Citation
Bacteriophages Reduce Pathogenic E.Coli Counts in Mice Without Distorting Gut Microbiota

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Title:
Bacteriophages Reduce Pathogenic E.Coli Counts in Mice Without Distorting Gut Microbiota
Creator:
Dissanayake, Upuli Anuradha
Publisher:
University of Florida
Publication Date:
Language:
English

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Epidemiology
Committee Chair:
Mai,Volker
Committee Co-Chair:
Prosperi,Mattia
Committee Members:
Hu,Hui
Graduation Date:
5/3/2019

Subjects

Subjects / Keywords:
bacteriophage

Notes

General Note:
During elimination of disease-causing pathogens antibiotic treatment disrupts the normal symbiotic gastrointestinal microbiota. The purpose of this study was to (i) investigate the efficacy of E. coli/Salmonella/Listeria bacteriophage cocktail (FOP) to reduce the pathogenic E. coli in experimentally infected mice, and (ii) determine whether bacteriophages preserve the normal gut microbiota when compared with antibiotic therapy. A total of 85 mice were inoculated with pathogenic E. coli O157:H7 strain 231 (nalidixic acid resistant (NalAcR)), via oral gavage. Mice were randomized into one of 6 groups, of which each group fell into one of three categories: 1st category of groups received PBS or No phage/No PBS as controls, 2nd category received FOP, FOP 1:10, or Ecoshield, as bacteriophage therapies and 3rd category received ampicillin as antibiotic therapy, with treatments administered twice daily for four consecutive days, except ampicillin. Stool samples collected at days 0, 1, 2, 3, 5, 10, were homogenized, and plated on LB plates containing NalAc to determine viable pathogenic E. coli counts. Weight for every group was monitored for each animal at every sample collection for trend analysis. We performed qPCR with specific E. coli primers to quantify the number of E. coli genome copies. We analyzed microbiota community profiles before and during treatment using DGGE (Denature Gradient Gel Electrophoresis). FOP bacteriophage treatment significantly (p-value less than 0.05) reduced E. coli pathogen concentration by more than 55%, and this reduction was the same as that observed with the antibiotic therapy. However, greater initial weight-loss occurred in mice treated with antibiotic therapy group (-5.44%) compared to both control and FOP bacteriophage groups (-3.56% and -2.24%, respectively). DGGE displayed no changes in gut microbiota composition in the control and the bacteriophage therapy groups after therapy. In contrast, the antibiotic group displayed noticeable distortion of the gut microbiota composition, only partially returning to normal by day 10. This study found that FOP administration was effective in reducing the levels of pathogenic E. coli in infected mice at a similar rate to ampicillin therapy. However, the FOP bacteriophage preparation had a milder impact on the gut microbiota compared to ampicillin: i.e., it did not trigger any distortion of the normal gastrointestinal microbiota; whereas, treatment with the antibiotic resulted in noticeable gastrointestinal microbiota distortion in mice.

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UFRGP
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All applicable rights reserved by the source institution and holding location.
Embargo Date:
11/30/2019

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BACTERIOPHAGES REDUCE PATHOGENIC E.COLI COUNTS IN MICE WITHOUT DISTORTING GUT MICROBIOTA By UPULI ANURADHA DISSANAYAKE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2019

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© 2019 Upuli Anuradha Dissanayake

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To Amma, Appachchi, Kelsey, Brian, Sravya, and the Bhagis

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4 ACKNOWLEDGMENTS It is with sincere gratitude and appreciation I thank my mentor, Dr. Volker Mai , for guidance without which the completion of this project would have not been possible . I also extend a special thanks to my thesis committee , Dr. Mattia Prosperi and Dr. Hui Hu. Dr. Maria Ukhanova deserves a very special mention for her patience in teaching me complex laboratory procedures and providing support throughout the project . I also thank all of my colleagues at the Emerging Pathogens Institute, University of Florida who extended their support in many ways. Last but not least, I thank my parents and friends for their continued love and encouragement.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 7 LIST OF FIGURES ................................ ................................ ................................ ......................... 8 LIST OF GRAPHS ................................ ................................ ................................ .......................... 9 LIST OF ABBREVIATIONS ................................ ................................ ................................ ........ 10 ABSTRACT ................................ ................................ ................................ ................................ ... 11 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .................. 13 Literature Revie w ................................ ................................ ................................ ................... 13 Antibiotic Resistance ................................ ................................ ................................ .............. 13 Food Borne Pathogens ................................ ................................ ................................ ............ 15 Gastrointestinal Microbiome ................................ ................................ ........................... 15 Bacteriophage Application ................................ ................................ ....................... 16 Hypothesis a nd Aims ................................ ................................ ................................ ....... 18 Study Objectives ................................ ................................ ................................ ..................... 18 2 MATERIALS AND METHODS ................................ ................................ ........................... 19 Study Design ................................ ................................ ................................ ........................... 19 Data collection ................................ ................................ ................................ ................. 20 Materials ................................ ................................ ................................ .......................... 23 Study Methods ................................ ................................ ................................ ........................ 24 Sample Analysis Methods ................................ ................................ ............................... 25 Microbiota Ana lyses Methods ................................ ................................ ......................... 25 Statistical Analyses Methods ................................ ................................ ........................... 26 3 RESULTS AND ANALYSIS ................................ ................................ ................................ . 27 Weight Data ................................ ................................ ................................ ............................ 27 Viable E.coli Colony Resul ts ................................ ................................ ................................ .. 28 qPCR and DGGE Results ................................ ................................ ................................ ....... 31 Analysis ................................ ................................ ................................ ................................ .. 33 4 DISCUSSION ................................ ................................ ................................ ......................... 34 Weight change ................................ ................................ ................................ ........................ 34

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6 Reduction of pathogenic E.coli ................................ ................................ ............................... 35 Microbiome Profile ................................ ................................ ................................ ................. 36 Limitations of study ................................ ................................ ................................ ................ 37 5 CONCLUSION ................................ ................................ ................................ ....................... 39 Investigation Findings ................................ ................................ ................................ ............ 39 Implications and Future Studies ................................ ................................ ............................. 40 APPENDIX ADDITIONAL TABLES ................................ ................................ ................................ ............... 41 LIST OF REFERENCES ................................ ................................ ................................ ............... 43 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ......... 46

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7 LIST OF TABLES Table page 2 1 Breakdown of each experiment (total of 6 experiments) by type of group included and number of animals. ................................ ................................ ................................ ...... 22 2 2 Components of each bacteriophage preparation used to create the F.O.P. bacteriopha ge cocktail total of 15 phages ................................ ................................ ........ 24 A 1 Percent Weight Change for all therapy groups. Denotes weight changes (in % weight change when compared to the weight taken at Day 0 as baseline) across all treatment groups over the course of Day 1, Day 2, Day 3, Day 5, and Day 10 compared to baseline values collected on Day 0. Values with * indicate statistical significance against the PBS control group. ................................ ................................ ........................... 41 A 2 E.coli viable counts for Bacteriophage therapy groups. Average E.coli counts from viable colonies grown in LB Agar plate s for all treatment groups included in experiments 1,2,3 and 4. Values with * signify statistically significance when compared against control group. ................................ ................................ ........................ 41 A 3 E.coli viable counts for F.O.P. and Ampicillin therapy groups. Average E.coli counts from viable colonies grown in LB Agar plates for all treatment groups included in Experiment 5 and 6. Values with * signify statistically significanc e ................................ 41 A 4 E.coli viable counts, p value calculations for all therapy groups against controls and against other therapy groups. P values calculated as t.test function in excel on viable E.coli counts from LB agar plating for each individual animal within each treatment groups. ................................ ................................ ................................ ................................ 42 A 5 E.coli viable counts, p value calculations for all therapy groups against controls and against other therapy groups. P values calculates as t.test function in excel between different therapy groups; viable E.coli counts; * denotes statistical s ignificance ............. 42

