Isolation of Bacteriophages Obtained from Limestones Cave Soils And

ISOLATION OF BACTERIOPHAGES FROM LIMESTONE CAVE SOILS AND EVALUATION OF THEIR POTENTIAL APPLICATION AS BIOCONTROL AGENTS OF PSEUDOMONAS AERUGINOSA

HASINA MOHAMMED MKWATA

A thesis presented in fulfillment of the requirements for the degree of Master of Science (Research)

School of Chemical Engineering and Science, Faculty of Engineering, Computing and Science SWINBURNE UNIVERSITY OF TECHNOLOGY

2018

ABSTRACT The emergence and frequent occurrence of multidrug-resistant and extremely drug- resistant bacteria have raised a major concern because infections caused by these bacteria are often associated with high mortality rates, prolonged hospitalization, and high treatment costs. This situation is predicted to worsen in the future due to a massive decline in the development of new antibiotics in recent years. Bacteriophages and their derivatives have long been exploited as powerful and promising alternative antibacterial agents in phage therapy and biocontrol applications. Limestone caves remain relatively unexplored as a source of novel lytic bacteriophages compared with other environments, despite being one of the most propitious sources for the discovery of novel antimicrobial compounds. This research presents, for the first time, the screening and isolation of lytic bacteriophages targeting different pathogenic bacteria from limestone caves of Sarawak, and evaluation of their potential application as biological disinfectants to control P. aeruginosa infections. A total of 33 lytic bacteriophages were isolated from samples obtained from FCNR and WCNR targeting bacterial strains Pseudomonas aeruginosa, Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Escherichia coli and Vibrio parahaemolyticus, using enrichment culture method. Phage amplification was performed, and lysates were obtained, and spot tested on lawns of various bacteria strains to assess their lysis spectrum. The result revealed that P. aeruginosa and V. parahaemolyticus infecting phage isolates showed the broadest host range among all the phage isolates. An interesting feature observed, was the ability of some phage isolates to exhibit trans-subdomain infectivity between gram positive and gram-negative bacterial hosts. Phage bacteriolytic activity was investigated in an in-vitro co-culture assay with P. aeruginosa PAO1 strain using five multiplicity of infection (MOI) ratios. Viable P. aeruginosa PAO1 cells that survived phage infection were enumerated at 6 hrs and 24 hrs post-infection and the counts were compared with those of untreated control. Bacteriophages FCPA3 (MOI 105), WCSS4PA (MOI 105) and Cocktail (MOI 104) showed the highest bacterial inactivation among all the tested phages at the end of 6 hrs of incubation. The highest bacterial log10 CFU/mL reduction was 11.82 equivalent to 100% reduction in bacteria observed in cultures treated with phage cocktail (Cocktail, MOI 104) at the end of 6 hrs of

incubation. Similarly, surviving bacterial counts assessed 24 hrs post-infection showed

4 2 that phages WCSS4PA (MOI 10 ) and Cocktail (MOI 10 ) had the highest bacterial log10 CFU/mL reduction of 10.5 and 10.86 respectively, equivalent to 100% reduction in bacterial cells. Some of the phages did not show any reduction in bacterial cells at 6 hrs and 24 hrs post-infection, instead the cells rebounded and surpassed those of the untreated control. Assessment of phage’s ability to be utilized as a biological disinfectant was performed on P. aeruginosa PAO1 contaminated sand samples. The sand samples served as a simulant of any environmental surface exposed to contamination with P. aeruginosa. Surviving bacterial cells following treatment with bacteriophages FCPA3, WCSS4PA and Cocktail were enumerated at 0 hr, 6 hrs, 24 hrs and 48 hrs post-treatment, and the counts were compared with those of untreated control. Over 99% reduction in bacterial cells were observed on all phage treated sand samples harvested at 6 hrs post- treatment. No reduction in bacterial cells was observed in sand samples harvested at 24 hrs and 48 hrs post-treatment despite phage recharge, instead, the cells rebounded and surpassed those of untreated controls. The ‘Bacterial rebound’ phenomenon mentioned in this study indicates that the bacteria evolved resistance against the infecting phage. This study suggests that P. aeruginosa bacteriophages obtained from Sarawak limestone caves (FCNR and WCNR) may present potentials to be developed into biological disinfectants to control P. aeruginosa infections, upon further exploration.

ACKNOWLEDGEMENT Foremost, I am deeply grateful to my coordinating supervisor, Assoc. Prof Dr Peter Morin Nissom for his valuable advice, critics, challenges, encouragement, and directions throughout my research study. Special thanks goes to my co-supervisor, Dr Lee Tung Tan for accepting to co-supervise my MSc research project. I extend my appreciation to Sarawak Biodiversity Centre (SBC) and Sarawak Forestry Department (SFD) for issuing the permits (SBC-RA-0110-PMN) which enabled me to have access to soil samples from Fairy Cave and Wind Cave Nature Reserves, located in Bau, Kuching Division, Sarawak, Malaysia. I also wish to thank the science laboratory officers, Nurul Arina Salleh, Cinderella Sio and Marciana Jane Richard, as well as Chua JiaNi, biosafety officer, for their assistance with regards to the provision of the materials and apparatus throughout the course of my research. My heartfelt thanks extend to my boyfriend, Armstrong Ighodalo Omoregie for his unwavering support and encouragement throughout my research journey. I am sincerely grateful to my parents, Mohammed Mkwata and Fatma Mwenda for their unconditional love, care, advice and encouragement throughout my studies. I am profoundly thankful to my Dad, for his financial support used to partially fund my research. I am grateful to Almighty God, whose blessings have enabled me to successfully accomplish my research study.

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DECLARATION I hereby declare that this research entitled “Isolation of bacteriophages obtained from limestones cave soils and evaluation of their potential application as biocontrol agents of Pseudomonas aeruginosa” is original and contains no material which has been accepted for the award to the candidate of any other degree or diploma, except where due reference is made in the text of the examinable outcome; to the best of my knowledge contains no material previously published or written by another person except where due reference is made in the text of the examinable outcome; and where work is based on joint research or publications, discloses the relative contributions of the respective workers or authors.

(HASINA MOHAMMED MKWATA) DATE: August 15, 2018

In my capacity as the Principal Coordinating Supervisor of the candidate’s thesis, I hereby certify that the above statements are true to the best of my knowledge.

(ASSOCIATE PROFESSOR DR. PETER MORIN NISSOM) DATE: August 15, 2018

PUBLICATIONS

Mkwata, HM, Tan, LT, & Nissom, PM, 2016, ‘Assessing the Diversity of Viruses in Soils Obtained from Limestone Caves,’ 15th International Peat Congress (IPC 2016), International Peatland Society, pp. 156-160.

Mkwata, H.M., Omoregie, A. I., Musa, I. B., Suyuh, J., Yee, P.H., Sing, L.W., Tan, L. T. & Nissom, P. M. (2018), “A Laboratory Practicum on Screening for Lytic Bacteriophages from Soil Samples”, Transactions on Science and Technology, (6 pages), ISSN: 2289-8786, published by e-VIBS, Faculty of Science and Natural Resources, Universiti Malaysia Sabah. (Accepted).

Omoregie, A. I., Siah, J., Pei, B. C. S., Yie, S. P. J., Weissmann, L. S., Enn, T. G., Rafi, R., Zoe, T. H. Y., Mkwata, H. M., Sio, C. A. & Nissom, P. M. (2018), “Integrating Biotechnology into Geotechnical Engineering: A Laboratory Exercise”, Transactions on Science and Technology, 13 pages), Volume 5, No. 2, ISSN: 2289-8786, published by e-VIBS, Faculty of Science and Natural Resources, Universiti Malaysia Sabah.

CONFERENCE AND PRESENTATIONS

Poster presenter, Assessing the Diversity of Viruses in Soils Obtained from Limestone Caves, 15th International Peat Congress (IPC 2016), International Peatland Society, 15- 19 August 2016, Kuching, Sarawak, Malaysia.

Oral presenter, Phage Therapy: The forgotten cure, Three Minute Thesis (3MT) Competition, 17 June 2015, Swinburne University of Technology, Sarawak campus, Kuching, Sarawak, Malaysia.

Participant, International Congress of the Malaysian Society for Microbiology, 7-10 December 2015, Batu Ferringhi, Penang, Malaysia.

Participant, Asian Congress on Biotechnology, 15-19 November 2015, Kuala Lumpur, Selangor, Malaysia.

TABLE OF CONTENTS

CONTENTS PAGE ABSTRACT ...... i ACKNOWLEDGEMENT ...... iii DECLARATION ...... iv PUBLICATIONS ...... v CONFERENCE AND PRESENTATIONS ...... v TABLE OF CONTENTS ...... vi LIST OF FIGURES...... ix LIST OF TABLES ...... xi LIST OF ABBREVIATIONS ...... xiii INTRODUCTION AND LITERATURE ...... 1.1 Background ...... 1 1.2 Antibiotic-resistant pathogens: A global threat ...... 3 1.3 Antibiotic-resistant mechanisms ...... 5 1.3.1 Decreased drug permeability...... 6 1.3.2 Active efflux ...... 6 1.3.3 Alteration or bypass of the drug target ...... 7 1.3.4 Production of antibiotic modifying enzymes ...... 9 1.3.5 Antibiotic inactivation by transfer of a chemical group ...... 10 1.4 Bacteriophages ...... 11 1.4.1 Bacteriophage structure and classification ...... 12 1.4.2 Bacteriophage replication cycles ...... 14 1.5 Phage therapy, biocontrol, and its advantages ...... 18 1.5.1 Bactericidal capacity ...... 18 1.5.2 Self-replicating pharmaceuticals...... 18 1.5.3 Specificity ...... 19 1.5.4 Narrow potential for inducing bacterial resistance ...... 19 1.5.5 Rapid discovery ...... 20 1.5.6 Safety and immunogenicity ...... 20 1.5.7 Single dose potential...... 21 1.5.8 Minimal environmental impact and relatively low cost ...... 21 1.5.9 Biofilm clearance...... 22 1.6 History of phage therapy ...... 22 1.7 Early therapeutic applications of phages ...... 23 1.8 Recent applications of phages in biocontrol and therapeutics ...... 26 1.8.1 Human pathogens treatment ...... 26 1.8.2 Sanitation ...... 29

1.8.3 Probiotics ...... 30 1.8.4 Food safety ...... 31 1.8.5 Water treatment ...... 32 1.9 Limestone Caves: A potential source for novel lytic phages ...... 33 1.10 Exploring Sarawak’s limestone caves for potential lytic phages ...... 36 1.11 Significance of the study ...... 39 1.12 Hypothesis ...... 39 1.13 Aims and objectives of the study ...... 39 1.14 Thesis Outline ...... 40 MATERIALS AND METHODS ...... 2.1. Isolation of lytic bacteriophages targeting bacterial pathogens ...... 41 2.1.1 Sampling site and sample collection ...... 41 2.1.2 Biological material ...... 41 2.1.3 Growth medium and sterilization ...... 42 2.1.4 Growth profiles of the bacterial hosts ...... 42 2.1.5 Maintenance and storage of bacterial hosts ...... 43 2.1.6 Screening for lytic bacteriophages ...... 43 2.1.7 Phage isolation and amplification ...... 44 2.1.8 Screening and isolation of multiphages ...... 44 2.1.9 Determination of phage titer ...... 45 2.1.10 Storage of lytic bacteriophages ...... 45 2.1.11 Revival of cryo-preserved lytic bacteriophages ...... 46 2.1.12 Host range assay ...... 46 2.2. Phage in-vitro bacteriolytic activity and a small-scale treatment of experimentally contaminated sand samples ...... 47 2.2.1 Preparation of bacterial culture...... 47 2.2.2 Preparation of phage stocks ...... 47 2.2.3 Phage in-vitro bacteriolytic activity ...... 48 2.2.4 Analysis of bacteria survival from phage treated cultures ...... 48 2.2.5 Preparation of sand samples ...... 48 2.2.6 Phage preparation in spray bottles...... 49 2.2.7 Treatment of contaminated sand samples with phage ...... 49 2.2.8 Analysis of bacterial survival following phage treatment ...... 50 2.2.9 Statistical analysis ...... 50 RESULTS AND DISCUSSION ...... 3.1 Introduction ...... 51 3.2 Results ...... 52 3.2.1 Isolation of lytic bacteriophages targeting bacterial pathogens ...... 52 3.2.2 In-vitro studies on phage bacteriolytic activity and assessment of bacterial survival following phage treatment...... 64 3.3 Discussion ...... 102 3.4 Conclusion ...... 117 GENERAL CONCLUSION AND FUTURE PERSPECTIVE ...... 4.1 General Conclusion ...... 119 vii

4.1.1 Aim of the thesis ...... 119 4.1.2 Summary of the findings ...... 120 4.2 Future Perspectives and Recommendation ...... 123 4.2.1 Morphological and Molecular characterization of the phage isolates ...... 123 4.2.2 Broadening applications of the phage isolates ...... 124 4.2.3 Assessment of phage stability ...... 124 4.2.4 Assessment of phage-resistant mutants ...... 124 4.2.5 Investigative studies on the expansion of host range ...... 125 REFERENCES ...... 126 APPENDICES ...... 165 Appendix I: Plaque appearance of bacteriophages infecting (A) K. pneumoniae, (B) P. aeruginosa, (C) E. coli and (D) V. parahaemolyticus, following an overnight incubation at 37oC...... 165 Appendix II: Multiplicity of infection (MOI) ...... 166 Appendix III: Optical density (OD) values of phage FCPA1 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 168 Appendix IV: Optical density (OD) values of phage FCPA2 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 169 Appendix V: Optical density (OD) values of phage FCPA3 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 170 Appendix VI: Optical density (OD) values of phage FCPA4 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 171 Appendix VII: Optical density (OD) values of phage FCPA5 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 172 Appendix VIII: Optical density (OD) values of phage FCPA6 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 173 Appendix IX: Optical density (OD) values of phage WCSS4PA obtained during an assessment of phage bacteriolytic activity at varied MOI ratios...... 174 Appendix X: Optical density (OD) values of phage WCSS5PA obtained during an assessment of phage bacteriolytic activity at varied MOI ratios...... 175 Appendix XI: Optical density (OD) values of phage Cocktail obtained during an assessment of phage bacteriolytic activity at varied MOI ratios ...... 176

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LIST OF FIGURES

Figures Page

1.1 Death attributable to antimicrobial-resistance every year by 2050 4 1.2 Antibiotic targets and mechanisms of resistance 5 1.3 A generalized structure of a tailed phage (left) and electron micrograph 13 images of the three families of tailed dsDNA phages that infect bacteria (right) 1.4 Schematic diagram showing lytic, lysogenic and pseudolysogenic cycles 15 of a bacteriophage 1.5 Phage bacteriolytic life cycle 17 1.6 Ancient phage preparations 25 1.7 Bacteriophage drugs produced by Eliava Biopreparations 29 1.8 Borneo Island’s map showing the geographical divisions 37 and features of Brunei Darussalam, Indonesia (Kalimantan) and East Malaysia (Sarawak and Sabah) 3.1 Fairy Cave (FC) Bau, Sarawak, Malaysia 53 3.2 Wind Cave (WC) Bau, Sarawak, Malaysia 53 3.3 Growth profile of the bacterial host cultures 55 3.4 Plaque appearance of bacteriophages infecting (A) S. aureus [left] and 57 S. pneumoniae (B) [right] 3.5 Phage titer determination of FCPA3 by double-layer plaque assay 57 3.6 Re-confirmation of P. aeruginosa bacteriophage lytic ability by spot test 61 assay 3.7 In-vitro bacteriolytic activity of FCPA1 at different MOI ratios 67 3.8 In-vitro bacteriolytic activity of FCPA2 at different MOI ratios 68 3.9 In-vitro bacteriolytic activity of FCPA3 at different MOI ratios 69 3.10 In-vitro bacteriolytic activity of FCPA4 at different MOI ratios 70 3.11 In-vitro bacteriolytic activity of FCPA5 at different MOI ratios 71 3.12 In-vitro bacteriolytic activity of FCPA6 at different MOI ratios 72 3.13 In-vitro bacteriolytic activity of WCSS4PA at different MOI ratios 73

3.14 In-vitro bacteriolytic activity of WCSS5PA at different MOI ratios 74 3.15 In-vitro bacteriolytic activity  cocktail at different MOI ratios 75 3.16 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 90 FCPA1 at different MOI ratios 3.17 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 91 FCPA2 at different MOI ratios 3.18 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 92 FCPA3 at different MOI ratios 3.19 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 93 FCPA4 at different MOI ratios 3.20 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 94 FCPA5 at different MOI ratios 3.21 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 95 FCPA6 at different MOI ratios 3.22 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 96 WCSS4PA at different MOI ratios 3.23 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 97 WCSS5PA at different MOI ratios 3.24 Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with 98 Cocktail at different MOI ratios 3.25 Survival of P. aeruginosa PAO1 cells on sand samples after treatment 101 with bacteriophages

LIST OF TABLES

Table Page

2.1 Description of bacterial strains used in this study 42 3.1 Description of soil samples collected at FCNR and WCNR 52 3.2 Growth kinetics of bacterial hosts grown in batch cultures 56 3.3 Morphological characteristics of bacteriophages isolated from 59-60 FCNR and WCNR 3.4 Assessment of bacteriophage host range by spot test assay 62-63 3.5 Assessment of phage bacteriolytic activity at the end of 6 hrs of 65-66 incubation 3.6 Analysis of variance (ANOVA) results for the recovery of bacteria 77 following an in-vitro treatment with FCPA1 3.7 Analysis of variance (ANOVA) results for the recovery of bacteria 78 following an in-vitro treatment with FCPA2 3.8 Analysis of variance (ANOVA) results for the recovery of bacteria 80 following an in-vitro treatment with FCPA3 3.9 Analysis of variance (ANOVA) results for the recovery of bacteria 81 following an in-vitro treatment with FCPA4 3.10 Analysis of variance (ANOVA) results for the recovery of bacteria 83 following an in-vitro treatment with FCPA5 3.11 Analysis of variance (ANOVA) results for the recovery of bacteria 84 following an in-vitro treatment with FCPA6 3.12 Analysis of variance (ANOVA) results for the recovery of bacteria 86 following an in-vitro treatment with WCSS4PA 3.13 Analysis of variance (ANOVA) results for the recovery of bacteria 87 following an in-vitro treatment with WCSS5PA. 3.14 Analysis of variance (ANOVA) results for the recovery of bacteria 89 following an in-vitro treatment with Cocktail.

3.15 Analysis of variance (ANOVA) results for surviving bacterial cells 99 recovered from sand treated samples at 0 hr using different phage samples. 3.16 Analysis of variance (ANOVA) results for surviving bacterial cells 100 recovered from sand treated samples at 6 hrs using different phage samples. 3.17 Analysis of variance (ANOVA) results for surviving bacterial cells 100 recovered from sand treated samples at 24 hrs using different phage samples. 3.18 Analysis of variance (ANOVA) results for surviving bacterial cells 101 recovered from sand treated samples at 48 hrs using different phage samples.

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LIST OF ABBREVIATIONS ANOVA Analysis of variance ASEAN Association of South East Asian Nations ARB Antibiotic-resistant bacteria BHI Brain heart infusion CRE Carbapenem-resistant Enterobacteriaceae CFU Colony forming unit DNA Deoxyribonucleic acid dsDNA Double-stranded DNA dsRNA Double-stranded RNA EIBMV Eliava Institute of Bacteriophages, Morphology, and Virology ESBLs Extended-spectrum -lactamases EPS Extracellular polymeric substances XDR Extended-spectrum -lactamases FCNR Fairy cave nature reserve FDA Food and Drug Administration GI Gastrointestinal GRAS Generally Recognized as Safe HIIET Hirszfeld Institute of Immunology and Experimental Therapy ICTV International Committee for Taxonomy of Viruses KPC- KP Klebsiella pneumoniae carbapenemase producing Klebsiella pneumoniae LPS Lipopolysaccharide Log Logarithm MRSA Methicillin-resistant Staphylococcus aureus MRAB Multidrug Acinetobacter baumannii MDR Multidrug-resistant MOI Multiplicity of Infection NDM1 New Delhi metallo-β- lactamase 1 OD Optical density PB Phage buffer

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PGHs Peptidoglycan hydrolases PBS Phosphate buffered saline PFU Plaque forming unit PAGE Polyacrylamide gel electrophoresis PFGE Pulsed-Field Gel Electrophoresis RH Relative humidity RFLP Restriction Fragment Length Polymorphism RNA Ribonucleic acid rRNA Ribosomal ribonucleic acid ssDNA Single-stranded DNA ssRNA Single-stranded RNA SDS Sodium dodecyl sulfate TEM Transmission Electron Microscopy TTC 2,3,5-Triphenyltetrazolium chloride TSA Tryptic soy agar TSB Tryptic soy broth WCNR Wind cave nature reserve WHO World health organization

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Chapter 1

INTRODUCTION AND LITERATURE

1.1 Background Bacterial infectious diseases are known to be one of the biggest threats to health and food security worldwide (Costelloe, et al., 2010, Prevention, 2013, Van Boeckel, et al., 2014). Multidrug-resistant (MDR) and extremely drug resistant (XDR) bacterial pathogens (Arora, et al., 2017) have recently emerged as a serious world threat (Bush, 2010, Michael, et al., 2014). For instance, ESKAPE bacterial pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) which are increasingly associated with nosocomial infections pose a serious challenge in medicine due to extreme resistance towards multiple antimicrobial agents (Moellering Jr, 2010, Rice, 2010). One of the most worrisome resistant pathogens undergoing pandemic dissemination is K. pneumoniae producing KPC-type carbapenemases (KPC-KP) which very frequently show an MDR or even an XDR phenotype, including last resort molecules such as colistin (Cantón, et al., 2012, Lee, et al., 2016, Tzouvelekis, et al., 2012). The growing number of antimicrobial-resistant pathogens, highlights a substantial liability on the healthcare systems, leading to a worldwide economic expense. For instance, morbidity and death rates, high treatment costs, diagnostic uncertainties, and lack of trust in traditional medicine (Santajit and Indrawattana, 2016). Factors such as globalization and increasing international mobility, abuse of antibiotics, horizontal gene transfer and evolution of bacteria have facilitated the spread of antibiotic-resistant pathogens (D’Andrea, et al., 2017, Lu and Koeris, 2011, Walsh, 2003). Nevertheless, shortage of new drug development by the pharmaceutical industry due to reduced incentives and challenging regulatory requirements (Jassim and Limoges, 2017), have also precipitated the emergence of antibiotic-resistant crisis (Gould and Bal, 2013, Prevention, 2013, Spellberg, 2014). This has resulted in a revived interest in unconventional antimicrobial treatments such as bacteriophages (Lu and Koeris, 2011). Bacteriophages (phages) are bacteria-specific viruses which infect and lyse their respective hosts (Sulakvelidze, et al., 2001). Bacteriophages are the most abundant viruses in the ocean (Hambly and Suttle, 2005), with numbers estimated at 1027 phage particles whereas the entire viriosphere is estimated to contain 1031 phage particles (Suttle, 2005, Wilhelm and Suttle, 1999). Due to their widespread in the environment, phages can be obtained from any sample that support bacteria proliferation (Jennifer, 2006). 1

Bacteriophages have shown great advancement since discovery and have been recognized as potentially powerful tools for eliminating bacterial infections (Liu, 2014). In addition, phages have facilitated the progress of modern biology, especially mastery of biological processes at a molecular level which has been pivotal in the establishment of modern biological sciences (Cairns, et al., 1968, Summers, 1999).

For a century, bacteriophages have been exploited as natural antibacterial agents in phage therapy (Roach and Debarbieux, 2017). In the early years of discovery, phage therapy resulted in mixed success, in large part due to poor understanding of the viruses themselves, as well as how they infect and kill bacteria (Abedon, et al., 2011). With the discovery of penicillin, phage therapies were largely superseded with the advent of the antibiotic era. Nevertheless, the rise of multidrug-resistant (MDR) bacterial infections, have renewed interest in the use of bacteriophages for treatment of human infections as well as in agriculture, veterinary science, industry, and food safety (McCarville, et al., 2016, Sulakvelidze, et al., 2001). Phages have shown an extensive application in biocontrol of food pathogens as opposed to other systems. For instance, in biocontrol of Listeria monocytogenes in food processing (Bai, et al., 2016), Salmonella enterica serovars typhirium in food animals (Wong, et al., 2014) and E.coli O157: H7 in inanimate surfaces (Viazis, et al., 2011). The effectiveness of phage therapy can be increased by creating a combination of phages commonly referred to ‘phage cocktails’ to target a wider variety of bacterial strains. Phage cocktails are well known to confer a broader spectrum of activity against infectious bacteria and prevent rapid development of phage-resistant mutants (Goodridge, 2010, Tanji, et al., 2005). Bacteriophages offers a sustainable approach against bacterial pathogens due to several factors such as, the ability to be easily isolated from the environment enriched with targeted bacteria, they are relatively inexpensive to produce, capability of infecting their hosts specifically and efficiently and development of phage products is relatively faster and more cost- effective than conventional drugs (Nagel, et al., 2016, Semler, et al., 2011, Yu, et al., 2017).

1.2 Antibiotic-resistant pathogens: A global threat Human medicine and food production are heavily dependent on the effective use of antibiotics (Baker, 2015). Antibiotics are arguably the most successful form of chemotherapy developed in the 20th century and perhaps over the entire history of medicine (Banin, et al., 2017). Since their discovery over 70 years ago, antibiotics have been one of the most significant advances in the modern medicine (Medina and Pieper, 2016). These drugs have saved millions of lives not only by treating infections but also as prophylactic measures in individuals with a weakened immune system such as those undergoing chemotherapeutic treatments against cancer or after organ transplantation (Medina and Pieper, 2016). In addition, antibiotics have found extensive applications in animal husbandry and aquaculture for growth promotion, feed efficiency, prophylaxis, as well as in the treatment of infections (Lekshmi, et al., 2017). Misuse of antibiotics have been reported in every environment where they have found applications, from small-scale clinical use by physicians (through unnecessary, indiscriminate or incorrect prescribing) and by patients (through incorrect dosing and the course of durations) to large-scale agricultural practice for disease treatment and prophylaxis or growth promotion in animal husbandry and food production.

These actions have provoked the emergence of antibiotic-resistant pathogens and present optimal environments for the dissemination and selection of resistance determinants (Lekshmi, et al., 2017, Pendleton, et al., 2013). Globally, 10 million people are expected to die by the year 2050 due to antimicrobial-resistance (Figure 1.1) (O’Neill, 2014). The advent of antibiotic-resistance reflects the ability of bacteria to evolve resistance mechanisms by which bacterial cell can escape the lethal action of antibiotics. Recent studies on metagenomics and functional genomics have provided an enthralling evidence that antibiotic resistance genes are ubiquitous and the natural reservoir of possible antibiotic resistance genes comprise of multiple ecosystems such as in agriculture (e.g. animal manure, soil, water, wastewater lagoons), the gut of humans and food animals, and even ancient soils (Lin, et al., 2015). The soil is an ideal forum for genetic exchange, easily resulting in the movement of resistance determinants from environmental or zoonotic bacteria to human pathogens (Pendleton, et al., 2013). Various novel antibiotic resistance genes present in the soil could be available to

clinically relevant bacteria and facilitate the existence of antibiotic-resistant pathogens (Lin, et al., 2015). Bacteria have established mechanisms to fight back the noxious impact of antimicrobial agents as an adaptive trait to their survival. The biological pressure inflicted by the constant exposure to diverse antibiotics during clinical application has resulted to a collective possession of resistant traits in major human pathogens, culminating in multidrug-resistant (MDR) bacteria, which are almost impossible to treat. For instance, methicillin-resistant Staphylococcus aureus (MRSA) is among some preeminent reported example. Other reported MDR bacteria are -lactamase-producing (ESBL) Klebsiella pneumoniae and Escherichia coli (Blair, et al., 2015), carbapenem-resistant Enterobacteriaceae (CRE) and multidrug Acinetobacter baumannii (MRAB) (Medina and Pieper, 2016).

