating positive for gelatin degradation. S. aureus was used as a positive control.

4.2.5 Determination of total phenolics (TPC)

The total phenolic content (TPC) for all 23 extracts in 3 different solvents of ethyl acetate, chloroform, and methanol, were estimated using the Folin Ciocalteu’s method with gallic acid as a standard, following a modified method of Gautham and Onkarappa (2013). The reagent was made by mixing phosphotungstic acid and phosphomolybdic acid, which was reduced to a mixture of blue oxides of tungsten and molybdenum after oxidation of the phenols. This blue colour produced a maximum absorption at around 765 nm and was proportional to the total quantity of phenolic compounds originally present.

Total phenolic content (TPC) was determined spectrophotometrically by combining 2.5 mL Follin-Ciocalteu reagent (diluted 1:10 v/v with distilled water) and 2 mL sodium carbonate solution (7.5% v/v) with 1 mL of 1 mg/mL solvent extracts. The tubes were vortexed and left to stand for 90 min at ambient temperature. The absorbance was read

105 spectrophotometrically against a reagent blank at 765 nm and compared to a standard curve plotted using different concentrations of gallic acid (0-1000 µg/mL). Gallic acid was used as a positive control and water as a negative control. The TPC of the extract was expressed in terms of milligrams (mg) of gallic acid equivalents per gram (GAE)/g) of dry weight using the equation:

C = cV/m, where c is the concentration of gallic acid as obtained from the calibration curve in mg/mL, V is the volume of the extract in mL, and m is the mass of the extract in grams.

The reactions were conducted in triplicate, and the results were averaged.

4.2.6 Determination of total antioxidant activity (TAA)

To determine the total antioxidant activity (TAA) of the extracts, 0.3 mL aliquots of 100

µg/mL solvent extracts were combined with 3 mL reagent solution of 0.6 M sulphuric sodium phosphate with 4 mM ammonium molybdate and incubated at 95 ˚C for 90 min in a water bath. The absorbance of all the sample mixtures was measured at 695 nm against a gallic acid (100 µg/mL) as the standard control and a reagent blank, as described by

Janardhan et al. (2014). Gallic acid was used as a positive control and water as a negative control. The absorbance of the extracts was expressed in GAE/g using the same formula as for TPC.

4.2.7 Determination of DPPH radical scavenging activity

DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity was determined following the method described by Janardhan et al. (2014). Briefly, 2 mL of different concentrations (0.005 - 0.100 mg/mL) of each extract and gallic acid standard were placed

106 into tubes containing 2 mL of 0.002% methanol. The tubes were then incubated in the dark at room temperature for 30 min and the optical density was measured at 517 nm against a reagent blank. Percentage scavenging activity was calculated using the following equation:

(%) = [(퐴 − 퐵)/퐴] × 100, where 퐴 is the absorbance of DPPH control and 퐵 is the absorbance of DPPH in the presence of extract/standard.

The IC50 was determined by producing standard curves for each extract and using their line equation to determine the concentration of extracts where 50% of the free radicals would be scavenged:

50 = mx + c

Where m is the gradient of the trendline, and c is the y-intercept and calculating for x will give the IC50.

4.2.8 Determination of total reducing power

To determine total reducing power, solvent extracts and gallic acid standard control at

0.100 mg/mL in phosphate buffer were mixed with 1% potassium ferricyanide in equal volumes and incubated at 50 ˚C for 20 min following a method described by Janardhan et al. (2014). After incubation, 2.5 mL of 10% trichloroacetic acid (TCA) was added to the mixture followed by centrifugation at 1677 x g for 10 min. Following centrifugation, 2.5 mL of the upper layer of the mixture was added to 2.5 mL of distilled water and 0.5 mL of 0.1% ferric chloride. Absorbance was then measured at 700 nm against a reagent blank.

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Gallic acid was used as a positive control and water as a negative control. Higher absorbance indicated higher reducing power.

4.2.9 Determination of DNA protecting potential

DNA nicking was evaluated using hydrogen peroxide after coating the DNA with the extracts to determine whether the extracts have any DNA damage protection properties.

To determine the ability of extracts to protect DNA from oxidation by hydrogen peroxide

(H2O2), in vitro tests were performed as described by Golla and Bhimathati (2014) and

Shameem et al. (2015). Briefly, the reaction mixture, containing 3 µl of pUC19 plasmid

DNA, 10 µl of Fenton’s reagent (30 mM H2O2, 50 mM Ascorbic acid, and 80 mM FeCl3) and 5 µl of 50 µg/mL of the extract or gallic acid standard, were incubated for 15 min at room temperature. The negative control was without the addition of extracts or standards and the positive control was normal pUC19 plasmid DNA. The tubes were then incubated for 1 h at 37 °C. The reaction was terminated by the addition of 2 µl of loading dye and running the content on 0.8% agarose gel in TBE buffer at 100 V for 45 min. The gel was visualised under UV light.

4.2.10 Data analysis

All photospectrometric determinations were done in triplicate. Normality tests were done using the Shapiro-Wilk test. Averages were compared to standards of gallic acid. ANOVA was carried out using the statistical package SPSS 24 on all tests to determine if there were statistically significant differences between the different solvent extracts and between the solvent extracts and the respective positive controls using the Tukey HSD and Duncan multiple range post hoc tests. Differences were deemed significant if the P value was less

108 than 0.05. A Pearson correlation was done between TPC and TAA to determine if there were any correlation between the results of these two tests.

4.3 RESULTS

4.3.1 Isolation of actinobacteria strains and their biochemical activities

Out of 140 isolates, 23 isolates were chosen for further study. Their IDs were designated an A for Khomas and a B for Hardap regions. A total of 15 isolates were chosen from tubers obtained from the Khomas Region and 8 isolates from tubers from the Hardap

Region. They were screened for various biochemical activity and enzyme production

(Table 4.1). Approximately 74% of isolates were urease positive, 78% were gelatinase positive, 70% were protease positive, 96% could degrade starch, 48% tested positive for indole-acetic acid production and 96% were catalase positive.

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Table 4 1: Biochemical characterization of isolates

Isolate Closest sequence Urease Gelatinase Protease Starch Indole-acetic Catalase ID similarity production production production degradation acid production production

A3 Streptomyces - + + + - + misionensis (NR0441381) A7 Unidentified + + + + - + actinobacteria A29 Agromyces flavus + + + + - + (NR10833801) A36 Streptomyces sp. - + - + + + (LC435676.1) A38 Nocardiopsis - - + + + - dassonvillei A39 Rubrobacter + - - - - + aplysinae (NR0746351) A57 Streptomyces - + + + - + misionensis (NR0441381) A63 Patulibacter + + - + - + brassicae (NR1536701) A64 Streptomyces flaveus + + + + + + (NR 0434911) A65 Streptomyces flaveus + + + + + + (NR 0434911) A66 Unidentified + + + + - + actinobacteria A67 Rhodococcus - - + + - + agglutinans (NR1368601) A68 Streptomyces + - + + - + virginiae (NR1156211) A69 Streptomyces flaveus + + + + + + (NR 0434911) A70 Streptomyces flaveus + + + + + + (NR 0434911) B12 Streptomyces + + - + + + vietnamensis (NR0437101) B21 Streptomyces flaveus + + + + + + (NR 0434911) B23 Patulibacter + + - + - + brassicae (NR1536701) B24 Patulibacter + + - + - + brassicae (NR1536701) B43 Unidentified + + + + - + actinobacteria B44 Curtobacterium - - + + + + pusillum (NR1048391) B69 Streptomyces flaveus + + + + + + (NR 0434911) B70 Streptomyces spp. + + - + + + Key: + = positive for specific test or enzyme, - = negative for specific test or enzyme

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4.3.2 Total Phenolic content

Ethyl acetate extracts contained significantly higher amounts of phenols than the extracts of the other solvents (p = 0.000). Extracts from isolate A36 (Streptomyces sp.) in ethyl acetate had the highest phenolic content of 1158.65 mgGAE/g, higher than that of the gallic acid standard (980.41 mgGAE/g), followed by the extracts from isolates B12

(Streptomyces vietnamensis) at 969.24 mgGAE/g and B44 (Curtobacterium pusillum) at

962 mgGAE/g. For chloroform extracts, isolate B44 (Curtobacterium pusillum) had the highest phenolic content (460.41 mgGAE/g) while all methanol extracts were below 200 mgGAE/g. Results for the 23 extracts in the three solvents are shown in Figure 4.1 compared to the gallic acid standard.

mgGAE/g of different strain extacts 1400 1200 1000 800 600

mgGAE/g 400 200

A3 A7

B21 B12 B23 B24 B43 B44 B69 B70

A36 A38 A39 A57 A63 A64 A65 A66 A67 A68 A69 A70

-200 A29 Gallicacid Strain extracts

Ethyl acetate Chloroform Methanol

Figure 4.1: mgGAE/g of strain extract in different solvents for TPC. All activity was statistically significant when compared to the positive control, gallic acid, with a Duncan multiple range test at P<0.05.

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4.3.3 Total antioxidant activity

The ethyl acetate extracts had the highest total antioxidant activity (p = 0.000) followed by chloroform, and lastly methanol. The ethyl acetate extracts from isolate A36

(Streptomyces sp.) had the highest TAA at 524.45 mgGAE/g followed by extracts from isolates B70 (Streptomyces sp.) at 343.52 mgGAE/g. Both these readings were higher than the gallic acid standard (301.96 mgGAE/g). Extracts from isolate B44 Curtobacterium pusillum) had the third highest TAA at 289.73 mgGAE/g. The chloroform extracts from isolate B70 (Streptomyces sp.) exhibited the highest TAA at 191.93 mgGAE/g while the

TAA of all methanol extracts was below 100 mgGAE/g. A Pearson correlation was done between the results of TPC and TAA which found a positive correlation of 0.706 which was also seen in the scatter plot. Results for the 23 extracts in the three solvents are shown in Figure 4.2 compared to the gallic acid standard.

mgGAE/g of extracts from different strains for total antixodant activity 600 500 400 300

200 mgGAE/g 100

A3 A7

B43 B12 B21 B23 B24 B44 B69 B70

A65 A70 A36 A38 A39 A57 A63 A64 A66 A67 A68 A69 -100 A29 Extracts from strains Gallicacid Ethyl acetate Chloroform Methanol

Figure 4.2: mgGAE/g of strain extract in different solvents for total antioxidant activity.

