COLLATERAL CHANGES IN SUSCEPTIBILITY OF BURKHOLDERIA MULTIVORANS by Jerilyn Nicole Flanagan A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biology Charlotte 2019 Approved by: ______________________________ Dr. Todd Steck ______________________________ Dr. Molly Redmond ______________________________ Dr. Adam Reitzel ______________________________ Dr. Jennifer Warner ______________________________ Dr. John Risley ii ©2019 Jerilyn Nicole Flanagan ALL RIGHTS RESERVED iii ABSTRACT JERILYN NICOLE FLANAGAN. Collateral changes in susceptibility of Burkholderia multivorans. (Under the direction of DR. TODD R. STECK) Antibiotic resistant bacteria, particularly in chronic infections, are difficult and costly to treat, so research into detection, identification, and treatment options is critical. Susceptibility measurement must accurately reflect the degree to which the strain will respond to antibiotics, so the first investigation was of parameters that affect antimicrobial susceptibility testing such as agar depth and hydration. Additionally, in order to study new ways in which bacteria may be vulnerable to antimicrobials, researchers must experimentally evolve bacteria to be drug-resistant. The second methodological investigation involved development of an easy, cost- and labor-efficient process for laboratory evolution of antibiotic-resistant bacteria. Burkholderia multivorans, a member of the Burkholderia cepacia complex (Bcc), can cause chronic lung infections in vulnerable patients. A possible treatment for chronic infections arises from the existence of collateral sensitivity (CS): decreased resistance to a non-treatment antibiotic acquired along with resistance to the treatment drug. Identifying CS patterns for bacteria may lead to sustainable treatment regimens that reduce development of multidrug resistant bacterial strains. CS has been found to occur in E. coli, P. aeruginosa, and S. aureus. The two latter studies report that B. multivorans exhibits antibiotic CS, as well as cross resistance (CR), describe CS and CR networks for six clinically-relevant antibiotics, and identify reciprocal CS drug pairs. Characterization of CS and CR patterns allow antibiotics to be separated into two clusters, which is a first step towards predicting antibiotic therapy strategies. iv DEDICATION There is no chance I would have completed this dissertation, much less my degree, without the staunch support of my favorite person, Robert Flanagan. It is impossible to put into words my love and appreciation without being trite and cheesy, so I’ll simply say that when all my mirrors were angry, the enchanted burgundy heart- shaped medallion was perfect. I love you. This dissertation (as well as anything good that ever comes from me) is for you. v ACKNOWLEDGEMENTS My deepest gratitude to Dr. Todd Steck for being my advisor. I appreciate the help of my committee members – Drs. Molly Redmond, Adam Reitzel, Jennifer Warner, and John Risley - throughout this process. I’m lucky to have people with genuine enthusiasm for science and academia as my mentors. I also gratefully acknowledge the assistance of Dr. James Oliver, my original advisor. To my labmates and fellow graduate students, I offer thanks for being a sounding board, and for sharing laughter, coffee, and my snacks. In particular, my utmost gratitude to Logan Kavanaugh for doing the wretched sequencing stuff. Without the help of people outside of academia, my accomplishments would never be. My Meghan is one of my favorite people, and I’m thankful she was always willing to say “bastard!” when necessary. I’m eternally grateful to Drs. Anthony Patterson and Kyra Grosman for fixing my brain when it was horribly broken and teaching me that the remaining broken bits were manageable. I thank the microbiology department at Memorial Regional Hospital in Florida for showing me that a nerdy love of all things bacterial is, in fact, super cool. I send a special shout-out to SSC. A special thanks goes to the billions of organisms that went unknowingly to their deaths to make my project work. I’ll always think of you when I smell bleach. vi TABLE OF CONTENTS List of Tables viii List of Figures ix List of Abbreviations x CHAPTER 1: Introduction 1 CHAPTER 2: The relationship between agar thickness and antimicrobial 7 susceptibility testing Citation and Abstract 7 Introduction 7 Materials and Methods 9 Results and Discussion 10 References 11 Tables and Figures 13-15 CHAPTER 3: Use of antibiotic disks to evolve drug-resistant bacteria 16 Citation and Abstract 16 Introduction 16 Materials and Methods 18 Results and Discussion 19 References 21 Tables and Figures 24 CHAPTER 4: Burkholderia multivorans exhibits antibiotic collateral 25 sensitivity