Figure 1.1: Death attributable to antimicrobial-resistance every year by 2050. Over 4 million deaths are predicted to occur from antimicrobial resistance in different regions situated in Africa and Asia (Review on Antimicrobial Resistance, 2014). 4

1.3 Antibiotic-resistant mechanisms Pathogenic microbes are able to resist specific antibiotics and they do so through mutations in chromosomal genes and by horizontal gene transfer (Blair, et al., 2015). The fundamental resistance of a bacterial species to a certain antibiotic is due to its ability to withstand the effect of that antibiotic as a result of built-in structural or functional characteristics (Blair, et al., 2015). Antibiotic resistance occurs through different molecular mechanisms such as decreased drug permeability, active efflux, alteration or bypass of the drug target, production of antibiotic-modifying enzymes and physiological states such as biofilms that are less susceptible to antibiotic activity (Figure 1.2) (Wright, 2016). By using established high-throughput screens of high-density genome mutant libraries constructed by targeted insertion or random transposons mutagenesis in bacteria such as Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa, many genes encoding for intrinsic resistance to antibiotics of different classes have been determined (Blair, et al., 2015). Below are some major important mechanisms responsible for antibiotic resistance in bacteria.

Figure 1.2: Antibiotic targets and mechanisms of resistance. Target modification, efflux, immunity and bypass, and production of antibiotic modifying enzymes are the major mechanisms of antibiotic-resistance (Wright, 2010).

1.3.1 Decreased drug permeability Gram-negative bacteria are well known to be intrinsically less permeable to numerous antibiotics unlike Gram-positive species as their outer membrane forms a permeability hindrance (Kojima and Nikaido, 2013, Vargiu and Nikaido, 2012). Hydrophilic antibiotics traverse the outer membrane by diffusing through outer-membrane porin proteins (Blair, et al., 2015). Permeability reduction of the outer membrane which restricts the antibiotic entrance into the bacterial cell is attained by the downregulation of porins or by substitution of porins with more-selective channels (Tamber and Hancock, 2003). Several reports have shown that reduction in porin expressions by Enterobacteriaceae, Pseudomonas spp. and Acinetobacter spp. has remarkably contributed towards resistance to newer drugs such as carbapenems and cephalosporins, to which resistance is normally facilitated by enzymatic degradation (Baroud, et al., 2013, Lavigne, et al., 2013, Tamber and Hancock, 2003). For instance, relevant clinical resistance to carbapenems in Enterobacteriaceae can take place due to unavailability of carbapenemase production if mutations reduce porin production or mutant porin alleles are available (Baroud, et al., 2013, Poulou, et al., 2013, Wozniak, et al., 2012). Moreover, several reports have highlighted that K. pneumoniae isolates that demonstrate porin alternates have been linked with clonal lineages that have resulted in global epidemics of infections (Novais, et al., 2012, Papagiannitsis, et al., 2013, Poulou, et al., 2013).

1.3.2 Active efflux Bacterial efflux pumps which function by transferring many antibiotics out of the bacterial cell are known to facilitate intrinsic resistance exhibited by Gram-negative bacteria to numerous drugs often used to treat Gram-positive bacterial infections. Following overexpression, these efflux pumps can present high levels of resistance to antecedent clinically valuable antibiotics (Blair, et al., 2015). Bacteria that are known to overexpress efflux pumps, such as Enterobacteriaceae, P. aeruginosa, and S. aureus have been isolated from patients for over 20 years (Everett, et al., 1996, Kosmidis, et al., 2012, Pumbwe and Piddock, 2000). Some efflux pumps such as the Tet pumps possess limited substrate specificity (Blair, et al., 2015). However, the majority of efflux pumps transport a broad range of structurally different substrates, thus commonly referred to

as multidrug resistance (MDR) efflux pumps (Blair, et al., 2015). For instance, MdeA in Streptococcus mutants, FuaABC in Stenotrophomonas maltophilia, KexD in Klebsiella pneumoniae and LmrS in Staphylococcus aureus (Floyd, et al., 2010, Hu, et al., 2012, Ogawa, et al., 2012). While all bacteria bear several genes that encode MDR efflux pumps on their chromosomes, some have been organized onto plasmids that can transfer between bacteria (Blair, et al., 2015). For example, genes coding for a unique tripartite resistance nodulation division (RND) pump have been uncovered on an IncH1 plasmid that was isolated from a Citrobacter freundii strain that also carried the gene for the antibiotic-target enzyme New Delhi metallo-β- lactamase 1 (NDM1) (Blair, et al., 2015). This is a fretting situation because it shows that, resistance mechanism is transmissible and could be quickly spread to other clinically relevant pathogens (Blair, et al., 2015). The RND family of MDR efflux pumps exist in Gram-negative bacteria and is the most characterized of the clinically relevant MDR efflux transporters. Upon overexpression, RND pumps result in clinically relevant levels of MDR and export an exceptional range of substrates (Piddock, 2006). For instance, multidrug efflux pump AcrB in E.coli and MexB in P.aeruginosa are some of the rigorously studied examples (Blair, et al., 2015).

1.3.3 Alteration or bypass of the drug target Alteration of the target structure that results in inefficient antibiotic binding, but that still allows the target to proceed with its normal function can result in resistance (Blair, et al., 2015). During an infection, a single point mutation in the gene encoding an antibiotic target can confer resistance to antibiotics, thus pathogenic bacterial strains possessing this mutation can grow rapidly (Blair, et al., 2015). Studies have reported that genes that encode drug targets of certain antibiotics usually occur in multiple copies. For instance, linezolid, a novel oxazolidinone antibiotic which has been used for more than 10 years since its introduction into the market targets 23S rRNA ribosomal subunit of Gram-positive bacteria, which is encoded by multiple, identical copies of its gene. Clinical use of linezolid has resulted in resistance in S. pneumonieae and S. aureus by mutations in one of these copies, followed by recombination at high frequency between homologous alleles, which rapidly results in a population carrying the mutant allele (Billal, et al., 2011, Gao, et al., 2010, Leclercq, 2002). Another example of a target change

involves possession of gene homologous to the original target, such as in methicillin- resistant S. aureus (MRSA) in which methicillin resistance is acquired by the acquisition of the staphylococcal cassette chromosome mec (SCCmec) element. This carries the mecA gene, which encodes the β-lactam-insensitive protein PBP2a. This protein permits cell wall biosynthesis despite inhibition of the native PBP by the presence of antibiotic (Katayama, et al., 2000). Numerous SCCmec elements have been located in different Staphylococcus species, and there is proof that the mecA allele has been mobilized several times (Shore, et al., 2011).

Lately, targets protection has been recognized as a clinically relevant mechanism of resistance exhibited by many major antibiotics. For example, the erythromycin ribosome methylase (erm) family of genes methylate 16S rRNA can change the drug-binding site, thus inhibiting the binding of macrolides, lincosamines, and streptogramins (Kumar, et al., 2014). A recent spotted example is a chloramphenicol-florfenicol resistance (cfr) methyltransferase, which methylates A2503 in the 23S rRNA thus conferring resistance to a broad range of drugs with targets near the site such as phenicols, pleuromutilins, streptogramins, lincosamides, and oxazolidonones, including linezolid (Long, et al., 2006). The emr and cfr genes are carried on plasmids and operate as vectors to drive their broad propagation (Leclercq, 2002, Zhang, et al., 2013).

Resistance to aminoglycosides can prevail due to alteration of the target ribosome by methylation. This was not previously perceived as a clinically relevant mechanism of resistance, however, in recent years the enzyme responsible for this type of mechanism have been spotted in varieties of bacterial pathogens. For instance, clinical isolates of Enterobacteriaceae obtained throughout North America, Europe and India, have been found to carry the armA gene, which encodes a methyltransferase, likewise clinical isolates obtained in North America, Central and South America and India have also been found to carry the armA gene which encodes another methyltransferase (Fritsche, et al., 2008, Hidalgo, et al., 2013).

In recent years, shortage of effective antibiotics has resulted to extensive use of last- resort antibiotics such as colistin for treatment of infections caused by multidrug- resistant P. aeruginosa, Accinetobacter spp. and Enterobacteriaceae, thus, leading to the development of polymyxin (colistin) resistance (Blair, et al., 2015). Polymyxin antibiotics

are cyclic antimicrobial peptides characterized with long hydrophobic tails comprising of polymyxin B and polymyxin E and target Gram-negative bacteria (Cai, et al., 2012, Lim, et al., 2010). Antibacterial activity is conferred by the hydrophobic chain which distorts both cell membranes (Kumar, et al., 2014, Wang, et al., 2013). This activity is frequently associated with changes in the expression affecting Lipopolysaccharide (LPS) production, which leads to target alterations thus, reducing the ability of the drug to bind to the target (Blair, et al., 2015). Additionally, colistin resistance can occur due to mutations in the genes encoding the PhoPO two-component system or its regulators through increased expression of the PmrAB system (Cannatelli, et al., 2013, Miller, et al., 2011). This type of resistance mechanism is very common in K. pneumoniae (Cannatelli, et al., 2014).

1.3.4 Production of antibiotic modifying enzymes Production of antibiotic modifying enzymes is a leading mechanism of antibiotic resistance that has been pertinent since the emergence of antibiotics such as penicillinase (a β-lactamase) in 1940 (Abraham and Chain, 1940). Since then, thousands of enzymes capable of degrading and modifying antibiotics of different classes, including -lactams, aminoglycosides, phenicols, and macrolides have been discovered. Nevertheless, certain subclasses of enzymes capable of degrading various antibiotics within the same class have been identified. For instance, the -lactam antibiotics, such as penicillins, cephalosporins, clavams, carbapenems and monobactams, are hydrolyzed by a diverse range of -lactamases (Livermore, 2008, Nordmann, et al., 2011, Woodford, et al., 2011). Antibiotic classes expansion that target inclusion of derivatives of enhanced properties has given rise to the emergence of hydrolytic enzymes with altered spectra of activity. For example, expansion of early -lactamases which were effective against first-generation -lactams resulted in the existence of extended-spectrum -lactamases (ESBLs) with activity against-cephalosporins (Johnson and Woodford, 2013). Gram- negative bacteria such as K. pneumoniae, E. coli, P. aeruginosa and A. baumannii, may carry diverse ESBLs and carbapenemases, such as the IMP (imipenemase), VIM (Verena integrin encoded metallo -lactamase), K. pneumoniae carbapenemase (KPC), OXA (oxacillinase) and NDM enzymes which perpetuate the existence of -lactam antibiotics resistant isolates (Blair, et al., 2015). This poses a serious consequence in the treatment

of hospitalized patients suffering from severe infections (Johnson and Woodford, 2013, Lynch III, et al., 2013, Voulgari, et al., 2013).

The CTX-M14 and CTX-M15 enzymes represent one of the most widely isolated ESBLs worldwide especially in cephalosporin-resistant E. coli and K. pneumoniae isolates. CTX- M15-producing K. pneumoniae isolates and CTX-M15-producing E. coli strains are predominantly nosocomial and community-acquired diseases respectively (Dhanji, et al., 2010, Poirel, et al., 2012, Zhao and Hu, 2013). The use of carbapenem antibiotics in clinical settings has grown over the past decade because of increased numbers of bacteria carrying ESBL genes (Blair, et al., 2015). This has, in turn, resulted in increased numbers of clinical isolates carrying -lactamases with carbapenem-hydrolyzing activity (Queenan and Bush, 2007, Queenan, et al., 2010, Tzouvelekis, et al., 2012). Although it was first detected on the chromosomes of single species, carbapenemase resistances are now plasmid-mediated and have been reported in bacteria such as Enterobacteriaceae, P. aeruginosa and A. baumannii (Tzouvelekis, et al., 2012). Carbapenemases dissemination has occurred through various ways as demonstrated by the kpc and ndm genes. For instance, serine carbapenemase KPC has been reported in several Enterobacteriaceae since it was first reported in K. pneumoniae in 1996 (Deshpande, et al., 2006, Yigit, et al., 2001). The kpc gene is plasmid-borne and is linked to a dominant clone of KPC-producing K. pneumoniae, ST258, which is found worldwide (Qi, et al., 2010). Since it was first reported in India in 2009, the NDM carbapenemase has grown to be one of the most extensive carbapenemases existing in Gram-negative pathogens such as A. baumannii, K. pneumoniae and E. coli throughout the world (Kumarasamy, et al., 2010). The ndm genes frequently occur on broad-host-range conjugative plasmids present in many incompatibility or replicon types, including IncA, IncC, IncF, IncHI1 and IncL-IncM (Giske, et al., 2012, Kumarasamy and Kalyanasundaram, 2011, Walsh, et al., 2011) and in concurrence with other antibiotic-resistance genes (Nordmann, et al., 2011) and are reported to confer resistance to all -lactams except aztreonam.

1.3.5 Antibiotic inactivation by transfer of a chemical group The addition of a chemical group by bacterial enzymes to a vulnerable antibiotic molecule can induce antibiotic resistance by inhibiting the antibiotic from binding to its

target protein because of steric hindrance (Blair, et al., 2015). This type of bacterial resistance involves a large and diverse family of antibiotic-resistance enzymes which can inactivate antibiotics by transfer of chemical groups such as acyl, phosphate, nucleotidyl, and ribitoyl (Wright, 2005). Aminoglycoside antibiotics are exceptionally vulnerable to modification because their molecules are large and have many exposed hydroxyl and amide groups. Aminoglycoside-modifying enzymes confer high resistance levels to antibiotics they modify (Blair, et al., 2015). For instance, a recent worrying incidence is the discovery of a novel genomic island in Campylobacter coli isolated from broiler chickens in China. This genomic island encodes six aminoglycoside-modifying enzymes, comprising members of all three classes and confers resistance to diverse aminoglycoside antibiotics often used to treat Campylobacter infections including gentamicin (Qin, et al., 2012).

Mechanistic and structural understanding of bacterial resistance offers much better opportunities for tackling antibiotic resistance problem because it allows the origin of the problem to be addressed rather than simply generating additional resistance in the future (Chellat, et al., 2016). Owing to the discovery gap during the last decades for novel antibiotics chemotherapies in the pharmaceutical industry and the occurrence of bacterial strains resistant to the current antibiotics, public health is running out of treatment options for dealing with infectious diseases. To respond to this emerging crisis, global organizations such as The World Health Organisation (WHO) have urged the scientific community to search for new approaches to combat antibiotic resistance. A lot of the research for new antibiotics is still focused on developing improved versions of existing molecules. Screening for novel antibiotics from natural sources enables to broaden the possibilities for treating infections. However, this approach does not eliminate the intrinsic risk for the initiation of resistance to these novel antibiotics (Chellat, et al., 2016).

1.4 Bacteriophages Viruses are the most widely distributed biological entities on earth (Suttle, 2005), with an estimate of 1031 virus-like particles in the biosphere most of which are bacteriophages

(McAuliffe, et al., 2007). Environmental viruses are indisputably the largest genetic diversity pool on the planet (Hambly and Suttle, 2005). Virus particles are ecologically significant as they shape microbial communities, cause the lysis of a large part of the ocean biomass on a daily basis, transfer genetic material among host organisms, and shunt nutrients between particulate and dissolved phases (Hambly and Suttle, 2005). Bacteriophages, widely known as phages (Greek “Phagein” meaning “to eat”) are viruses that specifically infect and lyse bacteria (Matsuzaki, et al., 2005, Sharma, et al., 2017). Bacteriophages can be obtained in all environments on earth, ranging from soil, sediments, water (both river and sea water) and in/on living or dead plants and animals (Elbreki, et al., 2014). In fact, they can be isolated from any material that sustains bacterial growth. For instance, many terrestrial ecosystem have been reported to contain 107 bacteriophages per gram of soil (Parisien, et al., 2008, Pedulla, et al., 2003) whereas, sewage is widely known to contain 108-1010 phage per millilitre (Dabrowska, et al., 2005, Dublanchet and Bourne, 2007). Phages just like all viruses are absolute parasites. Even though they carry all the information necessary in directing their own reproduction in a suitable bacterial host, they lack machinery for energy and protein production (Goldman and Green, 2015).

1.4.1 Bacteriophage structure and classification Bacteriophages (Figure 1.3a) are small viruses of about 20-200 nm in size and may differ greatly in size, shape, capsid symmetry and structure (Criscuolo, et al., 2017). A phage is made up of a nucleic acid genome encapsulated by a protein coat (capsid) and may contain lipids in the particle wall or in the envelope (Ackermann, 2006). Phage capsids may exhibit different morphologies extending from small hexagonal structures to filaments, or highly complex structures comprising a head and a tail (Melo, et al., 2017). Bacteriophage genome may vary from as few as 5 kb (e.g. Phage phiX174) to as many as 500 kb such as in Bacillus Bacteriophage G, the phage presenting the biggest known genome. Phages are regarded as metabolically inert particles due to the absence of necessary machinery for energy production or ribosomes for protein synthesis. Thus, phages depend on their hosts to produce progeny and their genome is devoted to directing the host for that function (Guttman, et al., 2005).

Figure 1.3: A generalized structure of a tailed phage (left) and electron micrograph images of the three families of tailed dsDNA phages that infect bacteria (right). a Myoviruses generally isolated from natural marine viral communities. They have distinguishing contractile tails, are typically lytic and frequently exhibit broad host ranges. b, Podoviruses possess a non-contractile tail, are typically lytic, have narrow host ranges and are less frequently isolated from seawater. c, Siphoviruses possess long non-contractile tails, they are often isolated from seawater, in most cases exhibit broad host range, and most of them can integrate into the host genome (Elbreki, et al., 2014, Suttle, 2005).

In most cases phages genetic material is carried in double-stranded DNA (dsDNA) and sometimes as single-stranded DNA (ssDNA), single-stranded RNA (ssRNA) or rarely as double-stranded RNA (dsRNA) (Melo, et al., 2017). Over the years, sophisticated phage classification system has been drawn up by the International Committee on Taxonomy of Viruses (ICTV) to account for the diversity. The ICTV has classified phages as one major order, 13 families, and 31 genera based on nucleic acid content, morphology, and genomic data. It is estimated that about 96% of all studied phages have tailed morphology and belong to three families, the Myoviridae (tail contractile), Siphoviridae (tail long and non-contractile) and Podoviridae (tail short) as shown in Figure 1.3b (Ackermann and Prangishvili, 2012, Klumpp, et al., 2010). These families comprise the order Caudovirales (Maniloff and Ackermann, 1998). Studies have reported most therapeutic phages to be tailed. However, some cubic phages (X174 and Q) (Bernhardt, et al., 2000, Bernhardt, et al., 2001) or filamentous phages (M13 and Pf3) (Matsuzaki, et al., 2005) have also been used. The remaining 4% comprises of tailless phages with varying structures: polyhedral (with either icosahedral or cubic symmetry),

pleomorphic (asymmetric e.g. shaped like a lemon or a droplet) and filamentous with a long and a thin morphology (Ackermann, 2003, Maniloff and Ackermann, 1998).

1.4.2 Bacteriophage replication cycles Bacteriophages are obligate parasites that can sustain two separate life cycles, lytic or lysogenic and can be defined by their genetics and interaction with the bacterial host (Feiner, et al., 2015, Ptashne, 2004). Distinctive receptors such as lipopolysaccharides, teichoic acids, proteins and flagella present on the top of the host bacteria are essential for the phage to infect bacteria (Sharma, et al., 2017). Owing to this specificity, phages can only infect specific hosts (Sharma, et al., 2017). Phage genome excision and integration are crucial steps in the onsite of the lytic and lysogenic cycles respectively. These events are mediated by phage-encoded DNA recombinases, such as integrases and excisionases, and take place at a specific attachment site in the bacterial genome (attB) which is identical to attachment site (attP) in the phage genome (Feiner, et al., 2015). Although the sequences select the phage specificity to the bacterial genome, secondary sites can also be utilised in the absence of original attB site. Additionally, some phages integrate randomly (e.g. phage Mu) within their host genome thus expanding variation and possible mutations within the bacterial population (Harshey, 2012). The first contact between a phage and its host occurs by random collision, given the cell carries specific receptors on its surface. This usually occurs between the receptor molecules of the host (e.g. teichoic acid in Gram-positive or lipopolysaccharide in Gram- negatives) and distinctive phage proteins located at the tip of the tail fibre, or at one end of a filamentous phage (Elbreki, et al., 2014). Phage attachment on the bacteria- host surface is influenced by different factors such as bacteria type (Gram-negative and Gram-positive), growth conditions, and virulence (Rakhuba, et al., 2010). Following adsorption, phage DNA is injected into the bacterial cytoplasm after a phage has firmly and irreversibly adsorbed to the cell surface (Lengeler, et al., 1999). Due to their propagation cycle, most phages can be broadly branched into two major groups: virulent and temperate (Figure 1.4).

Figure 1.4. Schematic diagram showing lytic, lysogenic and pseudolysogenic cycles of a bacteriophage. (a) Lytic phages enter a productive cycle, whereby the phage genome is replicated, and phage capsid and tail proteins are manufactured by utilizing bacterial cell machinery. This is followed by packaging of the phage genome into progeny phage particles which are released through bacterial lysis (b) Temperate phages enter a lysogenic cycle, in which the phage genome is integrated into the bacterial chromosome (prophage). Prophages can either get replicated together with the bacterial host chromosome during host cell replication or switch into lytic production due to DNA damage. (c) Pseudolysogeny is an unstable state whereby the phage genome fails to replicate or become established as a prophage due to nutrient-deprived circumstances. In this state, the phage genome exists as a non-integrated preprophage for a considerable time, resembling an episome, until the nutritional status is re-established and the phage can then enter an either a lysogenic or lytic life cycle (Feiner, et al., 2015).

Virulent phages straightaway redirect the host metabolism into the production of new phage virions which are released upon cell death within several minutes to hours following the initial phage attachment process (Elbreki, et al., 2014). This is often referred to as lytic cycle (Figure 1.5). Briefly, following phage DNA injection into the bacterial host, the DNA is replicated, and multiple copies of synthesized DNA are taken into the capsid, which is constructed de novo during the late stage of phage infection. Progeny phage particles are finalized by the attachment of a tail to the DNA-filled head (Matsuzaki, et al., 2005). The progeny phages are eventually liberated by the coordinated action of two proteins, holing and endolysin (Lysin) coded by the phage genome. Lysin is a peptidoglycan-degrading enzyme (peptidoglycan hydrolase). Holin proteins form a “hole” in the cell membrane, allowing lysin to reach the outer peptidoglycan layers (Wang, et al., 2000). The released descendant phages infect neighboring bacteria in a speedy manner. Virulent phage infection results in clear plaques on the lawns of the respective bacterial host (Elbreki, et al., 2014).

By contrast, temperate phages enter a lysogenic cycle, in which the phage genome is integrated into the bacterial chromosome (forming a prophage) and remain in a state called latent or dormant which does not promote cell death or production of phage particles (Figure 1.4) (Feiner, et al., 2015). Some prophages, however, remain as a low copy number plasmids and do not integrate into the bacterial chromosome (Edlin, et al., 1977, Ravin, et al., 2000). Prophages are replicated together with the bacterial host chromosome, and this lysogenic condition is sustained by the repression of the phage lytic genes. A switch to lytic production begins when stressful conditions such as DNA damage prompt the excision of the phage genome, which is followed by the expression of lytic genes that promote DNA replication, phage assembly, DNA packaging and bacterial lysis (Feiner, et al., 2015). Another documented but largely unexplored phage life cycle is pseudolysogeny (Feiner, et al., 2015). Pseudolysogeny is a phase of stalled development of a bacteriophage in the host cell, in which neither multiplication of the phage genome nor replication synchronized with the cell cycle and stable maintenance in the cell line, which proceeds with no viral genome degradation thus allowing the subsequent restart and resumption of virus development (Łoś and Węgrzyn, 2012).

Figure 1.5: Phage bacteriolytic life cycle. Scanning electron microscopy of Acinetobacter baumannii bacterial cell (false color) being lysed by phage vB-GEC_Ab-M-G7 during an infection. Cell lysis can take place within minutes to hours depending on each phage and metabolic status of the bacterium (Roach and Debarbieux, 2017).

Generally, pseudolysogeny itself is a nonreproductive stage. In this stage, the viral genome may be maintained for a potentially long period of time and is sometimes called “preprophage” (Miller and Ripp, 2002). This phenomenon occurs because of unfavorable growth conditions such as starvation occurring to the host cell and is often terminated with the instigation of either true lysogenization or lytic growth when the growth conditions are restored (Łoś and Węgrzyn, 2012). Pseudolysogeny has been postulated to play a crucial role in phage-bacteria interaction in water environments due to lower concentrations of nutrients and seasonal variability. Additionally, Ripp and Miller (1997) have demonstrated the importance of pseudolysogeny in maintaining the presence of phages for a prolonged time in natural ecosystems.

1.5 Phage therapy, biocontrol, and its advantages Phage therapy refers to the application of bacteria-specific viruses with the aim of minimizing or eradicating pathogenic bacteria (Kutter, et al., 2010). Phage biocontrol refers to the non-therapeutic antibacterial application of phages. More broadly, phages have been employed as biocontrol agents, reducing bacterial loads in foods, e.g., such as of Listeria monocytogenes in food processing (Bai, et al., 2016), of zoonotic pathogens in food animals (Atterbury, 2009) or in the treatment of plant pathogenic bacteria (Jones, et al., 2007). While phage therapy has become a predominantly pertinent technology especially in veterinary, agriculture, and food microbiology applications, it is for the treatment or prophylaxis of human infections that phage therapy first captured the world’s attention (Kutter, et al., 2010). There has been a compelling need for new, safe, effective and selectively non-toxic antibacterial agents, especially in the face of the antibiotic resistance crisis (Aminov, 2010). Phages and their products thus present one of the largest untapped resources of antibacterial agents (Abedon, et al., 2017). Phages have several characteristics that make them attractive therapeutic and biocontrol agents (Jassim and Limoges, 2017). Advantages of phages as therapeutic and biocontrol agents can be drafted based on their properties as listed below:

1.5.1 Bactericidal capacity Bacteriophages in contrast to antibiotics are bactericidal because after successfully infecting bacterial cells, they are incapable of gaining their viability. In contrast to this, antibiotics such as tetracycline are termed bacteriostatic because they can readily allow bacterial evolution towards resistance (Loc-Carrillo and Abedon, 2011).

1.5.2 Self-replicating pharmaceuticals Unlike antibiotics, phages increase in number specifically where their hosts are present during the bacteria-killing process. However, limitations such as their relatively high dependence on bacterial concentration may occur (Loc-Carrillo and Abedon, 2011). This means bacteriophages low number can be pragmatic, they will amplify and persist until the infection is eradicated or minimized to a point that the host immune system can clear the infection (Clark, 2015). The kinetics of phage action is advantageous when compared with antibiotics because the effects can be achieved with small doses (Payne

and Jansen, 2001). The downside of this is that the pharmacokinetics of phage therapy varies from that of antibiotic, and is more complex than that of antibiotic (Clark, 2015).

1.5.3 Specificity Bacteriophages are very specific to their bacterial hosts and frequently they target strains or subtypes of bacteria (Hyman and Abedon, 2010). This phenomenon is advantageous because phages can eliminate specific undesired bacterial strains while leaving the rest of the microflora undisturbed (Skurnik, et al., 2007). As a result, phages have been suggested as probiotic supplements particularly targeting bacteria which cause an imbalance in the gut such as Clostridium difficile, at the same time sparing the normal gut microflora (Rea, et al., 2013). However, in many real-world situations, phage specificity is a disadvantage because, in most human infections, the agent causing disease is not known (Clark, 2015). This is not an issue with relatively broad spectrum small-molecule antibiotics but in the case of phages, it warrants the use of cocktails which increases the complexity and cost of production (Clark, 2015, Kelly, et al., 2011).

1.5.4 Narrow potential for inducing bacterial resistance The relatively strict host range displayed by most phages restricts the number of bacterial types with which selection for specific phage-resistance mechanisms can arise (Hyman and Abedon, 2010). This is the reverse when chemical antibiotics are employed, as a considerable fraction of bacteria may be affected (Carlton, 1999). Moreover, some mutations that arise due to resistance, negatively influence bacterial fitness or virulence due to loss of pathogenicity-related receptors (Capparelli, et al., 2010, Skurnik and Strauch, 2006). Nevertheless, phages lack cross-resistance with antibiotics. Bacteriophages infect and kill their hosts using mechanisms dissimilar from those of antibiotics (Carlton, 1999, Loc-Carrillo and Abedon, 2011), thus, specific antibiotic resistant mechanisms cannot be transcribed into mechanisms of phage resistance (Lobocka, et al., 2014, Weber-Dąbrowska, et al., 2014). Therefore, bacteriophages can be utilized for curing antibiotic-resistant diseases such as those triggered by multi-drug resistant Staphylococcus aureus (Gupta and Prasad, 2011, Mann, 2008).