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8 LIST OF FIGURES Figure page 2 1 Summary of mouse study design. Top of figure denotes randomized mice groups and category of treatment each group belongs in. Bottom of figure denotes timeline of observation from the start of each experiment on Day 0, to the end of each experiment on Day 10. ................................ ................................ ................................ ....... 21 3 1 DGGE Analysis of combined cage samples taken from Experiment 5 and Experiment 6 denoting the gut microbiome profiles between PBS, F.O.P phage therapy, and ampicillin ther apy groups. ................................ ................................ ............. 32

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9 LIST OF GRAPHS Graph page 3 1 Displays the % weight change in all groups across the 10 days of treatment. Ampicillin displayed the greatest weight loss. Bars marked * indicate statistical significance when compared against PBS control groups. ................................ ................ 28 3 2 Denotes the pathogen reduction between controls and all bacteriophage therapy groups for the combined data of Experiments 1 4 for Day 1 using absolute numbers as the x axis scale. Bars marked wi th * indicate statistically significance when compared against PBS control group. ................................ ................................ ................ 29 3 3 Denotes the pathogen reduction between control s and all bacteriophage therapy groups for the combined data of Experiments 1 4 for Day 2 using absolute numbers as the x axis scale. Bars marked with * indicate statistically significance when compared against PBS control group. ................................ ................................ ................ 30 3 4 Denotes the pathogen reduction between controls and all bacteriophage therapy groups for the combined data of Experiments 1 4 for Day 3 using absolute num bers as the x axis scale. Bars marked with * indicate statistically significance when compared against PBS control group. ................................ ................................ ................ 30 3 5 Denotes the pathogen reduction between F.O.P., Ampicillin, and PBS for the combined data of Experiment 5 and Experiment 6. Bars marked with * indicate statistically significance. ................................ ................................ ................................ .... 31 3 6 Denotes the number of E.coli genomic copies within F.O.P., Ampicillin, and PBS for Experiment 5 and 6. This data represents the total DNA quantity to serve as a comparison for viable pathogen quantities det ermined through LB plating. ..................... 33

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10 LIST OF ABBREVIATIONS AMP Shorthand appreviation of Ampicillin, a beta lactam, penicillin derived antibiotic. E.coli This term serves as the shorthand designation of Escherichia coli , a gram negative, facultative anaerobic, rod shaped, coliform bact erium of the genus Escherichia found in the lower intestine. F.O.P. This is the shorthand name of our primary bacteriophage therapy of this study . It is shorthand for Food Outbreak Pill , which is the current name provided by Intralytix , Inc. who manufacture this bacteriophage preparation. It is a bacteriophage preparation comprised of three single target bacteriophage preparations compounded together. F.O.P. 1:10 This is the name of the diluted bacteriophage therapy F.O.P. (Food Outbr eak Pill) that has been diluted by a factor of 10. NalAc R Abbreviation for Nalidixic Acid, with the superscript R indicating Phage This is a shorthand term used in place of bacteriophage, used for convenience of language but is defined with the same definition as bacteriophage

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11 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science BACTERIOPHAGES REDUCE PATHOGENIC E.COLI COUNTS IN MICE WITHOUT DISTORTING GUT MICROBIOTA By Upuli Anuradha Dissanayake M ay 2019 Chair: Volker Mai Major: Epidemiology During elimination of disease causing pathogens antibiotic treatment disrupts the normal symbiotic gastrointestinal microbiota. The purpose of this study was to (i) investigate the E. coli/Salmonella/Listeria bacteriophage cocktail (F . O . P . ) to reduce the pathogenic E. coli in experimentally infected mice, and (ii) determine whether bacteriophages preserve the normal gut microbiota when compared with antibiotic therapy. A total of 85 mice were inoculated with pathogenic E . coli O157:H7 strain 231 (nalidixic acid resistant ( NalAc R )), via oral gavage. Mice were randomized into one of 6 groups, of which each group fell into one of three categories : 1 st category of groups received PBS or No phage/No PBS as controls , 2 nd category received F . O . P . , F . O . P . 1:10, or Eco S hield , as bac teriophage therapies and 3 rd category received ampicillin as antibiotic therapy , with treatments administered twice daily for four consecutive days, except ampic i llin. Stool samples collected at days 0, 1, 2, 3, 5, 10, were homogenized, and plated on LB plates containing NalAc to determine viable pathogenic E . coli counts. Weight for every group was monitored for each animal at every sample collection for trend ana lysis. We performed qPCR with specific E. coli primers to quantify the number of E. coli genome copies. We analyzed microbiota community profiles before and during treatment using DGGE (Denature Gradient Gel Electrophoresis).

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12 F . O . P . bacteriophage treatment significantly ( P 0.05) reduced E . coli pathogen therapy. However, greater initial weight loss occurred in mice treated with antibiotic therapy group ( 5.44%) co mpared to both control and F . O . P . bacteriophage groups . DGGE displayed no changes in gut microbiota profiles in the control and bacteriophage therapy groups during treatment . In contrast, the antibiotic group displayed noticeable distortion of the gut microbiota composition, only partially returning to normal by day 10. This study found that F . O . P . administration was effective in reducing pathogenic E. coli in infected mice. Notably , the F . O . P . bacteriophage preparation had a milder impact on the gut mi crobiota compared to ampicillin: i.e., it did not trigger any distortion of the normal gastrointestinal microbiota; whereas, treatment with the antibiotic resulted in noticeable gastrointestinal microbiota distortion in mice.

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13 CHAPTER 1 INTRODUCTION Literature Review microorganisms, such as bacteria, viruses, parasites or fungi; the diseases can be spread, directly or indirectly, from 1 ]. Literature notes historical records of bacterial infections and disease management across ancient Egypt, China, and Greece [2], yet treatment remained limited. Ultimately, our ability to treat infectious diseases changed with S ir Alexander fight against infectious agents [2]. Medicine transformed with the 1940 antibiotic development against highly virulent pathogens [ 3]. Yet, due to the misuse of antibiotics and the ability of microbes to genetically evolve, resistance to antibiotics emerged rapidly. Antibiotic Resistance Medical literature documents initial cases of antibiotic resistance as early as 1959 in Shigella (Tetracycline resistant, with tetracycline introduced clinically in 1948 [ 4 ]) , 1962 in Staphylococcus (Methicillin resistant, with methicillin synthesized in 1959 [ 5 ]), and 1965 in pneumococcus (penicillin resistant, with penicillin first used in a patient in 1942 [ 6 ]). The rapid emergence of decreased sensitivity towards common antibiotics pushed public health professionals to consider alternative therapy routes to fill growing gaps in treatment options [3]. Additionally, the increasing threat of spread of infectious agents due to the increase of proximity in urban living conditions compounded this public health issue; as the human population increased globally, the virulence of many pathogens increased in tandem [3]. Though the development of antibiotics h

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14 nearly all existing antibiotic drugs have been clinically documented in both acute and chronic illnesses [7]. Antibiotic resistance poses a severe threat to the general healthy populat ion. This problem is further aggravated in vulnerable patient populations, such as individuals who are immunosuppressed, those suffering from cardiovascular complications, genetic conditions, have a history of transplant or invasive surgery, compromised or gan systems, and pediatric populations. Due to these complex cases, clinicians require viable alternatives effective for pathogen reduction with minimal side effects as such patients are at an increased risk of higher morbidity and mortality. There is a bo dy of research on the emergence of antibiotic resistance, and it is thought that among the main causes driving antibiotic resistance are the overuse in humans including prophylactic use, overuse in veterinary medicine, and ecological sources that include c ommon farming practices [ 8 ]. In a retrospective cohort study of 358 children hospitalized with urinary tract infections (UTI), of which 87% were caused by Escherichia coli ( E.coli ), Lutter, et al. identified associations between antibiotic prophylaxis and resistance to antibiotics used to treat the infection (2005). Investigators of this study determined 27% of children with an E.coli caused infection with a history of prophylactic antibiotic use had resistance to cefotaxime sodium compared to 3% of childre n without such history . The study investigators concluded that children with antibiotic prophylaxis were the group with higher resistance to third generation cephalosporins against UTIs, a common pediatric infection that can lead to serious urologic compli cations or other medical comorbidities if left untreated [ 9 ]. Similar patterns of resistance were reported in other studies, with high rates of resistance against ampicillin, trimethoprim sulfamethoxazole, and first generation cephalosporins, highlighting the dangerous changes in sensitivities of pathogens to antibiotics [ 9 , 10 , 11 ].