All activity was statistically significant when compared to the positive control, gallic acid, with a Duncan multiple range test at P<0.05. 112

4.3.4 Free radical scavenging activity using DPPH assay

The absorbances and radical scavenging activity of the extracts were recorded (Appendix table 4.1-Appendix table 4.3). Free radical scavenging activity for all 23 extracts in the three different solvents was determined at different concentrations. The results for the highest concentration of 0.1 mg/mL are shown in Figure 4.3. The IC 50 was also calculated using the line equation of the curve produced by the different concentrations for each extract as shown in Figure 4.4 and Appendix table 4.4.

Free radical scavenging activity by DPPH assay of various isolate extracts at 0.1mg/mL

120% 100% 80% 60% 40% 20% 0%

Percentage of free radical scavenging activity scavenging radical free of Percentage Isolate extracts

Ethyl acetate extracts 0.1mg/ml chloroform extracts 0.1mg/ml methanol extracts 0.1mg/ml

Figure 4.3: Free radical scavenging activity of extracts at 0.1mg/mL of all three solvents compared to the gallic acid standard. All activity was statistically significant when compared to the positive control, gallic acid, with a Duncan multiple range test at P<0.05.

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IC50 for radical scavenging activity by DPPH assay

0.16 0.14

0.12 mg/mL 0.1 0.08 0.06 0.04

0.02 Concentration in Concentration 0

Isolate extracts

Ethyl acetate Chloroform Methanol

Figure 4.4: IC50 of extracts in all three solvents as compared to the gallic acid standard for free radical scavenging activity by DPPH assay. All activity was statistically significant when compared to the positive control, gallic acid, with a Duncan multiple range test at P<0.05.

The ethyl acetate extracts exhibited the highest radical scavenging activity (p = 0.000).

Ethyl acetate extracts from isolate B12 (Streptomyces vietnamensis) performed the best, with a free radical scavenging activity of 95% at 0.1mg/mL with an IC50 of 0.014 for 9 mg/mL followed by extracts from isolate A65 (Streptomyces flaveus) (93%) (IC50: 0.0149 mg/mL), and A69 (Streptomyces flaveus) (92%) (IC50: 0.0152 mg/mL). For chloroform extracts, extracts from isolate B12 (Streptomyces vietnamensis) showed the highest free radical scavenging activity (73%) at 0.1 mg/mL with an IC50 of 0.0689 mg/mL while all methanol extracts showed activity below 30%. Free radical scavenging activity was observed to increase with concentration.

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4.3.5 Total Reducing power

Reducing power tended to increase with increasing extract concentration. Figure 4.5

(Appendix table 4.5) shows the total reducing power for all 23 extracts compared to the gallic acid standard.

Total Reducing power of various extracts at 0.1mg/ml 0.900 0.800 0.700 0.600 0.500 0.400

Absobance 0.300 0.200 0.100

0.000

A3 A7

B12 B21 B23 B24 B43 B44 B69 B70

A57 A29 A36 A38 A39 A63 A64 A65 A66 A67 A68 A69 A70 Gallicacid Isolate extracts

Ethyl acetate extract 0.1mg/ml Chloroform extract 0.1mg/ml Methanol extracts 0.1mg/ml

Figure 4.5: Total reducing power of extracts at a concentration of 0.1mg/mL. All activity was statistically significant when compared to the positive control, gallic acid, with a

Duncan multiple range test at P<0.05.

The ethyl acetate extracts had the highest reducing power (p = 0.000). The ethyl acetate extracts with the highest activity were from isolates A7 (unidentified actinobacteria)

(0.849 ± 0.002) and B43 (unidentified actinobacteria) (0.849 ± 0.003) followed by A66

(unidentified actinobacteria) (0.843 ± 0.001). The gallic acid standard only had an activity of 0.402 ± 0.002. For chloroform, extracts from isolates B43 (unidentified actinobacteria) had the highest activity (0.196 ± 0.004) while all methanol extracts were below 0.050.

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4.3.6 DNA nicking assay

Results were recorded according to the amount of DNA damage protection. After the

DNA nicking assay, it was found that extracts from isolate B12 (Streptomyces vietnamensis), B44 (Curtobacterium pusillum) and A63 (Patulibacter brassicae) had the highest DNA damage protection ability against hydrogen peroxide, protecting both the linear and plasmid DNA from fragmentation. Extracts from isolates A7 (unidentified actinobacteria), A29 (Agromyces flavus), A36 (Streptomyces sp.), A66 (unidentified actinobacteria), A67 (Rhodococcus agglutinans), B43 (unidentified actinobacteria) and

B70 (Streptomyces sp.) protected the linear DNA from fragmentation but not the plasmid

DNA. Furthermore, extracts from isolates A68 (Streptomyces virginiae) and A57

(Streptomyces misionensis) had low DNA damage protection ability with fragmentation in both linear and plasmid DNA detected. The rest of the extracts had no DNA damage protection ability as no DNA was detected and as it had been completely degraded by the hydrogen peroxide.

4.4 DISCUSSION

This study shows that the secondary tubers of H. procumbens are rich in endophytic actinobacteria with various bioactivities. The presence and type of endophytic microbes mostly depend on plant tissue composition as well as its environment (Jaginakere et al.,

2016). Streptomyces species are catalase-positive and are known to degrade gelatin and starch (Smaoui et al., 2011) which also corresponds to the outcome of biochemical tests run on the isolates with the highest similarities to Streptomyces. Chen et al. (2011) also characterised A. flavus as being catalase-positive, being able to degrade gelatin starch and urea which corresponds to the results found in this study for isolate A29. Lejbkowicz et

116 al. (2005) described N. dassonvillei as being able to degrade gelatin and urease and being catalase-positive, which contradicts the findings of the current study for isolate A38. This might be because A38 is a novel species or subspecies. Jin et al. (2016) describes

Patulibacter brassicae as having white colonies with positive indole and catalase production which is consistent with the current study except for the indole production.

Indole acetic acid can have plant growth-promoting effects on the host plant which is a known characteristic of some endophytic microbes (Lodewyckx et al., 2010). Isolate A67 which closely matched Rhodococcus agglutinans had the ability to hydrolyse starch and produce catalase while being negative for urease and gelatinase activity which corresponds to the findings of the study by Gou et al. (2015). Zawadzka et al. (2013) also describes Curtobacterium pusillum as a plant growth promoter due to its productions of indole acetic acid. Their findings correspond to the findings of this study as seen by the activity of isolate B44.

In the current investigation, H. procumbens’ endophytic actinobacteria secondary metabolites were subjected to four in vitro antioxidant tests and a DNA nicking assay. Our findings corroborate those of other studies which point to medicinal plants as well as endophytic microbes as important natural sources of antioxidants (Jaginakere et al., 2016).

In studies done by Zheng et al. (2016) and Danagoudar et al. (2017), endophytic bacterium

Bacillus cereus SZ1 isolated from Artemisia annua L and the endophytic fungus

Aspergillus austroafricanus CGJ-B3 isolated from Zingiber officinale, respectively, showed good antioxidant and DNA damage protection activities. However, apart from this study, there is no previous published research on both the isolation of endophytic

117 actinobacteria from H. procumbens nor the determination of their antioxidant and DNA protection activities.

Nonetheless, H. procumbens ethyl acetate tissue extracts have been found to prevent brain lipid peroxidation induced by pro-oxidants under experimental conditions as well as combat against a decrease of catalase activity and thiol levels, which in the body is needed for the prevention of oxidative stress (Schaffer et al., 2013). Other plant extracts, such as the hydroalcoholic extracts from Desmostachya bipinnata L. Staph also showed antioxidant and DNA damage protection activities (Golla and Bhimathati, 2014).

Similarly, we also found that ethyl acetate extracts of endophytic actinobacteria isolates had the highest antioxidant activities, followed by chloroform and then methanol extracts.

Ethyl acetate is a powerful organic solvent because it is a hydrogen bond acceptor molecule and thus can extract solutes that donate electrons more readily than solvents such as chloroform (Siek, 1978). In a study by Lahneche et al. (2019), they also found that the ethyl acetate extracts of Centaurea sphaerocephala L had better antioxidant and DNA damage protection activity as compared to the n-butanol extracts they tested. There is usually also a correlation between TPC and TAA, due to the fact that phenols are natural antioxidants, which was confirmed in our study to have a positive correlation of 0.706 using the Pearson correlation statistical test. In similar studies, Georgriev et al. (2010) found that methanolic extracts of the aerial parts of H. procumbens showed higher DPPH radical scavenging activity than pure harpagoside, while Georgiev et al. (2012) found that crude methanolic extracts from cell and hairy root cultures of H. procumbens exhibited about twice the ion-chelating capacity of a commercial positive control, butylated hydroxyanisole. Thus, the findings of this current study and other studies suggest ethyl

118 acetate and methanol are the best solvents for the extraction of secondary metabolites from organic sources.

An interesting observation is that in addition to the above studies that demonstrate the antioxidant activity of H. procumbens, there are also multiple studies that demonstrate the antioxidant activity of endophytic actinobacteria from various plants (Golinska et al.,

2015; Jaginakere et al., 2016; Nafis et al., 2018; Photolo et al., 2020). Comparing these studies with the findings of the current study points to the fact that the antioxidant activity exhibited by H. procumbens can partially be attributed to its endophytic actinobacteria.

In an almost similar study, it was found that aqueous H. procumbens extracts reduce the

DNA damaging effects of SnCl2 on various E. coli strains (Almeida et al., 2007). The extracts were suspected to achieve this effect by either of the following ways: (i) chelators of the stannous ions, thus inhibiting the formation of free radicals, (ii) scavengers of free radicals, thus protecting the cells against oxidation, and/or (iii) acting as an oxidant compound upon the stannous ions, thus reducing the SnCl2 cytotoxicity. The major difference, however, between that study and the present study, is that the DNA damage protection activity was exhibited by the H. procumbens plant extracts, not its endophytic actinobacteria as is reported in this study. However, in a study by Mohammadipanah and

Momenilandi (2017), antioxidant producing actinobacteria strains (UTMC 537, UTMC

863, UTMC 2188, UTMC 2237, UTMC 2091) protected pUC19 DNA against UV- induced photolyzed H2O2-oxidative degradation. Thus, knowing that H. procumbens plant extract, as well as actinobacteria, have the ability to produce antioxidants that protect

DNA from degradation, it is possible that the endophytic actinobacteria from H. procumbens add to the plants’ DNA damage protection properties.