1.5.5 Rapid discovery This advantage comes from ubiquity and diversity of bacteriophages. Bacteriophages targeting many pathogenic bacteria can be easily isolated from different sources such as sewage or waste materials comprising high bacterial concentrations (Loc-Carrillo and Abedon, 2011). Thus, although bacteria can easily mutate to phage resistance, the natural environment can supply numerous phage substitutes differing in host range to attack a variety of bacterial infections. These phages may be applied in cocktails so that phage-resistant is challenged right from the start of the therapy (Goodridge and Abedon, 2003).

1.5.6 Safety and immunogenicity One element that seems reliable throughout the history of phage therapy is their safety as opposed to most antibiotics (Kutter, et al., 2010). It has been reported that phages are normally highly tolerated by humans who are constantly exposed to immense numbers of phages as part of their natural ecosystem (Clark, 2015). For instance, Miedzybrodzki, et al. (2012) has reported on the therapeutic use of phages in 153 patients in a study which covered rigorous safety data. The only reported adverse effect has been a relatively minor side effect, possibly due to endotoxin (and other super- antigens) from lysed bacteria, either those delivered in the crude phage preparations used or released in vivo by the destruction of the host phage replication (Clark, 2015). The high specificity displayed by phages signifies that they do not actively interact with human cells. However, phages do interact non-specifically with human cells, as the immune system regards phages as inert virus-like particles (Merril, et al., 2003). Many phages are reported to be immunogenic and can stimulate strong cellular (Keller and Engley, 1958) and humoral (Clark and March 2006, Clark, et al., 2002) immune responses. Although such immune responses do not affect the safety of phage products, they can affect the effectiveness of the treatment. Phages administered systemically can be cleared up by the immune response before any therapeutic effect occurs (Kutter, 2008). As a result, the first target for many phage applications is normally topical (Abedon, et al., 2011, Górski, et al., 2009). However, it has been suggested that, if conditions are optimized, phages can be applied systemically (Ryan, et al., 2011). Additionally, phages can be administered orally, after which they traverse the gut barrier

and enter circulation. For instance, in a study reported by (Sarker, et al., 2012), a cocktail of nine phages specific for E.coli (at up to 3 x 109 phages per dose ) was delivered to healthy participants with no observed side effects.

1.5.7 Single dose potential Single dose application relies on the phage’s ability to replicate, thus achieving an ‘active’ therapy. This situation is often regarded as phage amplification through auto ‘dosing” and culminate in substantial bacterial killing (Abedon and Thomas-Abedon, 2010, Capparelli, et al., 2010). Therefore, achieving efficacy following only a single dose, or far less frequent dosing, is clearly unnecessary. However, in many or most occasions, a single dose of phages is usually insufficient to achieve the desired efficacy (Capparelli, et al., 2010). Nevertheless, the ability of phages to replicate in situ and increase in density, given sufficient bacteria are present, could significantly minimize the treatment cost by reducing phage dose sufficient to achieve efficacy (Loc-Carrillo and Abedon, 2011).

1.5.8 Minimal environmental impact and relatively low cost Phages are predominantly composed of nucleic acids and proteins and usually exhibit narrow host ranges (Abedon and Thomas-Abedon, 2010). Unlike broad-spectrum antibiotics, discarded therapeutic phages will at worst affect only a small subset of environmental bacteria (Ding and He, 2010, Hyman and Abedon, 2010). In addition, phages that cannot tolerate degradative environmental factors such as sunlight, desiccation, or extreme temperature will be rapidly inactivated (Loc-Carrillo and Abedon, 2011). Phage production generally involves a combination of host growth and subsequent purification (Gill and Hyman, 2010). The cost of growing bacterial hosts differs depending on the species, whereas the cost of purifying the bacteria gets cheaper as the technology advances (Kramberger, et al., 2010). Generally, the cost of production per unit (Kutter, et al., 2010) are not out of line with the costs of pharmaceutical products while the cost of discovery and characterization can be relatively low (Skurnik, et al., 2007).

1.5.9 Biofilm clearance Bacteria which persist as biofilms tend to be intrinsically more resistant to antibiotics as the matrix physically restrict the entrance of the chemical to the target (Stewart and Costerton, 2001), along with other factors, such as ‘persister’ cells, where phenotypic drug tolerance occurs in a subpopulation of bacteria (Clark, 2015). Phages, unlike antibiotics, can naturally disrupt bacterial biofilms through various mechanisms such as through enzymes linked to the bacteriophage capsid, by carrying genes encoding biofilm degrading enzymes in their genomes or by upregulating genes in the target bacteria that make biofilm degrading enzymes (Abedon, 2011).

1.6 History of phage therapy The history of bacteriophage discovery has been a matter of prolonged debates and arguments over claims for priority for many decades (Sandeep, 2006, Skurnik and Strauch, 2006, Sulakvelidze, et al., 2001). Ernest Hankin, a British bacteriologist, reported in 1896 on the existence of antibacterial activity against Vibrio cholera in the waters of the Ganges and Jumna rivers in India. He proposed that the unknown substance capable of passing through the fine porcelain filters, and sensitive to heat was responsible for this phenomenon and for regulating the dissemination of cholera outbreaks (Sulakvelidze, et al., 2001). Two years later, Nikolay Fyodorovich Gamaleya noticed the same phenomenon while working with Bacillus subtilis. In 1915, Frederick Twort (a medically trained bacteriologist from England) re-introduced this matter advancing the hypothesis that such antibacterial activity could be due to a virus (Hermoso, et al., 2007). Due to several limitations encountered, such as financial difficulties (Summers, 1999, Twort, 1915), Twort did not take up this discovery, and it was another two years before bacteriophages were “officially” discovered by Felix d’Herelle, a French-Canadian microbiologist at the Institut Pasteur in Paris (Sulakvelidze, et al., 2001). Felix d’Herelle suggested this incident could have been by a virus competent at parasitizing bacteria and named the virus ‘bacteriophage’, a word that is derived from the fusion of ‘bacteria’ and ‘phagein’ (to eat in Greek) (Hermoso, et al., 2007). The first trial involving the therapeutic use of phages was accomplished by d’Herelle in 1919 where he used phages to tackle acute hemorrhagic dysentery despite

his phage phenomenon observation in 1910 while learning microbiologic means of regulating an epizootic of locusts in Mexico (Hermoso, et al., 2007, Sulakvelidze, et al., 2001). However, the first reported utilization of phages to treat infectious diseases in humans came in 1921 from Richard Bruynoghe and Joseph Maisin, who employed bacteriophages to treat staphylococcal skin disease. In 1930, various companies began the commercialization of phages targeting various bacterial pathogens while at the same time d’Herelle and other scientists continued advancing the study of phage therapy. During this same time, d’Herelle established phage therapy centers in various countries including the US, France, and Georgia (Hermoso, et al., 2007). During World War II the German and Soviet armies utilized phages to treat dysentery, and the US army conducted classified research on it (Hermoso, et al., 2007). Additionally, some practitioners employed phages as therapeutic agents in the West, from the 1920s to the early 1950s. This was considered as the ‘historic era’ for phage therapy. However, phage therapy was widely deserted shortly after the establishment of antibiotics in the 1940s and thus from 1950s to 1980s few data were published on this topic. Research focusing of the therapeutic use of phages has been somewhat abandoned in the West ever since until the past two decades when the growing incidence of antibiotic-resistant bacteria revived the interest in phage therapy (Hermoso, et al., 2007).

1.7 Early therapeutic applications of phages The first documented phage therapy research was a study conducted in Belgium by Bruynoghe and Maisin in 1921, describing the treatment of staphylococcal skin furuncles in human patients (Chhibber and Kumari, 2012). In this report, phages were administered to six patients by injecting the phage preparation close to the base of cutaneous boils (furuncles and carbuncles). This prompted recovery accompanied with reduction of pain, swelling and fever within 48 hours of treatment. A substantial amount of publications detailing phage treatment of typhoid fever, Shigella and Salmonella spp related colitis, peritonitis, skin infections, surgical infections, septicaemia, urinary tract infections and otolaryngology infections (Wittebole, et al., 2014) were also published in the 1930s in the journal of La Médicine (Abedon, et al., 2011, Wittebole, et al., 2014). Early, commercial production of phages was achieved by D’Herelle’s commercial

Laboratory in Paris, the Hirszfeld Institute of Immunology and Experimental Therapy (HIIET), Poland (founded in 1952), the Eliava Institute (EIBMV) in Tbilisi, Georgia (founded in 1923 by Giorgi Eliava and Felix d’Herelle) and companies such as Eli Lilly Company (Indianapolis, Ind.) (Sulakvelidze, et al., 2001). D’Herelle’s commercial laboratory in Paris produced at least five phage preparations such as Bacte-coli-phage, Bacte-rhinophage, Bacte-intestine-phage, Bacte-pyo-phage, and Bacte-staphy- phage targeting different bacterial infections. These phage preparations were marketed by the famous large French company L’Ore´al (Sharma, et al., 2017). In the United States, therapeutic phages were manufactured by the Eli Lilly Company (Indianapolis, Ind.) in the 1940s. These preparations comprised of seven phage products for human use against an array of pathogenic bacteria, such as staphylococci, streptococci and Escherichia coli. The preparations included phage-lysed, bacteriologically sterile broth cultures of the targeted bacteria or the same preparations in a water-soluble jelly base and aimed at treating various infections including abscesses, festered wounds, vaginitis, acute and chronic infections of the upper respiratory tract, and mastoid infections (Sulakvelidze, et al., 2001). Nevertheless, the effectiveness of phage preparations was contentious and with the emergence of antibiotics, commercial manufacturing of therapeutic phages was discontinued in most parts of the Western world (Eaton and Bayne-Jones, 1934, Krueger and Scribner, 1941).

The Eliava Institute (EIBMV) was regarded as one of the largest facilities involved in the generation of therapeutic phage preparations in the world. This institute developed phage preparations targeting a dozen of bacterial pathogens covering staphylococci, pseudomonas, proteus and many enteric pathogens (Sulakvelidze, et al., 2001). The Hirszfeld Institute of Immunology and Experimental Therapy (HIIET) phage laboratory was actively involved in expansion and production of phages for the treatment of septicaemia, furunculosis, and pulmonary and urinary tract infections and for the prophylaxis or treatment of postoperative and post-traumatic infections (Sulakvelidze, et al., 2001).

Figure 1.6. Ancient phage preparations. These preparations consisted of Monophages (targeted Staphylococcal, Streptococcal, E. coli, Pseudomonas, Dysentrial, and Typhoid), Poly- phages (Pyo and Intesti), Sera (targeted diphtheria, tetanus, gangrene, scarlet fever, meningococcus) and for identification of Salmonella and Shigella (Kutateladze and Adamia, 2008).

One of the most extensive phage therapy studies was the one carried out in Tbilisi, Georgia during 1963 and 1964 and focused on the application of therapeutic phages for prevention of bacterial dysentery (Babalova, et al., 1968). Likewise, Smith and Huggins revitalized phage therapy studies in the west in the 1980s. They reported successful results on therapeutic use of phages against systemic infections and enteritis in mice, calves, pigs and lambs (Smith and Huggins, 1983, Smith, et al., 1987, Smith, et al., 1987) even demonstrating the superiority of phage therapy against antibiotics in a mouse model of E. coli infection (Smith and Huggins, 1982). In recent years, the emergence of multi-drug resistant pathogens combined with the discouragingly low-rate production of clinically useful antibiotics has prompted a re-examination of bacteriophage therapy, with work being carried out to modern regulatory standards. Furthermore, the

emergence of high-throughput sequencing technology has encouraged on-going advancements in bacteriophage therapeutics and other uses (Monk, et al., 2010, Rohwer and Edwards, 2002).

1.8 Recent applications of phages in biocontrol and therapeutics Phages have proven extremely powerful at eradicating various bacterial diseases in controlled animal studies, particularly as a biocontrol agent in the elimination of food- borne diseases, owing to factors such as its target specificity, rapid bacterial killing and self-replicating potential (Jassim and Limoges, 2014). Furthermore, the capability of bacteriophage to reproduce at the infection site or whenever the bacterial host is present and their nonexistence in sterile areas guarantee an optimal self-adjusting dose of bacteriophages which is not common especially in non-biological modes of antimicrobial agents (Mizoguchi, et al., 2003). These features have thus enabled phage therapy and phage biocontrol grow into a predominantly applicable technology in veterinary, agricultural, and food microbiology applications (Jassim and Limoges, 2014).

1.8.1 Human pathogens treatment For many years since the introduction of phage therapy as a viable treatment of pathogenic bacteria in Eastern Europe, numerous studies have been conducted to evaluate the efficacy and safety of phage therapy including clinical experience (Chanishvili, 2012, Kutter, et al., 2010, Sulakvelidze, et al., 2001). However, these trials did not follow current Western rigorous standards (Barbu, et al., 2016). This rose many questions regarding the safety of phage therapy. For this reason, phage therapy clinical trials have focused on safety rather than efficacy, resolving some of these safety concerns (Vandenheuvel, et al., 2015). The first reported double-blind, randomized, placebo-controlled phase I trial to show the safety of phage treatment was performed by Nestle Research Center (Lausanne, Switzerland) (Bruttin and Brüssow, 2005). In this trial, it was reported that there were no significant side effects following administration of phage. In addition, the results showed that oral administration of T4 did not disturb the natural gut E. coli population. Subsequent studies were carried out to investigate

the metagenomic analysis of the entire anti-diarrheagenic phage collection to determine the clinical risk of a subset of phages following oral administration in healthy adults (Sarker, et al., 2012).

The first controlled phage therapy clinical trial occurred in 2009. This trial reported efficacy and safety in chronic otitis caused by antibiotic-resistant Pseudomonas aeruginosa following treatment with a therapeutic phage cocktail (Biophage-PA, Biocontrol, UK) (Wright, et al., 2009). A year later, during an assessment of treatment of chronic otitis infections in dogs using phages, the outcomes validated that topical administration of the phage combination resulted to lysis of P. aeruginosa in the ear without apparent toxicity and proved to be an appropriate and efficacious treatment against P. aeruginosa otitis (Hawkins, et al., 2010, Jassim and Limoges, 2014). The first FDA-approved phase I clinical phage trial was performed in 2007 at Southwest Reginal Wound Care Center in Lubbock, Texas. This trial aimed at evaluating the local administration of a small set of well-characterized phage in patients with chronic venous leg ulcers (Rhoads, et al., 2009). The study revealed that topical phage administration showed no safety concerns but at the same time did not affect wound healing. Although efficacy was outside the scope of the clinical trial, no significant results were obtained. The first fully regulated, placebo-controlled, double-blind, randomized phase II clinical trial of the efficacy of a bacteriophage therapeutic was completed in 2007 and reported a successful outcome against long-term infections with P. aeruginosa, despite using only a single dose of input bacteriophages in the nanogram range (Wright, et al., 2009). This trial supports the prediction that successful bacteriophage infection will lead to therapeutically useful replication of the therapeutic agent if susceptible host bacteria are present at the site of application (Monk, et al., 2010). Recently, Zhvania, et al. (2017), have demonstrated a successful treatment of a 16-years old male with Netherton syndrome (NS) (antibiotic resistant chronic Staphylococcus aureus skin infection) accompanied with an allergy to multiple groups of antibiotics, with several anti- staphylococcal phage preparations conducted at Eliava Phage Therapy Center. A massive improvement and substantial changes in his symptoms and quality of life were observed following a six months treatment.

Powerful supporting data on the potential for phage therapy has also been obtained from animal models (Monk, et al., 2010). Many animal models of infections have been utilized to study phages as prospective therapeutics, especially in the context of antibiotic-resistant infections affecting humans. These animal models serve as an essential bridge between in-vitro and clinical studies (Kusradze, et al., 2016). A significant number of bacteriophage therapy studies in animals have concentrated on respiratory infections, gastrointestinal infections and infections of skin and wounds (Malik, et al., 2017). For example, Debarbieux, et al. (2010) utilized a mouse lung infection model targeting P. aeruginosa. Both bacterial challenge and phage treatment were performed via intranasal instillation. Reported phage doses were 108 per animal treatment and 100-fold lower phage doses were found to be insufficient in preventing death. Following bacterial densities measurement via bioluminescence, treatment success in preventing lethality was found to diminish from 100% survival at 72 hr given a 2-hr delay in phage treatment to 75% survival given 4-hr delays and then to 25% survival given 6-hr delays in phage installations. Pre-treatment with phages 24-hr prior to bacteria challenge resulted in 100% survival. Phage therapy studies with animals has shown that in certain instances, it may help in reducing the densities of the infecting bacterial populations to levels that may allow the immune response to mount a successful defence to clear the infection (Alemayehu, et al., 2012, Debarbieux, et al., 2010, Smith and Huggins, 1982).

Despite the long history of successful use, phage therapy has not yet managed to re- enter Western medicine as a viable available treatment option due to a lack of randomized controlled trials, quintessential in the age of evidence-based medicine (Zhvania, et al., 2017). Safety concerns about the use of phages in human medicine have also been a major hurdle to the phage therapy development in the Western world, despite the fact that phage preparations have been commercially available in Russia and Georgia for decades (Vandenheuvel, et al., 2015). An example of a successful commercially available product is Pyo Bacteriophagum (Figure 1.7), a phage cocktail developed by the Eliava Institute in Georgia, which targets bacteria strains such as Staphylococcus aureus, Escherichia coli, Streptococcus spp., Pseudomonas aeruginosa, Proteus spp. (Aminov, et al., 2017). In addition, clinical use of phage therapy is reported

to be faced with long product development and approval timelines in Western regulatory frameworks. Due to this, many companies and researchers have instead undertaken applications focusing on food safety, agricultural, industrial, and clinical diagnostics (Lu and Koeris, 2011).

Figure 1.7. Bacteriophage drug produced by Eliava Biopreparations. A phage cocktail targeting Staphylococcus aureus, Escherichia coli, Streptococcus spp., Pseudomonas aeruginosa, Proteus spp. (Aminov, et al., 2017).

1.8.2 Sanitation Phage application for disinfection has been conducted in Georgia to disinfect operating rooms and medical apparatus as a preventive measure against nosocomial infections (Kutter, 2008). A complementary approach suggested by Novolytics company involves the use of a gel containing a phage cocktail targeting MRSA to treat nasal carriage of MRSA, thus greatly minimizing the prevalence and spread of MRSA (Abedon, et al., 2011). Elimination of S. aureus via experimental hand cleansing with phage-containing Ringers solution has also been reported. In this study, roughly 100-fold reduction in bacterial concentrations was detected after hand cleansing with a solution containing 108 phages/mL when compared with a phage-less control solution (O'flaherty, et al.,

2005). Different natural and man-made environments such as medical devices, dental plaques, water pipes, industrial and food processing settings may be colonized with microorganisms, causing microbial biofilm development (Kolter and Greenberg, 2006). Biofilms refer to surface-related communities encased in hydrated extracellular polymeric substances (EPS) matrix that is made up of polysaccharides, proteins, nucleic acids, and lipids and assists in maintaining a complex heterogeneous structure (Lu and Collins, 2007).

Biofilm-associated organisms especially those colonizing medical devices are resistant to antimicrobial agents, can escape the host immune system, and can behave as a nidus for infection (Donlan and Costerton, 2002). Hence, device-related infections, such as catheter-associated bloodstream infections, culminate in high morbidity and mortality among certain patients in populations (O'grady, et al., 2002). Bacteriophages among other novel action plans have been suggested to counteract device-associated biofilms either by reducing microbial attachment to the device or by targeting the biofilm following its development (Fu, et al., 2010). For example, Curtin and Donlan (2006) showed that a bacteriophage active against Staphylococcus epidermidis could be integrated into a hydrogel coating on a catheter result in significant reduction in biofilm formation by this bacteria in an in-vitro model system. Additionally, Sillankorva, et al. (2004), showed that, phage S1 was capable of reducing Pseudomonas fluorescens biofilm biomass by 85%. The biofilms tackled with phage S1 proved more efficient at controlling the bacteria in comparison to traditional chemical biocides.

1.8.3 Probiotics Due to high specificity, bacteriophages are regarded as unique tools for manipulating the bacteria microflora composition of the gastrointestinal (GI) tract in a clearly defined manner as opposed to other probiotic organisms or other antibacterial agents. Additionally, bacteriophages deliver a novel, safe and effective method for controlling the GI tract’s microflora (Abedon, et al., 2011). While probiotic bacterial formulations introduce non-pathogenic bacteria to disrupt the ability of pathogenic bacteria to colonize the GI tract, phage-based probiotics aid the GI tract balance by targeting specific pathogenic bacteria (Abedon, et al., 2011). Phage probiotics have been

suggested as the most effective method to effectively control bacterial pathogens such as Salmonella spp., Clostridium difficile, diarrheagenic E. coli and other bacteria with oral entryway and demand short or long-term colonization of the GI tract to generate a disease (Abedon, et al., 2011). The George Eliava Institute of Bacteriophages, Microbiology, and Virology have formulated ‘Instestiphage’, a potential phage probiotic among other phage therapies for human consumption (Nicastro, et al., 2016). Additionally, IntraLytix company is currently developing ‘ShigActive’, a phage probiotic that targets Shigella species in the gastrointestinal tract.

1.8.4 Food safety Bacterial pathogens control present on fresh fruits, vegetables and ready to eat foods is of utmost concern because these foods do not always go through further processing or cooking that would destroy bacterial pathogens prior to consumption (O'Flaherty, et al., 2009). The continuous rise in food-borne diseases due to pathogens such as Salmonella, Campylobacter, Escherichia coli and Listeria (Chibeu, 2013) which are associated with grave gastrointestinal infections has prompted interest to seek for alternative and effective technologies aiming at inactivating bacteria in food (Endersen, et al., 2014, Team, 2012). A necessity that needs to be presented by any of these new approaches is that it should be safe for humans, animals, and the environment while maintaining the nutritional value and the organoleptic properties of the final product (Rodríguez-Rubio, et al., 2016). Nonetheless, containing bacteria can also gain access to food throughout different stages of production such as slaughtering, milking, fermentation, processing, storage, and packaging. Thus, these new alternative technologies need to be employed throughout the entire food chain (farm to fork) (Rodríguez-Rubio, et al., 2016).

Phages have been suggested as natural substitutes for antibiotics in animal health, as biopreservatives in food and as tools for detecting pathogenic bacteria throughout the food chain (Garcia, et al., 2008). Magnone, et al. (2013), utilized EcoShield, SalmoFresh, and ShigActive to control E. coli O157: H7, Salmonella and Shigella spp. on fresh fruits and vegetables. EcoShield (ECP-100) is an FDA approved commercial phage cocktail composed of phages ECML-4, ECML-117 and ECML-134 and is employed to eradicate or minimize food contamination caused by E. coli O157: H7 (Carter, et al., 2012, Ferguson, et al., 2013). Spraying EcoShield (1 Å~ 106 to 5 Å~ 106 PFU/g) reduced E.coli numbers

by 94% and 87% in beef and lettuce with an E.coli contamination of about 103 CFU/g, respectively, throughout the 5-minute contact time (Carter, et al., 2012).

Many studies have also demonstrated the effectiveness of phage utilization on contaminated working surfaces used during food processing. For instance, a bacteriophage cocktail designated as BEC8 was examined for its ability to reduce enterohemorrhagic E. coli (EHEC) 0157: H7 strains applied on materials typically employed during food processing surfaces such as sterile stainless-steel chips, ceramic tile chips and high-density polyethylene chips (Viazis, et al., 2011). Bacterial cultures of EHEC O157: H7 strains were spot inoculated (106, 105 and 104 CFU/chip) on the surfaces which were followed by phage treatment to achieve a multiplicity of infection (MOI) ratio of 1,10 and 100. The results obtained showed that the phage cocktail was very effective within an hour against low levels of the EHEC bacterial cocktail at above room temperature in all three hard surfaces (Viazis, et al., 2011). Phage lytic enzymes such as endolysins have also been applied in food preservation. Endolysins are peptidoglycan hydrolases (PGHs) encoded by phage and applied to enzymatically disrupt the host cell wall during the final phase of reproduction (Schmelcher, et al., 2012). For instance, researchers have demonstrated that staphylococcal phage lysin LysH5 can eradicate S. aureus bacteria present in pasteurized milk and does this synergistically with bacteriocins (García, et al., 2010, Obeso, et al., 2008). Similarly, phage lysins designated as Ply118, Ply511 and Ply500 have been utilized as an antibacterial agent on iceberg lettuce (Schmeler, et al., 2011).

1.8.5 Water treatment Water resources are becoming limited due to contamination caused by various life- threatening bacterial pathogens and toxic chemicals. Existing issues facing water supply are such as contamination with chemical compounds (e.g. pharmaceutical and personal care products), and biological agents which can result in increased antimicrobial resistance in bacteria (Hartmann, et al., 2014, Larsson, et al., 2007, Pruden, et al., 2013). The use of these chemicals has increased to a point that propagation of antimicrobial resistance has become unavoidable (Pruden, et al., 2006). Many enteric bacteria with multiple resistance (MDR) such as Escherichia, Enterobacter, Klebsiella, Salmonella and

Shigella species, have been detected in drinking and recreational water resources (Kumar, et al., 2013). Antibiotic-resistant Pseudomonas species have also been isolated from drinking water (Vaz-Moreira, et al., 2012).

Traditional water purification methods such as chlorination, radiation, and filtration are used for the reduction of pathogenic bacteria in water systems and have many disadvantages (Ahiwale, et al., 2012). It has been reported that human exposure to disinfection by-products (DBPs) such as chlorine in water can result in eye, nose, stomach problems, and sinus irritation. Besides that, pathogenic bacteria residing in water bodies are reported to confer resistance to chemical disinfectants (Ahiwale, et al., 2012). Bacteriophages have been employed as a potential disinfectant in the natural waterbodies alone or in combination with physical and chemical processes (Ahiwale, et al., 2012). For instance, McLaughlin and Brooks (2008) demonstrated high inactivation rate of Salmonella enterica subsp. enteric serovar Typhimurium (ATCC 14028) in experimentally contaminated wells using mono phages and cocktail combinations.

Bacterial biofilms especially those formed by P. aeruginosa are known to obstruct filters at drinking water plants and usually require chlorine and costly flushing procedures to clean (Jassim, et al., 2016). Zhang and Hu (2013), have isolated P. aeruginosa phages from sewage and evaluated the results in comparison to the standard treatment using chlorine to destroy P. aeruginosa biofilms. The results showed 40% removal of P. aeruginosa biofilms using chlorine as opposed to 89% removal using phages at a titer of 107 PFU/mL. Moreover, the addition of lower concentration (105 PFU/mL) of phages followed by chlorine eradicated 96% of the biofilms. These studies demonstrate that a combination of phages and chlorine is a propitious approach to control bacterial biofilms in water systems.

1.9 Limestone Caves: A potential source for novel lytic phages Caves are diagnostic dissolution features in karst landscapes underlain by soluble rock such as limestone and dolomite, where surface water sinks into the subsurface and flows in a network of self-evolving underground steam passages (Ford and Williams, 2013). These features are sheltered from the atmospheric disturbances and represent an

ecosystem in which many environmental variables remain relatively constant. Connectivity usually occurs through entrances, skylights and rock cracks, the latter acting like narrow channels (Riquelme, et al., 2015). Caves constitute of an oligotrophic ecosystem (less than 2mg of total organic carbon (TOC) per liter), characterized by complete darkness or low level of light, low steady temperature and high humidity (Tomczyk-Żak and Zielenkiewicz, 2016). Despite the oligotrophic nature of the caves, the average number of microorganisms thriving in cave ecosystems is 106 cells/gram of rock (Barton and Jurado, 2007). Photosynthetic activity is limited to places with access to light, normally at the entryway to the cave, but also in the cave interior owing to the presence of artificial lights installed for the public. Light absence hinders the production of the primary organic matter by photosynthetic microorganisms (Tomczyk-Żak and Zielenkiewicz, 2016). Other methods of carbon assimilation are related to chemoautotrophy. In such conditions, energy is derived from binding chemical elements such as hydrogen and nitrogen, or volatile organic compounds, and also from the oxidation of reduced metal ions such as manganese and iron present on the rocks (Gadd, 2010, Northup and Lavoie, 2001).