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15 Food Borne Pathogens One of the many areas infectious diseases afflict populations is contaminated food and water, caused by food borne pathogens that are consistently listed as a global public health concern. Despite the frequency of bacterial contamination in food sources, medical treatment options to combat such infections are limited. Though non pathogenic E.coli bacteria are a normal part of the human gut flora, pathogenic E.coli are common culprits in foodborne infections, most notably shiga toxin producing E.coli (STEC) which causes diarrhea, hemorrhagic colitis, hemolytic uremic syndrome, and thrombotic thrombocytopenic purpura, with the latter two complications having h igh risks of fatality [ 12 , 13 ]. The standard clinical treatment against bacterial pathogens are regimens of antibiotics determined after speciation and antibiotic sensitivity profiling [1 4 ]. Yet in cases of infections caused by E.coli STEC O157:H7, the most common E.coli bacteria in North America associated with food borne outbreaks [ 13 ], the use of antibiotics is not advised as they aggravate the production of shiga toxins and can increase the 15 ]. Thus, clini cians must resort to supportive therapy and hydration to treat these cases and alternatives are needed for better treatment efficacy. Gastrointestinal Microbiome Though effective at reducing pathogen counts, antibiotics also produce undesirable clinical si de effects such as diarrhea, yeast infections, nausea, drug fever, allergic reactions, and in severe cases Clostridium difficile infection leading to colon damage [ 16] with many of these effects are directly associated to the distortion of the normal gastr ointestinal environment [ 17 ]. Distortion of the beneficial human gut microbiome is unwanted as normal gut flora contributes significant protective roles to health outcomes [ 17, 18 defined as a distinctive biological community of microorganisms working cohesively to maintain a stable environment

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16 [1 9 ]. The human body shares symbiotic relationships with a multitude of microorganisms inhabiting tissues, organ systems, and biofluids that 19 , 20 , 21,22 ]. The Human Microbiome Project has identified multiple microbial communities at various anatomic sites contributing to our overall microbiome in locations such as our skin surfaces, sinus es, oral and vaginal cavities, and the digestive tract with microorganisms outnumbering human cells by a factor of 10 in a healthy individual, emphasizing the integral role microorganisms fill in our natural homeostasis [ 21 ]. When the beneficial gut microb iota suffers from distortion of the microbiome environment there can be negative health outcomes resulting from the loss of their protective factors [ 17 ]. It is thought that dysbiosis in gut microbiome can contribute towards the development of colon, gastr ic, esophageal, pancreatic, laryngeal, breast and gallbladder carcinomas [ 23 ]. Bacteriophage Application One alternative to antibiotic treatment is the use of bacteriophages. Though promising reports of utilizing bacteriophages in the fight against infect ious bacteria have been published they have, to date, not resulted in common use [ 24 ]. Using bacteriophages to kill bacterial pathogens has been explored for the past century and has received renewed interest due to the rising levels of clinical antibiotic resistance s [ 24 ]. Bacteriophage therapy utilizes naturally occurring viruses that infect bacteria, which can be isolated from nature, to target an infectious agent in a human host. Structurally, bacteriophages are comprised of mostly proteins (protein ca psid) and nucleic acids (either DNA or RNA encapsulated by the protein capsid), rendering them mostly non toxic with regard to human use [ 25 ]. Bacteriophages are highly specific, infecting only a narrow range of targeted bacterial strains, generally result ing in minimal distortion of the surrounding microbiome community [ 25 , 26 , 27 ]. Bacteriophages are found in large numbers in the environment. They have been isolated and harvested from marine

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17 environments (both saltwater and freshwater), different food sourc es (various consumable red meats), fish, dairy products, soils, plants, and other animals. As new sources for novel antibiotics have become limited, the advantage of bacteriophages being the most abundant organisms within urther explored [1 8 , 28 ]. strains), bacteriophages generally do not have broad host range unlike most classes of antibiotics. For broad medical applications the narrow host range can be a disadvantage as the specific target has to be established prior to picking the correct bacteriophage treatment. This limitation highlights the need for effective yet safe combinations of phage preparations, allowing for the use of a ge neric cocktail against multiple pathogens. Without the ability to treat broadly as a first line of defense, the applicability of bacteriophages is hindered and resulted in the popularity of bacteriophage therapy being overshadowed despite the unique benefi ts it purports in maintaining 25 ]. The human gastrointestinal (GI) tract is diversely colonized by abundant symbiotic microbiota, playing critical roles in immunomodulation, digestion o f various compounds, and protecting against negative health outcomes [ 29 , 30 ]. Research has recognized the relationship between health and the gut microbiome in (but not limited) to inflammatory bowel diseases, obesity, and metabolic disorders [ 30 ]. As the GI tract is inhabited by an estimated ~100 trillion commensal bacteria contributing both daily and long term, maintenance of the microbial balance is complex [ 31 , 32 ]. Regaining protective gut microbiota in correct proportions after antibiotic disruption ta kes time and can leave the host susceptible to additional damage. Since bacteriophages target specific strains of bacteria, harnessing this targeting ability provides an

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18 Hyp othesis and Aims With the use of phages in humans documented by recent literature as safe [5,6,8,9,17,41], we hypothesized that the administration of bacteriophages to reduce pathogenic E.Coli counts will be effective without the deleterious side effects on the normal gut microbiome typical in antibiotic use. With the prevalence of contaminated food and water illnesses estimated by the Centers for Disease Control to be 48 million individuals annually in the United States [ 31 ], the impact of our findings ma y support bacteriophages as a much needed natural alternative to the negatives of antibiotic therapy. Study Objectives The objectives of this study are the pathogen reduction efficacies of multi target bacteriophages compared to antibiotic treatme nt and single target bacteriophage preparations while assessing the impact of the multi target bacteriophage preparation on the gut microbiota. We evaluated the use of a multi target bacteriophage preparation against a pathogenic strain of E.coli in three distinct scenarios to investigate these objectives.