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Thus, the results of this study indicate that endophytic actinobacteria from H. procumbens’ secondary tubers are a good source of antioxidants, DNA protective compounds and a variety of enzymes. This has great significance, especially in the pharmaceutical industry given that cells sometimes require some aid in combatting oxidative stress, including

DNA damage (Sabahi, 2018). If new medications can be produced to combat oxidative stress, it could help prevent various ailments (Ore and Akinloye, 2019). Given that the synthetic antioxidants are largely toxic, finding natural antioxidant sources is pertinent

(Golla and Bhimathati, 2014; Lee et al., 2014). Furthermore, considering that microbial sources of enzymes are biocatalysts for many reactions and the fact that actinobacteria have high metabolic versatility, the enzymes they produce have potential uses in the biotechnological and biomedical fields. For example, proteases have industrial applications in the pharmaceutical, leather, detergent, food, and brewing industries while amylases (starch degradation) can be utilized in the detergent, baking, paper, and textile industries (Mukhtar et al., 2017).

4.5 CONCLUSION

A variety of endophytic actinobacteria from 6 different families and 7 genera were isolated from the secondary tubers of H. procumbens. As the results indicate, ethyl acetate extracts of isolate A36 (Streptomyces sp.) had higher TPC and TAA than the gallic acid standard and all ethyl acetate extracts had higher reducing power and high radical scavenging activity compared to gallic acid. Furthermore, 61% of the extracts showed some degree of

DNA damage protection against hydrogen peroxide. This demonstrates that the plant- associated endophytic actinobacteria from H. procumbens produce compounds that have good antioxidant and DNA damage protection potential. Additionally, all 23

120 actinobacterial isolates produced a variety of enzymes that could be useful in industry.

Further research is needed to identify these enzymes and antioxidants as well as determine whether they are beneficial to the host plant and whether certain molecules are produced due to host and endophyte interactions.

121

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APPENDIX

Appendix table 4.1: Free radical scavenging activity of ethyl acetate extracts at different concentrations Con: 0.005 0.01 0.025 0.05 0.1

Gallic 0.020±0.001 0.011±0.002 0.004±0.001 0.002±0.001 0.000 acid (89%) (94%) (98%) (99%) (100%) A3 0.190±0.002 0.174±0.004 0.073±0.002 0.058±0.004 0.047±0.002 (0%) (8%) (62%) (69%) (75%) A7 0.190±0.001 0.187±0.002 0.103±0.012 0.075±0.006 0.049±0.004 (0%) (2%) (46%) (61%) (74%) A29 0.191±0.001 0.190±0.001 0.190±0.001 0.182±0.004 0.115±0.002 (0%) (0%) (0%) (4%) (39%) A36 0.191±0.002 0.167±0.006 0.149±0.012 0.089±0.004 0.024±0.002 (0%) (12%) (22%) (53%) (87%) A38 0.190±0.001 0.190±0.002 0.173±0.004 0.124±0.012 0.077±0.006 (0%) (0%) (9%) (35%) (59%) A39 0.190±0.001 0.190±0.001 0.191±0.002 0.190±0.002 0.150±0.006 (0%) (0%) (0%) (0%) (21%) A57 0.190±0.002 0.177±0.005 0.070±0.004 0.052±0.002 0.042±0.004 (0%) (7%) (63%) (73%) (78%) A63 0.190±0.002 0.186±0.004 0.114±0.002 0.092±0.006 0.063±0.002 (0%) (2%) (40%) (52%) (67%) A64 0.182±0.002 0.104±0.006 0.064±0.004 0.028±0.003 0.017±0.002 (4%) (45%) (66%) (87%) (91%) A65 0.187±0.004 0.100±0.004 0.066±0.003 0.025±0.006 0.014±0.005 (2%) (47%) (65%) (87%) (93%) A66 0.190±0.001 0.190±0.002 0.109±0.006 0.085±0.002 0.046±0.004 (0%) (0%) (43%) (55%) (76%) A67 0.191±0.002 0.191±0.001 0.190±0.001 0.147±0.004 0.091±0.003 (0%) (0%) (0%) (22%) (52%) A68 0.190±0.002 0.190±0.001 0.166±0.004 0.107±0.002 0.086±0.006 (0%) (0%) (13%) (44%) (55%) A69 0.185±0.003 0.107±0.004 0.065±0.004 0.027±0.002 0.015±0.002 (3%) (44%) (66%) (86%) (92%) A70 0.182±0.004 0.105±0.002 0.065±0.003 0.027±0.003 0.016±0.005 (4%) (45%) (66%) (87%) (91%) B12 0.167±0.006 0.098±0.002 0.047±0.003 0.022±0.006 0.009±0.002 (12%) (48%) (75%) (88%) (95%) B21 0.182±0.002 0.104±0.006 0.064±0.004 0.028±0.003 0.017±0.002 (4%) (45%) (66%) (87%) (91%) B23 0.190±0.002 0.184±0.006 0.118±0.001 0.090±0.003 0.061±0.002 (0%) (3%) (38%) (53%) (68%) B24 0.190±0.001 0.187±0.003 0.116±0.004 0.093±0.002 0.065±0.005 (0%) (2%) (49%) (51%) (66%) B43 0.190±0.001 0.188±0.004 0.104±0.009 0.076±0.004 0.048±0.002 (0%) (1%) (45%) (60%) (75%) B44 0.190±0.001 0.190±0.001 0.174±0.005 0.160±0.002 0.134±0.003 (0%) (0%) (8%) (16%) (29%) B69 0.182±0.002 0.104±0.006 0.064±0.004 0.028±0.003 0.017±0.002 (4%) (45%) (66%) (87%) (91%) B70 0.190±0.001 0.190±0.002 0.190±0.001 0.124±0.005 0.073±0.002 (0%) (0%) (0%) (35%) (62%)

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Appendix table 4.2: Free radical scavenging activity of chloroform extracts at different concentrations

Con: 0.005 0.01 0.025 0.05 0.1 Gallic 0.038±0.001 0.014±0.002 0.007±0.001 0.003±0.001 0.000 acid (80%) (93%) (96%) (98%) (100%) A3 0.190±0.002 0.190±0.001 0.177±0.004 0.124±0.003 0.062±0.002 (0%) (0%) (11%) (35%) (67%) A7 0.190±0.001 0.190±0.002 0.184±0.006 0.102±0.003 0.073±0.002 (0%) (0%) (3%) (46%) (62%) A29 0.191±0.001 0.190±0.001 0.190±0.001 0.190±0.001 0.174±0.004 (0%) (0%) (0%) (0%) (8%) A36 0.191±0.002 0.190±0.001 0.190±0.001 0.180±0.004 0.097±0.003 (0%) (0%) (0%) (5%) (49%) A38 0.190±0.001 0.190±0.002 0.190±0.001 0.190±0.001 0.164±0.006 (0%) (0%) (0%) (0%) (14%) A39 0.190±0.001 0.190±0.001 0.191±0.002 0.190±0.001 0.190±0.001 (0%) (0%) (0%) (0%) (0%) A57 0.190±0.002 0.190±0.001 0.172±0.004 0.115±0.003 0.064±0.002 (0%) (0%) (9%) (39%) (66%) A63 0.190±0.002 0.190±0.001 0.182±0.004 0.156±0.002 0.094±0.003 (0%) (0%) (4%) (18%) (51%) A64 0.190±0.001 0.190±0.001 0.187±0.004 0.103±0.003 0.073±0.002 (0%) (0%) (2%) (46%) (62%) A65 0.190±0.001 0.190±0.001 0.182±0.004 0.105±0.003 0.071±0.002 (0%) (0%) (4%) (48%) (63%) A66 0.190±0.001 0.190±0.001 0.188±0.006 0.100±0.003 0.076±0.002 (0%) (0%) (1%) (47%) (60%) A67 0.191±0.002 0.191±0.001 0.190±0.001 0.181±0.003 0.124±0.004 (0%) (0%) (0%) (5%) (35%) A68 0.190±0.002 0.191±0.002 0.190±0.001 0.174±0.006 0.105±0.003 (0%) (0%) (0%) (8%) (45%) A69 0.190±0.001 0.190±0.001 0.179±0.006 0.107±0.002 0.070±0.002 (0%) (0%) (6%) (44%) (63%) A70 0.190±0.001 0.190±0.001 0.184±0.002 0.101±0.004 0.076±0.003 (0%) (0%) (3%) (47%) (60%) B12 0.190±0.001 0.190±0.001 0.190±0.001 0.162±0.006 0.051±0.002 (0%) (0%) (0%) (15%) (73%) B21 0.190±0.001 0.190±0.001 0.187±0.006 0.105±0.004 0.073±0.005 (0%) (0%) (2%) (45%) (62%) B23 0.190±0.001 0.190±0.001 0.178±0.004 0.149±0.002 0.093±0.003 (0%) (0%) (6%) (22%) (51%) B24 0.190±0.002 0.190±0.002 0.180±0.004 0.150±0.002 0.097±0.003 (0%) (0%) (5%) (21%) (49%) B43 0.190±0.002 0.190±0.001 0.182±0.006 0.106±0.003 0.077±0.002 (0%) (0%) (4%) (44%) (59%) B44 0.190±0.001 0.190±0.001 0.190±0.001 0.190±0.001 0.177±0.005 (0%) (0%) (0%) (0%) (7%) B69 0.190±0.001 0.190±0.001 0.184±0.002 0.103±0.003 0.071±0.002 (0%) (0%) (3%) (46%) (63%) B70 0.190±0.001 0.190±0.002 0.190±0.001 0.190±0.001 0.157±0.005 (0%) (0%) (0%) (0%) (17%)

127

Appendix table 4.3: Free radical scavenging activity of methanol extracts at different concentrations

Con: 0.005 0.01 0.025 0.05 0.1 Gallic 0.040±0.001 0.012±0.002 0.008±0.001 0.002±0.001 0.000 acid (79%) (94%) (96%) (99%) (100%) A3 0.190±0.002 0.190±0.001 0.190±0.001 0.190±0.001 0.175±0.002 (0%) (0%) (0%) (0%) (8%) A7 0.190±0.001 0.190±0.002 0.190±0.001 0.190±0.001 0.182±0.002 (0%) (0%) (0%) (0%) (4%) A57 0.190±0.002 0.190±0.001 0.190±0.001 0.190±0.001 0.178±0.002 (0%) (0%) (0%) (0%) (6%) A66 0.190±0.001 0.190±0.001 0.190±0.001 0.190±0.001 0.180±0.002 (0%) (0%) (0%) (0%) (5%) B12 0.190±0.001 0.190±0.001 0.190±0.001 0.190±0.001 0.152±0.002 (0%) (0%) (0%) (0%) (20%) B24 0.190±0.002 0.190±0.002 0.190±0.001 0.190±0.001 0.190±0.001 (0%) (0%) (0%) (0%) (0%) B43 0.190±0.002 0.190±0.001 0.190±0.001 0.190±0.001 0.178±0.002 (0%) (0%) (0%) (0%) (6%)