The presence of organic matter in the caves permits the development of heterotrophs (Groth, et al., 1999). Due to the oligotrophic environment of the caves, existence and functioning of species are limited to those adapted to the oligotrophic conditions (Wu, et al., 2015). This is explained by the domination of chemoautotrophic microorganisms in a certain cave (Chen, et al., 2009, Sarbu, et al., 1996), which fixes carbon and imports energy into food web (Wu, et al., 2015).

Studies on the microbial composition dominating oligotrophic cave settings, have disclosed a surprisingly high degree of diversity and abundance within the domains of bacteria and archaea in diverse cave habitats such as soils, sediments, stream waters, and rock surfaces (Barton and Jurado, 2007, Engel, et al., 2004, Tomczyk-Żak and Zielenkiewicz, 2016). Numerous and familiar bacterial phyla have been uncovered in cave environments by sequencing of 16S rRNA genes, thus greatly advancing the knowledge of bacterial diversity since its establishment in microbial ecology (Roesch, et al., 2007). The dominant taxa on cave walls are largely associated with a few phyla such as Proteobacteria, Acidobacteria, and Actinobacteria (Barton and Jurado, 2007, Cuezva,

et al., 2012, Pašić, et al., 2009). Bacterial abundance in cave sediments could be proportionate to that in overlying soils, however, the rock surfaces are mostly colonized by the lowest diversity natural microbial communities (Macalady, et al., 2007, Yang, et al., 2011).

The study of virus diversity and specifically bacteriophages using samples of water, soil, or sediments from caves remains undocumented until to date (Ghosh, et al., 2016). However, studies of the viral communities of other extreme habitats which are characterized by low level of nutrients have revealed the presence of viral families and bacteriophages (Ghosh, et al., 2016). For instance, a metagenomic analysis conducted on the viral diversity of Antarctica freshwater ecosystems revealed a high number of viral families. Pyrosequencing of 89,347 sequences exhibited no similarity to the available gene bank databases. Furthermore, a transition in genetic structures from single-stranded (ssDNA) to double-stranded (dsDNA) was observed among assemblages from an ice-covered lake in spring to an open water late in summer (López-Bueno, et al., 2009). Studies have highlighted that microbial populations found in caves are regulated by existing viral communities. For instance, the viral-mediated killing of algal blooms is essential for microbial population regulation in the ocean, thereby influencing food-web interactions and affecting geochemical cycles (Fuhrman, 1999, Suttle, 2007).

Thus, cave microbial consortia may also contain massive viral communities that require assessment (Jurado, et al., 2014). This information is essential in understanding cave microbial interactions and population dynamics. Nevertheless, cave viruses could also serve as therapeutic agents because of their potential lytic properties (Tan, et al., 2008). The emergency and widespread of antibiotic-resistant and multi-drug resistant bacterial pathogens (superbugs) and the stalled novel antibiotic discovery are the main driving forces towards the search for novel antimicrobial compounds from extreme environments (Maria de Lurdes, 2013). Extreme environments are considered one of the most propitious sources of beneficial compounds (Cheeptham, 2012). Several studies have reported on secondary metabolites produced by microorganisms that colonize extreme environments as possible sources of useful compounds such as extremozymes (Singh, et al., 2011), exopolysaccharides (Nicolaus, et al., 2010), biosurfactants (Banat, et al., 2010), antitumoral (Chang, et al., 2011), radiation-

protective drugs (Singh and Gabani, 2011), antibiotics , immunosuppressants, and statins (Harvey, 2000). Bioactive compounds such as Cervimycins A-D and xiakemycin A are some of the novel antibiotics generated by cave-dwelling bacteria (Herold, et al., 2005, Jiang, et al., 2015). These antibiotics have shown activity against methicillin- resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecalis. Xiakemycin A is also efficacious against methicillin-resistant Staphylococcus epidermidis and vancomycin-resistant Enterococcus faecalis. In addition, it demonstrates antifungal and cytotoxic effects against cancer cells. To date, cervimycin C is the most studied antimicrobial compound obtained from caves and its resistance in Bacillus subtilis, as well as its biosynthesis, have been thoroughly investigated (Bretschneider, et al., 2012, Herold, et al., 2004, Krügel, et al., 2010).

1.10 Exploring Sarawak’s limestone caves for potential lytic phages Borneo is the third largest island in the world and is notable for its high level of biodiversity (Myers, et al., 2000, Slik, et al., 2010). This island (Figure 1.8) has a total landmass of 740,000 square kilometers and consist of the independent Sultanate of Brunei Darussalam, the Indonesian territory of Kalimantan, and the Malaysian states of Sarawak and Sabah (Rautner, et al., 2005, Sulaiman and Mayden, 2012). Borneo’s forests are home to the highest level of plants and mammal species in Southeast Asia (Bellard, et al., 2014), including 581 species of birds and 240 species of mammals, and the island is regarded as a major evolutionary hotspot (De Bruyn, et al., 2014). Extensive development has led to a significant land cover change on the island, with 389,566 km2, approximately 53% of the total area of the island, remaining under natural forest cover (Gaveau, et al., 2014). In 2007, the countries situated in Borneo Island made a declaration to protect 220,000 square kilometers of pristine rainforest habitats (also known as the “Heart of Borneo”) to prevent deforestation and develop plantation activities for the sake of the island’s biodiversity (Sulaiman and Mayden, 2012).

Malaysia is ranked 14th on the list of the 17 global mega-diverse countries on earth (Keong, 2015). Its forests sustain varieties of unique flora and fauna species of extraordinarily abundance and very high rates of endemism and uniqueness (Keong,

2015). Furthermore, Malaysia ranks 14th in the world for its vascular plants (15,500 species as recorded in 2004) densities. It is a home to 336 species of mammals, approximately 750 species of birds with a high level of endemism and 212 species of amphibians. Thus, Malaysia’s ecosystem is regarded as one of the globally significant and distinctive ecosystems with high conservation preference (Keong, 2015). Different laws have been enacted to protect the environment and natural biodiversity. For instance, Wildlife protection ordinance, Sarawak (1998) and Environmental protection enactment, Sabah (2002, amended 2004) (Keong, 2015). At the regional level, the ASEAN Centre for Biodiversity has been set up to strengthen coordination for the purpose of conservation and sustainable utilization of biodiversity (Keong, 2015).

Figure 1.8: Borneo Island’s map showing the geographical divisions and features of Brunei Darussalam, Indonesia (Kalimantan) and East Malaysia (Sarawak and Sabah). This island is known as the world's third largest island and one of the twelve mega-biodiversity regions (Lateef, et al., 2014, Tan, et al., 2009).

Sarawak is the largest state in Malaysia, located along the northwest coast of Borneo island and covering 124,500 square kilometers (Rautner, et al., 2005). This state comprises of 512, 387.47 hectares of the protected area constituting 18 National parks, four wildlife sanctuaries, five nature reserves and the largest peatland area in Malaysia (Forest Department Sarawak, 2013, Van der Meer, et al., 2013). This rich biodiversity has attracted the attention of scientists within and outside Malaysia. So far, existing scientific studies have focused on peat soils, plants, corals, microbes in aquatic and forest environments (Cole, et al., 2015, Kuek, et al., 2015, Lateef, et al., 2014, Miyashita, et al., 2013, Sa'don, et al., 2015). Malaysia is a home to abundant limestone caves located in places such as Langkawi Island, Kedah-Perlis, Kinta Valley, Perak, Selangor, Gua Musang, and Kelantan Bakhshipouri, et al. (2009).

Sarawak’s limestone forest is one of the nine main types of forests reported in Sarawak, covering about 520 m2 or 0.4% of the total area (Banda, et al., 2004, Julaihi, 2004). This forest constitutes of several limestone caves which have become the focal point of investigating the varieties of bats indigenous to the Wind and Niah Caves (Mohd, et al., 2011, Rahman, et al., 2010, Rahman, et al., 2010). Analyses such as the evolution of limestone formation, biological influence on the formation of stalagmite, investigation of trace metal ratios and carbon isotopic composition have also been performed in Sarawak’s Niah and Mulu caves (Cucchi, et al., 2009, Dodge-Wan and Mi, 2013, Moseley, et al., 2013). Many south-east Asia’s limestone outcrops which have been historically free from agricultural practices due to their rugged terrain (Clements, et al., 2006), may operate as biodiversity pool that restocks degraded environments during ecosystem reassembly (Schilthuizen, 2004). Recently, studies have been reported on the presence of microorganisms isolated from Fairy Cave and Wind Cave Nature Reserves, Sarawak Malaysia, capable of producing urease enzyme and inducing calcium carbonate mineral for the biocement application (Omoregie, 2016).To date, there has been no study on phage diversity conducted in Sarawak limestone caves, utilizing samples such as water, soil, or sediments despite the reported biodiversity and species endemism. This research gap has initiated the relevance of screening for lytic phages from Fairy cave and Wind cave nature reserves located in Bau, Sarawak.

1.11 Significance of the study This current study explores the prospects of isolating lytic phages from Sarawak limestone caves capable of infecting pathogenic bacteria strains. Phages infecting P. aeruginosa were further studied for their biocontrol efficiency on P. aeruginosa PAO1 contaminated sand samples individually and in a cocktail. Sarawak limestone caves represent one of Malaysia’s biodiversity reservoir that has not yet been explored for potential therapeutic microbes including bacteriophages. Furthermore, the study of virus diversity and specifically bacteriophages from limestone caves and their potential applications have not been reported elsewhere in the literature. This research gap initiated the relevance of the current study. The phages reported in this study present potentials to be developed into biological disinfectants to control P. aeruginosa infections.

1.12 Hypothesis The hypotheses of the present study are listed below; i. The reported abundance of bacteria in oligotrophic environments such as limestone caves suggest the presence of phages capable of infecting them. Since microbial populations in caves are regulated by existing viral communities, hence, it is possible that lytic phages will be present and abundant and can be isolated using standard phage isolation methods. ii. There is a strong correlation between multiplicity of infection (MOI) ratio and the bacterial inactivation during phage biocontrol studies. iii. Phage cocktails and multiphages are more effective in inactivating bacterial pathogens than monophages.

1.13 Aims and objectives of the study This research sought to investigate the diversity of bacteriophages in limestone caves and evaluate their potential application as biological disinfectants to control infections caused by P. aeruginosa bacteria. To fulfill the general purpose of this research, three independent studies were designed with the following objectives: i. To screen and isolate lytic bacteriophages from limestone cave soil samples.

ii. To investigate the phage bacteriolytic activity in in-vitro. iii. To treat sand samples contaminated with P. aeruginosa using the isolated phages.

1.14 Thesis Outline This thesis is divided into four chapters: Introduction and Literature Review (Chapter 1), Materials and Methods (Chapter 2), Results and Discussion (Chapter 3) and General Conclusion and Recommendations (Chapter 4). Concluding remark is shown at the end of Chapter 3 to summarise the contents of this chapter.

Chapter 1, provides a brief introductory background of the study and a broad review of the literature on phage therapy and biocontrol which has been reported by other researchers. This chapter also introduces the prospect of screening for bacteriophages from Sarawak’s limestone caves. The significance, hypothesis, and aim of the research are also mentioned. Chapter 2, gives a detailed description of the materials and methods undertaken to fulfill the main objective of the current study. This chapter provides a detail description of the methods used to screen and isolate lytic phages from Sarawak limestone caves. Phage bacteriolytic activities were investigated on all isolated P. aeruginosa phages at varied multiplicity of infection (MOI) ratios. Assessment of phage ability to disinfect P. aeruginosa contaminated sand samples was carried out using the best P. aeruginosa phage candidates (FCPA3, WCSS4PA, Cocktail), selected based on their high efficiency in inactivating the bacteria. Chapter 3, presents the results and discusses the findings of the current study with relevant statistical analysis. The exploration and biodiversity of lytic phages from Sarawak limestone caves and the application of these phages in biocontrol of P. aeruginosa. Chapter 4, presents a concise overview of the most significant findings extracted from the work presented in this thesis. The scope for further research within this field is also presented as future directions.

Chapter 2

MATERIALS AND METHODS

2.1. Isolation of lytic bacteriophages targeting bacterial pathogens 2.1.1 Sampling site and sample collection Soil sampling was conducted at Fairy Cave (N 01°22’53.39” E 110°07’02.70”) and Wind Cave (N 01°24’54.20” E 110°08’06.94”) Nature Reserves located in Bau, Kuching Division, Sarawak, East Malaysia. Samples were collected upon authorized permission from Sarawak Forest Department and Sarawak Biodiversity Centre (SBC-RA-0110-PMN). A total of seven soil samples were collected at a depth of 0-25 cm, six of which were obtained from regions surrounded by rocks and vegetation and one soil sample mixed with bat Guano which was obtained from the cave floor of the Fairy Cave Nature Reserve (FCNR). Temperature and percentage relative humidity of the sampling sites were measured by using traceable digital hygrometer/thermometer (Thermo Fisher Scientific). Each sample was collected using sterile tools, placed in sterile polystyrene containers, sealed and stored in an ice box (at the sampling site) before being transported to Swinburne University of Technology, Sarawak campus for further microbiological analysis. In the laboratory, the soil samples were temporarily stored in the refrigerator at 4oC prior to the commencement of the phage screening experiments.

2.1.2 Biological material Bacterial strains used in this study are presented in Table 2.1. These strains were purchased from American Type Culture Collection (ATCC) Manassas, Virginia, United States of America except V. parahaemolyticus which was acquired from the Swinburne University of Technology Sarawak Campus (SUTS) microbiology strain collections. All the bacteria except V. parahaemolyticus were aseptically grown on Petri plates containing Tryptic soy agar (TSA) (40.0 g. L-1, HiMedia Laboratories Pvt. Ltd). To grow V. parahaemolyticus, Petri plates containing TSA supplemented with 1.5% NaCl (w/v) (Sigma-Aldrich (M) Sdn Bhd) was used. The plates were incubated (Incucell, MMM Medcenter Einrichtungen GmnH) at 37oC under aerobic conditions for up to 24 hrs and then stored in the fridge at 4oC prior to use.

Table 2.1: Description of bacterial strains used in this study Bacterial Strain Genotype Source Source Designation E. coli MG 1655 ATCC 47076 K. pneumoniae K6 ATCC 700603 P. aeruginosa PAO1 ATCC 15692 S. aureus PS 88 ATCC 33742 S. pneumoniae R6 ATCC BAA-255 S. typhi TA 1537 ATCC 29630 V. parahaemolyticus Wild strain SUTS NA

2.1.3 Growth medium and sterilization Brain-heart infusion (BHI) broth (HiMedia, Mumbai, India) served as growth media for screening and amplification of bacteriophages from soil samples. Nutrient broth (Oxoid, Basingstroke, UK), Nutrient agar (Oxoid, Basingstroke, UK), Tryptic soy broth (HiMedia, Laboratories Pvt. Ltd) and Tryptic soy agar (HiMedia, Laboratories Pvt. Ltd) were utilised as routine growth media for cultivation of all the bacterial hosts except V. parahaemolyticus where 3% NaCl (w/v) (Sigma-Aldrich (M) Sdn Bhd) was supplemented into the growth media. The growth media were prepared in accordance with their respective manufacturer’s instructions. Sterilisation of growth media, chemicals and glassware were performed with the use of an autoclave machine (Hirayama-HVE-110) at 121oC, 103.42 kPa for 20 minutes.

2.1.4 Growth profiles of the bacterial hosts A colony of a bacteria strains grown on TSA (40.0 g. L-1 HiMedia, Laboratories Pvt. Ltd) was inoculated into the universal bottle (20 mL capacity) containing 10 mL of Brain heart infusion (BHI) broth (37.0 g. L-1Oxoid, Basingstoke, UK) and then incubated overnight at 37oC and 150 rpm. Batch cultures were prepared by inoculating 2.5 mL from an overnight grown bacterial culture into BHI broth prepared in a 250mL capacity conical flask. The contents were grown at 37oC and 150 rpm for up to 6 hrs. Aliquots (3 mL) were withdrawn from the culture flask every 30 minutes and optical density was measured at 600 nm wavelength using a spectrophotometer (Genesys TM 20- Thermo Scientific).

2.1.5 Maintenance and storage of bacterial hosts Glycerol stock method was used for both short and long-term storage of the bacterial hosts following a modified procedure of Fortier and Moineau (2009). For short-term bacteria preservation, 500 µL of bacterial culture was transferred into a sterile 1 mL cryotube. About 500µL of 50% glycerol (Sigma-Aldrich (M) Sdn Bhd) was added into the cryotube to obtain a final glycerol concentration of 25% (v/v). The contents were mixed gently by inverting the tube a few times and stored at -20oC. For long-term preservation of bacteria, the same approach was used but the tubes were stored at -80oC. For the case of reviving stored cells, sterile toothpick or inoculation loop was used to scrap off the splinters of solid ice (Omoregie, 2016). The resulting culture was then streaked out on either TSA or BHI agar plate which served as a stock plate for culture preparation. In the case of revival of V. parahaemolyticus, the culture was streaked out on either BHI agar or NA supplemented with 3% NaCl. Stock plates were replaced every three to four weeks or sooner where necessary.

2.1.6 Screening for lytic bacteriophages Phage enrichment and isolation were carried out by inoculating 1 g of soil sample into 100 mL of sterile BHI broth (37.0 g. L-1Oxoid, Basingstoke, UK). Four milliliters (4 mL) of sterile 10 mM CaCl2 (Sigma-Aldrich (M) Sdn Bhd) was added into the same broth and the contents were incubated for 1 hr at 37oC. About 5 mL of bacteria-host culture grown to its mid-exponential phase was subsequently added to the soil sample broth and the contents were incubated aerobically overnight with shaking at 37oC and 150 rpm. Thereafter, 1 mL of 1% TTC (2,3,5-triphenyl tetrazolium chloride) (HiMedia, Laboratories

Pvt. Ltd) and 1.2 mL of sterile 10 mM CaCl2 solutions were added into 100 mL liquefied nutrient agar (28.0 g. L-1, 45oC, Oxoid, HiMedia, Laboratories Pvt. Ltd) prepared in a Schott bottle (250 mL). About 5 mL of previously cultured broth was then inoculated into the Schott bottle and the contents were gently mixed and poured out into sterile Petri dishes, avoiding the formation of any bubbles. The plates were left to air dry inside a biological safety cabinet (Class II, type A2, Thermo ScientificTM) for 15 min and then incubated (Incucell, MMM Medcenter Einrichtungen GmnH) without inversion (Sambrook and Russell, 2001) under aerobic conditions for 24 hrs at 37oC. Incubation of the plates without inversion was performed so as to encourage sweating of the fluid

onto the surface of the dish allowing bacteriophages to spread easily (Sambrook and Russell, 2001).

2.1.7 Phage isolation and amplification After a careful examination of the plates, plaques were identified and characterized based on the size, shape, clarity, presence or absence of a halo as per Basra, et al. (2014). A double-layered agar plate technique was performed on these plaque isolates for at least three times to obtain a homogeneous plaque formation. Following this, a sterile straw was used to excavate the agar part containing the plaque and this was amplified in 4 mL of BHI broth (supplemented with 100 μL of 10 mM CaCl2 solution) containing 1 mL of bacterial culture grown to its mid-exponential phase. The contents were incubated aerobically overnight at 37oC and 150 rpm. The bacteria were expected to lyse in 6-8 hrs and become slightly turbid due to cell debris. The contents were then centrifuged (Eppendorf®, 5424R) at 8000 g for 5 min and the supernatant containing phage particles was filtered through a 0.22 μm syringe filter. A drop (approximately 50 L) of chloroform was added into the recovered phage lysates and the tubes were stored temporarily in the fridge at 4oC.

2.1.8 Screening and isolation of multiphages Multiphages were screened following the same procedure as indicated in subsection 2.1.6. After a careful examination of the plates following an overnight incubation was performed to identify and record unique plaque morphologies, plaque isolation followed by amplification was not performed as this method selects for lytic monophages. Instead, phage amplification was carried out by inoculating 1 mL of filter sterilized soil sample bacterial broth from which plaques were present in 9 mL of sterile BHI broth. The contents were then incubated aerobically overnight at 37oC and 150 rpm. After bacterial lysis was observed, the contents were centrifuged (Eppendorf®, 5424R) at 8000 g for 5 min and the supernatant containing phage particles was filtered through a 0.22 μm syringe filter. A drop of chloroform (approximately 50 L) was added to the recovered phage lysates and the tubes were stored temporarily in the fridge at 4oC.

2.1.9 Determination of phage titer Phage particles were enumerated using the double-layered agar plate technique following a modified method of Merabishvili, et al. (2009). A serial dilution of the bacteriophage lysate in microfuge tubes was performed using phage buffer (PB) (10 mM

Tris [pH 7.5], 10mM MgCl2 and 68 mM NaCl) (Sigma-Aldrich (M) Sdn Bhd) supplemented with a 10 mM CaCl2 solution. About 0.1 mL of this dilution was inoculated into another microfuge tube containing 0.5 mL of log-phase bacterial culture, and the tubes were incubated at 37oC for 10 min to allow phage adsorption to occur. Each of the cell-phage content was poured into a sterile 15 mL centrifuge tube containing 3 mL of top agar. This top agar was prepared by adding 0.7% agar (w/v) in 37.0 g. L-1 BHI broth (Oxoid, Basingstoke, UK), and the temperature maintained at 45oC in a water bath. The mixture was then plated onto pre-warmed TSA plates. The plates were left to cool for approximately 15 min inside a laminar flow biosafety cabinet and then incubated at 37oC for up to 24 hrs. This experiment was performed in triplicates for each phage dilution. To estimate the original bacteriophage concentration, plates with 30-300 (Kropinski, et al., 2009, Sutton, 2011) distinguishable homogeneous plaques were enumerated and the phage titer (PFU/mL) was calculated as shown in the formula below (eqn. 1):

�� (No of plaques)(dillution factor) �� ( ) = (eqn. 1) �� Volume plated (mL)

2.1.10 Storage of lytic bacteriophages Short term storage of phage isolates was performed by transferring 100 μL of phage lysate into a sterile cryotube containing a drop of chloroform. The contents were mixed gently by inverting the tube a few times and then stored at 4oC in a fridge. For the long- term storage of phage isolates, 100 μL of phage lysate was added into a sterile cryotube containing 200 μL of 75% (v/v) glycerol in phage buffer (PB) (Fortier and Moineau, 2009, Pardon, et al., 2014) and the contents were gently mixed by inverting the tube a few times and the vials were frozen at -80oC. Cryoprotectant solution [75% (v/v) glycerol in phage buffer] was prepared by adding 75% of glycerol (Thermo Fisher Scientific) in a

Schott bottle containing 25% of phage buffer (10 mM Tris [pH 7.5], 10mM MgCl2 and 68 mM NaCl) (Sigma-Aldrich (M) Sdn Bhd). The contents were thoroughly mixed by

inverting the bottle a few times and then sterilized by autoclaving at 121oC, 103.42 kPa for 20 min.

2.1.11 Revival of cryo-preserved lytic bacteriophages To revive cryo-preserved phages, an overnight culture of the host strain was prepared and about 0.5 mL of it was transferred into a test tube containing 2.0 mL of TSB or BHI broth. With the use of an inoculating loop, frozen top part of the phage solution was scrapped off and added into the broth. The contents were incubated aerobically overnight at 37oC and 150 rpm. The next morning, the amplified phage culture was centrifuged (Eppendorf®, 5424R) for 10 min at 8000 g and the supernatant was filter sterilized using 0.45 µm syringe filter and stored at 4oC.

2.1.12 Host range assay Bacteria strains used for host range assay were grown to their mid-log phase in BHI broth. About 0.3 mL of bacteria-host culture was then inoculated into a sterile 15 mL centrifuge tube containing 3 mL molten top agar supplemented with 100 µL of 10 mM

-1 CaCl2 solution. The top agar was prepared by adding 0.7% agar (w/v) in 37.0 g. L BHI broth (Oxoid, Basingstoke, UK) and the temperature maintained at 45oC in a water bath. The contents were gently mixed and quickly poured onto pre-warmed TSA agar plate and left to air dry in the laminar flow biosafety cabinet for 15 min. Phage host range was determined by spotting 10 μL of phage lysate preparation (approximately 1015 PFU/mL) three times onto different host plates. For control purpose, each bacteria strain was mock infected with sterile phage buffer. The Petri plates were incubated at 37oC for up to 36 hrs under aerobic conditions. A successful phage infection was scored based on plaque formation on a susceptible bacterial lawn.

2.2. Phage in-vitro bacteriolytic activity and a small-scale treatment of experimentally contaminated sand samples

2.2.1 Preparation of bacterial culture Bacteria strain P. aeruginosa PAO1 used in sand decontamination studies was prepared by inoculating a bacteria colony from a stock plate into 10 mL of sterile Brain-heart infusion (BHI) broth (37.0 g. L-1, Oxoid Thermo Scientific Microbiology). The contents were incubated at 37oC and 150 rpm for 24 hrs in an incubator shaker (CERTOMAT® CT plus–Sartorius) under aerobic conditions. Prior to decontamination experiments, aliquots of 100 μL were transferred into pre-sterilised universal bottles containing 9 mL of sterile BHI broth and the contents grown at 37oC and 150 rpm to mid-exponential phase.

2.2.2 Preparation of phage stocks This study utilized six highly lytic single plaque phages designated as FCPA1, FCPA2, FCPA3, FCPA4, FCPA5 and FCPA6, and two multi-phages designated as WCSS4PA and WCSS5PA specific for P. aeruginosa PAO1 bacteria. A phage cocktail (Cocktail) was prepared by combining equal volumes of phage lysates (approximately 1015 PFU/mL) obtained from the six single-plaque bacteriophages (FCPA1, FCPA2, FCPA3, FCPA4, FCPA5 and FCPA6,) following a modified procedure of Viazis, et al. (2011). To obtain high titer phage stocks for the experiments, a modified procedure by Fortier and Moineau (2009) was adopted. Briefly, P. aeruginosa host strain was grown in 10 mL of

BHI broth to its early log phase (OD6000.1). About 100 μL of 10 mM CaCl2 solution and 100 μL of phage lysate were added into the bacterial culture. The contents were incubated for 8 hrs at 37oC and 150 rpm to allow amplification of the phage. Afterward, the contents were centrifuged at 8000 g for 10 min and the supernatant containing phage particles was filtered through 0.22 μm syringe filter. Each time bacteriophage stocks were grown or amplified, their titer was determined using the double agar overlay technique following a modified protocol of Merabishvili, et al. (2009). Phage lysates were stored in the fridge at 4oC prior to use.

2.2.3 Phage in-vitro bacteriolytic activity The bacteriolytic activity of phages was performed as suggested by Wang, et al. (2016) with minor modifications. To begin with, an overnight P. aeruginosa PAO1 culture was diluted 1:100 (v/v) in sterile BHI broth and incubated at 37oC and 150 rpm until a mid- exponential phase was attained (7.76 x 1010 CFU/mL). This culture was then diluted using Phosphate buffer saline (PBS) solution to obtain a concentration of 1.0 x 1010 CFU/mL. About 25 mL aliquots of the culture were dispensed into 100-mL capacity conical flasks and equal volumes (25 mL) of bacteriophage lysates were added to obtain different multiplicity of infection (MOI) ratios (101,102,103,104 and 105). The titers of the phages were diluted to desired concentrations using phage buffer (PB). The contents were then incubated at 37oC and 150 rpm for up to 6 hrs. P. aeruginosa PAO1 bacterial culture with an equal volume of phage buffer (PB); (10 mM Tris [pH 7.5], 10mM MgCl2 and 68 mM NaCl) (Sigma-Aldrich (M) Sdn Bhd) was used as a control. The phage bacteriolytic activity was determined by monitoring the cell absorbance of the culture solution (OD600) for 6 hrs with 30 minutes interval. Incubation was continued for up to 24 hrs and viable counts (CFU/mL) of the recovered bacteria were determined at 6th and 24th hrs post-incubation. Optical density measured at a wavelength of 600 nm and viable bacterial counts (CFU/mL) were recorded as an average of three independent biological repeats.

2.2.4 Analysis of bacteria survival from phage treated cultures To determine the CFU/mL counts of the recovered bacteria from phage treated cultures, 1 mL sample was withdrawn at a specific time and centrifuged at 8000 g for 10 min in a 1.5 mL capacity micro-centrifuge tube. The supernatant was discarded, and the pellet was washed twice using Phosphate-buffered saline (PBS); 137 mM NaCl, 2.7 mM KCl,10 mM Na2HPO4, 1.8 mM KH2PO4 pH 7.4 (Sigma-Aldrich (M) Sdn Bhd) before being resuspended in the same solution. Serial dilution was performed in PBS and plating was done on Tryptic soy agar (40.0 g. L-1, HiMedia Laboratories Pvt. Ltd). Plates were incubated at 37oC overnight and viable bacteria cells (CFU/ml) were enumerated.