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19 CHAPTER 2 MATERIALS AND METHODS Study Design We evaluated the efficacy of a multi target bacteriophage preparation against pathogenic bacteria using a study with three investigative arms. The first arm wa s designed to the compare the multi target bacteriophage therapy to evaluate if efficacy is impacted by combination style bacteriophage preparations. The second arm was designed to determine efficac y of the bacteriophage cocktail at two different concentrations. The third arm was designed to i) establish efficacy of the multi target bacteriophage cocktail compared to standard antibiotic therapy, and ii) evaluate potential distortion of gut microbiota . We investigated using an in vivo study of mice randomized into six groups observed over the course of 10 consecutive days, with each group assigned to a specific therapy combating an initial challenge of a pathogenic E.coli strain sensitive to our bacteriophage preparations. Three types of bacteriophage treatments are included in this study; 1) the multi target bacteriophage E.coli, Salmonella, and Listeria monoct yogenes bacteriophages) labeled F.O.P. 2) the F.O.P. bacteriophage preparation diluted by a factor of 10 with standard phosphate buffer solution (PBS) labeled F.O.P. 1:10 and 3) an E.coli specific bacteriophage preparation labeled as EcoShield TM . A total of 85 C57BL male mice (8 weeks old) were acquired from The Jackson Laboratory (JAX) and acclimated for seven bacteriophage cocktail preparation (labeled as F.O.P.) and th e E.coli specific bacteriophage (EcoShield TM ) were provided by Intralytix, Inc. Figure 1 summarizes the timeline of the therapy experiments conducted while Table 1 summarizes the animal group categories used.

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20 The initial challenge and all subsequent therap ies were administered via oral gavage, to ensure standardized ingestion by the animals. Oral gavage was performed using appropriately sized and sterilized gavage needles. We determined the first two animal groups to serve as control groups , the next three groups to facilitate the three distinct bacteriophage therapies, and the final group to facilitate the antibiotic therapy. The first control group received neither phosphate buffer solution (PBS) nor any bacteriophage therapy but received the oral gavage p rocedure to standardize stress levels and was labeled No PBS/No Phage. The second control group received only PBS. The third group received normal strength F.O.P. therapy. The fourth group received F.O.P. 1:10 therapy. The fifth group received normal stren gth EcoShield TM . The sixth group received ampicillin (AMP). After data collection on the tenth day animals were sacrificed. We followed standard protocols for all animal procedures provided by the Institutional Animal Care & Use Committee (IACUC) and ACS g uidelines. Data collection We measured body weight and collected stool samples from each individual animal on Day 0 after the initial pathogenic E.coli challenge. Stool samples were used for LB Agar plating to determine viable counts. We aliquoted a samp le of the stock of fresh E.coli culture in LB broth used to challenge the mice and determined a culture density baseline of 1.59 x10 9 cells/ml of pathogenic E.coli which was diluted appropriately to achieve 1.0 x10 8 E.coli cells per mouse for initial challen ge. To allow only optimal viable E.coli colony growth on LB Agar plates and reduce growth of other microorganisms, all plates contained a quinolone antibiotic, nalidixic acid (NalAc), to which our pathogenic E.coli is resistant. After standard incubation, E.coli colonies for each animal were counted manually and recorded by sample collection date. Limited fecal suspensions from each sample were taken for plating, to preserve enough of the original sample for all subsequent laboratory analysis.

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21 Aliquots fro m individual samples were then combined by cage but stratified by sample collection day for DNA extraction. Quantitative polymerase chain reaction (qPCR) was used to determine pathogenic E.coli volumes of each therapy group for comparison against viable E. coli plating counts. Fresh aliquots taken from the combined cage samples were analyzed through denature gradient gel electrophoresis (DGGE) to determine distortion of microbiota profiles over the ten days of observation for PBS, F.O.P. therapy, and ampic illin therapy. The acrylamide gel created for DGGE allowed for a visual analysis of band patterns to assess severity of distortion within these three therapy groups. Figure 2 1 Summary of mouse study design. Top of figure denotes randomized mice groups and category of treatment each group belongs in. Bottom of figure denotes timeline of observation from the start of each experiment on Day 0, to the end of each experiment on Day 10.

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22 Table 2 1 Breakdown of each experiment (total of 6 experiments) by type of group included and number of animals . No PBS/No Phage (No treatment) PBS (Phosphate Buffer) F.O.P. (Bacteriophage Cocktail) F.O.P. 1:10 Dilution EcoShield TM ( E.coli phage) AMP (ampicillin) Number of Animals (n = 85 total) Experiment 1 15 mice Experiment 2 15 mice Experiment 3 15 mice Experiment 4 10 mice Experiment 5 15 mice Experiment 6 15 mice

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23 Materials The Foodborne Outbreak Pill (F.O.P.) bacteriophage cocktail was designed and manufactured by Intralytix, Inc. Researchers at Intralytix combined three FDA evaluated, commercial grade phage preparations originally developed (and currently utilized) in appli Additional information on the ingredients and manufacturing of ListShield TM , EcoShield TM , a nd SalmoFresh TM can be found in the appendix. In addition to the F.O.P. phage preparation, numerous other phage preparations are described with detail in previous reports [21,22], including complete ingredient lists of phages used. Each of the fifteen phag es constituting the F.O.P. preparation is diluted from a high titer stock to achieve a goal concentration of approximately 1x10 10 PFU / mL prior to mixing, with the cocktail including a 1X PBS to serve as a buffering agent. The F.O.P. phage preparation com ponents are summarized in Table 2. When not in use, the cocktail was stored at 4°C, away from light. The E.coli only bacteriophage preparation, EcoShield PXTM, tested against the F.O.P. therapy is an active component of the F.O.P bacteriophage preparation and was also provided by Intralytix Inc. We did not evaluate microbiome profiles on samples from mice who received the EcoShield TM bacteriophage. Mice w ere ear punched for identification and allowed to acclimate prior to the start of an experiment. LB Agar plates were made under sterile conditions of 36g of powdered LB agar per 900ml distilled water, thoroughly mixed with agitation, autoclaved, and cooled to 70OC for the addition of NalAc. For each bottle of 900ml liquid LB Agar, we added 0.9ml of NalAc, mixing thoroughly on low heat to prevent agar solidification without damaging the antibiotic. Stock of NalAc was prepared under sterile conditions to a fi nal concentration of 25mg/ml. All plates were

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24 made 1 3 days prior to Day 0 for each experiment to prevent degradation of plate quality at the time of sample streaking. Table 2 2 Components of each bacteriophage preparation used to create the F.O.P. bacteriophage cocktail total of 15 phages Salmonella phage SBA 1781 Listeria monocytogenes phage LMSP 25 Escherichia coli O157:H7 phage ECML 359 Salmonella phage SKML 39 Listeria monocytogenes phage LMTA 34 Escherichia coli O157:H7 phage ECML 363 Salmonella phage SPT 1 Listeria monocytogenes phage LMTA 148 Escherichia coli O157:H7 phage ECML 117 Salmonella phage SSE 121 Listeria monocytogenes phage LMTA 57 Salmonella phage STML 13 1 Listeria monocytogen es phage LMTA 94 Salmonella phage STML 198 Listeria monocytogenes phage LIST 36 Study Methods Each experiment began with t hree specific oral gavage procedures performed on Day 0 ( Figure 1 ) . Each of the three gavages were buffered by a 2.5 hour waiting period from the previous procedure. The mice received a prophylactic gavage, the E.coli challenge gavage, and a treatment gavage. The prophylactic gavage given was the therapy assigned at rand om to each cage in each experiment. Mice were then challenged 2.5 hours later with 0.2ml fresh 4 hour culture of pathogenic E. coli O157:H7 nalidixic acid resistant (NalAc R ) strain231 to achieve a dose of 1x10 8 cfu E.coli in each animal. 2.5 hours post chal lenge, stool samples were collected first and then mice were gavaged with 1x10 9 cfu of the matching respective therapy (prophylaxis and therapy type were identical for each cage based on randomization). All treatments, excluding ampicillin, were administer ed twice daily by oral gavage for four consecutive days [Days 0, 1, 2, 3]. The ampicillin therapy was the only therapy was administered before and after bacterial challenge only on Day 0 and not on any other day (however ampicillin mice underwent gavage pr ocedure on all days). Stool samples were collected on Days 0, 1, 2, 3, 5, and 10.