Appendix table 4.4: IC 50 for free radical scavenging activity by DPPH assay

Sample Solvents Ethyl acetate Chloroform Methanol Gallic acid 0.0007 0.0018 0.0023 A3 0.0273 0.0694 0.1369 A7 0.0373 0.0681 0.1505 A29 0.1120 0.1369 - A36 0.0450 0.1010 - A38 0.0779 0.1277 - A39 0.1220 - - A57 0.0253 0.0680 0.1416 A63 0.0480 0.0981 - A64 0.0149 0.0683 - A65 0.0149 0.0656 - A66 0.0409 0.0697 0.1442 A67 0.0950 0.1229 - A68 0.0758 0.1063 - A69 0.0152 0.0680 - A70 0.0149 0.0694 - B12 0.0123 0.0777 0.1233 B21 0.0149 0.0689 - B23 0.0475 0.0974 - B24 0.0454 0.1013 - B43 0.0380 0.0724 0.1416 B44 0.1012 0.1388 - B69 0.0149 0.0672 - B70 0.0756 0.1261 - 128

Appendix table 4.5: Absorbance of extracts at 700nm to show reducing power as compared to gallic acid at 0.1mg/mL

Ethyl acetate Chloroform Methanol Gallic acid 0.402±0.002 0.403±0.002 0.403±0.003 A3 0.384±0.004 0.176±0.004 0.013±0.006 A7 0.849±0.002 0.195±0.003 - A29 0.302±0.007 0.040±0.004 - A36 0.623±0.002 0.092±0.002 - A38 0.747±0.002 0.103±0.001 - A39 0.171±0.001 0.063±0.003 - A57 0.380±0.007 0.176±0.001 0.013±0.006 A63 0.384±0.004 0.048±0.001 0.013±0.002 A64 0.656±0.003 0.109±0.002 0.011±0.001 A65 0.655±0.002 0.110±0.001 0.024±0.003 A66 0.843±0.001 0.193±0.001 - A67 0.153±0.003 0.007±0.001 - A68 0.278±0.005 0.030±0.001 - A69 0.654±0.001 0.110±0.003 0.021±0.001 A70 0.654±0.001 0.110±0.005 0.024±0.002 B12 0.477±0.003 0.052±0.001 0.110±0.001 B21 0.654±0.000 0.109±0.004 0.024±0.001 B23 0.389±0.003 0.052±0.002 0.011±0.004 B24 0.389±0.002 0.049±0.002 0.012±0.001 B43 0.849±0.003 0.196±0.004 - B44 0.557±0.002 0.135±0.003 0.010±0.003 B69 0.662±0.005 0.108±0.002 0.025±0.004 B70 0.280±0.004 0.074±0.001 -

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CHAPTER 5: QUALITATIVE ANALYSIS OF BIOACTIVE CONSTITUENTS FROM ENDOPHYTIC ACTINOBACTERIA ISOLATED FROM HARPAGOPHYTUM PROCUMBENS USING THIN LAYER CHROMATOGRAPHY (TLC) AND GAS CHROMATOGRAPHY-MASS SPECTROMETRY (GC-MS) M.E. Lang1, S. Louw2, and J.D. Uzabakiriho1 1Department of Biological Sciences, University of Namibia, Namibia 2Department of Chemistry and Biochemistry, University of Namibia, Namibia

ABSTRACT

Actinobacteria are major producers of various important bioactive compounds and are known to form symbiotic relationships with plants. To date, extracts of actinobacteria associated with Harpagophytum procumbens have not been studied, though the plant has a wide variety of known medicinal properties. After isolation of endophytic actinobacteria and extraction of secondary metabolites, a total of 18 ethyl acetate extracts were screened for the presence of terpenoids, alkaloids, phenols and flavonoids using TLC based qualitative phytochemical screens. Three of the bioactive extracts discussed that had the highest activities in the antimicrobial (isolates B44 and A65) and antioxidant assays (from isolate B12) were then further characterised using GC-MS. TLC screens revealed that none of the samples contain terpenoids, while 13 contain alkaloids, 17 contain phenols and 8 contain flavonoids. A total of 23 volatile compounds were identified in the three extracts based on the MS and retention index data of the GC-MS analyses. Extracts B12,

B44 and A65 contained 10, 9 and 14 compounds, respectively. These volatile compounds include alkanes, alkenes/alcohols, carboxylic acids/esters and amides. Alkanes and alkenes, produced by various microbes are used in the production of gasoline, diesel and jet fuels, while compounds such as esters and carboxylic acids can display antibacterial,

130 antifungal and anti-inflammatory properties (Wenzel and Bode, 2004; Dickschat et al.,

2011; Wang and Lu, 2013; Apsari et al., 2019). Octadecanamide also has antibacterial properties (Tanvir et al., 2016). All these compounds have previously been extracted from actinobacteria (Danaei et al., 2014; Janardhan et al., 2014; Tanvir et al., 2016; Chen et al., 2017; Apsari et al., 2019; Cao et al., 2019).

Keywords: actinobacteria, GC-MS, TLC, H. procumbens

5.1 INTRODUCTION

Actinobacteria are gram-positive, filamentous, saprophytic bacteria, in the order

Actinomycetales and the family Actinomycetaceae and have a high G+C ratio. Various actinobacteria genera are major producers of commercially important bioactive compounds that are novel chemical entities (Ravi and Kannabiran, 2018). Out of 23 000 bioactive compounds isolated from microbes, 10 000 were from actinobacteria of which

7600 were isolated from Streptomyces species specifically (Sharma et al., 2014). These natural bioactive compounds have various activities such as antibacterial, antifungal, antiviral, anticancer and antimalarial (Oskay et al., 2004; Mohan and Rajamanickam

2018). However, in recent years, the rediscovery of already identified bioactive compounds has increased and therefore researchers have shown increased interest in exploring endophytic actinobacteria (Saravanakumar et al., 2010). Furthermore, the prevalence of pathogens developing resistance to present-day drugs has increased; hence there is a pressing need to discover novel bioactive compounds (Sharon et al., 2013).

Endophytic actinobacteria from Harpagophytum procumbens (Devil’s claw) is an example of an unexplored source holding the potential to produce novel bioactive

131 compounds with complex chemical structures. Endophytes are symbionts, often bacteria, fungi or actinobacteria which reside in the intercellular spaces of plants without causing apparent disease and often having a unique mutually beneficial relationship with the host plant (Sahani and Thakur, 2019). They are capable of synthesizing bioactive agents that can be used by plants for defense against pathogens and/or stimulating plant growth in exchange for nutrition (Kanjana et al., 2019).

Harpagophytum procumbens belongs to the Pedaliaceae family and is native to the sub-

Saharan parts of Africa including the Kalahari Sands of Namibia, South Africa, Angola,

Zambia, Zimbabwe, and Botswana (Chrubasik et al., 2004). It has traditionally been used, mostly by the San people, to treat several symptoms such as fever, malaria, indigestion, and pain (Brendler et al., 2006). In addition, it was demonstrated that H. procumbens extracts have beneficial effects in the case of rheumatic diseases and have anti- inflammatory effects (Lanhers et al., 1992; Andersen et al., 2004). However, no studies have been performed on its endophytic actinobacteria. In this study, the metabolites produced by endophytic actinobacteria isolated from H. procumbens were investigated for the first time.

5.2 MATERIALS AND METHODS

5.2.1 Chemicals and materials

High-performance liquid chromatography grade dichloromethane (DCM; Biodynamics,

Windhoek, Namibia) was used during GC/MS. The TLC mobile phase liquids, alkane mixture and reference standards used for retention time comparison were of analytical grade and TLC plates were silica gel-based. All chemicals and materials were purchased from Sigma Aldrich (Germany), Biodynamics and Genmed (Windhoek, Namibia). 132

5.2.2 Thin-layer chromatography screening of phytochemicals

For qualitative phytochemical analysis by TLC, 20 µl of each of the 17 ethyl acetate extracts were separately loaded on silica gel TLC plates together with solutions of positive controls. Ethyl acetate was used as a negative control. The TLC analyses were performed using different solvent systems. Each analysis was performed in triplicate. Retention factors (Rf) were determined using the following equation:

퐷𝑖푠푡푎푛푐푒 푡푟푎푣푒푙푙푒푑 푏푦 푡ℎ푒 푠푎푚푝푙푒 푅푓 = 퐷𝑖푠푡푎푛푐푒 푡푟푎푣푒푙푙푒푑 푏푦 푡ℎ푒 푠표푙푣푒푛푡

5.2.2.1 Alkaloids

Methanol and concentrated ammonia mixed in a ratio of 200:3 were used as the mobile phase for alkaloid detection as in the method described by Suliman (2018) with modifications. Dragendroff reagent was used as a spraying reagent to identify alkaloid compounds in the extracts. The manifestation of an orange colour on the TLC plate indicated the presence of alkaloids in the samples. Quinine served as a positive control.

5.2.2.2 Terpenoids

For the detection of terpenoids, hexane and ethyl acetate (1:1) were used as the mobile phase using vanillin-sulfuric acid as a spraying reagent as in the method described by

Suliman (2018). The plates were heated at 120 °C for 5 min. A brown spot indicated the presence of terpenoids. β-sitosterol served as a positive control.

133

5.2.2.3 Flavonoids

The mobile phase used for flavonoids was n-butanol, acetic acid, and water (2:2:6) and all plates were visualized under UV light at 254 nm and 366 nm after drying (Sharma and

Janmeda, 2017). Quercetin was used as a positive control.

5.2.2.4 Phenols

For the analysis of phenols, the mobile phase was hexane, ethyl acetate and acetic acid

(31:14:5) and viewed under UV light at 254 nm and 366 nm, using gallic acid as the positive control (Medic-Saric et al., 2004).