2.2.5 Preparation of sand samples Evaluation of phage’s ability to be utilized as a biological disinfectant to control infections caused by P. aeruginosa was performed on P. aeruginosa PAO1 contaminated

sand samples. The sand samples served as a simulant of any environmental surface exposed to contamination with P. aeruginosa. Sand decontamination studies were performed on Petri plates (Surface area=56.75cm2) containing 20 g of sterile sand. Sand was obtained from Swinburne University of Technology Sarawak Concrete Laboratory (E002) and was thoroughly cleaned by washing it several times under running water, followed by rinsing it with deionized water at least three times. The sand was then dried overnight in an oven set to 100oC. About 20 g of sand was dispensed into clean and dry universal bottles and sterilized by autoclaving at 121oC, 103.42 kPa for 30 minutes prior to use.

2.2.6 Phage preparation in spray bottles Plastic spray bottles of 50 mL capacity were purchased from a local supermarket and sterilization was done by soaking 10% (v/v) of bleach inside the bottles overnight, followed by rinsing the bottles at least three times with sterile deionized water. Spray bottles were then further sterilized by exposing them to ultraviolet (UV) radiation inside a laminar flow hood for 45 min. About 25 mL of phage lysates (approximately 1015 PFU/mL) for bacteriophages FCPA3, WCSS4PA and Cocktail were dispensed into the bottles and samples were temporarily stored in the fridge at 4oC prior to use.

2.2.7 Treatment of contaminated sand samples with phage The ability of bacteriophage isolates to decontaminate P. aeruginosa PAO1 immobilized sand samples were assessed as follows; to begin with, 4 mL of freshly grown mid- exponential phase P. aeruginosa PAO1 culture (OD600=0.5) having a concentration of 7.76 x 1010 CFU/mL was uniformly mixed with 20 g of sterile sand in a Petri dish using a sterile spatula. This sand was compacted to form a matrix of approximately 3 mm thick. Using a spray bottle, phage lysate (approximately 1015 PFU/mL) which was prepared as demonstrated in subsection 2.2.2, was sprayed on the surface of the sand (thirty times) delivering a volume of 2.55 mL. A negative control sample was prepared following the same procedure as per section 2.2.7, but no phage was sprayed on it. This experiment was performed in triplicate and the samples were incubated at 37oC for 6 hrs, 24 hrs, and 48 hrs. Exactly twenty-four hours post-incubation, samples were sprayed with phage for the second time (2.55 mL) and incubation was continued until 48 hrs. Phage

recharge was performed to investigate the effect of an additional dose of phage at preventing regrowth of bacteria which was evident during the phage in-vitro bacteriolytic activity studies presented in (Subsection 2.2.3).

2.2.8 Analysis of bacterial survival following phage treatment About 1 g from phage treated and non-treated (control) sand samples were collected at different time intervals during the treatment process (t= 0 hr, t=6 hrs, t=24 hrs and t=48 hrs) and placed into sterile test tubes containing 10 mL of PBS solution (pH 7.4). The tubes were vortexed for 1 min and a serial dilution in PBS solution was conducted. Plating was done on TSA Petri dishes and incubation was performed for up to 24 hrs at 37oC. Viable bacterial cell reductions (CFU/mL) were calculated by subtracting treated sand sample cell counts from negative control cell counts (Tomat, et al., 2014).

2.2.9 Statistical analysis The data obtained in this study was presented as mean  SE (standard deviation) for three independent replicates. The rate of bacterial inactivation by phages (FCPA1, FCPA2, FCPA3, FCPA4, FCPA5, FCPA6, WCSS4PA, WCSS5PA and the Cocktail) in comparison to untreated control at different MOIs was evaluated and analyzed using GraphPad Prism software (version 7.0d). A one-way analysis of variance (ANOVA) and Tukey-Kramer’s post hoc analysis was performed using StatPlus program (version 6.0) to indicate any significant difference between groups. The value of p<0.05 was considered as significant. Logarithmic values in terms of log10 CFU/mL for viable bacterial count were used in order to normalize the data. The logarithmic mean, mean log10

CFU/mL was calculated by averaging the individual log10 CFU/mL values. The mean log reduction (LR) in CFU/mL was calculated by subtracting the mean log10 CFU/mL of negative control from mean log10 CFU/mL of test samples. Mean LR CFU/mL ≥1 was considered as significant. Percentage bacterial load reduction was calculated as shown in following formula below (eqn. 1):

(A−B) x 100 �� = (eqn. 2) � Where, A is the number of viable bacteria before treatment B is the number of viable bacteria after treatment

Chapter 3

RESULTS AND DISCUSSION

3.1 Introduction The emergence and spread of multi-drug resistant (MDR) bacteria are alarming and have prompted interests in the search for fresh alternative schemes to tackle the problem (Parmar, et al., 2017). One example is P. aeruginosa, an opportunistic pathogen commonly isolated in clinical samples (Yu, et al., 2017). Phage biocontrol has received an increasing level of interest by many researchers to mitigate the propagation of antibiotic-resistance bacteria (Viertel, et al., 2014). Virulent bacteriophages (phages) represent a viable antibacterial scheme that could be particularly beneficial to control pathogenic bacteria with little impact on the rest of microbial community (Loc-Carrillo and Abedon, 2011). One rising application of lytic phages is disinfection of surfaces and materials commonly used in hospitals and food processing industries. The disinfection of hard surfaces faces considerable challenges due to an increase in bacterial resistance to traditional chemical sanitizers including hypochlorous acid and benzalkonium chloride (Abuladze, et al., 2008). The study in this chapter explores the prospect of isolating lytic bacteriophages from limestone caves with potentials to be utilised as biological disinfectants to control infections caused by P. aeruginosa bacteria. Studies on isolation and application of lytic bacteriophages obtained from limestone cave environment have not been reported in preceding literature. However, the potential of using cave microorganisms as a source of antimicrobial agents and drug discovery has been recently reviewed (Ghosh, et al., 2016). This research gap forms the basis of the current study. This chapter discusses the outcome of the experiments conducted to isolate lytic bacteriophages from Sarawak limestone cave soils targeting various pathogenic bacteria. Investigative studies on assessment of lytic abilities of P. aeruginosa phages in an in-vitro co-culture assay at a varied MOI ratio and their potentials to treat sand samples contaminated with P. aeruginosa PAO1 cells are also reported. The results presented in this chapter shows presence and diversity of bacteriophages in limestone cave environment with potentials to be further explored and developed into biological disinfectants of P. aeruginosa.

3.2 Results 3.2.1 Isolation of lytic bacteriophages targeting bacterial pathogens 3.2.1.1 Soil collection A total of seven samples (Table 3.1) were collected in January 2016 from FC (also known as Gua Pari) as shown in Figure 3.1 and WC (also known as Lubang Angin) as shown in Figure 3.2. These caves are about 5-7 km south-west of Bau and 30 km from Kuching, Sarawak (Mohd, et al., 2011). The caves are part of the nature reserves protected by environmental laws that preserve the forest, national parks, and nature reserve (Omoregie, 2016). They cover 56 and 6.16 hectares respectively and are largely surrounded by forests (Sarawak Forest Department, 1992).

Table 3.1: Description of soil samples collected at FCNR and WCNR Sample Sample Colour Texture oC (%) Code ID collected RH

WC1 Soil mixed with Yellowish- Fine 30.6 94 Guano brown WC2 Soil Brown Fine 29.7 90

WC3 Soil Black Coarse 28.7 84

FC1 Soil Brown Fine 24.8 76

FC2 Soil Black Coarse 26.5 73

FC2 Soil Brown Fine 28.1 80

FC4 Soil Brown Clay 30.6 79

WC= Wind cave; FC= Fairy cave; oC= Temperature; (%) RH = Relative humidity.

Figure 3.1: Fairy Cave (FC) Bau, Sarawak, Malaysia. [A] Entrance view of the cave (left). [B] View of cave chamber (right). Four samples were taken from inside the cave chamber.

Figure 3.2: Wind Cave (WC) Bau, Sarawak, Malaysia. [A] Entrance to the cave (left). [B] View of cave chamber (right). Three samples were taken from inside the cave chamber.

3.2.1.2 Bacterial host growth profile Optical density (OD) at a wavelength of 600 nm, an indicator of bacterial growth, was studied for up to 6 hr under aerobic batch conditions in a sterile Brain-heart infusion (BHI) broth as presented in Figure 3.3. It was observed from the graph that, the growth curve of the bacterial host increased in response to time and all the tested bacteria had similar growth patterns for the total duration of the incubation. As indicated in Figure 3.3, bacterial cultures continued to have a progressive cell growth, hence, stationary phase or death phase was not observed. The lag phase of all the bacterial hosts was brief, noticeably and lasted for 0.5 hrs. The lag phase is usually characterized by no immediate increase in cell numbers, as the bacteria are synthesizing new components. During this stage, the cells may be old and depleted of ATP, essential, cofactors, and ribosomes, thus these must be synthesized before growth can begin (Willey, et al., 2009). This was followed by the log (exponential) phase marked by constant bacterial growth rate and cell doubling in number at regular intervals. As seen in Figure 3.3 all the bacterial hosts entered exponential phase after 1 hr of incubation and this phase lasted for up to 3 hrs. Table 3.2 summarises the results of the growth kinetics of the bacterial hosts during the batch culturing. The growth rate (specific growth rate) refers to the change in a number of cells per minute, which can be estimated as the change in OD per minute. Ideally, bacterial cultures grow exponentially mimicking a first-order chemical reaction and the OD increases as a function of ln (OD), not OD itself (Hall, et al., 2013). In this study, specific growth rate,  (eqn. 3), at the different times of sampling was estimated from the OD600 growth curve using five consecutive OD600 measurements as described by Berney, et al. (2006) in the formula below. In practice, specific growth rate, , is equal to the slope of ln OD versus time (t).

lnOD600 Specific growth rate,  = , where t is time (eqn. 3) t

�� Doubling time (td) = , where  is the specific growth rate (eqn. 4) 

Doubling time (eqn. 4) or generation time refers to the time it takes for cell division to occur, with shorter time implying a more rapid bacterial growth (Maier, et al., 2009). Doubling time can be calculated from a linear portion of a semilog plot of growth versus

time. The mathematical expression for this portion of the growth curve can be rearranged and solved to calculate doubling time as shown in equation 4 above. Analysis of the growth kinetics of the bacterial hosts showed that the highest specific growth rate () (0.644 h-1) was exhibited by S. aureus whereas the lowest specific growth rate was 0.359 h-1 exhibited by P. aeruginosa. On the other hand, analysis of doubling time of the bacteria revealed that P. aeruginosa had the shortest doubling time (td) of 0.249 and S. aureus had the longest doubling time of 2.726. Maximum optical density (OD600) which was studied for up to 6 hrs was achieved by P. aeruginosa (1.496), whereas, V. parahaemolyticus (1.277) had the lowest maximum optical density among all the bacteria strains.

E. coli S. pneumoniae V. parahaemolyticus S. aureus P. aeruginosa K. pneumoniae

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Figure 3.3: Growth profile of the bacterial host cultures. The bacteria host were grown in sterile brain-heart infusion broth (37.0 g. L-1Oxoid, Basingstoke, UK) at 37oC and 150 rpm for 6 hrs under aerobic conditions. Error bars represent standard error of the mean.

Table 3.2: Growth kinetics of bacterial hosts grown in batch cultures Specific Maximum optical Doubling Bacterial host cultures growth rate density (OD600) of time, td [g] , [h-1] bacteria V. parahaemolyticus 0.623 0.432 1.277

P. aeruginosa 0.359 0.249 1.496

S. aureus 0.644 0.446 1.476

E. coli 0.406 0.282 1.357 S. pneumoniae 0.453 0.314 1.333 K. pneumoniae 0.418 0.290 1.476

3.2.1.3 Enrichment culturing and bacteriophage isolation Using the methods presented in subsection 2.1.6, 2.1.7 and 2.1.8, a total of thirty-three bacteriophages targeting different bacterial strains, and having distinct morphological plaque formation were isolated from Sarawak limestone cave samples. Soil samples obtained from Fairy and Wind Caves, were cultured in Brain-heart infusion (BHI) broth containing 10 mM CaCl2 solution and a respective bacteria host, to screen for lytic bacteriophages. About 5 mL of this soil-bacteria culture was inoculated into liquefied nutrient agar supplemented with 1% (v/v) TTC solution (2,3,5-triphenyl tetrazolium chloride) and 10 mM CaCl2 solution, and the contents plated out on pre-warmed Petri dishes. Following an overnight incubation, plaques were formed in the areas where phages destroyed bacteria cells. Uninfected viable bacteria cells developed into a smooth lawn of confluent bacteria growth, which reduced TTC to red formazan turning the agar red. Tetrazolium chloride (TTC) which was incorporated into the agar served as a motility assay. The metabolic activity of viable active cells can break down TTC to TPF (1,3,5-triphenyl formazan), a red colored compound (Kumar, et al., 2011). Lytic bacteriophages were isolated based on their ability to form clear plaques on their respective bacteria lawns. Figure 3.4 shows plaque formation due to lysis of the bacterial host S. aureus and S. pneumoniae after 24 hrs incubation at 37oC. About 79% of the phage isolates were obtained from FCNR soil samples whereas the remaining 21% represented phages obtained from WCNR. In Figure 3.5, the isolated phage particles were enumerated using double-layer plaque assay and their titer recorded as PFU/mL.

Figure 3.4: Plaque appearance of bacteriophages infecting (A) S. aureus [left] and S. pneumoniae (B) [right]. The incubated Petri dishes contained nutrient agar supplemented with 10 mM CaCl2 and 1% TTC (2,3,5-triphenyltetrazolium chloride).

Figure 3.5: Phage titer determination of FCPA3 by double-layer plaque assay. Petri plates from top-left to top-right shows lower dilution of viral titer, the Petri plates from the lower- left to lower-right shows higher dilution of viral titer.

Table 3.3 outlines the sample description and phage plaque characteristics of the isolates obtained from Sarawak limestone cave (FCNR and WCNR) soil samples. Majority of the phage isolates exhibited distinctive features such as mixed plaque morphology suggesting the presence of different phage traits infecting the same bacterial host (Gallet, et al., 2011). Several turbid phages were discarded because it was likely they were formed by temperate phages which are not fit for phage therapy studies. After a careful examination of plaque morphology, distinctive phage plaques were amplified in BHI broth enriched with their respective bacteria host as explained in section 2.1.7. Amplified phage lysates were subjected to phage titer assay using the double-layer plaque technique so as to determine the concentration of the phage particles. Amongst all the isolates, P. aeruginosa infecting bacteriophages designated as FCPA4, WCSS4PA and WCSS5PA showed the highest phage titer (1015 PFU/mL). Figure 3.5, shows phage titer assay, determined by double-layer plaque assay for phage FCPA3 after 24 hrs of incubation at 37oC. Titrated phages were preserved in sterile cryotube containing 200 μL of 75% (v/v) glycerol in phage buffer (PB) using modified methods adapted from Fortier and Moineau (2009) and (Pardon, et al., 2014) as explained in subsection 2.1.10 and the cryotube was then stored in a freezer at -80oC.

Table 3.3: Morphological characteristics of bacteriophages isolated from FCNR and WCNR Plaque Designated phage Phage titer Sampling Origin Bacteria host Size Plaque description ID (PFU/mL) (mm) FCNR FCVP1 V. parahaemolyticus 6 Clear, round 1.19 x 109 FCNR FCVP2 V. parahaemolyticus 5 Clear, round 6.3 x 108 FCNR FCVP3 V. parahaemolyticus 4 Clear, round 1.1 x 107 FCNR FCVP4 V. parahaemolyticus 4 Clear, round 8.5 x 107 FCNR FCVP5 V. parahaemolyticus 6 Clear, round 8.0 x 106 FCNR FCVP6 V. parahaemolyticus 4 Clear, round 1.18 x 109 WCNR WCVP3 V. parahaemolyticus Nil Turbid Nil WCNR WCVP4 V. parahaemolyticus Nil Turbid Nil WCNR WCVP5 V. parahaemolyticus Nil Turbid Nil FCNR FCSA1 S. aureus 4 Clear, round 1.89 x 107 FCNR FCSA3 S. aureus 3 Clear, round 1.20 x 107 FCNR FCSA4 S. aureus 3 Clear, round 1.36 x 108 FCNR FCSA6 S. aureus 2 Clear, round 1.22 x 106 FCNR FCKP1 K. pneumoniae 3 Clear, round 2.26 x 1012 WCNR WCKP1 K. pneumoniae 3 Clear, round 6.1 x 1015 WCNR WCKP4 K. pneumoniae 2 Clear, round 1.51 x 1014 FCNR FCEC1 E. coli 6 Clear, round 4.3 x 106 FCNR FCEC3 E. coli 5 Clear, round 1.01 x 108

FCNR FCEC6 E. coli 5 Clear, round 4.2 x 107 FCNR FCEC7 E. coli Nil Turbid Nil FCNR FCPA1 P. aeruginosa 3 Clear, round 2.28 x 1013 FCNR FCPA2 P. aeruginosa 3 Clear, round 1.37 x 1013 FCNR FCPA3 P. aeruginosa 5 Clear, round 3.01 x 1014 FCNR FCPA4 P. aeruginosa 3 Clear, round 1.52 x 1015 FCNR FCPA5 P. aeruginosa 3 Clear, round 2.16 x 1013 FCNR FCPA6 P. aeruginosa 4 Clear, round 9.4 x 108 WCNR WCSS4PA P. aeruginosa Nil Clear, web-pattern 1.25 x 1015 WCNR WCSS5PA P. aeruginosa Nil Clear, web-pattern 4.5 x 1015 FCNR FCSP1 S. pneumoniae 5 Clear, round 1.50 x 108 FCNR FCSP2 S. pneumoniae 4 Clear, round 2.29 x 107 FCNR FCSP3 S. pneumoniae 4 Clear, round 1.19 x 108 FCNR FCSP4 S. pneumoniae 3 Clear, round 1.25 x 108 FCNR FCSP5 S. pneumoniae 3 Clear, round 1.87 x 107

3.2.1.4 Bacteriophage host range analysis One of the goals of this study was to determine the phage specificity with the expectation that some phages would have broader host range than others due to the presence or absence of phage receptor molecules or intracellular restriction mechanisms (Jensen, et al., 2015). Spot tests were performed on TSA Petri plates containing lawns of various bacteria as described in subsection 2.1.12. The Petri plates were then assessed for the presence of plaques on the lawns of the bacteria (Figure 3.6). Based on spot test results as shown in Table 3.4, the majority of phage isolates were capable of infecting E. coli (72.7%), P. aeruginosa (66.7%) and K. pneumoniae (48.5%) bacterial strains. The broadest host range was exhibited by a P. aeruginosa phage designated as FCPA3 which was capable of lysing S. aureus, K. pneumonia, E. coli and S. typhimurium bacterial strains. This phage exhibited high virulence on S. aureus and K. pneumoniae bacteria lawns. Generally, broad host range was seen in V. parahaemolyticus and P. aeruginosa phage isolates. For example, V. parahaemolyticus phages (FCVP1, FCVP2, FCVP3) were able to lyse bacteria stains S. aureus, P. aeruginosa and E. coli, while P. aeruginosa phages (FCPA1, FCPA2, FCPA4, FCPA5 and FCPA6) were capable of lysing bacteria strains S. aureus, E. coli and S. typhirium. In addition, bacterial strains S. pneumoniae and S. typhirium were lysed by the least number of phages among all the bacteria tested.

Figure 3.6: Re-confirmation of P. aeruginosa bacteriophage lytic ability by spot test assay. Bacteriophages were spot-tested on Tryptic soy agar (supplemented with 10 mM CaCl2) containing lawn of P. aeruginosa.

Table 3.4: Assessment bacteriophage host range by spot test assay Designated V. parahaem S. aureus P. S. pneumon K. pneumo E. coli S. Phage ID olyticus aeruginosa are niae typhirium FCVP1 + ++ ++ - - + - FCVP2 ++ ++ + - - ++ - FCVP3 ++ ++ ++ - - ++ - FCVP4 ++ ++ ++ - - ++ - FCVP5 ++ - ++ - - ++ - FCVP6 ++ - ++ - - ++ - WCVP3 - - - - + ++ - WCVP4 - - ++ - + ++ - WCVP5 - - ++ - - + - FCSA1 - ++ - - ++ + - FCSA3 - ++ - - ++ + - FCSA4 - - - - ++ + - FCSA6 - - - - ++ + - FCKP1 - - - ++ ++ - - WCKP1 - - - - ++ - - WCKP4 - - ++ - ++ - - FCEC1 - - - - ++ ++ - FCEC3 - - - - ++ ++ - WCEC6 - - - - ++ - - WCEC7 - - - - ++ - - FCPA1 - + ++ - - + + FCPA2 - + ++ - - + +

FCPA3 - ++ ++ - ++ + +  - + ++ - - + + FCPA4 FCPA5 - + ++ - - + + FCPA6 - + ++ - - + + WCSS4PA - - ++ - ++ - - WCSS5PA - - ++ - ++ - -

FCSP1 - - ++ ++ - ++ - FCSP2 - - ++ ++ - ++ - FCSP3 - - ++ ++ - ++ -  - - ++ - - - - FCSP4 FCSP5 - + ++ - - - -

Lysis pattern was measured qualitatively as (++) for full lysis, (+) for partial lysis and (-) for no lysis.

3.2.2 In-vitro studies on phage bacteriolytic activity and assessment of bacterial survival following phage treatment. 3.2.2.1 Phage bacteriolytic activity The lytic abilities of bacteriophages against P. aeruginosa PAO1 cells were evaluated in an in-vitro co-culture assay for up to 6 hrs at varied MOI ratios as shown in Figure 3.7 to Figure 3.15. The results showed that the growth of P. aeruginosa PAO1 was inactivated when co-cultured with phage in a concentration-dependent manner, with OD values declining more quickly at higher MOI (104 and 105) than at lower MOI (103, 102 or 101). The OD values decrease very quickly, just 30 minutes after phage addition except for phages FCPA4 and FCPA6, suggesting the occurrence of bacterial lysis. However, it was possible to differentiate these phages into three clusters, the first consisting of FCPA1, FCPA2, FCPA4 and FCPA6, for which OD values decreased slowly and steadily until the end of the incubation time when compared with uninfected control. This group was not very effective at inactivating the bacteria in all the tested MOI ratios except FCPA2 (MOI 105). The second cluster consisted of phages FCPA5, WCSS4PA and WCSS5PA. In this group, the OD values decreased slowly for a period of time and then rose slowly again until the end of the incubation time. For instance, in FCPA5, the OD decreased steadily for up to 4 hrs and then slowly started rising until the end of the 6 hrs of incubation. In phage WCSS5PA, the OD values decreased steadily for the first 3 hrs and then took a sharp rise until the end of the 6 hrs of incubation. In phage WCSS4PA, OD values were seen to decrease sharply in the first 2 hrs and then rose again slowly and steadily until the end of the 6 hrs of incubation, except for the highest MOI (105) where the lower OD values were maintained throughout the incubation period. The last cluster consisted of only the phage cocktail (Cocktail). In phage cocktail (Cocktail), the OD decreased sharply for the first 2 hrs then maintained this lower OD until the end of the 6 hrs of incubation. Table 3.5 shows absorbance readings obtained from the phage treated cultures at the end of the 6 hrs of incubation. From this result, bacteriophages FCPA3 (MOI 105), WCSS4PA (MOI 105) and Cocktail (MOI 104) showed the highest bacterial inactivation with OD values decreasing to 0.200, 0.319 and 0.288 when compared with the OD of untreated controls i.e. 1.370, 1.533, 1.557 respectively.

Table 3.5: Assessment of phage bacteriolytic activity at the end of 6 hrs of incubation Samples absorbance Phage ID Tested MOI ratio (OD600) FCPA1 101 1.377 102 1.362 103 1.461 104 1.283 105 1.155 Uninfected control 1.370 FCPA2 101 1.418 102 1.171 103 1.043 104 1.069 105 0.703 Uninfected control 1.370 FCPA3 101 0.766 102 0.566 103 0.588 104 0.383 105 0.200 Uninfected control 1.370 FCPA4 101 1.431 102 1.441 103 1.493 104 1.527 105 1.495 Uninfected control 1.563

FCPA5 101 1.407 102 1.129 103 0.941 104 0.919 105 0.900 Uninfected control 1.471 FCPA6 101 1.188 102 1.266 103 1.309 104 1.317 105 1.329 Uninfected control 1.563 WCSS4PA 101 1.229 102 1.189 103 1.168 104 0.897 105 0.319 Uninfected control 1.533 WCSS5PA 101 1.136 102 1.076 103 1.105 104 1.096 105 1.146 Uninfected control 1.533 Cocktail 101 0.945 102 0.616 103 0.349 104 0.288 105 0.405 Uninfected control 1.557

Control ΦFCPA1 (MOI 103) ΦFCPA1 (MOI 101) ΦFCPA1 (MOI 104) ΦFCPA1 (MOI 102) ΦFCPA1 (MOI 105)

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Figure 3.7: In-vitro bacteriolytic activity of FCPA1 at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage FCPA1 at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean

Control ΦFCPA2 (MOI 103) 1 ΦFCPA2 (MOI 10 ) ΦFCPA2 (MOI 104) 2 ΦFCPA2 (MOI 10 ) ΦFCPA2 (MOI 105)

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Figure 3.8: In-vitro bacteriolytic activity of FCPA2 at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage FCPA2 at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean

Control ΦFCPA3 (MOI 103) ΦFCPA3 (MOI 101) ΦFCPA3 (MOI 104) ΦFCPA3 (MOI 102) 5

2.0 ΦFCPA3 (MOI 10 )

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Figure 3.9: In-vitro bacteriolytic activity of FCPA3 at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with phage FCPA3 at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

Control ΦFCPA4 (MOI 103) ΦFCPA4 (MOI 101) ΦFCPA4 (MOI 104) 2 ΦFCPA4 (MOI 10 ) ΦFCPA4 (MOI 105)

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Figure 3.10: In-vitro bacteriolytic activity of FCPA4 at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage FCPA4 at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

Control ΦFCPA5 (MOI 103) ΦFCPA5 (MOI 101) ΦFCPA5 (MOI 104) ΦFCPA5 (MOI 102) ΦFCPA5 (MOI 105)

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Figure 3.11: In-vitro bacteriolytic activity of FCPA5 at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage FCPA5 at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

Control ΦFCPA6 (MOI 103) ΦFCPA6 (MOI 101) ΦFCPA6 (MOI 104) ΦFCPA6 (MOI 102) ΦFCPA6 (MOI 105)

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Figure 3.12: In-vitro bacteriolytic activity of FCPA6 at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage FCPA6 at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

Control ΦWCSS4PA (MOI 103) WCSS4PA (MOI 101) ΦWCSS4PA (MOI 104) ΦWCSS4PA (MOI 102) ΦWCSS4PA (MOI 105)

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Figure 3.13: In-vitro bacteriolytic activity of WCSS4PA at different MOI ratios. Mid–exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage WCSS4PA at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

Control ΦWCSS5PA (MOI 103) 1 ΦWCSS5PA (MOI 10 ) ΦWCSS5PA (MOI 104) 2 ΦWCSS5PA (MOI 10 ) ΦWCSS5PA (MOI 105)

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Figure 3.14: In-vitro bacteriolytic activity of WCSS5PA at different MOI ratios. Mid–exponential cultures of P. aeruginosa PAO1 were co-cultured with bacteriophage WCSS5PA at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

Control Φ(MOI 103) Φ(MOI 101) ΦCocktail (MOI 104) 2 Φ(MOI 10 ) ΦCocktail (MOI 105)

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Figure 3.15: In-vitro bacteriolytic activity of Cocktail at different MOI ratios. Mid– exponential cultures of P. aeruginosa PAO1 were co-cultured with phage cocktail (Cocktail) at different multiplicity of infection (MOI) ratios. Error bars represent standard error of the mean.