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25 Sample Analysis Methods We collected 3 pellets (approx. 50 mg) of stool per animal into tubes containing 0.45ml of PBS and homogenized with 3 sterilized glass beads. From the homogenized stool samples, we removed a suspension of 0.1ml and diluted the suspension by a factor of 10 with PBS. We streaked 0.1ml from this dilution on LB Agar + NalAc plates to count viable pathogenic E. coli counts per animal. We streaked an addition al set of plates with a serial dilution from the first plating process for a final dilution of 1 to 1000. All samples were plated in duplicates and incubated for 24 hours at 37 o C. The weight of each animal was recorded (in grams) at initial challenge, at e very stool collection, and prior to sacrificing for trend analysis. Microbiota A nalyses Methods same cage into a combined cage sample for a total volume of 0.5ml using a cu t pipette tip. DNA was extracted using a modified Qiagen stool DNA protocol (Mai et al. 2006). DNA was amplified by qPCR using sequencing primers (1Slt224 gene stx1 ATG TCA GAG GGA TAG ATC CA) and (1Slt385 gene stx1TAT AGC TAC TGT CAC CAG ACA AT) to determ ine the number of E.coli genome copies within treatment groups for Days 0,1,2, and 3. We analyzed microbiota community profiles using DGGE (Denature Gradient Gel Electrophoresis). A 457 bp fragment from the V6 to V8 region of the bacterial 16S rDNA gene w as amplified with primers U968 GC and L1401. DGGE was performed in an 8% (wt/vol) polyacrylamide gel with a denaturing gradient ranging from 40% to 50% at the top and bottom of the gel, respectively (100% denaturing conditions were defined as 7 M urea and 40% formamide). After electrophoresis (16 h, 65 V, 60 o C), the gel was stained with SYBER Green (Novex, San Diego, CA). DGGE analysis was performed only for F.O.P bacteriophage therapy, ampicillin therapy, and PBS therapy groups for Days 0, 1, 5, and 10. W e compared the degree of

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26 microbiota distortion between treatment groups by comparing banding patterns indicative of microbiota diversity within each group and evaluating levels of band conservation. Distortion for both F.O.P. therapy and ampicillin therapy were compared against the PBS control group. Statistical A nalyses Methods Statistical analysis was conducted in Microsoft Excel v16.22 in which databases housing all collected data for weight and E.coli counts were stored. Two tail distribution t tests and p values were used to assess (i) concentrations of E. coli O157:H7 strain 231 between varying therapy groups compared with control groups, and (ii) average percent change of weight by cage for each therapy group on Days 1,2,3,5, and 10 as compared to b aseline Day 0. Viable E.coli colony counts were determined for each individual animal and averaged by therapy group for statistical testing (assuming unequal variances).

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27 CHAPTER 3 RESULTS AND ANALYSIS Weight Data We observed weight loss in all groups on Day 1 from the initial challenge on Day 0. Over this 24 hour period, the bacteriophage groups had minimal average weight loss (calculated as percent change) when compared to control and antibiotic groups (p < 0.05). On Day 1, the F.O.P. 1:10 group had a weight loss of 1.28% from Day 0, the smallest negative change of all groups when compared to EcoShield and F.O.P. therapy (weight loss of 1.81% and 1.69% respectively). These Day 1 values were statistically significan t against PBS and No PBS/No Phage groups, which had weight loss of 3.42% and 2.93% respectively. We used only the PBS group as the control for statistical significance and weight change trends for Days 2, 3, 5 and 10. The ampicillin group had the greatest weight loss with a 5.44% reduction for Day 1 and maintained greatest weight loss over all groups for Day 2 with 4.69% negative weight change, Day 3 with 3.97%, and Day 5 with 4.14%. Within the bacteriophage therapy groups, Day 1 showed the greatest weight loss in EcoShield (1.81%), though this changed on Day 2 to F.O.P. therapy with 2.36% weight loss, followed by F.O.P. 1:10 with 2.00% weight loss, but Day 3 greatest weight loss was again in EcoShield with 1.94%. The weight loss values of F.O.P. 1:10 staye d close to, but lower than, the F.O.P. therapy group on all days except for Day 5 where F.O.P. 1:10 had slightly more weight loss though this may be due to F.O.P. therapy losing two animals between Day 3 and Day 5. On Day 10 the F.O.P. group had the great est recovery of weight, with a positive weight change on of 4.15%, compared to PBS with 0.64% weight gain, and ampicillin with 1.17% weight gain. Day 10 was the only day to show positive weight change above the Day 0 baseline values. There is a notable dec rease in weight for the No phage/No PBS group on Day 3. This may be due to the fact that the initial experiment with No phage/No PBS group did not

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28 collect weight data for Day 5 unlike the other experiments. Graph 1 denotes the average weight change in perc ent of all treatment groups including statistical significance and standard error. Graph 3 1 Displays the % weight change in all groups across the 10 days of treatmen t . A mpicillin displayed the greatest weight loss. Bars marked * indicate statistical si gnificance when compared against PBS contro l groups . Viable E.coli C olony Results Graph 2, Graph 3, and Graph 4 show the results of the first and second arms of this study while Graph 5 shows the results of the third arm of this study. Our results of viable E.coli count reductions shown are for Day 1,2, and 3 as all significant reductio ns occurred prior to Day 3. Graph 2 shows colony counts of bacteriophage groups against control groups for Day 1 where all bacteriophage treatments had significant reductions in viable pathogen counts, compared to the PBS control group, at similar levels o f efficacy . Graph 3 shows the F.O.P. treatment group with the highest reduction, followed by EcoShield, with a significant reduction compared to the three remaining groups. Graph 4 shows that by Day 3, no bacteriophage groups had significant reductions as the PBS reduction caught up with the pathogen counts in the bacteriophage groups.

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29 Graph 5 denotes the average value per treatment group for experiment 5 and experiment 6 of v iable E.coli colony counts from plating between PBS therapy, F.O.P. therapy, and a mpicillin therapy. There was a significant reduction in pathogenic E.coli counts for both the F.O.P and ampicillin groups. Graph 3 2 Denotes the pathogen reduction between controls and all bacteriophage therapy groups for the combined data of Experimen ts 1 4 for Day 1 using absolute numbers as the x axis scale. Bars marked with * indicate statistically significance when compared against PBS control group.

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30 Graph 3 3 Denotes the pathogen reduction between controls and all bacteriophage therapy groups f or the combined data of Experiments 1 4 for Day 2 using absolute numbers as the x axis scale. Bars marked with * indicate statistically significance when compared against PBS control group. Graph 3 4 Denotes the pathogen reduction between controls and al l bacteriophage therapy groups for the combined data of Experiments 1 4 for Day 3 using absolute numbers as the x axis scale. Bars marked with * indicate statistically significance when compared against PBS control group.

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31 Graph 3 5 Denotes the pathogen reduction between F.O.P., Ampicillin, and PBS for the combined data of Experiment 5 and Experiment 6. Bars marked with * indicate statistically significance. qPCR and DGGE Results We found no significant changes in the number of E.coli genome copies across treatment groups when samples were analyzed through DNA extraction and qPCR (Graph 6), indicating that reductions observed in viable E.coli counts are representative of actual pathogen reduction within the animals . Equal fecal suspens ions of stool from every animal were combined by cage for DNA extraction and DGGE analysis. The bands produced in each column, for different treatment days in groups PBS, F.O.P., and ampicillin indicate microbiota diversity though they do not provide infor mation on the species of microorganisms affected by distortion. Based on the resulting DGGE image and band patterns within each group, there were no observable differences in microbiota distortion within groups treated with PBS and FOP over the 10 days fol lowing the E.coli treatment intervention, however the ampicillin group had microbiota distortion detectable after two doses of antibiotic on Day 0 and continued distortion throughout

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32 treatment though the group did not receive additional ampicillin treatmen ts. During the post intervention observation window (Day 5 to Day 10) the ampicillin group had partial recovery by Day 10 but did not return to baseli ne profile, as shown in Figure 3 1 . Figure 3 1 DGGE Analysis of combined cage samples taken from Experi ment 5 and Experiment 6 denoting the gut microbiome profiles between PBS, F.O.P phage therapy, and ampicillin therapy groups.