5.2.3 GC-MS analysis

The GC‒MS analyses were performed on 3 samples that showed high antimicrobial and antioxidant activity (B12, B44 and A65) using a Thermo Scientific Focus GC coupled to an ITQ 700 MS with helium as the carrier gas with a flow rate of 1.0 mL/min (constant flow) and a split ratio of 10. An SGE BP5MS capillary GC column (30 m × 0.25 mm i.d) with a 5% diphenyl, 95% dimethyl polysiloxane stationary phase (0.25 μm film thickness) was utilized for separation. The mass spectra were recorded at an ionisation energy of 70 eV and a mass range of m/z 25‒625 was scanned. The temperature of the injector was maintained at 220 °C, while the source and transfer line temperatures were 200 °C and

250 °C, respectively. To ensure optimal separation of the volatile compounds, the oven was programmed at a rate of 2 °C/min from 45 °C (held for 3 min) to 300 °C (Sheehama et al., 2019). A volume of 1 µl of each of the extract stock solutions was analysed.

134

A mixture of alkanes (C10-C40) was analysed under the same conditions as the sample solutions and the linear Kỏvats retention indices of the compounds were calculated using the following equation (Harris, 2010):

′ ′ 푙표푔푡푟(푢푛푘푛표푤푛) − 푙표푔푡푟(푛) 퐼 = 100 [푛 + (푁 − 푛) × ′ ′ ] 푙표푔푡푟(푁) − 푙표푔푡푟(푛)

Where: I is the retention index

N is the number of carbon atoms in the larger alkane

n is the number of carbon atoms in the smaller alkane

′ 푡푟(unknown) is the adjusted retention time of the unknown compound in the

sample

′ 푡푟(n) is the adjusted retention time of the alkane that elates before the unknown

′ 푡푟(N) is the adjusted retention times of the alkane that elates after the unknown

′ 푡푟 is the adjusted retention time = tr – tm, where tr is the actual retention time and

tm is the time that it takes for an un-retained compound to move through the

column.

5.3 RESULTS AND DISCUSSION

5.3.1 TLC phytochemical screens for terpenoids, alkaloids, phenols, and flavonoids

TLC is widely used as a separation or purification method for chemical and biological compounds (Tanvir et al., 2016). Due to its simplicity and low cost, it is a convenient method to utilize. Ethyl acetate extracts of 18 isolated endophytic actinobacteria were

135 screened by TLC for phenols, alkaloids, terpenoids and flavonoids using different solvent systems and visualisation methods. These compounds were screened due to their known antioxidant activities (Shad et al., 2014)

In the TLC screen for terpenoids, the presence of brown spots indicated the presence of these phytochemicals. However, the only brown spot that was observed was that of the positive control, β-sitosterol (Rf = 0.32) (Figure 5.1). For alkaloids, the TLC screen revealed the presence of this phytochemical by means of an orange spot (Figure 5.2). It was found that all samples except B23 contain alkaloids. In the TLC screen for phenols, the presence of a blue spot under UV light indicated the presence of these phytochemicals.

Phenols were detected in all samples except for B23 (Figure 5.3). In the TLC screen for flavonoids, the presence of a dark black spot under UV light indicated the presence of this phytochemical. Samples B12, B21, B24, B44, B70 A36 A63, A69 contain flavonoids

(Figure 5.4). The Rf values of all samples are listed in Table 5.1.

+ - B12 B21 B23 B24 B43 B44 B69 B70 A3 A7 A29 A36 A38 A63 A64 A69 A70

Figure 5.1: TLC screen for terpenoids. A brown spot is observed where a terpenoid is present (The positive control (+) is β-sitosterol (Rf = 0.32) and the negative control (-) is ethyl acetate).

136

+ - B12 B21 B23 B24 B43 B44 B69 B70 A3 A7 A29 A36 A38 A63 A64 A69 A70 Figure 5.2: TLC screen for alkaloids. An orange spot is observed where an alkaloid is present (The positive control (+) is Quinine (Rf = 0.66) and the negative control (-) is ethyl acetate).

+ - B12 B21 B23 B24 B43 B44 B69 B70 A3 A7 A29 A36 A38 A63 A64 A69 A70

Figure 5.3: TLC screen for phenols. A blue spot is observed where a phenol is present

(The positive control (+) is gallic acid (Rf = 0.73) and the negative control (-) is ethyl acetate).

137

+ - B12 B21 B23 B24 B43 B44 B69 B70 A3 A7 A29 A36 A38 A63 A64 A69 A70 Figure 5.4: TLC screen for flavonoids. A black spot is observed where a flavonoid is present (The positive control (+) is Quercetin (Rf = 0.39) and the negative control (-) is ethyl acetate).

138

Table 5.1: Phytochemicals detected in the ethyl acetate extracts of endophytic actinobacteria isolated from H. procumbens.

Sample Rf values of the phytochemicals detected in the TLC screens Terpenoids Alkaloids Phenols Flavonoids β-sitosterol 0.32 - - - Quinine - 0.66 - - Gallic acid - - 0.73 - Quercetin - - - 0.39 B12 - 0.83 and 0.80 0.90 0.52 B21 - 0.83 0.90 0.82 B23 - - - - B24 - - 0.87 0.82, 0.52 and 0.13 B43 - 0.83 and 0.68 0.90 - B44 - - 0.90 0.82, 0.52 and 0.13 B69 - 0.83 0.90 - B70 - 0.83 0.90 0.82, 0.52 and 0.13 A3 - - 0.90 - A7 - 0.83 and 0.72 0.90 - A29 - 0.83 and 0.80 0.90 - A36 - 0.83 0.90 0.79 A38 - 0.83 and 0.80 0.90 - A63 - 0.83 0.90 0.13 A64 - 0.74 0.90 - A69 - 0.83 and 0.72 0.90 0.82 A70 - 0.71 and 0.63 0.85 -

None of the extracts contained any terpenoids, although terpenoids have been found to be associated with actinobacteria as indicated by Shirai et al. (2010). This might be due to the fact that terpenoids are relatively non-polar and thus might not have been extracted with the ethyl acetate solvent. Thus, more solvent systems should be used to extract a broader array of compounds from the actinobacteria isolates.

Sixteen of the extracts contained phenols. Phenols, found in all plant materials, are natural antioxidants and exert antiallergic, anti-inflammatory, antidiabetic, antimicrobial, antiviral, etc, properties and can help prevent diseases such as cancer, heart problems, 139 cataracts, eye disorders and Alzheimer’s disease (Huyut et al., 2017). Actinobacteria have long been known for their production of high phenolic content as indicated by Janardhan et al. (2014).

Traces of flavonoids were detected in 8 of the extracts. Flavonoids have previously been found to be associated with actinobacteria as reported by Cao et al. (2019), who found 3 new lavandulylated flavonoids from a sponge-derived Streptomyces sp. Flavonoids, a subgroup of phenols, are abundantly found in plants and are a large group of polyphenolic compounds with a benzo-γ-pyrone structure (Kumar and Pandey, 2013). They have a variety of pharmacological activities, including their antioxidant activity and ability to induce human protective enzyme systems. They also help plants fight off microbial infections which might be one of the ways these endophytic actinobacteria benefit the H. procumbens host plant (Kumar and Pandey, 2013).

Alkaloids were found in 13 of the extracts. Alkaloids are a group of natural compounds that contain nitrogen and have a low molecular weight. They are known for their medicinal properties including emetic, anticholinergic, antitumor, diuretic, antiviral and antimicrobial activities (De Almeida et al., 2017). They are usually synthesised from amino acids and are biologically active. In a study by Chen et al. (2017), alkaloids were identified that are associated with endophytic actinobacteria from Fritillaria unibracteata in western Sichuan plateau and their antimicrobial potential was determined. This is another example where such endophytes could help protect the host plant from infections.

140

5.3.2 Identification of the volatile constituents

In the two preceding chapters, the ethyl acetate extracts of the actinobacteria isolates B12,

B44 and A65 showed promising antimicrobial and antioxidant activities. Hence, these extracts were further investigated. Using GC-MS, a total of 23 volatile compounds were identified in these extracts (Table 5.2). This was done by comparing their mass spectra and experimental RI values to those in the National Institute of Standards and Technology

(NIST) mass spectra and RI databases (version 11). Subsequently, if the experimentally determined RI falls within the RI range of 10 units of a value found in the database, where the authors determined the RI value experimentally, it is regarded as a positive identification (Bicchi et al, 2018).

Samples B12, B44 and A65 contained 10, 9 and 14 of the identified compounds respectively (Figure 5.5-Figure 5.7). Compounds 1 and 2 were present in all three extracts and compounds 3, 4, 5, 6, 7 and 9 were present in both B12 and A65. These results revealed that the extracts of the metabolites that are produced by actinobacteria are complex mixtures of compounds, consisting mostly of alkanes, alkenes, carboxylic acids, esters and amides (Table 5.2). Out of the 23 different compounds identified, 9 are alkanes,

3 are alkenes or alcohols, 5 are acids or esters, 2 are amides and 4 are unknowns.

141

RT: 0.00 - 180.06 123.65 NL: 440000 128.63 4.45E5 TIC MS 420000 20190206_ 2_B12 400000

380000

360000

340000

320000

300000 138.28 149.35 157.13 280000 159.68 170.88

260000

240000

220000 200000 2

RelativeAbundance 3 180000 7 32.06 87.80 45.51 160000 4 140000 1 57.50 8 122.84 120000 17.26 5 88.15 100000 68.29 6 119.25 9 117.72 78.15 89.25 80000 46.86 115.22 59.82 70.35 112.96 35.08 94.99 60000 24.13 57.10 64.59 86.83 5.19 41.07 74.69 40000 5.87 20000 7.09

0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 Time (min)

Figure 5.5: Total ion chromatogram of the ethyl acetate extract from actinobacteria isolate

B12.

RT: 0.00 - 180.06 12 71.99 NL: 4.00E6 TIC MS 3800000 20190213_ 2_B44 3600000

3400000

3200000 15 80.93 3000000

2800000

2600000

2400000

2200000

2000000

1800000 RelativeAbundance 1600000

1400000

1200000

1000000

800000

600000 128.61 131.22 139.07 149.96 400000 127.77 158.14 164.78 1 2 11 14 121.70 32.05 16 17 200000 17.26 45.49 59.52 79.67 88.99 114.85 61.96 107.59 5.26 7.24 17.63 31.02 35.69 55.72 13 0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 Time (min)

Figure 5.6: Total ion chromatogram of the ethyl acetate extract from actinobacteria isolate

B44.

142

RT: 0.00 - 180.06 123.62 NL: 850000 8.56E5 TIC MS 800000 20190214_ 2_A65

750000

700000

650000 128.61 600000

550000

500000

450000

400000

RelativeAbundance 350000

300000 2 133.34 142.04 156.69 159.25 163.16 178.85 250000 32.03 3 200000 1 45.49 17.25 9 22 4 89.20 93.09 57.49 150000 23 122.81 6 19 7 100.42 46.83 5 80.74 87.81 120.95 68.29 78.14 103.93 100000 18 21 118.55 5.90 48.15 71.76 20 31.00 35.05 59.79 17.60 53.45 50000 14.45

0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 Time (min)

Figure 5.7: Total ion chromatogram of the ethyl acetate extract from actinobacteria isolate

A65.