Citation and Abstract 25 Introduction 26 Materials and Methods 28 Results 31 Discussion 34 References 38 Tables and Figures 44-47 CHAPTER 5: Reciprocal collateral sensitivity of Burkholderia 48 multivorans and genetic mutations involved Citation and Abstract 48 Introduction 49 Materials and Methods 51 Results 55 Discussion 61 References 65 vii Tables and Figures 76-83 CHAPTER 6: CONCLUSIONS 84 REFERENCES 87 APPENDIX A: EVOLVED STRAIN LIST 93 APPENDIX B: ANTIMICROBIAL SUSCEPTIBILITY TESTING 106 RESULTS SPREADSHEETS viii LIST OF TABLES CHAPTER 2 Table 1: Minimum inhibitory concentration and zone of inhibition 13 values on regular agar plates Table 2: Minimum inhibitory concentration and zone of inhibition 14 values on dehydrated agar plates CHAPTER 3 Table 3: Exposures needed to evolve resistant strains of bacteria to 24 one of six antibiotics CHAPTER 4 Table 4: Antibiotics used for experimental evolution and testing 44 CHAPTER 5 Table 5: Antibiotics used for experimental evolution and testing 76 Table 6: Strains evolved and collateral changes observed 77 Table 7: Statistical significance of clustering within/between 79 antibiotics Table 8: Mutations in strains with a treatment drug of levofloxacin 82 and collateral sensitivity to meropenem Table 9: Mutations in strains with a treatment drug of meropenem 83 and collateral sensitivity to levofloxacin ix LIST OF FIGURES CHAPTER 2 Figure 1: Linear regression of minimum inhibitory concentration 15 (MIC) values compared to agar plate weight CHAPTER 3 Figure 2: Image of bacterial strains before and after evolution of 24 antibiotic resistance CHAPTER 4 Figure 3: Number of evolved strains exhibiting collateral 45 sensitivity and cross-resistance Figure 4: Heat map of cross-resistance (CR) interactions 46 Figure 5: Network of collateral susceptibility changes 47 CHAPTER 5 Figure 6: Heat map of collateral resistance and sensitivity 78 interactions Figure 7: Cross-resistance and collateral sensitivity interactions by 78 cluster Figure 8: Change in minimum inhibitory concentration by non- 80 treatment drug Figure 9: Reciprocal collateral resistance/sensitivity pair patterns 81 x LIST OF ABBREVIATIONS AST antimicrobial susceptibility testing B. multivorans Burkholderia multivorans Bcc Burkholderia cepacia complex βLA non-beta-lactam antibiotic CHL chloramphenicol CAZ ceftazidime CF cystic fibrosis CR cross-resistance CS collateral susceptibility/sensitivity MIC minimum inhibitory concentration NON-βLA non-beta-lactam antibiotic NTD non-treatment drug MEM meropenem LVX levofloxacin MIN minocycline SXT trimethoprim-sulfamethoxazole TD treatment drug ZOI zone of inhibition 1 CHAPTER 1: INTRODUCTION Antimicrobial resistance is a critical problem facing our medical system due to rapid evolution of resistant bacteria, over-exposure to antimicrobials leading to pan- resistance, and lack of new antibiotics. When bacteria can no longer be treated by an antibiotic to which it was sensitive, infections are harder to control, the risk of spread is increased, morbidity is prolonged with added financial cost, and the risk of death is greater (1). Monitoring bacteria for antimicrobial resistance, developing new antimicrobials or substances to boost efficacy of existing antibiotics, and investigating different ways to exploit bacterial weaknesses are all important components to the clinical counterstrike. Antimicrobial susceptibility testing (AST) is an in vitro method of evaluating the level of resistance of a bacterial strain to the drug of interest. Interpretative breakpoints are established to predict treatment efficacy of an antimicrobial agent in an infected patient based on in vitro testing (2). “Resistant” bacteria are defined as strains that are not normally inhibited by usually achievable systemic concentration of an antimicrobial agent with normal dosage schedule, which is correlated with a specific concentration of the drug when tested in vitro. The “susceptible” or “sensitive” category includes isolates that are inhibited by the antibiotic at a physiologically achievable concentration. The “intermediate” designation is used to describe organisms that might respond to the antibiotic, depending on the location of the infection and the drug dosage. There are several methods of antimicrobial susceptibility testing, including broth dilution and agar diffusion methods (3). For agar diffusion, an antibiotic-impregnated sterile carrier material such as a paper disk or plastic strip is placed on the top of a solid 2 growth medium and the antibiotic diffuses out, creating a concentration gradient in the medium with the area closest to the disk containing the highest concentration of antibiotic. Inconsistency in test administration