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33 Graph 3 6 Denotes the number of E.coli genomic copies within F.O.P., Ampicillin, and PBS for Experiment 5 and 6. This data repre sents the total DNA quantity to serve as a comparison for viable pathogen quantities determined through LB plating. Analysis The F.O.P. bacteriophage treatment significantly (P < 0.05) reduced E. coli pathogen concentration by > 55%, and this reduction was the same as that observed with the antibiotic therapy. However, greater initial weight loss occurred in mice treated with an tibiotic therapy group ( 5.44%) compared to both control and FOP bacteriophage groups ( 3.56% and 2.24%, respectively). DGGE displayed no changes in gut microbiota composition in the control and the bacteriophage therapy groups after therapy. In contrast, the antibiotic group displayed noticeable distortion of the gut microbiota composition, only partially returning to normal by day 10. Results from qPCR of combined cage samples displayed similar levels of E. coli DNA across all groups on Day 1 with simila r rates of washout on Day 2, 3, and 10; however, in counts of viable E. coli colonies from LB plating we observed significant differences in E. coli quantities for FOP and Ampicillin groups when compared to PBS. The data collected from DNA extraction and qPCR does not discriminate between viable E.coli as it only quantifies fragments of E.coli DNA which can result from both viable and lysed cells. As we found no differences in the number of E.coli genomic copies among different groups over the course of tr eatment, we determined that efficacy against viable E.coli and the reduction observed in colony growth on LB plating is indicative of the practical effectiveness of each therapy group in reducing viable E.coli counts in the mice .

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34 CHAPTER 4 DISCUSSION Weight change As shown in Table 2 and Graph 1, different therapy groups displayed varying levels of weight loss when compared against baseline weights of Day 0, and when compared against the rates of weight loss observed in respective control groups. For Experiments 1 4 , weight loss occurred in all the animals, however there was reduced weight loss in both the full dose F.O.P cocktail therapy group and the EcoShieldTM therapy group, at similar rates. Animals lost an average of 0.4 grams of body weight in both groups, ind icating that there is no additional combination effect on weight loss from the F.O.P cocktail as opposed to the single target bacteriophage preparation EcoShieldTM. Though the animals had similar protection against weight loss regardless of which full dose bacteriophage was administered against the pathogenic E.coli challenge, animals in the therapy group receiving the diluted F.O.P showed the least amount of weight loss, losing an average of 0.32 grams of body weight. This could indicate that the effect of weight loss may have a dose response relationship with bacteriophage therapy. The PBS therapy group in Experiments 1 4 showed the greatest weight loss, however this may be due to the stress of the oral gavage procedure and not wholly due to the E.coli ch allenge and placebo therapy. The control group that did not receive any therapy displayed less weight loss than the PBS therapy group, suggesting that the oral gavage procedure may have contributed to initial weight loss. However, as the bacteriophage grou ps received therapy via oral gavage as well, comparisons of those groups against the PBS therapy group are credible. In experiment 5 and 6, weight loss was assessed for Days 1,2,3,5 and 10 against baseline values determined for each therapy group at Day 0 . We noted the same relationship between PBS therapy and F.O.P therapy as seen in Experiments 1 4, with the F.O.P. therapy group showing a

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35 much lower percent change of weight loss from baseline compared against PBS. Additionally, the ampicillin group showe d the highest percent change of weight with mice losing 5.44% of body weight by Day 1 as opposed to 2.24% of body weight change in the F.O.P. cocktail therapy group. This trend remained consistent through the Day 2 and Day 3. By Day 5, both the PBS thera py group and the F.O.P therapy group had plateaued to similar weight loss percent changes, while ampicillin continued to remain greater in weight loss. As antibiotics are well documented for having significant gastrointestinal side effects, explaining why mice treated with ampicillin would demonstrate greater weight loss than other groups. Our data indicates that bacteriophage therapy, while weight loss did occur, was markedly less severe than the weight loss suffered from antibiotic therapy. Reduction o f pathogenic E.coli Graphs 2, 3, 4 and 5 show varying observable reduction s in counts of pathogenic E.coli colonies for the initial three days of treatment administration among all therapies . As the E.coli strain utilized in this study is not pathogenic to mice, we observed relatively rapid washout of the pathogen from the mice as compared to previous studies evaluating Shigella and Listeria [23]. The pathogen reduction becomes variable from Day 2 onward, with F.O.P. 1:10 showing minimal reduction between Day 1 and Day 2, but a large drop on Day 3, unlike other groups. Day 1 and 2 show F.O.P. therapy as more effective than EcoShield. Graph 5 highlig hts a reduction greater than 55% by Day 2 of treatment in the F.O.P. bacteriophage therapy group, a competitive reduction when compared against ampicillin, though ampicillin provided a faster rate of pathogenic count reduction. Ultimately, against other ph age therapies and antibiotic therapy, the F.O.P. therapy reduced pathogenic counts significantly during the first 48 hours of all experiments and did not have a significant difference in reduction rate when compared against ampicillin, though ampicillin wa s observed to have a slightly higher efficacy throughout.

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36 However, by Day 3 within the bacteriophage groups the F.O.P. therapy was as effective as both the F.O.P. 1:10 dilution and the EcoShield therapy. Graphs 2, 3 and 4 suggest that there may be a dose response association between pathogenic count reduction rate and the concentration of the bacteriophage therapy administered when comparing the reduction of the full dose F.O.P. cocktail against the diluted dose of F.O.P. cocktail. Though both concentratio ns reduced the pathogenic count , and the difference between the rates was not significant despite the diluted dosage resulting in a slightly lower reduction , there is data supportive of bacteriophage therapy concentrations having different efficacy perform ance . By testing the F.O.P. 1:10 and observing muted effects compared to the full dose of F.O.P cocktail , could indicate that effects are attributable to the phage , but the impact of the protective effects is associated with the concentration of the therap y administered , or the concentration of the pathogen at the time of phage therapy administration . If a milder effect is desired, the concentration of the bacteriophage preparation can be altered to achieve a milder or more pronounced effect. The clinical i mplications of bacteriophage therapy in that dosages can be customized or titrated according to the specific conditions of the infection. Both the F.O.P bacteriophage and the EcoShield TM reduced the pathogenic counts at a similar rate, resulting in no indi cation that one preparation worked with higher efficiency than the other in this study. We did observe that the rate of reduction of both bacteriophages were each slightly lower but comparable in efficacy against ampicillin therapy, respectively. Microbiom e Profile Figure 2 is the DGGE image obtained from samples of Experiments 5 and 6. By using temperature to distinguish nucleic acids across the acrylamide gel, different base pair sequences within different genes denature at various rates, resulting in ban ds of distinct genetic material forming down the gel. Our image distinctly shows that specific bands remain in the same