143

Table 5.2: Constituents identified in the three ethyl acetate extracts from the actinobacteria isolates B12, B44 and A65.

Compound RI Identification Present in nr Tentative identities Rt RI (exp)a (literature)b method extract 1 3-Methyl-decane (branched C11 A,B B12, alkane) 17.26 1071 1070.4 B44,A65 2 A,B B12, Tridecane 32.06 1291 1300 B44,A65 3 A,B B12, A65 Pentadecane 45.51 1504 1500 4 A,B B12, A65 Heptadecane 57.50 1715 1700 5 A,B B12. A65 Nonadecane 68.29 1926 1900 6 A B12, A65 Unknown 78.15 2139 - 7 A,B B12, A65 Octadecenamide analogue 87.80 2367 2375 8 A,B B12 9-Octadecenamide 88.15 2376 2375 9 Unknown cyclohexane carboxylic acid A B12, A65 ester 89.25 2401 10 A B12 Unknown 99.92 2690 11 A B44 Unknown 59.38 1749 12 A B44 Unknown C18 carboxylic acid/ester 71.99 1999 13 A B44 Unknown unsaturated acid/ester 79.38 2166 - 14 A B44 Unknown ethyl octadecenoate 79.67 2172 - 15 A B44 Unknown C20 carboxylic acid/ester 80.93 2199 16 A B44 Unknown 87.01 2349 - 17 A,B B44 C24 alkene or C21 alcohol 88.99 2395 - 18 A,B A65 C20 alkene or C17 alcohol 71.76 1994 - 19 A,B A65 C22 alkene or C19 alcohol 80.74 2195 - 20 A,B A65 Tricosane 85.19 2305 2300 21 A,B,C A65 Tetracosane 88.99 2395 2400 22 A,B A65 Pentacosane 93.09 2504 2500 23 A,B,C A65 Hexacosane 96.82 2600 2600 a: Experimentally determined RI values, b: RI values from the NIST RI database, A: Comparison of the mass spectrum with NIST database and published data, B: Comparison of RI with NIST RI database, C: Comparison of retention time with the authentic reference standard.

5.3.2.1 Alkanes

Comparison of the mass spectra of compounds 1, 2, 3, 4, 5, 20, 21, 22 and 23 (Figures

5.8-5.12 and Figures 5.27-5.30) to those in the NIST MS database revealed that they may be alkanes. Fragmentation patterns for alkanes usually contain clusters of peaks about 14 mass units apart, representing a loss of CH2. In general, fragments correspond to m/z 29,

144

43, 57, 71, 85 99, etc with some differences depending on the instrument used,

corresponding to the ±CnH2n+1 ion peaks. The peaks observed at m/z 43 and 57 are usually the peaks with the highest relative abundance due to their stability and do not undergo significant secondary fragmentation (Nicolescu, 2017). These two peaks were present in the mass spectra of all the compounds listed above. The RI values of compounds 2, 3, 20,

21, 22 and 23 were within 10 units of those of normal alkanes and therefore were positively identified as tridecane (2), pentadecane (3), heptadecane (4), nonadecane (5), tricosane (20), tetracosane (21), pentacosane (22) and hexacosane (23). In addition, the retention times of compounds 21 and 23 correspond to those of the authentic reference standards, tetracosane and hexacosane in the mixtures of alkanes that were analysed for the RI determinations. However, compounds 1, 4 and 5 had RI value differences of greater than 10 from the values for n-alkanes, hence they were presumably branched alkanes.

Hence these 3 compounds were tentatively identified as branched C11 (1), C17 (4) and C19

(5) alkanes.

Alkanes and alkenes are major components of gasoline, diesel, and jet fuels. It has been reported that they are produced naturally by a wide range of microbes. There are five known microbial pathways where fatty acid derivatives are converted into alkanes and alkenes (Wang and Lu, 2013). These can be used by the microbes as an energy source.

Alkanes have previously been found in extracts from actinobacteria, especially

Streptomyces species such as Streptomyces griseus (Scholler et al., 2002; Danaei et al.,

2014).

145

5.3.2.2 Alkenes and alcohols

Comparison of the mass spectra of compounds 17, 18 and 19 to those in the NIST MS database revealed that they may be alkenes or alcohols (Figures 5.24-5.26). The mass spectra of alkenes contain a peak at m/z 41, corresponding to the allyl carbocation

(Nicolescu, 2017). Alkenes also fragment in clusters of peaks 14 units apart but with the most prominent peaks corresponding to the ±CnH2n-1 ion series (Silverstein et al., 2005).

This usually leads to a prominent peak at m/z 55. The mass spectra of compounds 17, 18 and 19 contain prominent peaks at m/z 41 and 55, as well as several peaks corresponding

+ to the CnH2n-1 ion series. However, the mass spectra of alcohols also usually contain

+ prominent peaks at m/z 41 and 55, together with the CnH2n-1 ion series, while the molecular ion is often undetectable (Silverstein et al., 2005) Since alcohols frequently cleave at β bonds, primary alcohols usually show a prominent peak at m/z 31, with secondary and tertiary alcohols sometimes showing a smaller peak at that position

(Hamming and Foster, 1972). However, this peak was not present in the mass spectra of compounds 17, 18 and 19. Hence, based on the MS data alone it could be deduced that these three compounds are either alkenes or 2° or 3° alcohols. The RIs of compounds 17,

18 and 19 are 2395, 1994 and 2195, respectively. These values correspond to the RI values that appear in the NIST RI database for monounsaturated C24, C20 and C22 alkenes, respectively. However, the NIST RI database RIs of C21, C17 and C19 long-chain aliphatic alcohols also correspond to the respective RI values. Hence these compounds were tentatively identified as a C24 alkene or a C21 alcohol (17), a C20 alkene or a C17 alcohol

(18) and a C22 alkene or a C19 alcohol (19). Alkenes and alcohols such as isoprene, 1- butanol, 2-methyl-1-propanol, 3-methyl-3-buten-1-ol, 3-methyl-1-butanol, 2-methyl-1-

146 butanol, 2-phenylethanol, and cyclohexanol have been found in extracts from actinobacteria some having antifungal and antibacterial activities (Scholler et al., 2002;

Danaei et al., 2014).

5.3.2.3 Carboxylic acids and esters

The mass spectra of compounds 9, 12, 13, 14 and 15 (Figure 5.16 and Figure 5.19-5.21) were all similar and could be carboxylic acids or esters, based on the comparison of their mass spectra to those in the NIST 11 MS database. The mass spectra of carboxylic acid_esters (R’COOR2) usually have the following peaks (Nicolescu, 2017):

Table 5.3: Mass spectra of carboxylic acids and esters

m/z values for fragment ions with different alkyl (R) groups Fragment CH3 C2H5 C3H7 C4H9 C5H11 ion R1+ 15 29 43 57 71 R1CO+ 43 57 71 85 99 1 + R C(OH)2 61 75 89 103 117 R2OCO- 59 73 87 101 McLafferty 74 88 102 116

Compound 9 has peaks at m/z 43, 57, 71 and 85, though the other compounds do not line up with the table’s interpretations. None of the other compounds follow any pattern as set out by the table. Esters usually have a base peak at m/z 74 with smaller peaks at m/z 83,

99 and 101 (Hamming and Foster, 1972). Although the mass spectra of compounds 9, 12 and 14 had low-intensity peaks at m/z 83, 99 and 101, none had the base peak at m/z 74 as expected for methyl esters, but at m/z 41, 55 and 55, respectively instead. Compound 13 only had a peak at m/z 83 while compound 15 had peaks at m/z 83 and 101 with base peaks at m/z 67 and 55, respectively. The mass spectra of compounds 12 and 15 were more

147 similar to those of the free fatty acids octadecanoic acid and eicosanoic acid, respectively, but their RI values did not match those in the database. Thus, these compounds were tentatively identified as an unknown cyclohexane carboxylic acid ester (9), an unknown

C18 carboxylic acid/ester (12), and an unknown acid/ester (13), an unknown ethyl octadecenoate (14) and an unknown C20 carboxylic acid/ester (15).

Esters are the functional groups present in various organic compounds, drugs, and natural products (Matsumoto et al., 2018). Waxes secreted by animals and plants also contain esters produced from long-chain carboxylic acids and alcohols. Fats and oils contain esters of long-chain carboxylic acids and glycerol. Some industrial uses of esters include the production of perfumes, essential oils, food flavourings, cosmetics, plastics, and surfactants (Matsumoto et al., 2018). Several studies have shown that certain actinobacteria produce carboxylic acids and esters such as n-hexadecanoic acid, and carbonochloridic acid, 2-chloroethyl ester and 3-[(1-carboxyvinyl)oxy]benzoic acid, some of which have displayed antibacterial, antifungal and anti-inflammatory properties

(Wenzel and Bode, 2004; Dickschat et al., 2011; Apsari et al., 2019). Thus, these might help the host plant fight off various infections in humans. Unfortunately, due to the mass spectra and RI values of the compounds extracted not matching up with those available in the database, they could only be partially identified.

5.3.2.4 Amides

The mass spectra of compounds 7 and 8 (Figures 5.14-5.15) were found to be almost identical. The spectra both matched that of 9-octadecenamide found in the NIST MS database. The experimentally determined RI of compound 8 was 2376, matching the value of the Z-9-octadecenamide reported in literature. Hence, compound 8 was positively 148

identified as Z-9-octadecenamide, while compound 7 (with an RI of 2367) is presumably

an isomer of compound 8 with a different double bond configuration and/or bond position.

Octadecenamide has previously been extracted from actinobacteria and reportedly has

antibacterial properties (Tanvir et al., 2016). Cis-9-octadecenamide, which is a lipid, has

been shown to affect serotonergic systems and block gap-junction communication in glial

cells in the nervous system. It was also isolated from the cerebrospinal fluids of sleep-

deprived cats (Cravatt et al.,1996).

20190206_2_B12 #1368-1374 RT: 17.23-17.29 AV: 7 SB: 9 17.07-17.11 , 17.44-17.47 NL: 2.84E4 T: + c Full ms [25.00-625.00] 41 100

50 43 39 45

RelativeAbundance 40

35 57 30

20 71 15 55

10 27 70 85 5 29 53 67 83 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.8: MS for compound 1, identified as 3-methyl-decane (branched C11 alkane) in

the ethyl acetate extracts from isolates B12, B44 and A65.