3.2.2.2 Assessment of bacterial survival following phage in-vitro bacteriolytic activity. To evaluate the efficiency of the phage isolates to inhibit or eradicate P. aeruginosa PAO1 cells, the in-vitro susceptibility of P. aeruginosa PAO1 bacteria cells to bacteriophages at varied MOI ratios were assessed at 6 hrs and 24 hrs post-infection as explained in subsection 2.2.4. The surviving bacterial cells were expressed as log10 CFU/mL and were compared with those of uninfected control. Surviving P. aeruginosa PAO1 cells following an in-vitro treatment with bacteriophages FCPA1, FCPA2, FCPA3, FCPA4, FCPA5, FCPA6, WCSS4PA, WCSS5PA and Cocktail at varied MOI ratios are presented in Figure 3.16 to 3.24.

The in-vitro susceptibility results of P. aeruginosa PAO1 cells to phage FCPA1 as presented in Figure 3.16, showed significant bacterial log reductions at both 6 hrs and 24 hrs post-infection. The lowest bacterial recovery was achieved at MOI of 105. Exactly

5 6 hrs post-infection, the recovered bacteria cells at MOI of 10 were 10.6 log10 CFU/mL and those of uninfected control were 16.9 log10 CFU/mL. This resulted in a 6.3 log reduction in bacteria cells. Even at lower MOI ratios (101, 102, 103, 104), FCPA1 managed to reduce P. aeruginosa PAO1 cells by 4.2, 4.7, 5.5 and 5.3 logs respectively.

5 At 24 hrs post-infection, recovered bacteria cells at MOI of 10 were 13.7 log10 CFU/mL and those of uninfected control were 19.2 log10 CFU/mL, resulting in a 5.5 log reduction in bacteria cells. The results obtained from ANOVA (Table 3.6) and Tukey-Kramer’s post hoc analysis revealed that there were significant differences among all the group means except when the mean of MOI 102 at 6 hrs was compared with the means of MOI 103 at 24 hrs and MOI 104 at 24 hrs, when the mean of MOI 103 at 6 hrs was compared with the means of MOI 104 at 6 hrs and MOI 105 at 6 hrs, when the mean of MOI 104 at 6 hrs was compared with the means of MOI 105 at 6 hrs, when the mean of MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs and MOI 104 at 24 hrs and when MOI 105 at 24 hrs, when the mean of MOI 102 at 24 hrs was compared with the means of MOI 105 at 24 hrs, when the mean of MOI 104 at 24 hrs was compared with the means of MOI 103 at 24 hrs and MOI 105 at 24 hrs, and when the uninfected control at 6 hrs was compared with the means of MOI 101 at 24 hrs, MOI 102 at 24 hrs and MOI 105 at 24 hrs, respectively.

Table 3.6: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with FCPA1

Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 38.048 12.683 0.359 0.3461

MOI 101 (24 hrs) 52.858 17.619 0.288 0.3098

MOI 102 (6 hrs) 36.504 12.168 0.279 0.3052

MOI 102 (24 hrs) 45.087 15.029 0.000351 0.0106

MOI 103 (6 hrs) 34.354 11.451 0.287 0.3092

MOI 103 (24 hrs) 55.312 18.437 0.098 0.1808

MOI 104 (6 hrs) 34.718 11.573 0.397 0.3639

MOI 104 (24 hrs) 42.918 14.306 0.0000792 0.0051

MOI 105 (6 hrs) 31.794 10.598 0.23 0.2768

MOI 105 (24 hrs) 41.078 13.693 0.171 0.2389

Control (6 hrs) 50.713 16.9043 0.2801 0.3056

Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares =286.728, 4.768; mean square =26.066, 0.199 and F statistic =130.803.

The results of phage FCPA2 (Figure 3.17) revealed significant bacterial log reductions in higher MOI ratios (103, 104, 105) than lower MOI ratios (101 and 102) at 6 hrs post- infection. MOI ratio of 104 had the highest bacterial log reduction when compared with the rest MOI ratios. Recovered bacteria cells were 7.7 log10 CFU/mL and those of the uninfected control were 16.9 log10 CFU/mL, resulting in a 9.2 log reduction in bacterial cells. On the other hand, MOI ratio of 103 showed the highest bacterial log reduction when compared with the rest tested MOI ratios at 24 hrs post-infection. At this MOI, the recovered bacteria cells were 13.7 log10 CFU/mL whereas those of uninfected control were 19.2 log10 CFU/mL resulting in a 5.5 log reduction in bacteria cells. The results obtained from ANOVA (Table 3.7) and Tukey-Kramer’s post hoc analysis revealed that

there were significant differences among all the group means except when the mean of MOI 102 at 6 hrs was compared with the means of MOI 103 at 24 hrs and MOI 104 at 24 hrs, when the mean of MOI 103 at 6 hrs was compared with the means of MOI 104 at 6 hrs and MOI 105 at 6 hrs, when the mean of MOI 104 at 6 hrs was compared with the means of MOI 105 at 6 hrs, when the mean of MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs and MOI 104 at 24 hrs and when MOI 105 at 24 hrs, when the mean of MOI 102 at 24 hrs was compared with the means of MOI 105 at 24 hrs, when the mean of MOI 104 at 24 hrs was compared with the means of MOI 103 at 24 hrs and MOI 105 at 24 hrs, and when the uninfected control at 6 hrs was compared with the means of MOI 101 at 24 hrs, MOI 102 at 24 hrs and MOI 105 at 24 hrs, respectively.

Table 3.7: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with FCPA2 Sample Standard Group Sum Mean variance deviation MOI 101 (6 hrs) 27.985 9.328 0.0000166 1.039 MOI 101 (24 hrs) 47.617 15.872 0.309 0.042 MOI 102 (6 hrs) 23.812 7.937 0.048 0.133 MOI 102 (24 hrs) 44.154 14.718 0.202 0.568 MOI 103 (6 hrs) 26.828 8.943 0.000227 0.015 MOI 103 (24 hrs) 41.185 13.728 0.222 0.471 MOI 104 (6 hrs) 41.015 13.672 0.018 0.218 MOI 104 (24 hrs) 50.945 16.982 0.322 0.45 MOI 105 (6 hrs) 36.049 12.016 1.08 0.004 MOI 105 (24 hrs) 46.876 15.625 0.002 0.556 Control (6 hrs) 50.713 16.9043 0.2801 0.3056 Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares =471.440, 4.405; mean square =42.858, 0.184, and F statistic =233.513.

The results of phage FCPA3, as shown in Figure 3.18 revealed presence of significant bacterial log reductions in samples infected at MOI of 104 and 105 when compared with the rest tested MOIs at 6 hrs post-infection. Recovered bacteria cells were 7.7 log10

CFU/mL and 8.2 log10 CFU/mL respectively, whereas those of an uninfected control was

16.9 log10 CFU/mL. This resulted in a 9.2 and 8.7 log reduction in bacterial cells respectively. At 24 hrs post-infection, MOI of 105 had the highest bacteria log reduction when compared with the rest MOIs. At this MOI, recovered bacteria cells were 10.9 log10

CFU/mL and those of uninfected control were 19.2 log10 CFU/mL, resulting in an 8.3 log reduction in bacteria cells. The results obtained from ANOVA (Table 3.8) and Tukey- Kramer’s post hoc analysis revealed that there were significant differences among all the group means except when the mean of MOI 101 at 6 hrs was compared with the means of MOI 104 at 24 hrs and MOI 105 at 24 hrs, when MOI 102 at 6 hrs was compared with the means of MOI 103 at 6 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the means of MOI 103 at 6 hrs was compared with the means of MOI 104 at 6 hrs, MOI 103 at 24 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the means of MOI 104 at 6 hrs was compared with the means of MOI 103 at 24 hrs and MOI 104 at 24 hrs, when the means of MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs, when the means of MOI 103 at 24 hrs was compared with the means of MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the means of MOI 104 at 24 hrs was compared with the means of MOI 105 at 24 hrs, and the mean of uninfected control at 6 hrs was compared with the means of MOI 101 at 24 hrs and MOI 102 at 24 hrs respectively.

Table 3.8: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with FCPA3 Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 35.221 11.74 0.000250 0.0091

MOI 101 (24 hrs) 44.981 14.994 0.328 0.3306

MOI 102 (6 hrs) 33.813 11.271 0.0000880 0.0054

MOI 102 (24 hrs) 44.252 14.751 0.0770 0.1605

MOI 103 (6 hrs) 30.751 10.25 0.0000238 0.0028

MOI 103 (24 hrs) 42.771 14.257 0.0000249 0.0029

MOI 104 (6 hrs) 22.952 7.651 0.155 0.2274

MOI 104 (24 hrs) 41.725 13.908 0.000115 0.0062

MOI 105 (6 hrs) 24.742 8.247 0.159 0.2302

MOI 105 (24 hrs) 32.596 10.865 0.293 0.3123 Control (6 hrs) 50.713 16.9043 0.2801 0.3056

Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares =368.556, 2.642; mean square =33.505, 0.110, and F statistic =304.227.

The results of phage FCPA4 as shown in Figure 3.19 revealed presence of significant bacterial log reductions in samples infected at MOI of 105 when compared with the rest MOIs (101, 102, 103, 104) at 6 hrs post-infection. Recovered bacteria cells at MOI 105 were 8.6 log10 CFU/mL whereas those of uninfected control were 16.9 log10 CFU/mL, resulting in an 8.3 log reduction of bacterial cells. At 24 hrs post-infection, MOI of 103 showed the highest bacteria log reduction when compared with the rest MOIs. At this

MOI, recovered bacteria cells were 12.2 log10 CFU/mL and those of uninfected control were 19.2 log10 CFU/mL, resulting in a 7.0 log reduction in bacterial cells. The results obtained from ANOVA (Table 3.9) and Tukey-Kramer’s post hoc analysis revealed that there were significant differences among all the group means except when the mean of

MOI 101 at 6 hrs was compared with the means of MOI 104 at 24 hrs and MOI 105 at 24 hrs, when MOI 102 at 6 hrs was compared with the means of MOI 103 at 6 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the means of MOI 103 at 6 hrs was compared with the means of MOI 104 at 6 hrs, MOI 103 at 24 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the means of MOI 104 at 6 hrs was compared with the means of MOI 103 at 24 hrs and MOI 104 at 24 hrs, when the means of MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs, when the means of MOI 103 at 24 hrs was compared with the means of MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the means of MOI 104 at 24 hrs was compared with the means of MOI 105 at 24 hrs, and the mean of uninfected control at 6 hrs was compared with the means of MOI 101 at 24 hrs and MOI 102 at 24 hrs respectively.

Table 3.9: Analysis of variance (ANOVA) results for recovery of the bacteria following an in-vitro treatment with FCPA4 Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 41.103 13.701 0.0009 0.0174

MOI 101 (24 hrs) 49.181 16.394 0.2594 0.294

MOI 102 (6 hrs) 40.505 13.502 0.1629 0.233

MOI 102 (24 hrs) 49.702 16.567 0.2465 0.2867

MOI 103 (6 hrs) 37.311 12.437 0.0626 0.1445

MOI 103 (24 hrs) 36.683 12.228 0 0.0036

MOI 104 (6 hrs) 35.299 11.766 0.3647 0.3487

MOI 104 (24 hrs) 38.334 12.778 0 0.0015

MOI 105 (6 hrs) 25.787 8.596 0.0001 0.0042

MOI 105 (24 hrs) 39.238 13.079 0 0.0021 Control (6 hrs) 50.713 16.9043 0.2801 0.3056

Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares =15.5883, 0.1097; mean square =33.505, 0.110, and F statistic =142.0855.

The results of phage FCPA5 (Figure 3.20) revealed the presence of significant bacterial log reduction in samples infected at higher MOI (103, 104, 105) than lower MOI (101 and 102) at 6 hrs post-infection. The highest bacterial log reduction was observed from recovered bacterial cells which were infected at MOI of 105. At this MOI, recovered bacterial cells were 7.5 log10 CFU/mL and those of uninfected control were 16.9 log10 CFU/mL, resulting in a 9.4 log reduction in bacterial cells. On the other hand, recovered bacterial cells harvested at 24 hrs post-infection revealed a significant log reduction at MOI of 104 when compared with the rest MOIs. At this MOI, recovered bacteria cells were 13.3 log10 CFU/mL whereas those of uninfected control were 19.2 log10 CFU/mL resulting in a 5.9 log reduction in bacterial cells. The results obtained from ANOVA (Table 3.10) and Tukey-Kramer’s post hoc analysis revealed that there were significant differences among all the group means except when the mean of MOI 101 at 6 hrs was compared with the means of MOI 102 at 6 hrs and MOI 104 at 24 hrs, when MOI 103 at 6 hrs was compared with the means of MOI 104 at 6 hrs and MOI 105 at 6 hrs, when MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs and MOI 103 at 24 hrs, when MOI 103 at 24 hrs was compared with the means of MOI 101 at 24 hrs and MOI 105 at 24 hrs, and when the mean of uninfected control at 6 hrs was compared with the mean of MOI 101 at 24 hrs, MOI 102 at 24 hrs and MOI 103 at 24 hrs, respectively.

Table 3.10: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with FCPA5 Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 38.189 12.73 0.000154 0.0071

MOI 101 (24 hrs) 50.209 16.736 0.297 0.3147

MOI 102 (6 hrs) 34.592 11.531 0.001 0.02

MOI 102 (24 hrs) 50.532 16.844 0.271 0.3005

MOI 103 (6 hrs) 28.928 9.643 0.341 0.3373

MOI 103 (24 hrs) 47.148 15.716 0.199 0.2573

MOI 104 (6 hrs) 26.334 8.778 0.000360 0.0109

MOI 104 (24 hrs) 39.935 13.312 0.0000184 0.0026

MOI 105 (6 hrs) 22.544 7.515 0.186 0.2489

MOI 105 (24 hrs) 44.632 14.877 0.304 0.3183 Control (6 hrs) 50.713 16.9043 0.2801 0.3056

Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares =448.240, 3.760; mean square =40.749, 0.157, and F statistic =260.117.

The results of phage FCPA6, as shown in Figure 3.21, revealed significant log reduction in bacteria at MOI of 103 and 104 compared with the rest MOIs at 6 hrs post-infection. The highest bacterial log reduction was observed in samples infected at MOI of 104. At this MOI ratio, recovered bacterial cells were 7.3 log10 CFU/mL whereas those of

-1 uninfected control were 16.9 log10CFU.mL , resulting in 9.6 log reduction in bacterial cells. On the other hand, bacterial cells recovered at 24 hrs post-infection revealed a significant bacterial log reduction at MOI of 105 when compared with the rest MOI ratios. At this MOI, recovered bacteria cells were 13.0 log10 CFU/mL whereas those of uninfected control were 19.2 log10 CFU/mL, resulting in a 6.2 log reduction in bacterial cells. The results obtained from ANOVA (Table 3.11) and Tukey-Kramer’s post hoc analysis revealed that there were significant differences among all the group means

except when the mean of MOI 101 at 6 hrs was compared with the means of MOI 102 at 6 hrs and MOI 105 at 6 hrs, when the mean of MOI 105 at 6 hrs was compared with the means of MOI 102 at 6 hrs and MOI 101 at 6 hrs, when the mean of MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs and MOI 103 at 24 hrs, and when the mean of uninfected control at 6 hrs was compared with the mean of MOI 102 at 24 hrs and MOI 103 at 24 hrs, respectively.

Table 3.11: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with FCPA6 Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 50.713 16.904 0.280 0.1921 MOI 101 (24 hrs) 57.498 19.166 0.000219 0.0102 MOI 102 (6 hrs) 50.713 16.904 0.28 0.3482 MOI 102 (24 hrs) 57.498 19.166 0.000219 0.0073 MOI 103 (6 hrs) 50.713 16.904 0.28 0.3896 MOI 103 (24 hrs) 57.498 19.166 0.000219 0.2938 MOI 104 (6 hrs) 50.713 16.904 0.280 0.1479 MOI 104 (24 hrs) 57.498 19.166 0.000219 0.0062 MOI 105 (6 hrs) 50.713 16.904 0.28 0.3025 MOI 105 (24 hrs) 57.498 19.166 0.000219 0.0023 Control (6 hrs) 50.713 16.9043 0.2801 0.3056 Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares (46.036, 3.64) and mean square (4.185, 0.140), F statistic (229.857).

The results of phage WCSS4PA as seen in Figure 3.22, showed significant log reductions in bacteria cells at 6 hrs post-infection in all the MOI ratios. However, the highest bacterial log reduction was observed in samples infected at MOI of 105. At this MOI ratio, the recovered bacterial cells were 6.6 log10 CFU/mL and those of uninfected control were 16.9 log10 CFU/mL, resulting in a 10.3 log reduction in bacterial cells. Similarly, the recovered bacterial cells at 24 hrs post-infection revealed significant bacterial log reductions in all the MOI ratios. However, the highest log reduction was observed in bacterial cultures infected at MOI of 104. At this MOI, recovered bacteria cells were 8.7 log10 CFU/mL whereas those of uninfected control were 19.2 log10 CFU/mL, resulting in a 10.5 log reduction in bacterial cells. The results obtained from ANOVA (Table 3.12) and Tukey-Kramer’s post hoc analysis revealed that there were significant differences among all the group means except when the mean of MOI 101 at 6 hrs was compared with the means of MOI 102 at 6 hrs, MOI 103 at 6 hrs, MOI 104 at 6 hrs, MOI 101 at 24 hrs, MOI 102 at 24 hrs, MOI 103 at 24 hrs and MOI 105 at 24 hrs, the mean of MOI 102 at 6 hrs was compared with the means of MOI 103 at 6 hrs, MOI 104 at 6 hrs, MOI 101 at 24 hrs, MOI 102 at 24 hrs, MOI 103 at 24 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, the mean of MOI 103 at 6 hrs was compared with the means of MOI 101 at 24 hrs, MOI 103 at 24 hrs and MOI 104 at 24 hrs, the mean of MOI 104 at 6 hrs was compared with the means of MOI 101 at 24 hrs, MOI 102 at 24 hrs and MOI 103 at 24 hrs, the mean of MOI 101 at 24 hrs was compared with the means of MOI 102 at 24 hrs, MOI 103 at 24 hrs and MOI 105 at 24 hrs, the mean of MOI 102 at 24 hrs was compared with the means of MOI 103 at 24 hrs, and MOI 105 at 24 hrs and the mean of MOI 103 at 24 hrs was compared with the means of MOI 104 at 24 hrs, and MOI 105 at 24 hrs, respectively.

Table 3.12: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with WCSS4PA Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 31.276 10.425 0.0710 0.1535

1 MOI 10 (24 hrs) 31.311 10.437 0.247 0.287

MOI 102 (6 hrs) 30.204 10.068 0.24 0.2828

MOI 102 (24 hrs) 32.645 10.882 0.263 0.2958

MOI 103 (6 hrs) 27.255 9.085 0.0000298 0.0032

MOI 103 (24 hrs) 28.894 9.631 0.258 0.293

MOI 104 (6 hrs) 31.956 10.652 0.0190 0.0805

MOI 104 (24 hrs) 26.149 8.716 0.241 0.2836

MOI 105 (6 hrs) 19.876 6.625 0.166 0.235

MOI 105 (24 hrs) 31.995 10.665 0.151 0.2242 Control (6 hrs) 50.713 16.9043 0.2801 0.3056

Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares (399.208, 3.871) and mean square (36.292, 0.161), F statistic (225.014).

The results of phage WCSS5PA as seen in Figure 3.23, revealed the lowest bacterial log reduction in samples infected at MOI of 104 at 6 hrs post-infection when compared with the rest MOI ratios. At this MOI, the recovered bacterial cells were 12.1 log10 CFU/mL whereas those of uninfected control were 16.9 log10 CFU/mL, resulting in a 4.8 log reduction in bacterial cells. At 24 hrs post-infection, the highest bacteria log reduction was observed in cultures infected at MOI of 105. At this MOI, recovered bacterial cells were 12.2 log10 CFU/mL whereas those of uninfected control were 19.2 log10 CFU/mL, resulting in a 7.0 log reduction in bacterial cells. The results obtained from ANOVA (Table 3.13) and Tukey-Kramer’s post hoc analysis revealed that there were significant

differences among all the group means except when the mean of MOI 101 at 6 hrs was compared with the means of MOI 102 at 6 hrs, MOI 103 at 6 hrs, MOI 105 at 6 hrs and MOI 101 at 24 hrs, when the mean of MOI 102 at 6 hrs was compared with the means of MOI 103 at 6 hrs, MOI 104 at 6 hrs, MOI 105 at 6 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the mean of MOI 103 at 6 hrs was compared with the means of MOI 105 at 6 hrs and MOI 104 at 24 hrs, when the mean of MOI 104 at 6 hrs was compared with the means of MOI 104 at 24 hrs, and when the mean of MOI 101 at 24 hrs was compared with the means MOI 102 at 24, respectively.

Table 3.13: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with WCSS5PA. Sample Standard Group Sum Mean variance deviation

MOI 101 (6 hrs) 40.725 13.575 0.0550 0.135 MOI 101 (24 hrs) 47.243 15.748 0.116 0.1968 MOI 102 (6 hrs) 37.934 12.645 0.182 0.246 MOI 102 (24 hrs) 54.215 18.072 0.000388 0.0114 MOI 103 (6 hrs) 39.462 13.154 0.00200 0.0251 MOI 103 (24 hrs) 44.928 14.976 0.0000494 0.0041 MOI 104 (6 hrs) 36.186 12.062 0.0000330 0.0033 MOI 104 (24 hrs) 39.785 13.262 0.0000132 0.0021 MOI 105 (6 hrs) 40.468 13.489 0.007 0.0495 MOI 105 (24 hrs) 36.557 12.186 0.244 0.2852 Control (6 hrs) 50.713 16.9043 0.2801 0.3056 Control (24 hrs) 57.498 19.166 0.000218 0.0085 sample size mean =3; degrees of freedom =11,24; sum of squares (185.790, 1.773) and mean square (16.890, 0.074), F statistic (228.652).

The results of phage cocktail (Cocktail) as shown in Figure 3.24, revealed significant bacterial log reductions in all the MOI ratios at both 6 hrs and 24 hrs post-infection. At

6 hrs post-infection, the lowest bacterial recovery was 5.08 log10 CFU/mL obtained from

4 samples treated at MOI 10 . The uninfected control count was 16.90 log10 CFU/mL, resulting in an 11.82 log reduction in bacterial cells. At 24 hrs post-infection, MOI of 102 had the highest bacterial log reduction when compared with the rest MOI ratios. At this

MOI, recovered bacterial cells were 8.34 log10 CFU/mL whereas those of uninfected control were 19.2 log10 CFU/mL, resulting in a 10.86 log reduction in bacteria cells. The results obtained from ANOVA (Table 3.14) and Tukey-Kramer’s post hoc analysis revealed that there were significant differences among all the group means except when the mean of MOI 101 at 6 hrs was compared with the means of MOI 102 at 24 hrs, MOI 103 at 24 hrs, MOI 104 at 24 hrs and MOI 105 at 24 hrs, when the mean of MOI 102 at 6 hrs was compared with the means of MOI 102 at 24 hrs, when the mean of MOI 103 at 6 hrs was compared with the means of MOI 104 at 6 hrs and MOI 105 at 6 hrs, when the mean of MOI 104 at 6 hrs was compared with the means of MOI 105 at 6 hrs, when the mean MOI 102 at 24 hrs was compared with the means of MOI 104 at 24 hrs, when the mean MOI 103 at 24 hrs was compared with the means of MOI 104 at 24 hrs and MOI 105 at 24 hrs, and when the mean MOI 104 at 24 hrs was compared with the means of MOI 105 at 24 hrs, respectively.

Table 3.14: Analysis of variance (ANOVA) results for the recovery of bacteria following an in-vitro treatment with Cocktail. Sample Standard Group Sum Mean variance deviation MOI 101 (6 hrs) 26.691 8.897 0.000648 0.0147 MOI 101 (24 hrs) 39.284 13.095 0.00002.84 0.0031 MOI 102 (6 hrs) 22.766 7.589 0.26 0.0156 MOI 102 (24 hrs) 25.023 8.341 0.148 0.2222 MOI 103 (6 hrs) 17.608 5.869 0.0000345 0.0034 MOI 103 (24 hrs) 28.279 9.426 0.244 0.285 MOI 104 (6 hrs) 15.241 5.08 0.0000303 0.0032 MOI 104 (24 hrs) 27.447 9.149 0.175 0.2415 MOI 105 (6 hrs) 17.04 5.68 0.002 0.0234 MOI 105 (24 hrs) 29.169 9.723 0.00200 0.0245 Control (6 hrs) 26.691 8.897 0.000648 0.0147 Control (24 hrs) 39.284 13.095 0.0000284 0.0031 sample size mean =3; degrees of freedom =11,24; sum of squares (636.020, 1.2.223) and mean square (57.820, 0.093), F statistic (624.098)

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.16: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with FCPA1 at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104 MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.17: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with FCPA2 at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.18: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with FCPA3 at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.19: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with FCPA4 at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.20: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with FCPA5 at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.21: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with FCPA6 at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.22: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with WCSS4PA at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

MOI 101 MOI 103 MOI 105 25

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.23: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with WCSS5PA at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

Control MOI 102 MOI 104

1 3 5 25 MOI 10 MOI 10 MOI 10

15 CFU/mL

10 10

Log 5

0 rs rs h h 6 4 2 Time

Figure 3.24: Survival of P. aeruginosa PAO1 cells after an in-vitro treatment with  Cocktail at different MOI ratios. Bacteria recovery was performed at 6 hrs and 24 hrs post-incubation. Error bars represent standard error of the mean.

3.2.2.3 Survival of bacterial cells on sand treated samples The ability of phage isolates to inhibit or eradicate P. aeruginosa PAO1 bacterial cells in experimentally contaminated sand samples were assessed at 0 hr, 6 hrs, 24 hrs and 48 hrs post-treatment. The surviving bacterial cells following treatment with phages

(FCPA3, WCSS4PA and Cocktail) were expressed as log10 CFU/mL and were compared with those of uninfected control as shown in Figure 3.25. The highest bacteria log reduction was seen exactly 6 hrs after treatment with phages (FCPA3, WCSS4PA and

Cocktail). Recovered bacterial cells were 7.04 log10 CFU/mL, 6.61 log10 CFU/mL and 5.55 log10 CFU/mL respectively.

This resulted in 4.6, 5.03 and 6.09 logs reduction respectively when compared with the uninfected control (11.64 log10 CFU/mL). The highest bacterial log reduction was 6.09 log10 CFU/mL obtained from sand samples treated with a phage cocktail (Cocktail). At 24 hrs and 48 hrs post-treatment, surviving bacterial counts showed no significant difference when compared with that of the untreated control. The ANOVA data presented in Table 3.15-3.18 and post hoc analysis using the Tukey-Kramer’s procedure (α=0.05) further revealed that at 6 hrs post-treatment, the mean of WCSS4PA (M= 6.608; SD= 0.182), and cocktail (M= 5.554; SD= 0.205) were significantly different from the mean of FCPA3 (M= 7.043; SD= 0.281), and untreated control (M= 11.645; SD= 0.643).

Table 3.15: Analysis of variance (ANOVA) results for surviving bacterial cells recovered from sand treated samples at 0 hr using different phage samples. Sample Standard Group Sum Mean variance deviation

30.5747 10.19 0.019 0.079 ⏀FCPA3

29.0346 9.678 0.269 0.3 ⏀WCSS4PA

⏀Phage 29.5304 9.844 0.177 0.243 Cocktail 29.3091 9.77 0.303 0.318 ⏀Control sample size mean =3; degrees of freedom =3, 8; sum of squares = 0.4529, 1.5357; mean square =0.1510, 0.1920 and F statistic =0.7864.

Table 3.16: Analysis of variance (ANOVA) results for surviving bacterial cells recovered from sand treated samples at 6 hrs using different phage samples.

Sample Standard Group Sum Mean variance deviation

⏀FCPA3 21.13 7.043 0.079 0.162

⏀WCSS4PA 19.82 6.608 0.033 0.104

⏀Phage Cocktail 16.66 5.554 0.042 0.118

34.93 11.64 0.414 0.371 ⏀Control sample size mean =3; degrees of freedom =3, 8; sum of squares = 65.3752, 1.1349; mean square =21.7917, 0.1419 and F statistic =153.6141.

Table 3.17: Analysis of variance (ANOVA) results for surviving bacterial cells recovered from sand treated samples at 24 hrs using different phage samples. Sample Standard Group Sum Mean variance deviation

⏀FCPA3 24.1513 8.05 0.0001 0.006

⏀WCSS4PA 23.1924 7.731 0.172 0.24

⏀Phage Cocktail 22.2131 7.404 0.142 0.218

⏀Control 21.5348 7.178 0.183 0.247 sample size mean =3; degrees of freedom =3, 8; sum of squares = 1.3074, 0.9961; mean square =0.4358, 0.1245 and F statistic =3.4998.