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37 location across each lane for the PBS therapy group (first four lanes on the left). These same visually distinct bands can be seen in mi ddle four lanes denoting F.O.P. therapy and stay conserved when compared against PBS. However, in the right four lanes denoting ampicillin therapy it is clear there is significant distortion immediately between Day 0 and Day 1. The distortion partially cal ibrates back to the baseline by Day 10 however notable distortion remains. This data suggests that the microbiome profile of the overall gut environment was severely negatively affected by the use of ampicillin wherein the F.O.P. bacteriophage group did no t disturb the microbiome profile during the process of reducing the pathogenic E.coli from the animal. Combined with the weight loss trends and rates of pathogenic cell reduction we observed, this demonstrates that the antibiotic therapy resulted in negati ve impacts on the gut microbiome with notable gastrointestinal side effects, while the bacteriophage therapy resulted in milder gastrointestinal side effects despite also significantly reducing E.coli pathogen counts. Limitations of study Regarding f ecal recovery from enteric diseases in animal models , see ing similar results in human populations is expected . Though animal models are sufficient to investigate the efficacy and impact of different therapies, it should be noted that the gut microbiome of mice is different than that of humans. Similar trends in distortion are likely to be seen in humans, however the severity in distortion may vary when evaluated in humans, as we have distinctly different gut microbiomes from one another while the mice existed in controlled conditions. The gut microbiome is directly impacted by factors like the microbiome in the mouth, the nutrition we consume, or animal exposure in our environments, which will impact gut microbiota analysis in people. Another slight limitation is the use of a pathogen that is not clinically pathogenic to mice but is clinically pathogenic to humans. Though the data produced by this study is legitimate to contribute towards research of bacteriophages against pathogens we cannot attest to how

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38 bacteri disease effects). Finally, we designed our study to only observe the animals for a total of 10 days, as that was sufficient to investigate our study objective on whet her distortion occurred (which we were able to determine). If we allowed for a longer observation time in order to add to the microbiome profile analysis, we may have been able to determine at what timepoint the distortion in the antibiotic treatment group gut microbiota returned back to the baseline profile, adding additional depth to the conclusions on the effects of antibiotics on gut microbiota as opposed to the effects of bacteriophage therapy.

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39 CHAPTER 5 CONCLUSION Investigation Findings Through the observation of reduction in viable pathogenic E.coli counts by the F.O.P bacteriophage cocktail, we were able to draw three conclusions on the use of this particular phage preparation when compared against control groups, single target bacterio phage groups, and antibiotic groups. During this study, we observed three main effects of E.coli/ Salmonella/ Listeria bacteriophage cocktail (F.O.P.) . i) The F . O . P . bacteriophage treatment is effective at reducing E.coli pathogen counts in infected mice. ii) The F . O . P . bacteriophage treatment did not show disruption of the gut microbiota community while the antibiotic treatment group did show significant disruption of gut microbiota as early as the first day of treatment. iii) The F . O . P . bacteriophage treated group ha d the smallest percent of weight change. The greatest initial weight loss observed was the antibiotic treatment group when compared with both the F . O . P . bacteriophage treated group and PBS group. This study found that F . O . P . administration was effective in reducing the levels of pathogenic E. coli in infected mice at a similar rate to ampicillin therapy, which has important clinical applications. However, the F . O . P . bacteriophage preparation had a milder impact on the gut microbiota compared to ampicillin: i.e., it did not trigger any distortion of the normal gastrointestinal microbiota; whereas, treatment with the antibiotic resulted in noticeable gastrointestinal microbiota distortion in mice.

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40 Implications and Future Studies The findings of this study support the growing research in the use of bacteriophage therapy as a reliable clinical alternative to antibiotics against bacterial pathogens. As patients develop resistance to first and second line antibiotic therapies, the limited clinical option s available as a last line of treatment are often toxic, with harsh side effects [3 4 ]. Bacteriophage therapy has potential to aid in the antibiotic resistance crisis public health currently faces, providing targeted therapy with milder effects, adding an e xtra level of therapeutic defense for patients with decreasing options. With the rise of antibiotic resistance organisms and research showing the valuable relationship between a healthy gut microbiome and reduction in adverse health outcomes, investing in bacteriophage therapy as a pharmacological treatment choice is necessary.

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41 APPENDIX ADDITIONAL TABLES Table A 1 Percent Weigh t Change for all therapy groups . Denotes weight changes (in % weight change when compared to the weight taken at Day 0 as baseline ) across all treatment groups over the course of Day 1, Day 2, Day 3, Day 5, and Day 10 compared to baseline values collected on Day 0. Values with * indicate statistical significance against the PBS control group. Weight (% change) Day 1 Day 2 Day 3 Day 5 Day 10 No phage, No PBS 2.93% 2.85% 6.80% 3.17% ______ PBS 3.42% 3.79% 3.11% 2.29% +0.64% F.O.P. 1.69% * 2.36% * 1.66% * 0.32% +4.15% EcoShield TM 1.81% * 1.24% * 1.94% * 1.33% * ______ F.O.P. (1:10) 1.28% * 2.00% * 1.42% * 0.85% * ______ Ampicillin (AMP) 5.44 % * 4.69 % 3.97% 4.14% +1.17% Table A 2 E.coli viable counts for Bacteriophage therapy groups . Average E.coli counts from viable colonies grown in LB Agar plates for all treatment groups included in experiments 1,2,3 and 4. Values with * signify statistically significance when compared against control group . (cfu/50 mg stool) Day 1 Day 2 Day 3 No PBS/ No Phage 1.21E+05 5.17E+03 1.42E+02 PBS 1.13E+05 4.90E+03 3.25E+01 F.O.P Cocktail 7.29E+04 * 5.90E+02 * 3.85E+01 * F.O.P 1:10 Dilution 7.89E+04 * 8.23E+02 2.90E+01 * EcoShield TM 7.63E+04 * 3.20E+03 * 8.00E+00 * Table A 3 E.coli viable counts for F.O.P. and Ampicillin therapy groups . Average E.coli counts from viable colonies grown in LB Agar plates for all treatment groups included in Experiment 5 and 6. Values with * signify statistically significance (cfu/50 mg stool) Day 1 Day 2 Day 3 PBS 1.34E+05 3.40E+03 2.42E+02 F.O.P Cocktail 6.10E+04 * 2.01E+03 * 5.60E+01 * Ampicillin 2.76E+04 * 1.15E+03 * 3.90E+01 *

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42 Table A 4 E.coli viable counts , p value calculations for all therapy groups against controls and against other therapy groups . P values calculated as t.test function in excel on viable E.coli counts from LB agar plating for each individual animal within each treatment groups. No Phage/ No PBS v. PBS No Phage/N o PBS v. F.O.P. No phage/ No PBS v. EcoShi eld TM No phage/ No PBS v. F.O .P. (1:10) PBS v. F.O.P. PBS v. EcoSh ield TM PBS v. F.O.P. 1:10 F.O.P. v. EcoSh ield TM F.O.P. v. F.O.P. (1:10) F.O.P. (1:10) v. EcoShi eld TM Day 1 0.55991 7 1.296 x10 05 * 0.0002 2* 2.335x 10 05 * 0.0044 2* 0.0193 * 0.0069 * 0.5586 1 0.68741 6 0.7924 26 Day 2 0.76939 1 9.63x10 07 * 0.0108 0* 0.8868 0 3.29x1 0 08 * 0.0134 * 0.8052 3 0.0025 * 7.6503x 10 19 * 0.0007 9* Day 3 0.04672 * 0.055484 0.0377 9* 0.0140 6* 0.6885 03 0.8243 1 0.0828 7 0.3709 5 0.00018 3* 0.0231 0* Table A 5 E.coli viable counts , p value calculations for all therapy groups against controls and against other therapy groups . P values calculates as t.test function in excel between different therapy groups; viable E.coli counts; * denotes statistical significance P values F.O.P. cocktail v. PBS Ampicillin v. PBS F.O.P. cocktail v. Ampicillin Day 1 0.002355208 * 5.30102x10 05 * 1.1986x10 05 * Day 2 0.055871802 0.002514946 * 0.014930837 * Day 3 0.005345975 * 0.002252626 * 0.505828384