149

20190206_2_B12 #2897-2903 RT: 32.03-32.08 AV: 7 SB: 11 31.77-31.82 , 32.30-32.34 NL: 4.19E4 T: + c Full ms [25.00-625.00] 41 100

60 43 55

50 57 45

RelativeAbundance 40 39

25 71

15 55 85

10 69 27 5 83 29 67 53 58 82 86 99 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.9: MS for compound 2, identified as tridecane in the ethyl acetate extracts from

isolates B12, B44 and A65.

20190206_2_B12 #4288-4294 RT: 45.48-45.54 AV: 7 SB: 11 45.59-45.64 , 45.39-45.43 NL: 3.36E4 T: + c Full ms [25.00-625.00] 41 100

70 57 65

60 43

45 RelativeAbundance 40 39

35 71 30

25 85 20

15 55 69

10 27 83 5 99 29 67 53 58 82 95 110 113 127 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.10: MS for compound 3, identified as pentadecane in the ethyl acetate extracts

from isolates B12 and A65. 150

20190206_2_B12 #5527-5535 RT: 57.47-57.54 AV: 9 SB: 16 57.65-57.73 , 57.18-57.24 NL: 2.43E4 T: + c Full ms [25.00-625.00] 41 100

85 57 80

65 43 60

45 71

RelativeAbundance 40 39 35 85 30

20 55 69 15

10 83 99 5 27 67 113 29 97 53 58 82 110 127 141 153 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.11: MS for compound 4, identified as heptadecane in the ethyl acetate extracts

from isolates B12 and A65.

20190206_2_B12 #6641-6650 RT: 68.24-68.33 AV: 10 SB: 6 68.48-68.51 , 67.88-67.89 NL: 1.36E4 T: + c Full ms [25.00-625.00] 41 100

95 57

70 43 65

55 71 50

RelativeAbundance 40 85 39 35

25 55 69 20

15 99 83 10 67 113 27 111 5 95 127 29 82 53 58 86 110 125 133 141 155 177 189 205 217 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.12: MS for compound 5, identified as nonadecane in the ethyl acetate extracts

from isolates B12 and A65.

151

20190206_2_B12 #7655-7672 RT: 78.05-78.21 AV: 18 SB: 11 78.70-78.76 , 77.05-77.08 NL: 1.65E4 T: + c Full ms [25.00-625.00] 174 100

RelativeAbundance 130 40

35 41 57 30

25 43 314 20 71

15 85 39 175 10 55 69 5 59 83 99 131 176 315 27 97 113 127 146 210 44 61 100 141 155 172 197 284 316 329 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.13: MS for compound 6, an unknown constituent in the ethyl acetate extracts

from isolates B12 and A65.

20190206_2_B12 #8658-8673 RT: 87.75-87.88 AV: 16 SB: 23 90.22-90.31 , 87.40-87.51 NL: 1.33E4 T: + c Full ms [25.00-625.00] 55 100

80 126 75

70 72 65 41

39 55 59 67 50

45 81 RelativeAbundance 40 43 112 35 79 30 44 95 83 25 98 20

15 91 109 86 238 10 65 123 140 154 5 107 134 184 27 53 151 198 29 165 182 185 221 235 240 252 264 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.14: MS for compound 7, identified as an octadecenamide analogue in the ethyl

acetate extracts from isolates B12 and A65.

152

20190206_2_B12 #8695-8730 RT: 88.08-88.40 AV: 36 SB: 39 90.82-91.10 , 87.46-87.54 NL: 7.35E3 T: + c Full ms [25.00-625.00] 55 100

80 41 75 126 70

65 39 67 72 60

50 59 81 45

43 RelativeAbundance 40 79 112 35 95

30 44 83 25

20 98 91 15 109

10 86 238 65 123 140 154 27 107 135 5 53 151 184 29 198 221 51 165 168 192 206 235 239 252 264 269 322 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.15: MS for compound 8, identified as 9-octadecenamide in the ethyl acetate

extract from isolate B12.

20190206_2_B12 #8815-8823 RT: 89.20-89.28 AV: 9 SB: 6 89.66-89.68 , 89.10-89.12 NL: 4.45E3 T: + c Full ms [25.00-625.00] 41 100

85 57

75 111

70 129

65 55

60 71

50 43

45 83 39 RelativeAbundance 40 85 35

20 69 147 15 67 97 99 10 113 27 72 101 127 5 95 29 53 81 141 155 59 110 124 169 178 184 197 240 325 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.16: MS for compound 9, an unknown constituent (possible cyclohexane

carboxylic acid ester) in the ethyl acetate extracts from isolates B12 and A65.

153

20190206_2_B12 #9917-9924 RT: 99.87-99.94 AV: 8 SB: 6 99.64-99.68 , 100.08 NL: 7.90E3 T: + c Full ms [25.00-625.00] 314 100

RelativeAbundance 40

25 160 315 20

57 242 10 41 43 71 39 5 55 69 85 116 146 316 27 58 83 97 113 127 158 161 208 243 283 341 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.17: MS for compound 10, an unknown constituent in the ethyl acetate extract

from isolate B12.

20190213_2_B44 #5731-5736 RT: 59.36-59.40 AV: 6 SB: 8 60.12-60.15 , 59.20-59.23 NL: 1.24E4 T: + c Full ms [25.00-625.00] 186 100

90 127 85 107

65 135 60 67 55 163 50

45 91 RelativeAbundance 167 40 126

35 95 79 30

25 39 195 41 65 139 154 20 77 227 105 15 111

10 171 43 5 117 51 55 151 177 222 29 68 80 99 196 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.18: MS for compound 11, an unknown constituent in the ethyl acetate extract

from isolate B44.

154

20190213_2_B44 #7039-7046 RT: 71.95-72.01 AV: 8 SB: 9 72.18-72.22 , 71.60-71.63 NL: 4.58E5 T: + c Full ms [25.00-625.00] 55 100

60 73 55 157

50 213 45 241 41 185 RelativeAbundance 61 40 199 35

30 39 87 25 171 129 227 20 143 42 115 15 101 83 10 255 69 285 81 95 5 284 27 45 79 88 109 121 130 144 158 172 186 200 214 239 242 256 286 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.19: MS for compound 12, an unknown constituent (possible C18 carboxylic

acid/ester) in the ethyl acetate extract from isolate B44.

20190213_2_B44 #7808-7815 RT: 79.37-79.43 AV: 8 SB: 5 79.49-79.50 , 79.26-79.28 NL: 1.60E4 T: + c Full ms [25.00-625.00] 67 100

85 79

75 81 70

RelativeAbundance 77 40 95

30 39

25 41 91 55 20 135 121 65 15 109 82 149 96 10 150 262 68 136 178 83 97 131 110 164 5 43 69 137 263 27 159 177 187 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.20: MS for compound 13, identified as an unknown unsaturated acid or ester in

the ethyl acetate extract from isolate B44.

155

20190213_2_B44 #7836-7846 RT: 79.62-79.71 AV: 11 SB: 4 79.80-79.82 , 79.58 NL: 1.12E4 T: + c Full ms [25.00-625.00] 55 100

90 67 85

65 81

60 83 55 41 95 50 39 45 79 RelativeAbundance 40 96

35 97

25 69 98

20 77 110 91 264 15 73 155 123 265 10 43 135 152 65 107 124 138 166 5 53 61 222 27 147 165 180 175 189 220 235 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.21: MS for compound 14, identified as an unknown ethyl octadecenoate in the

ethyl acetate extract from isolate B44.

20190213_2_B44 #7974-7978 RT: 80.92-80.95 AV: 5 SB: 7 81.16-81.19 , 80.61-80.63 NL: 3.14E5 T: + c Full ms [25.00-625.00] 55 100

85 157 213

65 73 269 60

50 41 45

RelativeAbundance 40 61 199

35 171 87 30 227

25 39 185 241 255 43 115 20 129 143 15 101 312 10 83 69 97 5 95 283 45 88 158 214 270 27 79 109 123 144 172 186 200 228 256 313 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.22: MS for compound 15, identified as an unknown C20 carboxylic acid or ester

in the ethyl acetate extract from isolate B44.

156

20190213_2_B44 #8601-8611 RT: 86.96-87.05 AV: 11 SB: 6 86.67-86.71 , 87.25 NL: 7.06E3 T: + c Full ms [25.00-625.00] 115 100

75 67 70

65 55 95

60 41

50 81 45 73

RelativeAbundance 87 40

35 57 39 30 121 43 25 93 20 101 111 15 109 139 149 158 10 135 59 5 29 167 53 141 169 178 213 223 262 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.23: MS for compound 16, an unknown constituent in the ethyl acetate extract

from isolate B44.

20190213_2_B44 #8812-8820 RT: 88.96-89.03 AV: 9 SB: 5 88.61-88.63 , 89.43 NL: 1.09E4 T: + c Full ms [25.00-625.00] 55 100

95 41 90

75 97

70 69 65

55 67 83 50

45 111

39 RelativeAbundance 40 81 57 35

20 95 125 43 15

10 70 79 5 124 139 27 65 85 110 53 87 115 138 153 211 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.24: MS for compound 17, identified as a C24 alkene or a C21 alcohol in the ethyl

acetate extract from isolate B44.

157

20190214_2_A65 #7008-7016 RT: 71.72-71.80 AV: 9 SB: 4 71.63-71.64 , 71.97 NL: 6.82E3 T: + c Full ms [25.00-625.00] 41 100 55

70 69 65 39 60

55 67 97 50

45 83 57 RelativeAbundance 40

35 111 30 81

25 43

20 70 15

10 96 125 27 79 65 5 28 53 77 110 124 38 51 91 109 113 135 139 149 154 267 327 341 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.25: MS for compound 18, identified as a C20 alkene or a C17 alcohol in the ethyl

acetate extract from isolate A65.

20190214_2_A65 #7935-7941 RT: 80.71-80.76 AV: 7 SB: 2 80.87 , 80.60 NL: 1.27E4 T: + c Full ms [25.00-625.00] 55 100 41 95

70 69 65 97

55 67

50 39 83 45

RelativeAbundance 40 57 111

35 81 30

20 43

15 125 70 96 10 71 95

27 85 5 53 65 110 124 29 139 77 109 112 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.26: MS for compound 19, identified as a C22 alkene or a C19 alcohol in the ethyl

acetate extract from isolate A65.