100

Table 3.18: Analysis of variance (ANOVA) results for surviving bacterial cells recovered from sand treated samples at 48 hrs using different phage samples.

Sample Standard Group Sum Mean variance deviation

⏀FCPA3 23.1346 7.712 0.166 0.235

⏀WCSS4PA 21.1268 7.042 0.02 0.081 ⏀Phage Cocktail 23.2816 7.761 0.343 0.338

⏀Control 22.666 7.555 0.094 0.177 sample size mean =3; degrees of freedom =3, 8; sum of squares = 0.9719, 1.2446; mean square =0.3240. 0.1556 and F statistic =2.0834.

Control (uninfected) ΦFCPA3 ΦWCSS5PA ΦCocktail 15

10 CFU/mL

10 5 Log

0 rs rs rs rs h h h h 0 6 4 8 2 4 Time

Figure 3.25: Survival of P. aeruginosa PAO1 cells on sand samples after treatment with bacteriophages. Error bars represent standard error of the mean.

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3.3 Discussion This study reports on isolation, host range analysis, and assessment of in-vitro bacteriolytic activities of lytic phages isolated from Sarawak limestone caves (FCNR and WCNR). Investigative studies designed to test the potentials of selected P. aeruginosa phages to decontaminate sand samples are also reported. The study of viral diversity from limestone caves is very limited despite the abundance of caves all over the world. Most studies on phage isolation have utilized sewage as an optimal resource (Lobocka, et al., 2014). Although caves are considered as an extreme environment to life due to lack of organic carbon input from photosynthesis and absence of light and various physicochemical micro-gradients, studies have reported on the presence of vast microbial communities with unexpected biodiversity (Northup and Lavoie, 2001, Tomczyk-Żak and U., 2015). Nevertheless, caves have been reported to harbor microorganisms that display variable enzymatic and antimicrobial activities which are different from those observed in other extreme environments. This further explains that caves are rich reservoir of potential antimicrobials and suggests that investigating cave microbiota opens new frontiers for drug discovery (Ghosh, et al., 2016, Lamprinou, et al., 2015, Nimaichand, et al., 2015). It is crucial to understand bacteriophages and their interactions with bacterial hosts as this provides insights into the molecular biology and may result to an improved understanding of treatment methods against bacterial infection (Bolger-Munro, et al., 2013). The study of bacterial growth kinetics is specifically significant in determining the number of bacterial cells present in the liquid medium (Mohammed, 2013). Previous studies have reported that metabolic state of bacterial cells influences their susceptibility to phage infection, phage latent period and burst size and hence the success of new phage isolation attempts (Weinbauer, 2004). In most cases, exponentially growing cells are the most susceptible and can support the fastest and the most efficient phage production (Wommack and Colwell, 2000). It has been reported that Gram-negative bacteria such as E. coli tend to minimize their overall rate of protein synthesis while upgrading the expression of certain groups of proteins recognized as stationary phage specific . These proteins safeguard cells from oxidative damage and allow cells to stay viable during stationary phase (Braun, et al., 2006). Furthermore, it has also been urged that due to nutrient starvation, stationary phase cells decrease in 102

size and become more spherical rather than rod-like shape thus, providing a very small surface area to enable proper binding of the phage (Abedon, 1990, Ingraham, et al., 1983, Lange and Hengge-Aronis, 1991). Since stationary phase bacterial cells are smaller, the number of collision between phage and bacterial cells is significantly lowered because the cells tend to absorb less phage resulting to the production of insufficient progeny (Braun, et al., 2006). Nevertheless, factors such as cell metabolic poisons or free phage poisons released by cells in the media can reduce bacterial susceptibility to infection and phage progeny production (Abedon, 1990). Therefore, due to dramatic effects associated with the use of stationary phase bacteria during phage therapy studies, it's recommended to use log phase cultures for optimal viral progeny production. Thus, the growth profiles of the selected phage host i.e. V. parahaemolyticus, S. aureus, K. pneumoniae, E. coli, P. aeruginosa and S. pneumoniae were performed as shown in Figure 3.3 and Table 3.2, and mid-exponential phase bacterial cultures were employed during phage isolation and decontamination experiments.

About 33 lytic bacteriophages were isolated from FCNR and WCNR soil samples following an enrichment technique. Among these isolates, were two multiphages designated as WCSS4PA and WCSS5PA. Majority of these phage isolates were obtained from FCNR soil samples (79%). Despite phage abundance in the environment, less than 1% of phage species present in the environmental samples can be detected by plaque assay with cultivable hosts (Ashelford, et al., 2003, Williamson, et al., 2003). The possibility to visualize bacterial host lysis due to phage attack, in the form of plaques on the lawns of bacterial cells enables detection and isolation of most of the environmental phages against cultivable hosts, if only they are present (Kropinski, et al., 2009, Mazzocco, et al., 2009). Numerous ways have been proposed to enhance phage plaque visibility on a bacterial lawn. A feasible method may involve the use of compounds such as 2,3,5-triphenyltetrazolium chloride (TTC), ferric ammonium citrate and sodium thiosulfate. These compounds facilitate visualization or detection of plaques that are too small or too turbid to be easily seen (McLaughlin and Balaa, 2006). Sublethal doses of antibiotics such as 2.5–3.5 μg/mL of ampicillin can be incorporated into the top agar to improve phage plaque contrast. This method enables the formation of plaques with

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increased diameter and visibility in standard conditions such as in the case of E. coli phages (Łoś, et al., 2008). Phage isolation reported in this study utilized pour plate method in which 1% TTC (2,3,5-triphenyl tetrazolium chloride) solution was added. This enabled improved resolution of phage plaques as seen in Figure 3.4. The use of TTC (2,3,5-triphenyl tetrazolium chloride) to improve phage plaque resolution was first reported by Pattee (1966) who worked on Phage 83, which was employed in the genetic analysis of Staphylococcus aureus. In his study, phage isolation was carried out using the agar-layer technique and the plates were incubated at 37oC for 8 hrs or until the plaques were sufficiently developed to be scored. The assay plates containing fully developed plaques were then flooded with 10 mL of TSB containing 0.1% TTC (2,3,5-triphenyl tetrazolium chloride) solution and plates were incubated for 20 minutes at 37oC. Each plaque appeared as sharp and clear area against the intense red background produced by the reduction of TTC to the insoluble formazan by the indicator cells.

Elimination of temperate phages from the collection of newly obtained isolates is one of the most important early tasks in the selection of phages for therapeutic use, as temperate phages are estimated to comprise about 50% of environmental isolates (Ackermann, 2005). A commonly accepted criterion to distinguish obligately lytic and temperate phages is the ability to form clear plaques by the former (Guttman, et al., 2005). In most cases, plaque clarity is a good indicator of phage propagation strategy. However, the preliminary classification of a phage as obligatory lytic or temperate based on plaque observation should be treated with caution. For instance, Lobocka, et al. (2014) postulated that obligately lytic phages that form clear plaques can be more or less overgrown by resistant or infection escaping bacteria on cell layers of certain other strains and make the impression of being turbid. Following isolation, distinctive plaques were amplified in BHI broth containing respective bacterial host. The contents were filter sterilized and the titer of lysates was determined as seen in Figure 3.5 and Table 3.3.

Bacteriophage host-range analysis is a crucial factor in assessing phage diversity in the environment (Malki, et al., 2015). Broad host range phages are rendered suitable in phage therapy or phage biocontrol applications. In phage therapy, a broad host range phage that can kill multiple species of bacteria is equivalent to a broad spectrum

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antibiotic (Ross, et al., 2016). Thus, a smaller number of broad host range is more useful than many narrow host range phages. Another key advantage of host range analysis in phage therapy studies is the specificity of the phage-host range which spares non- pathogenic bacteria from being killed during the treatment. Contrarily, this same specificity may limit the ability and usage of a specific phage to a small set of potential pathogens requiring more precise diagnosis (Mapes, et al., 2016, Nilsson, 2014, Ross, et al., 2016). In the present study, P. aeruginosa and V. parahaemolyticus infecting bacteriophages exhibited the broadest host range among all the isolates. Interestingly, this broad lysis spectrum extended beyond a single bacteria phylum. For instance, V. parahaemolyticus phages designated as FCVP2, FCVP3 and FCVP4 were capable of infecting S. aureus bacteria which belongs to a completely different phylum i.e. Eubacteria. Another important feature observed during the host range analysis was the ability of some phage isolates to display trans-subdomain infectivity between gram positive and gram-negative bacterial hosts. For instance, S. pneumoniae phage isolates (FCSP1, FCSP2 and FCSP3) were able to infect and lyse P. aeruginosa and E. coli bacteria. This has been previously argued that such results might be caused not by the added bacteriophage but by the temperate bacteriophage which was originally in the host bacteria tested (Khan, et al., 2002). Previous studies have assigned classification as a “generalist” when a phage demonstrates capacity to infect more than one species of a bacterial genus, while some restricting the definition further to include strains of a specific species (Bono, et al., 2013, Czajkowski, et al., 2014, Merabishvili, et al., 2014). Similar findings have been reported by Malki, et al. (2015) where bacteriophages isolated from lake Michigan was capable of infecting several bacteria phyla and it was proposed that such a broad-host-range was likely related to the oligotrophic nature of the lake and the competitive benefit this characteristic may have contributed to phages in nature. These results imply that bacteriophage host-range is not always genera-restricted, and the oligotrophic environment of Fairy cave might have in one way or another contributed to the broad lytic spectrum exhibited by V. parahaemolyticus infecting phage isolates. This scenario has also been highlighted by (Nilsson, 2014) where it was urged that phages with the ability to use more universal surface receptors for adsorption, exhibit broader host range and are usually found in environments with poor nutrients. 105

The host range assay results also revealed that a significant number of the phage isolates failed to infect some bacteria strains such as V. parahaemolyticus, S. pneumoniae, and S. typhimurium. The resistance of bacteria on a bacteriophage may be due to several mechanisms. These include modification of phage attachment or adsorption sites (receptors), restriction-modification systems and CRISPER-Cas mechanisms or Clustered regularly interspaced short palindromic repeats (CRISPRs) and the CRISPR-associated (cas) genes (Seed, 2015, Sharma, et al., 2017). Alteration of phage adsorption sites (receptors) appears to be the most common mechanism by which bacteria evade phage infection and become resistant to phage (Bohannan and Lenski, 2000, Hyman and Abedon, 2010). Additionally, bacteria may synthesize exopolysaccharide (EPS) or masking proteins e.g. protein A of S. aureus to mask the phage receptor and thus conferring resistance to phage attack. To encounter the effect of EPS or masking proteins, bacteriophages may conquer the barrier by cleaving the EPS layer using polysaccharide lyase or a polysaccharide hydrolase (Labrie, et al., 2010, Örmälä and Jalasvuori, 2013). Bacteria may also possess restriction-modification systems that defend hosts from exogenous DNA. In this case, bacteria system can recognize and modify the phage DNA. In most cases, the phage DNA is cleaved by restriction endonucleases upon entering the bacterial cell through the restriction- modification system and thus protecting bacterial cell from phage DNA attack (Pleška, et al., 2016, Sharma, et al., 2017). To encounter this, phages may adopt an anti- restriction strategy to avoid recognition by endonuclease enzyme. For example, T4 phage evades restriction endonuclease attack because it possesses hydroxymethylcytosine (HMC) instead of cytosine. Even so, some bacteria may modify their system to recognize hydroxymethylcytosine (HMC) and destroy phage DNA (Bickle and Kruger, 1993, Borgaro and Zhu, 2013). Interestingly, anti-restriction strategy in Staphylococcus phage K possesses 5′ GATC-3′ cleavage site which confers DNA protection from restriction endonucleases (Bryson, et al., 2015, Tock and Dryden, 2005).

CRISPER-Cas mechanism presents a novel strategy by which prokaryotes acquire resistance against viruses (Sharma, et al., 2017). The main function of CRISPER-Cas is to provide immunity against foreign DNA such as phage genomic DNA and plasmid

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DNA (Gasiunas, et al., 2014). Clustered regularly interspaced short palindromic repeats (CRISPR) loci are arrays of short repeats separated by equally short “spacer” sequences (Biswas, et al., 2016). Along with the CRISPR-associated (cas) genes, encode an adaptive immune system of archaea and bacteria that protects the cell against viral infection (Barrangou, et al., 2007, Marraffini and Sontheimer, 2008). This system functions by inserting a short piece of an infecting viral genome as a spacer in the CRISPR array. The spacer sequence is transcribed and processed to generate a small antisense RNA (the CRISPR RNA or crRNA) that is used as a guide for the recognition and destruction of the invader in subsequent infections (Brouns, et al., 2008, Carte, et al., 2008, Deltcheva, et al., 2011). Thus, spacer acquisition immunizes the bacterium and its progeny against the virus from which it was taken. Barrangou, et al. (2007) has highlighted an example of antiphage activity of CRISPER-Cas mechanism in Streptococcus thermophiles where exposure to virulent phage gave rise to the phage- resistant mutants due to insertion of additional 30 bp spacer resembling protospacer of infecting phage. The event of acquiring immunity against phage can be explained briefly in the following steps like adaptation or spacer attainment, transcription of acquired spacer (small CRISPER RNAs (crRNAs), on recurrent phage attack this crRNAs form a complex with Cas protein), and immunity against phage (crRNAs-Cas complex direct nuclease to trace and chop the invading phage DNA (Marraffini, 2015).

Another key observation seen in this study was the inability of some phage isolates (e.g. WCVP3, WCVP4, WCVP5, FCSA4, FCSA6, FCSP4 and FCSP5) to lyse the bacteria hosts from which they were first isolated during the host range analysis experiments. Although plaque formation was not observed, this does not necessarily mean that infection did not occur. It is possible that the phage-infected the host bacteria and resulted in a lysogenic relationship. But regardless of whether bacteriophage and the host started lysogenic interactions or not, the observed phenomena certainly indicate that infectivity of the bacteriophages changed or the resistance of host bacteria to the bacteriophages varied during the course of the study. The possibility that these bacteriophages could not re-infect their bacterial hosts might be due to the occurrence of spontaneous single mutation in the host bacteria which caused it to gain resistance to the phage (Khan, et al., 2002). According to Ross, et al.

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(2016), bacteriophage host range is not a fixed property of each species of bacteriophage. Rather, it is one that can evolve over time and can show unexpected plasticity. Modifying procedures and growth conditions can favor the isolation of novel phages with broader host ranges. By mixing a few well differentiated phage host bacterial strains in a cultivation flask which is inoculated with an original source of phages (typically a filtrate of water, sewage, soil suspension etc.), usually suffices for the isolation of polyvalent phages assuming they are present in the tested sample (Carvalho, et al., 2010, Lobocka, et al., 2014, Van Twest and Kropinski, 2009). For instance, Mapes, et al. (2016) developed a host range expansion protocol that aimed at broadening the host range of P. aeruginosa-specific bacteriophages. Their study reported culturing a mixture of four phages with a mix of 16 different host strains and isolated individual phage strains by plaque isolation after multiple passages of phage mix onto the fresh mix. Over the course of 30 cycles, host range was expanded following spot test assay on both the 16 host strains and an additional 10 P. aeruginosa strains.

Assessment of phage in-vitro bacteriolytic activity and decontamination of sand samples utilized P. aeruginosa crude phage lysates, selected based on their broad host range, high titer and virulence. It is recommended that bacteriophage preparations especially those targeting Gram-negative bacteria, be purified in order to remove endotoxins or lipopolysaccharides, cell debris and other contaminating substances prior to applications (Van Belleghem, et al., 2017). However, the degree of purification of phage preparation is largely a function of the type of application the phage will be used for. For instance, phages which are to be administered in a medical (human or animal) setting must be thoroughly purified to remove bacterial endotoxins as these elicit a wide variety of pathophysiological effects in the body due to their immunogenic, pro- inflammatory and pyrogenic effects (Aderem and Ulevitch, 2000, Bonilla, et al., 2016). Excessive or systemic exposure to endotoxins may prompt a systemic inflammatory reaction associated with multiple pathophysiological effects such as endotoxin shock, tissue injury and death (Anspach, 2001, Erridge, et al., 2002, Ogikubo, et al., 2004). Thus, it is important to remove endotoxins from phage preparations as these may affect efficacy and safety of the administration during phage therapy (Van Belleghem, et al., 2017). On the other hand, extensive purification of phage preparations is of less

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importance especially if the phage preparations are to be used for disinfection or as foliar sprays in plant agriculture, as the later will be washed away well before any animal or human consumes the plant (Balogh, et al., 2010, Gutiérrez, et al., 2016). In such cases, simply removing the live bacterial cells along with larger cell debris via filtration may be sufficient (Gill and Hyman, 2010).

Phage bacteriolytic activities were investigated in an in-vitro co-culture assay as presented in Figure 3.7 to 3.15. Five MOI ratios were tested to optimize the phage dose required to inhibit or completely eradicate the bacteria, and also to provide a basis on which to select the most appropriate phages for subsequent sand decontamination experiments. High MOI dose was intended to examine whether P. aeruginosa PAO1 bacterial cells could be reduced by passive inundation (Payne and Jansen, 2001). Passive inundation refers to a scenario where numbers of bacterial cells are depleted by attachment of overwhelming numbers of phage but without productive replication of the phage (Carrillo, et al., 2005). The use of lower phage doses was anticipated to initiate active proliferation of the phage and bacteria, with the phage eventually overwhelming their host (Carrillo, et al., 2005). Additionally, the use of higher MOI dose was considered as an appropriate strategy for inhibiting or eliminating P. aeruginosa PAO1 bacterial cells with the purpose of minimizing the likelihood of acquired host resistance to phages over time (Carrillo, et al., 2005). Generally, the growth of P. aeruginosa PAO1 was inactivated when co-cultured with phage in a concentration-dependent manner, with OD values declining more quickly at higher MOI (104 and 105) than at lower MOI (103, 102 or 101).

The uninfected P. aeruginosa PAO1 cells showed steady growth, with OD600 values increasing at different time points as expected. The highest bacterial inactivation at the end of the 6 hrs of incubation was seen in cultures infected with bacteriophages FCPA2, FCPA3, WCSS4PA and Cocktail. For instance, FCPA2 at MOI 105, FCPA3 at MOI 105, WCSS4PA at MOI 105 and Cocktail at MOI 104 managed to decrease the absorbance

(OD600) values of the infected cultures to 0.702, 0.200, 0.319 and 0.288 respectively when compared with the uninfected control cultures. The absorbance (OD600) readings of uninfected control cultures for phages FCPA2, FCPA3, WCSS4PA and Cocktail were 1.370, 1.370, 1.533 and 1.557 respectively. The phage bacteriolytic activity curves of the named phages followed a very similar pattern where an initial rise in turbidity was

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observed which was then followed by a decrease in turbidity which stabilized to the end of the incubation period. This result implies that the phages continued to grow during the initial infection and lysis occurred as the infection proceeded. However, cell lysis was observed much earlier in cultures infected with phage at high MOI ratio than at low MOI ratio. For example, in bacterial cultures infected with phage FCPA3 at MOI of 105, cell lysis began 30 minutes post-infection whereas at lower MOI ratios (104, 103,102,101) cell lysis began 4 hrs post-infection. This observation could be due to increased stress on the host cells which resulted in bacterial lysis (Brewster, et al., 2012). Another possible reason to this could be each phage causes lysis at different rates with phages FCPA3, WCSS4PA and Cocktail being the fastest when compared with the rest phages. In addition, this phenomenon could be due to due to the speed at which the phages attaches to the host cell receptors, enters the cell, replicates, assembles or lyses the cell (Young, et al., 2003). The phage bacteriolytic activities of FCPA4, FCPA5 FCPA6,

WCSS5PA were marked by a slow decrease in absorbance (OD600) which lasted for a period of time, followed by a slow rise in absorbance which lasted to the end of 6 hrs incubation. The increase in OD may be due to the presence of phage-resistant bacterial cells (Tan, et al., 2014).

Development of phage resistant bacteria is often correlated with a concomitant loss of virulence (Laanto, et al., 2012). This arises mainly due to the cell surface components such as lipopolysaccharides (LPS) and proteins that act as receptors for phage adsorption, which can also act as virulence factors. Furthermore, mutations occurring on these receptors which causes bacteriophage resistance results in a reduction in pathogenicity (Silva, et al., 2014). Therefore, bacteria regrowth after phage therapy will result too few or no big consequences in terms of virulence (Capparelli, et al., 2010, Filippov, et al., 2011, Wagner and Waldor, 2002). It is recommended to carry out further studies to detect mutations in the outer bacterial molecules of resistant bacteria following phage therapy, as these can act as phage receptors and possibly at the same time as virulence factors (Silva, et al., 2014). Bacteriophages have several features that make them potential therapeutic agents against infectious bacteria. One of these features is the highly specific and effective lysis of the targeted pathogenic bacteria (Zhang, et al., 2015). Generally, the in-vitro bacteriolytic activity results obtained in this

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study demonstrated that phage isolates possessed strong bacteriolytic activity which is important for use in phage therapy. The highest bacteriolytic activity was observed in P. aeruginosa bacterial cultures infected with phages FCPA3 (MOI 105) and Cocktail (MOI 104). Various studies have revealed that two or more phages with different host ranges in a single suspension (a phage cocktail) acts more effective than a use of a single phage alone (Chan, et al., 2013, Gu, et al., 2012, Jaiswal, et al., 2013). The use of multiphage therapy has also been reported to be more efficient in reducing the bacterial density when compared with monophage therapy. For instance, Hall, et al. (2012) investigated the effect of using one, two or four phages either sequentially or simultaneously against P. aeruginosa PAO1 planktonic cultures and the results showed that simultaneous application of phages was consistently equal or superior to the sequential application with respect to efficacy. This study reports similar observation where a multiphage designated as WCSS4PA showed efficient bacterial reduction when compared with monophage isolates. One possible limitation of the study conducted by Hall, et al. (2012) was the use of optical density measurements to estimate bacterial population density. It was claimed that the relationship between population size and optical density can be altered by the evolution of phage resistance. For example, resistant genotypes may overproduce alginate or extracellular polymeric substances (EPS) that results in OD measurements inflation.

Viable P. aeruginosa PAO1 cells that survived in-vitro treatment with bacteriophages were enumerated at 6 hrs and 24 hrs post-infection as shown in Figure 3.16 to 3.24. The number of surviving bacteria cells assessed 6 hrs post-infection were compared with bacterial counts assessed prior to phage infection (10.89 log10 CFU/mL) and also at 6 hrs post-infection (16.90 log10 CFU/mL). Significant (p0.05) log10 CFU/mL reductions were observed when surviving bacteria cells harvested 6 hrs post-infection were compared with those of untreated control, also harvested at 6 hrs post-infection. All the phages showed over 99.99 % reduction in bacteria following the treatment. The highest bacterial log10 CFU/mL reduction was 11.82 equivalent to 100% reduction in bacteria observed in cultures treated with phage cocktail (Cocktail) at MOI of 104. Moreover, bacteriophages designated as FCPA3, FCPA5, FCPA6 and WCSS4PA also showed higher bacterial log10 CFU/mL reductions of 9.2, 9.4, 9.6 and 10.3 respectively,

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equivalent to over 99.99% reduction in bacteria. The lowest bacterial log10 CFU/mL reduction was observed in cultures infected with phage WCSS5PA (4.8 log10 CFU/mL). However, when surviving bacteria cells harvested 6 hrs post-infection were compared with bacterial counts harvested prior to phage infection, not all phages were effective at reducing P. aeruginosa PAO1 bacterial cells. The highest bacterial log10 CFU/mL reduction was 5.8 equivalent to 99.99% bacterial reduction which was observed in cultures treated with phage cocktail (Cocktail). Following this was a multiphage

(WCSS4PA) which showed a log10 CFU/mL reduction of 4.26 equivalent to 99.99% bacterial reduction. Bacteriophage WCSS5PA did not show any reduction in bacterial cells but instead the bacterial cells rebounded and surpassed those of the untreated control. Phage FCPA1 showed the lowest bacterial log10 CFU/mL reduction (0.16) equivalent to 30 % reduction in bacterial cells.

Another comparison was performed between surviving bacterial cells harvested 24 hrs post-infection and that of untreated control harvested before any infection was initiated

(10.89 log10 CFU/mL). The results showed significant bacterial log reductions in cultures treated with phages WCSS4PA and Cocktail only. Phages WCSS4PA and Cocktail showed a bacterial log10 CFU/mL reduction of 2.17 and 1.74 equivalent to 99.33% and 98.18% bacterial load reduction respectively. Again, the rest bacteriophages did not show any reductions in bacterial cells but instead, the cells rebounded and surpassed those of the untreated control. Surviving bacteria cells harvested 24 hrs post-infection were then compared with uninfected control (19.17 log10 CFU/mL) harvested at the same time. The results showed significant bacterial log reduction amongst all the tested phages. All the phages achieved greater than 99.99% reduction in bacterial load when compared with uninfected control. The highest bacterial log reduction was observed in bacteriophages WCSS4PA (MOI 104) and Cocktail (MOI 102). These phages showed a bacterial log10 CFU/mL reduction of 10.5 and 10.86 respectively, equivalent to 100% reduction in bacterial cells. Nevertheless, bacteriophage FCPA3 (MOI 105) showed the highest bacterial log10 CFU/mL reduction of 8.3 equivalent to over 99.99% reduction in bacterial cells amongst all the tested monophages. Surprisingly, multiphage WCSS5PA showed higher bacterial log10 CFU/mL reduction (7.0) equivalent to over 99.99% bacterial reduction after 24 hrs post-infection. Previous results indicated that, phage

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WCSS5PA achieved the lowest bacterial log10 CFU/mL reduction (4.8) among all the tested phages at 6 hrs post-infection when compared with uninfected control assessed at the same time. Additionally, phage WCSS5PA showed no reduction in bacterial cells following assessment at 6 hrs and 24 hrs post-infection when compared with uninfected control assessed before the infection was initiated. Instead, the cells rebounded and surpassed those of uninfected control.

Treatment of experimentally contaminated sand samples utilized crude phage lysates obtained from phages FCPA3, WCSS4PA and Cocktail, owing to their efficient bacteriolytic activities. Surviving bacterial cells following phage treatment were enumerated at 0 hr, 6 hrs, 24 hrs and 48 hrs as shown in Figure 3.25. When surviving bacterial cells at 0 hrs (assessed just after phage addition and before incubation) were compared with viable P. aeruginosa PAO1 counts obtained from untreated sand samples (9.77 log10 CFU/mL), harvested at the same time, no significant bacterial reduction was observed as expected. However, a bacterial log10 CFU/mL reduction of 0.09 equivalent to 19.18% reduction in bacteria cells was observed in sand samples sprayed with phage WCSS4PA. Surviving bacterial cells assessed at 6 hrs, 24 hrs, and 48 hrs post-treatment were compared with bacterial counts obtained from untreated sand samples (9.77 log10 CFU/mL) assessed prior to phage treatment. The results showed significant bacterial log10 CFU/mL reduction in all the three phages. However, the highest bacterial log10 CFU/mL reduction was 4.2 equivalent to 99.99% bacterial load reduction observed in sand samples sprayed with a phage cocktail (Cocktail). Phages

FCPA3 and WCSS4PA showed bacterial log10 CFU/mL reductions of 2.73 and 3.16 equivalent to 99.8% and 99.9% bacterial load reduction. Surviving bacterial cells assessed 24 hrs post-treatment also showed the highest bacterial log10 CFU/mL reduction in phage cocktail (Cocktail), followed by WCSS4PA and FCPA3. Bacterial log10 CFU/mL reductions observed in these samples were 2.36, 2.04 and 1.72 equivalent to 99.57%, 99.09% and 98.09% bacterial load reductions respectively. At 48 hrs post- treatment, the highest bacterial log10 CFU/mL reduction was 2.73 equivalent to 99.81% bacterial load reduction observed in WCSS4PA followed by 2.05 equivalent to 99.13% and 2.01 equivalent to 99.2% observed in FCPA3 and Cocktail respectively. The number of surviving bacteria cells assessed 6 hrs post-treatment were compared with

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those of untreated sand samples (11.64 log10 CFU/mL) assessed at the same time. All the three phages i.e. FCPA3, WCSS4PA and Cocktail achieved high bacterial log10 CFU/mL reductions of 4.60, 5.03 and 6.09 respectively, equivalent to over 99.99% reduction in bacterial cells.