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43 LIST OF REFERENCES 1) Ashkenazi SH, Even Tov SM, Samra ZM, Dinari GA. Uropathogens of various childhood populations and their antibiotic susceptibility. The Pediatric infectious disease journal. 1991 Oct;10(10):742 6. 2) Grüneberg RN. Changes in urinary pathogens and their antibiotic sensitivities, 1971 1992. Journal of Antimicrobial Chemotherapy. 1994 May 1;33(suppl_A):1 8. 3) de Gunzburg J, Ghozlane A, Ducher A, et al. Protection of the Human Gut Microbiome From Antibiotics. J Infect Dis. 2017;217(4):628 636. 4) Coryell, M., McAlpine, M., Pinkham, N.V., McDermott, T.R. , Walk, S.T., 2018. The gut microbiome is required for full protection against acute arsenic toxicity in mouse models. Nature Communications 9, 5424. 5) Sheflin AM, Whitney AK, Weir TL. Cancer promoting effects of microbial dysbiosis. Curr Oncol Rep . 2014;16(10):406. 6) Sulakvelidze A, Alavidze Z, Morris JG. Bacteriophage therapy. Antimicrob Agents Chemother . 2001;45(3):649 59. 7) Nelson ML, Levy SB. The history of the tetracyclines. Annals of the New York Academy of Sciences. 2011 Dec 1;1241(1):17 32. 8) Matsuzaki S, Rashel M, Uchiyama J, Sakurai S, Ujihara T, Kuroda M, Ikeuchi M, Tani T, Fujieda M, Wakiguchi H, Imai S. Bacteriophage therapy: a revitalized therapy against bacterial infectious diseases. Journal of infection and chemotherapy. 2005 Oct 1; 11(5):211 9. 9) Stapleton PD, Taylor PW. Methicillin resistance in Staphylococcus aureus: mechanisms and modulation. Sci Prog . 2002;85(Pt 1):57 72. 10) Tan SY, Tatsumura Y. Alexander Fleming (1881 1955): Discoverer of penicillin. Singapore Med J . 2015;56(7):366 7. 11) Chang Q, Wang W, Regev Yochay G, Lipsitch M, Hanage WP. Antibiotics in agriculture and the risk to human health: how worried should we be?. Evol Appl . 2014;8(3):240 7. 12) Chandel NS, Budinger GR. The good and the bad of antibiotics. Sci Transl Med. 2013;5(192):192fs25. 13) Ventola CL. The antibiotic resistance crisis: part 1: causes and threats. P T. 2015;40(4):277 83. 14) Lin DM, Koskella B, Lin HC. Phage therapy: An alternative to antibiotics in the age of multi drug resistance. Wor ld J Gastrointest Pharmacol Ther. 2017;8(3):162 173.

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44 15) Loc Carrillo C, Abedon ST. Pros and cons of phage therapy. Bacteriophage. 2011;1(2):111 114. 16) Kutter E, De Vos D, Gvasalia G, Alavidze Z, Gogokhia L, Kuhl S, et al. Phage therapy in clinical pract ice: treatment of human infections. Curr Pharm Biotechnol. 2010;11:69 86. 17) Skurnik M, Pajunen M, Kiljunen S. Biotechnological challenges of phage therapy. Biotechnol Lett. 2007;29:995 1003. doi: 10.1007/s10529 007 9346 1. 18) Carlton RM. Phage therapy: past history and future prospects. Arch Immunol Ther Exp (Warsz) 1999;47:267 274. 19) Alisky J, Iczkowski K, Rapoport A, Troitsky N. Bacteriophages show promise as antimicrobial agents. J Infect. 1998;36:5 15. doi: 10.1016/S0163 4453(98)92874 2. 20) Thur sby E, Juge N. Introduction to the human gut microbiota. Biochem J . 2017;474(11):1823 1836. Published 2017 May 16. doi:10.1042/BCJ20160510 21) Sweeney TE, Morton JM. The human gut microbiome: a review of the effect of obesity and surgically induced weight loss. JAMA Surg . 2013;148(6):563 9. 22) Jandhyala SM, Talukdar R, Subramanyam C, Vuyyuru H, Sasikala M, Nageshwar Reddy D. Role of the normal gut microbiota. World J Gastroenterol . 2015;21(29):8787 803. 23) Haque SZ, Haque M. The ecological community of co mmensal, symbiotic, and pathogenic gastrointestinal microorganisms an appraisal. Clin Exp Gastroenterol . 2017;10:91 103. Published 2017 May 5. doi:10.2147/CEG.S126243 24) Clokie MR, Millard AD, Letarov AV, Heaphy S. Phages in nature. Bacteriophage . 2011; 1(1):31 45. 25) Moye ZD, Woolston J, Van den Abbeele P, Duysburgh C, Verstrepen L, Marzorati M and Sulakvelidze A. A bacteriophage cocktail eliminates Salmonella Typhimurium from the human colonic microbiome while preserving cytokine signaling and preventi ng attachment to and invasion of human cells by Salmonella in vitro Journal of Food Protection 26) Moye ZD, Woolston J, Sulakvelidze A. (2018). Bacteriophage Applications for Food Production and Processing. 27) Mai V, Ukhanova M, Reinhard MK, Li M, Sulak velidze A. Bacteriophage administration significantly reduces Shigella colonization and shedding by Shigella challenged mice without deleterious side effects and distortions in the gut microbiota. Bacteriophage . 2015;5(4):e1088124. Published 2015 Aug 28. doi:10.1080/21597081.2015.1088124 28) Sengupta S, Chattopadhyay MK, Grossart HP. The multifaceted roles of antibiotics and antibiotic resistance in nature. Frontiers in microbiology. 2013 Mar 12;4:47.

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45 29) Fair, R. J., & Tor, Y. (2014). Antibiotics and bact erial resistance in the 21st century. Perspectives in medicinal chemistry , 6 , 25 64. doi:10.4137/PMC.S14459 30) Lutter SA, Currie ML, Mitz LB, Greenbaum LA. Antibiotic Resistance Patterns in Children Hospitalized for Urinary Tract Infections. Arch Pediatr Adolesc Med. 2005;159(10):924 928. doi:10.1001/archpedi.159.10.924 31) Lushniak B. D. (2014). Antibiotic resistance: a public health crisis. Public health reports (Washington, D.C. : 1974) , 129 (4), 314 6. 32) Rahal EA, Fadlallah SM, Nassar FJ, Kazzi N, Matar GM. Approaches to treatment of emerging Shiga toxin producing Escherichia coli infections highlighting the O104:H4 serotype. Front Cell Infect Microbiol . 2015;5:24. Published 2015 Mar 18. doi:10.3389/fcimb.2015.00024 33) Bielaszewska M, Idelevich EA, Zhang W, et al. Effects of antibiotics on Shiga toxin 2 production and bacteriophage induction by epidemic Escherichia coli O104:H4 strain. Antimicrob Agents Chemother . 2012;56(6):3277 82. 34) Kutateladze M, Adamia R. Bacteriophages as potential new thera peutics to replace or supplement antibiotics. Trends Biotechnol. 2010;28:591 595.

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46 BIOGRAPHICAL SKETCH The author of this thesis is an alumnus of the University of Florida where she received During a five year hiatus from academic pursuits, Upuli was employed with the University of Florida Physicians Primary Care Pediatrics department, where she continued to work during the pursuit of her mast degree, in addition to her employment with the UF Department of Neurosurgery through the Neuromedicine Clinical and Academic Interdiscplinary Program as a graduate intern. She hopes to continue her education in academic medical research, wi th a focus on infectious diseases and the human microbiome.