158

20190214_2_A65 #8394-8401 RT: 85.14-85.20 AV: 8 SB: 4 85.66-85.68 , 84.83 NL: 9.24E3 T: + c Full ms [25.00-625.00] 41 57 100

65 71

55 43

50 85

RelativeAbundance 40 39 35

30 55 25

20 99 69 97 15 83 67 113 10 27 81 127 141 5 29 96 125 58 110 155 38 53 72 86 124 139 169 183 197 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.27: MS for compound 20, identified as tricosane in the ethyl acetate extract from

isolate A65.

20190214_2_A65 #8791-8800 RT: 88.94-89.02 AV: 10 SB: 8 89.80-89.86 , 87.53 NL: 1.15E4 T: + c Full ms [25.00-625.00] 55 100 41 95

70 97 65 69 60

55 67 39 50 57 83

45 RelativeAbundance 40 81 111 35

30 43 25

20 71 125 15 96 79 10 85 110 126 27 112 5 72 29 53 65 109 139 86 123 152 167 198 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.28: MS for compound 21, identified as tetracosane in the ethyl acetate extract

from isolate A65.

159

20190214_2_A65 #9217-9228 RT: 93.04-93.13 AV: 12 SB: 9 93.27 , 92.85-92.92 NL: 1.98E4 T: + c Full ms [25.00-625.00] 57 100 41 95

70 71 65

60 85 55 43

RelativeAbundance 40

35 39

30 55 25 99 20 97 69 15 113 83 67 111 10 127 81 5 27 96 141 125 155 53 58 72 95 110 124 139 169 183 197 211 225 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.29: MS for compound 22, identified as pentacosane in the ethyl acetate extract

from isolate A65.

20190214_2_A65 #9605-9614 RT: 96.79-96.86 AV: 10 SB: 8 97.26-97.32 , 96.10 NL: 1.85E4 T: + c Full ms [25.00-625.00] 57 100

95 41

70 71

60 85 55 43 50

RelativeAbundance 40

35 39

30 55 25 99 20 97 69 15 83 113 67 10 127 81 96 141 5 27 125 155 110 169 58 72 95 124 139 152 183 197 211 315 0 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 m/z

Figure 5.30: MS for compound 23, identified as hexacosane in the ethyl acetate extract

from isolate A65.

160

5.4. CONCLUSION

The TLC phytochemical screen of the ethyl acetate of 18 endophytic actinobacteria indicated the presence of traces of alkaloids, phenols, and flavonoids in 13, 17 and 8 extracts, respectively, while none of the extracts contained any terpenoids. Using GC-MS, a total of 23 volatile compounds, namely alkanes, alkenes/alcohols, carboxylic acids/esters and amides, were identified in three of the extracts (B12, B44 and A65) as 3- methyl-decane(branched C11 alkane) (1), tridecane (2), pentadecane (3), heptadecane (4), nonadecane (5), unknown constituent (6), octadecenamide analogue (7), 9- octadecenamide (8), unknown cyclohexane carboxylic acid or ester (9), unknown constituent (10), unknown constituent (11), unknown C18 carboxylic acid or ester (12), unknown unsaturated acid or ester (13), unknown ethyl octadecenoate (14), unknown C20 carboxylic acid or ester (15), unknown constituent (16), C24 alkene or C21 alcohol (17),

C20 alkene or C17 alcohol (18), C22 alkene or C19 alcohol (19), tricosane (20), tetracosane

(21), pentacosane (22) and hexacosane (23). The group of compounds present in the highest number is the alkanes, with 9 out of the 23 compounds being identified as alkanes.

The GC/MS data supported the TLC phytochemical screening that there were no terpenoids in the extracts. Compounds 1 and 2 were found in all three extracts, whereas compounds 3, 4, 5, 6, 7 and 9 were found in both B12 and A65. Compounds 8 and 10 are unique to the ethyl acetate extract of isolate B12, compounds 11, 12, 13, 14, 15, 16 and

17 are unique to the ethyl acetate extract of isolate B44 and compounds 18, 19, 20, 21, 22 and 23 are unique to the ethyl acetate extract of isolate A65. The ethyl acetate extract of isolate B44 was the most diverse.

161

Phenols are natural antioxidants and exert antiallergic, anti-inflammatory, antidiabetic, antimicrobial, antiviral properties (Huyut et al., 2017). Flavonoids have antioxidant activity and help plants fight off microbial infections. Alkaloids are known for their medicinal properties including emetic, anticholinergic, antitumor, diuretic, antiviral and antimicrobial activities (De Almeida et al., 2017). Alkanes and alkenes are major components of gasoline, diesel and jet fuels and can be used by the microbes as an energy source. Alkenes and alcohols can have antifungal and antibacterial activities (Scholler et al., 2002; Danaei et al., 2014). Carboxylic acids and esters can exhibit antibacterial, antifungal, and anti-inflammatory properties (Wenzel and Bode, 2004; Dickschat et al.,

2011; Apsari et al., 2019). Octadecenamide has antibacterial properties and it has been shown to affect serotonergic systems and block gap-junction communication in glial cells in the nervous system (Cravatt et al.,1996; Tanvir et al., 2016). Thus endophytic actinobacteria isolated from H. procumbens are a great source for a variety of compounds that are useful across numerous industries

162

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CHAPTER 6: GENERAL CONCLUSIONS AND RECOMMENDATIONS

Though ethnobotanical endophytic bioprospecting is still scanty, this study has revealed that the arid zone plant H. procumbens’ secondary tubers are a good source of a miscellany of endophytic actinobacteria including many rare actinobacteria and potentially novel taxa. It suggests that these strains might yield diverse groups of metabolites endowed with antioxidant and antimicrobial potential and genes for their biosynthesis. A total of 7 genera was identified, the most dominant genus being that of Streptomyces and 6 rare actinobacteria genera Patulibacter, Agromyces, Norcadiopsis, Rubrobacter,

Rhodococcus, and Curtobacterium. Thus, to confirm their identity, further experiments are required such as cellular fatty acid composition, DNA-DNA relatedness value, whole- cell sugar analysis and whole-genome sequencing among others.

From a total of 140 endophytic actinobacteria isolated, 23 isolates were chosen for further study based on their primary antimicrobial activity. Further analysis showed that they produce extracellular metabolites with broad-spectrum antimicrobial activity against gram-positive bacteria, gram-negative bacteria, Mycobacteria and Candida before and after solvent extraction. Actinobacterial ethyl acetate extracts yielded the highest activity against the test organisms compared to chloroform and methanol. The antimicrobial potential of the extracts was also shown to be affected by the growth conditions of the actinobacteria such as the carbon source, pH, temperature and whether the media was supplemented with host plant extracts. Thus, it is important to determine the optimal growth conditions for extracellular metabolite production. Further studies should focus on testing the antimicrobial potential of these isolates on a wider variety of microorganisms

166 such as those that might be antibiotic-resistant to known therapeutic antibiotics. Testing more growth parameters will also help to optimize the production of these metabolites.

The presence of PKSI and NRPS gene clusters in the 23 actinobacteria isolates was determined since they are good indicators of secondary metabolite production. Twenty of the 23 isolates had at least one of the gene clusters while 3 had both. Thus, the prevalence of these gene clusters contributed to the antimicrobial activity of these isolates. Since only the presence of these gene clusters were determined, further studies could sequence these gene clusters to help determine which metabolites they encode, and which pathways might be used to produce those metabolites. More studies are also needed to determine the presence of other beneficial gene clusters.

Furthermore, the 23 actinobacteria isolates were tested for their ability to produce a variety of industrially useful enzymes such as urease, gelatinase, protease, amylase, catalase, and indole acetic acid. All 23 isolates produced at least one of these enzymes which shows that endophytic actinobacteria isolated from H. procumbens are a reservoir for numerous secondary metabolites, including enzymes. Future research could establish whether these actinobacteria produce other industrially important enzymes such as oxidases and which pathways they utilize to produce these enzymes and their natural uses by the microbes as well as if they have any importance to the host plant.

Additionally, solvent extracts from the 23 actinobacteria isolates were subjected to various in vivo antioxidant tests, such as determining the total phenolic content, total antioxidant activity, total reducing power and free radical scavenging activity as well as a DNA nicking assay. Ethyl acetate extracts again had the highest activity across the board. A large portion of these extracts had even higher activity than the gallic acid standard. Ethyl

167 acetate extracts from 21 of the 23 actinobacteria isolates had at least some degree of DNA damage protection activity, with 3 extracts protecting both the linear and plasmid DNA from fragmentation by hydrogen peroxide. Thus, these results demonstrate that the plant- associated endophytic actinobacteria from H. procumbens produce compounds that have good antioxidant and DNA damage protection activity. Further research can be conducted to determine the identity of the compounds that have these activities and further quantify their abundance.

Finally, ethyl acetate extracts of 18 actinobacteria isolates were selected due to their high antimicrobial and antioxidant activities for TLC phytochemical screening to determine the presence of terpenoids, alkaloids, phenols and flavonoids, which were detected in 0, 13,

17 and 8 extracts, respectively. Following this, three of the top-performing ethyl acetate extracts (from isolates B12, B44 and A65) were chosen for GC-MS analysis after which

23 compounds were tentatively identified as 3-Methyl-decane(branched undecane) (1),

Tridecane (2), Pentadecane (3), Heptadecane (4), Nonadecane (5), Unknown (6),

Octadecenamide analogue (7), 9-Octadecenamide (8), Unknown cyclohexane carboxylic acid ester (9), Unknown (10), Unknown (11), Unknown C18 carboxylic acid/ester (12),

Unknown unsaturated acid/ester (13), Unknown ethyl octadecenoate (14), Unknown C20 carboxylic acid/ester (15), Unknown (16), C24 alkene or C21 alcohol (17), C20 alkene or

C17 alcohol (18), C22 alkene or C19 alcohol (19), Tricosane (20), Tetracosane (21),

Pentacosane (22) and Hexacosane (23). Several compound types were detected using the

TLC screens which were not detected using GC/MS. Hence, other techniques must be utilized such as HPTCL and NMR. Individual compounds must be isolated and further characterised by NMR. The isolated compounds can also be tested for their bioactivity

168 such as antimicrobial potential as well as their plant growth-promoting traits since they were produced by endophytic actinobacteria. It might also be of interest to study the compounds produced by other bacterial and fungal endophytes of H. procumbens that might lend a survival advantage to the host plant as from this study, it is clear that H. procumbens is a rich source of biologically active endophytes.

169