It was also observed that P. aeruginosa PAO1 cells in the untreated control sand samples showed favorable growth at 6 hrs post-treatment despite limited nutrient supply. Various studies have reported that P. aeruginosa exhibits extensive metabolic diversity which enables it to thrive in different ecological niches such as soils, plants, water and animals (LaBauve and Wargo, 2012, Orlandi, et al., 2015). It is this metabolic flexibility that allows P. aeruginosa to succeed as an opportunistic pathogen causing both community-acquired and hospital-acquired infections which can be life-threatening (LaBauve and Wargo, 2012). Studies have reported that beach sands can serve as a vehicle for exposure of humans to pathogens, resulting in increased health risks. For instance, analysis of Israel beaches revealed various levels of P. aeruginosa, with higher counts found on beach sands than in the seawater samples (Ghinsberg, et al., 1994). In an interesting report by Velonakis, et al. (2014), factors affecting the survival of pathogenic bacteria such as P. aeruginosa in beach sands were examined. The results indicated greater survival and proliferation of P. aeruginosa along with S. aureus in sterile beach sands than seawater. In the current study, it was possible for P. aeruginosa cells to grow in sand samples at 6 hrs post-incubation because the cells were still at a mid-exponential phase when introduced into the sand samples. At this phase bacteria, cells divide rapidly and double in number at regular intervals. The growth kinetics result presented in Table 3.2 showed that P. aeruginosa had a rapid growth with a very short doubling time (td) of 0.249. In addition, the prospect of P. aeruginosa cells to replicate in sand samples at 6 hrs post-incubation could be due to the presence of nutrients supplied by Brain-heart infusion (BHI) media used to grow the bacteria cells.

When the number of surviving, bacterial cells assessed at 24 hrs post-treatment were compared with those obtained from untreated sand samples assessed at the same time

(7.18 log10 CFU/mL), no reduction in bacterial cells was observed in all the three phages. In fact, all the three phages showed an increase in bacterial cells which surpassed that of the untreated control. Similarly, when the number of surviving bacterial cells assessed

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at 48 hrs post-treatment was compared with those of untreated sand samples assessed at the same time (7.56 log10 CFU/mL), no significant reduction in bacterial cells was observed in all the three phages. However, bacteriophage WCSS4PA showed bacterial log10 CFU/mL reduction of 0.51 equivalent to 69.36% reduction in bacterial cells. Sand samples treated with bacteriophages FCPA3 and Cocktail showed an increase in bacteria cells which surpassed those of the untreated control. This study demonstrates the usefulness of virulent bacteriophages isolated from Sarawak limestone caves in inactivating the growth of P. aeruginosa PAO1 cells. The effectiveness of the phages against P. aeruginosa PAO1 bacterial target varied significantly when compared with the control and among each other. The results attained in this study showed that effective phage infection and subsequent destruction of the host cells is strongly determined by multiplicity of infection (MOI) ratio. The multiplicity of infection (MOI) refers to the ratio of phages to host cells (Bigwood, et al., 2009). Higher MOI ratio resulted in significant growth suppression of the bacterial host. For example, all phages showed better inactivation when MOI ratio of at least 103 was used. This agrees with the findings reported in other analyses that showed that application of higher MOI ratio resulted in higher bacterial inactivation. For instance, O'flynn, et al. (2004) achieved efficient inactivation of Escherichia coli O157: H7 on beef using MOI of 106 in which 2 x 108 PFU of phages were applied to pieces of meat inoculated with 2 x 102 CFU of the pathogen. Similarly, Atterbury, et al. (2007) reported better efficacy with phage application at MOI of 106 during in-vitro studies against Salmonella serovars.

Based on the results obtained in this study, a phage cocktail (Cocktail) was the most efficient in reducing colonialization of P. aeruginosa bacteria during in-vitro bacteriolytic activity and sand decontamination studies when compared with monophages. The use of combination of two or more phages with different host ranges in a single suspension (a phage cocktail) has been reported to be more effective than the use of a single phage alone (Chan, et al., 2013, Gu, et al., 2012, Hall, et al., 2012). For instance, Fu, et al. (2010) reported a significant reduction of biofilm formation by P. aeruginosa M4 on catheters using a cocktail of five best phages as opposed to treatment with a single phage. As clearly explained by Schmerer, et al. (2014), one advantage of using a phage cocktail is the presence of a large collective host range that may obviate the need to characterize

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phage sensitivities of the infecting pathogenic bacteria. Another advantage relies on thwarting resistance when multiple phages target the same bacterium. In this case, the evolution of resistance to all such phages may be required before treatment fails. A third possible mechanism is dynamical: two phages may collectively kill the bacterial population more rapidly or more completely than either phage alone. This latter process of ‘synergy’ between phages is relatively unexplored, perhaps because its demonstration requires a quantitative assessment of bacterial densities during treatment (Schmerer, et al., 2014). Although the results reported in this study showed efficient growth suppression of P. aeruginosa bacteria in both the phage in-vitro bacteriolytic activity and sand treatment experiments, a regrowth of bacteria at 24 hrs and 48 hrs post-treatment (in the case of sand treatment) was noticed. As highlighted in literature, surviving bacteria may be due to a reduced probability of viruses to find host bacteria (Bull, et al., 2002, Levin and Bull, 2004), a non-replicating condition of surviving bacteria that is physiologically refractory to phage infection (Bull, et al., 2002), lysogenic conversion (Skurnik and Strauch, 2006) and due to the development of phage resistance by the bacterial host (Levin and Bull, 2004). The assumption of bacteria regrowth due to the low probability of an encounter between viruses and the bacteria- host is not likely because an increase in MOI (MOI 105) did not increase the efficiency of phage therapy. Furthermore, the assumption of non-replicating bacteria to be physiologically refractory to phage infection is also unlikely because following the peak of bacterial inactivation by the phages, the remaining bacteria grew at a high rate and reached densities similar to those observed in the controls (Silva, et al., 2014).

The occurrence of lysogeny, which can also render the bacterium immune to not only the original phages buy also to related phages might be one of the reasons for bacterial regrowth after phage treatment. However, it is essential to evaluate the occurrence of lysogenic conversions following rigorous testing to exclude this possibility (Silva, et al., 2014). The hypothesis of bacteria re-growth due to the presence of phage-resistant bacterial mutants may be possible. The resistance of bacteria towards phage may be due factors such as mutations that affect phage adsorption, restriction modification or the mechanisms of abortive infection such as the presence of clustered regularly interspaced short palindromic repeats (CRISPRs) in the bacterial genome as discussed

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earlier in this chapter (Allison and Klaenhammer, 1998, Barrangou, et al., 2007, Donlan, 2009). When pre-treated sand samples were treated a second time with phage (recharged) at 24 hrs, P. aeruginosa bacterial densities were not significantly different from those assessed at 48 hrs post-treatment. The observation that recharged treatment of sand samples did not allow bacteria growth suppression explains that surviving bacteria during the first treatment may be phage-resistant mutants and an increase in phage dose did not render bacterial cells susceptible to phage. These findings support the idea that, applying phages in a single dose takes advantage of the phage potential to replicate and thereby achieve ‘active’ therapy, i.e., significant phage amplification via auto “dosing” that results in greater bacterial killing (Abedon and Thomas-Abedon, 2010, Capparelli, et al., 2010). Achieving efficacy following only a single dose, or far less frequent dosing, is an obvious convenience, though in many or most instances a single dosage of phages should not be expected, a priori, to be sufficient to achieve desired efficacy (Capparelli, et al., 2010). Another reason that might have contributed to the re-growth of bacteria even after phage recharge could be due to impaired diffusion of bacteriophages depending on the structure and composition of the matrices (Marcó, et al., 2010). It is assumed that, in solid media, the diffusion of bacteriophages could be limited, thus reducing phage adsorption on bacteria and consequently the phage infection capacity. For example in a study reported by Guenther, et al. (2009) it was shown that the use of bacteriophages was limited by their diffusion in solid food matrices such as hot dogs, smoked salmon, and seafood.

3.4 Conclusion The study in this chapter reports, the isolation of lytic bacteriophages from soil samples collected at Sarawak limestone caves (FCNR and WCNR), targeting different pathogenic bacteria. Phage lysates were spot tested on various bacterial strains to determine their lysis spectrum. Analysis of phage bacteriolytic activity was performed in an in- vitro co- culture assay with P. aeruginosa PAO1 using different multiplicity of infection (MOI) ratios. Surviving P. aeruginosa PAO1 cells following an in-vitro treatment with phage were enumerated at 6 hrs and 24 hrs post-infection and the counts were compared with

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those of uninfected P. aeruginosa PAO1 cultures (Controls). The final part of this work explored the applicability of the phage isolates as biological disinfectants to control infections caused by P. aeruginosa. Decontamination experiments were conducted by spraying selected phages (a monophage FCPA3, a multiphage WCSS4PA and a phage cocktail Cocktail) individually onto sand samples immobilized with P. aeruginosa PAO1 cells, followed by incubation for up to 48 hrs. About 33 lytic phages were isolated from limestone cave soil samples with P. aeruginosa and V. parahaemolyticus phage isolates displaying the broadest host range. The highest bacterial inactivation was seen in cultures infected with phages FCPA3, WCSS4PA and Cocktail when compared with uninfected P. aeruginosa PAO1 cultures (Controls). Plate count results performed to assess bacterial survival following in-vitro treatment with phage reveled that phage

4 cocktail (Cocktail, MOI 10 ) had the highest bacterial log reduction of 11.82 log10 CFU/mL equivalent to 100% reduction in bacterial cells at the end of 6 hrs of incubation. Similarly, phages WCSS4PA (MOI 104) and Cocktail (MOI 102) also reported the highest bacterial log reduction of 10.86 log10 CFU/mL and 10.5 log10 CFU/mL respectively, equivalent to 100% reduction in bacterial cells at the end of 24 hrs of incubation. Some of the phages failed to show any bacterial reduction at 6 hrs and 24 hrs post-infection, instead the cells rebounded and surpassed those of the untreated control. Sand decontamination experiments reported over 99% reduction in P. aeruginosa PAO1 bacterial cells in all three tested phages (FCPA3, WCSS4PA and Cocktail) when compared with untreated control at 6 hrs post-treatment. The highest bacterial log reduction was 4.2 log10 CFU/mL equivalent to 99.99% reduction in bacterial cells achieved by sand samples sprayed with a phage cocktail (Cocktail). However, no significant bacterial reduction was seen in sand samples harvested at 24 hrs and 48 hrs post-treatment despite phage recharge at 24 hrs, instead, the cells rebounded and surpassed those of untreated control. The results presented in this chapter demonstrates the presence of lytic phages from Sarawak limestone cave soils capable of inactivating P. aeruginosa PAO1 bacterial cells. However, further studies are warranted especially on the emergence of phage-resistant mutants, assumed to be the cause of bacterial regrowth during phage bacteriolytic and small-scale sand decontamination studies reported in this study.

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Chapter 4

GENERAL CONCLUSION AND FUTURE PERSPECTIVE

4.1 General Conclusion

4.1.1 Aim of the thesis The emergence and widespread of multi-drug resistant bacteria, accompanied by a slow progress in the development of new antibiotics, have built up interests in the search for alternative and natural antimicrobial agents (Gorski, et al., 2016, Jassim and Limoges, 2014). Virulent bacteriophages represent a viable antibacterial technology that has proven effective to control multi-drug resistant bacterial pathogens (Nagel, et al., 2016). The large variation of increasingly multi-drug resistant bacteria causing infections, demands exploration of previously untapped biological niche such as limestone caves for potential novel lytic bacteriophages. Preceding studies have reported on the presence of novel bioactive compounds from caves with antimicrobial properties. Novel antibiotics such as Cervimycins A-D and xiakemycin A have been successfully isolated from cave bacteria (Herold, et al., 2005, Jiang, et al., 2015). These antibiotics have shown activity against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecalis. Xiakemycin A has been reported to extend its activity to include Staphylococcus epidermidis and vancomycin-resistant Enterococcus faecium. In addition, it has demonstrated additional antifungal and cytotoxic effects against cancer cells (Bretschneider, et al., 2012, Herold, et al., 2004). These findings indicate that caves are a rich reservoir of potential and novel antimicrobials which can open new frontiers for drug discovery. This thesis is thus, the first report on the isolation of lytic bacteriophages from Sarawak limestone caves (FCNR and WCNR) with the potential to be developed into biological disinfection agents to control infections caused by P. aeruginosa bacteria.

The preceding chapters (Chapter 2 and Chapter 3) described the studies undertaken to fulfill the major aims of the thesis, which were: i. To screen and isolate lytic phages from limestone cave soil samples. ii. To investigate the phage bacteriolytic activity in in-vitro. iii. To treat sand samples contaminated with P. aeruginosa using isolated phages. This chapter provides an overview of the major findings of this research study as well as identifying the scope for further research.

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4.1.2 Summary of the findings 4.1.2.1 Bacteriophage isolation and host range analysis There are no documented studies on presence and diversity of bacteriophages inhabiting limestone caves despite the fact that caves are known to harbor novel antimicrobial compounds, active against many multi-drug resistant bacteria. This study broadens our knowledge about the presence and diversity of bacteriophages inhabiting Sarawak limestone caves (FCNR and WCNR). A total of 33 lytic bacteriophages were isolated from Sarawak limestone cave samples targeting bacterial strains V. parahaemolyticus, S. aureus, K. pneumoniae, E. coli, P. aeruginosa and S. pneumoniae following enrichment method. The phage isolates were tested against strains of a well- defined bacterial collection (host range assay), a strategy used to screen for suitable biocontrol candidates. In phage therapy and biocontrol studies, a broad host range phage capable of killing multiple species of bacteria is equivalent to a broad spectrum antibiotic (Ross, et al., 2016). In this study phage isolates, V. parahaemolyticus and P. aeruginosa phages showed the broadest host range. A fascinating observation was the ability of V. parahaemolyticus phage isolates to infect bacterial strain S. aureus which belongs to a completely different phylum i.e. Eubacteria. Nevertheless, another observation seen was the ability of some phage isolates to display trans-subdomain infectivity between gram positive and gram-negative bacterial hosts. For instance, S. pneumoniae phage isolates (FCSP1, FCSP2 and FCSP3) were capable of infecting P. aeruginosa and E. coli bacteria. This phenomenon is attributed to the oligotrophic nature of the cave environment from which the samples were collected (Malki, et al., 2015). Furthermore, phages with the ability to use more universal receptors for adsorption exhibit broader host range and are usually found in environments with poor nutrients (Nilsson, 2014).

4.1.2.2 Assessment of phage in-vitro bacteriolytic activity The most important criteria for selecting phages for therapeutic or biocontrol applications are specificity and effective lysis of the targeted bacteria (Zhang, et al., 2015). This study assessed the ability of selected P. aeruginosa phage isolates individually and, in a cocktail, to inhibit or completely inactivate the bacterial host in an

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in-vitro co-culture assay for up to 6 hrs. The spectrophotometric method which involves the use of optical density measurement was utilized in the assessment of phage lytic activity because it is rapid and non-destructive to the cells (Sutton, 2011). Five MOI ratios were tested to optimize the phage dose required to inhibit or completely inactivate the bacterial host and to provide a basis on which to select the most suitable phages for subsequent sand decontamination experiments. The results showed that the growth of P. aeruginosa PAO1 was inactivated when co-cultured with phage in a concentration-dependent manner, with OD values declining more quickly at higher MOI (104 and 105) than at lower MOI (103, 102 or 101). Overall, bacteriophages designated as FCPA3, WCSS4PA and Cocktail showed the highest bacterial inactivation when compared with the rest phages. One possible drawback in the use of optical density measurement to estimate bacterial population density during phage bacteriolytic studies is the evolution of phage resistance. Resistant genotypes may overproduce alginate or extracellular polymeric substances (EPS) as mentioned earlier in this thesis (Section 3.1), which may result in OD measurements inflation Hall, et al. (2012). Hence, it was imperative that bacterial cell concentration by plate count needed to be performed for accurate results. Survival of P. aeruginosa PAO1 bacterial cells following an in-vitro co-culture with phage were determined using plate count at 6 hrs and 24 hrs post-infection and the results were expressed as log10 CFU/mL. Uninfected bacterial cultures were used as the controls of the experiment. The results revealed that phage

4 cocktail (Cocktail, MOI 10 ) had the highest bacterial log10 CFU/mL reduction of 11.82 equivalent to 100% reduction in bacterial cells at the end of 6 hrs of incubation. However, surviving bacterial counts assessed 24 hrs post-infection showed that a multiphage (WCSS4PA, MOI 104) and a phage cocktail (Cocktail, MOI 102) had the highest bacterial log10 CFU/mL reduction of 10.5 and 10.86 respectively, equivalent to 100% reduction in bacterial cells. These findings support the notion that, when two or more phages in the cocktail attack the same bacterium, the combination results in a better killing than the application of a single phage. Some of the phages did not show any reduction in bacterial cells at 6 hrs and 24 hrs post-infection, but instead, the cells rebounded and surpassed those of the untreated control. This phenomenon has been attributed to presence and development of phage-resistant mutants.

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4.1.2.3 Evaluation of phage isolates as biological disinfectants against P. aeruginosa In order to evaluate the applicability of the phage isolates to be employed as biological disinfectants against P. aeruginosa PAO1 bacteria, a small-scale decontamination experiment was designed, which utilized experimentally contaminated sand samples. Decontamination process was performed by spraying selected phages (a monophage FCPA3, a multiphage WCSS4PA and a phage cocktail Cocktail) individually onto the sand samples followed by incubation for up to 48 hrs. Untreated samples were used as the controls of the experiment. Over 99% reduction in P. aeruginosa PAO1 bacterial cells were observed on all phage treated sand samples harvested at 6 hrs post-treatment.

However, the highest bacterial log10 CFU/mL reduction was 4.2 equivalent to 99.99% reduction in bacteria achieved by sand samples sprayed with a phage cocktail (Cocktail). No significant reduction in bacterial cells was observed in sand samples harvested at 24 hrs and 48 hrs post-treatment despite phage recharge at 24 hrs, but instead, the cells rebounded and surpassed those of untreated controls. Phage recharge was performed to investigate the effect of an additional dose of phage at preventing regrowth of bacteria and possibly reduce bacterial colonialization on the sand samples. The occurrence of bacterial regrowth despite phage recharge could be due to the timing of the additional dose, as this has been shown to be crucial in effective infection control (Hall, et al., 2012, Torres-Barceló, et al., 2014). The results attained in this study demonstrates that phage cocktail (Cocktail) was the most efficient at reducing P. aeruginosa PAO1 colonialization when compared with a monophage (FCPA3). This is in line with preceding literature that has reported the use of phage cocktail to be more effective than the use of a single phage alone (Chan, et al., 2013, Gu, et al., 2012, Hall, et al., 2012).

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4.2 Future Perspectives and Recommendation The work presented in this thesis intended to screen and isolate lytic bacteriophages from limestone cave environment and demonstrate their applicability as biological disinfectants to control infections caused by P. aeruginosa. The results attained in this study suggests that the phage isolates designated as FCPA3, WCSS4PA and Cocktail, are promising biological disinfectant candidates against colonialization of P. aeruginosa. Although this work focused on disinfection of contaminated sand samples, phage application can be extended to include other materials such as hospital equipment or indwelling devices that would benefit from an additional method of sterilization. This will, in turn, reduce the use of antibiotics in the treatment of human diseases as well as minimizing the number of chemicals and detergents needed to decontaminate such surfaces. However, this can only be achieved by carrying out further investigative studies on the phage isolates reported in this study. Additionally, this work can be used as a starting point for several other lines of investigations to attain a deeper understanding of the application of phages in biocontrol of bacterial pathogens.

4.2.1 Morphological and Molecular characterization of the phage isolates Future studies should consider the preliminary characterization of the phage isolates by transmission electron microscopy (TEM). This will not only permit phage classification to one of the morphologically distinguishable families but will allow its inclusion to a group of phages of similar size and morphology within a family (Lobocka, et al., 2014). Phage characterization focusing on growth kinetics and DNA analysis-based methods of phage grouping such as Pulsed-field gel electrophoresis (PFGE) and Restriction fragment length polymorphisms (RFLP) should be performed. Phage growth kinetics will determine the latent period and the burst size of the isolates. PFGE will allow grouping or identification of phages based on the size of their virion DNA. The DNA of phages within each genome size group can be further differentiated based on digestion profiles with restriction endonucleases. The optimal set of enzymes for digestion needs to be selected either based on an in silico analysis of genomes of known phages that infect bacteria of the same or related species as those infected by the tested phage isolates or empirically (Lobocka, et al., 2014). RFLP allows assessment of bacteriophage genome diversity (Clokie, et al., 2011). Proteomic approaches to identify viral structural proteins

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by SDS-PAGE can also be performed. Whole genome sequencing of the phage isolates will allow a thorough investigation of the phage’s obligate lytic nature and estimate its safety, especially the risk of participating in the horizontal transfer of bacterial, plasmid and temperate phage’s genes. It is postulated that a distinctive feature of temperate phages that infect bacterial pathogens are genes encoding pathogenicity-related traits. Thus, identification of such genes should exclude a phage for studies involving phage therapy (Lobocka, et al., 2014).

4.2.2 Broadening applications of the phage isolates It will be interesting to further analyze phage specificity, infection process, adsorption potentials and biocontrol efficiency of the phage isolates using a wide collection of clinical strains. Testing the potential of phage isolates obtained in this study on clinical strains will expand applications of the phages as biocontrol agents of pathogenic bacteria. Future studies should also examine the influence of non-target host cells on sand samples to be decontaminated. There is a possibility that, a non-target host bacteria may affect the ability of the phages to adsorb to the intended host as highlighted by Wilkinson (2001).

4.2.3 Assessment of phage stability A sensible investigation step should evaluate phage stability under storage conditions and formulations. Phages are composed of protein structures which may render them unstable in solution formulations (Vandenheuvel, et al., 2015). Phage storage should ensure the stability of phage particles in the form and conditions in which preparation is stored, but the form of application should also protect phage particles against losing their activity (Weber-Dąbrowska, et al., 2016). Stability of the phage can be monitored based on parameters such as temperature and pH. Furthermore, it will be worthwhile to investigate the synergistic effect of the best bacteriophage candidates reported in this study (FCPA3, WCSS4PA and Cocktail) and commercial chemical disinfectants in decontamination studies.

4.2.4 Assessment of phage-resistant mutants Regarding bacterial regrowth observed during phage in-vitro bacteriolytic activity studies, more specific tests such as searching for modifications in bacterial phage

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receptors should be performed to evaluate the development of resistance and explain the occurrence of viable P. aeruginosa PAO1 bacteria during phage biocontrol studies. Investigations focusing on potential phage receptors identification to determine whether there is any correlation between phage susceptibility and phage receptor types can be conducted. Additionally, the frequency of the occurrence and the stability of bacteriophage resistant mutants (BRM) can also be analyzed.

4.2.5 Investigative studies on the expansion of host range The use of a phage cocktail (Cocktail) and a multiphage (WCSS4PA) proved to be more effective at reducing bacterial colonialization during both in-vitro bacteriolytic activity and sand treatment studies reported in this work. The use of phage cocktail is claimed to eliminate cross-resistance, and based on this fact, a bacterium which is resistant to one phage may remain sensitive to another. Additionally, cocktails that are composed of different receptors for binding to bacteria may be a better solution for eliminating the development of resistance in bacteria (Gill and Hyman, 2010). Future work should look at modifying isolation procedures and growth conditions that favor the isolation of phages with broader host ranges. Recent advances in sequencing technologies and genetic engineering have made it possible to design phages with more predictable and domesticated therapeutic properties. For instance, recombinant phages with hybrid tail fibers can be created to broaden the bacterial host ranges (Lin, et al., 2012).

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APPENDICES

Appendix I: Plaque appearance of bacteriophages infecting (A) K. pneumoniae, (B) P. aeruginosa, (C) E. coli and (D) V. parahaemolyticus, following an overnight incubation at 37oC.

A B

C D

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Appendix II: Multiplicity of infection (MOI) Multiplicity of infection (MOI) refers to the ratio of infectious virions to the cells in a culture (Shabram and Aguilar-Cordova, 2000). Multiplicity of infection (MOI) can be calculated by dividing the number of phage added (mL added x PFU/mL) by the number of bacteria added (mL added x cells/mL) as shown below: MOI= (PFU/mL x Volume added)  (CFU/mL x Volume added) In order to calculate the MOI, it is recommended to determine the number of cells you are infecting and the titer of the virus inoculated on them. In this study P. aeruginosa bacterial cells grown to their mid-exponential phase (7.76 x 1010 CFU/mL) were treated with phages having titers ranging from 1.25 x 1015 PFU/mL and 5.83 x 1015 PFU/mL.

Dilution formula (C1V1=C2V2) was used to prepared desired concentrations of both bacteriophage and bacteria. Desired phage concentration was 1.0 x 1015 PFU/mL and that of bacteria was 1.0 x 1010 CFU/mL. For instance, to make 50 mL of 1.0 x 1015 PFU/mL phage lysate from a stock solution of 5.83 x 1015 PFU/mL, the following calculation was performed.

C1V1=C2V2

15 15 (5.83 x 10 PFU/mL) V1= (1.0 x 10 PFU/mL) x 50 mL

V1= 8.58mL Thus, 8.58 mL of 5.83 x 1015 PFU/mL phage lysate stock was added into (50 mL - 8.58 mL) = 41.42 mL of a diluent (PB). Likewise, to make 50 mL of (1.0 x 1010 CFU/mL) bacteria solution from a stock solution of 7.76 x 1010 CFU/mL, the following calculation was performed.

C1V1=C2V2

10 10 (7.76 x 10 CFU/mL) V1= (1.0 x 10 CFU/mL) x 50 mL

V1=6.44 mL Thus, 6.44 mL of 7.76 x 1010 CFU/mL bacteria stock solution was added into (50 mL – 6.44 mL) = 43.56 mL of a diluent (PBS). Since the aim of this study was to test infection frequencies at different MOI ratios, it was necessary that conditions were identical between experiments. Thus, equal volumes of phage and bacteria were used, with the total volume set to 50 mL. Five MOI ratios were selected (101, 102, 103, 104, 105). The reason to why high MOI ratios were selected, was to investigate whether the use of high MOI dose could inhibit or eliminate

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P. aeruginosa bacterial cells by passive inundation and possibly minimise the occurrence of phage resistant mutants. The use of similar MOI range has also been reported by Atterbury, et al. (2007) where application of phage 10 at MOI of 106 reduced S. enterica serotype Typhimurium counts to below the limit of detection in 24 hrs. In order to obtain these selected MOI ratios (101, 102, 103, 104, 105), phage stock with a

15 titer of 1.0 x 10 PFU/mL was diluted using the dilution formula (C1V1=C2V2) as described earlier, to obtain phage lysates with titer ranging from (1x 1011, 1x 1012, 1x 1013, 1x 1014 and 1x 1015) PFU/mL. About 25 mL of the desired phage concentration was added into 25 mL of P. aeruginosa bacterial culture with a concentration of 1.0 x 1010 CFU/mL. The MOI ratios were calculated as follows:

��/�� MOI= ��/�� MOI 10 or 101= (1x 1011 PFU/mL)  (1x 1010 CFU/mL) MOI 100 or 102= (1x 1012 PFU/mL)  (1x 1010 CFU/mL) MOI 1000 or 103= (1x 1013 PFU/mL)  (1x 1010 CFU/mL) MOI 10000 or 104= (1x 1014 PFU/mL)  (1x 1010 CFU/mL) MOI 100000 or 105= (1x 1015 PFU/mL)  (1x 1010 CFU/mL)

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Appendix III: Optical density (OD) values of phage FCPA1 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix IV: Optical density (OD) values of phage FCPA2 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix V: Optical density (OD) values of phage FCPA3 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix VI: Optical density (OD) values of phage FCPA4 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix VII: Optical density (OD) values of phage FCPA5 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix VIII: Optical density (OD) values of phage FCPA6 obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix IX: Optical density (OD) values of phage WCSS4PA obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix X: Optical density (OD) values of phage WCSS5PA obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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Appendix XI: Optical density (OD) values of phage Cocktail obtained during an assessment of phage bacteriolytic activity at varied MOI ratios

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