Bioinformatic Analysis of Streptomyces to Enable Improved Drug Discovery

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Bioinformatic Analysis of Streptomyces to Enable Improved Drug Discovery University of New Hampshire University of New Hampshire Scholars' Repository Master's Theses and Capstones Student Scholarship Spring 2019 BIOINFORMATIC ANALYSIS OF STREPTOMYCES TO ENABLE IMPROVED DRUG DISCOVERY Kaitlyn Christina Belknap University of New Hampshire, Durham Follow this and additional works at: https://scholars.unh.edu/thesis Recommended Citation Belknap, Kaitlyn Christina, "BIOINFORMATIC ANALYSIS OF STREPTOMYCES TO ENABLE IMPROVED DRUG DISCOVERY" (2019). Master's Theses and Capstones. 1268. https://scholars.unh.edu/thesis/1268 This Thesis is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Master's Theses and Capstones by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. BIOINFORMATIC ANALYSIS OF STREPTOMYCES TO ENABLE IMPROVED DRUG DISCOVERY BY KAITLYN C. BELKNAP B.S Medical Microbiology, University of New Hampshire, 2017 THESIS Submitted to the University of New Hampshire in Partial Fulfillment of the Requirements for the Degree of Master of Science in Genetics May, 2019 ii BIOINFORMATIC ANALYSIS OF STREPTOMYCES TO ENABLE IMPROVED DRUG DISCOVERY BY KAITLYN BELKNAP This thesis was examined and approved in partial fulfillment of the requirements for the degree of Master of Science in Genetics by: Thesis Director, Brian Barth, Assistant Professor of Pharmacology Co-Thesis Director, Cheryl Andam, Assistant Professor of Microbial Ecology Krisztina Varga, Assistant Professor of Biochemistry Colin McGill, Associate Professor of Chemistry (University of Alaska Anchorage) On February 8th, 2019 Approval signatures are on file with the University of New Hampshire Graduate School. iii ACKNOWLEDGEMENTS As a graduate student at UNH I was blessed to become close to the people that supported me. I would like to thank my advisors, Dr. Brian Barth and Dr. Cheryl Andam, for their time, patience, and guidance. My passion for research stemmed from the opportunities, faith, and time that they invested in me. Without their support, so many life altering experiences would not have happened, including but not limited to, going to graduate school, publishing my first paper, going to the Alaska, mastering my fear of public speaking with the three-minute thesis, trying bioinformatics, attending conferences, receiving scholarships and fellowships, and applying for my current job. I am extremely grateful. Thank you also to my other committee members, Dr. Kriztina Varga and Dr. Colin McGill for your guidance and time. My class professors, including Dr. Matt MacManes, Dr. Kelley Thomas, Erica Stelmach, and Anthony Westbrook answered countless of questions. In particular, Anthony Westbrook was an integral influence on my fascination with bioinformatics. His enthralling teaching style and his investment in his student’s understanding was crucial to the dry lab portion of my thesis. I would also like to acknowledge Dr. Timothy Montminy, Dr. Louis Tisa, and Amy Michaud. Each of them welcomed my impromptu visits to their offices to discuss research or life questions. I worked as a teaching assistant with each of them, which in and of itself was an incredible experience. Additionally, much of the wet lab portion of my experiments would not have been possible without help from Amy Michaud. She constantly helped me solve the problems that inevitably popped up along the way. iv I would also like to thank my lab mates. They made my time in the lab and outside of it such a pleasure. There are many of them between Dr. Barth and Dr. Andam’s labs, so I will only individually highlight a few, but all of them were deeply appreciated. The graduate students, most specifically Cooper Park, Josh Smith, Vera Wang, and Vicky Papakotsi, were amazing. Thank you for the many laughs, philosophical, and academic talks that helped me along the way. Cooper Park is genius bioinformatician and teacher. I am lucky to be able to say that he is one of my best friends. As apartment mates, he would often tutor me in bioinformatics after a long day of school work. He spent countless hours helping me and I cannot explain how much that means to me. Josh Smith would also welcome my spontaneous visits to his cubical to ask various questions about my scripts. Vera would train me and all the other Barth lab mates in the mouse house and the lab with endless patience, as well. Finally, before I took Anthony Westbrook’s python course, Joseph Sevigny helped to teach me the basics of bash and generate figures. Thanks also to Stephen Simpson and the rest of the Hubbard Center for Genomic Studies team for sequencing all the bacterial strains that I isolated for my research. I had a wonderful support network outside of school, too. My mom would constantly check in to see how I was doing. She would drive more than three hours up to New Hampshire and back in a day just to have lunch with me. She understood it was hard for me to spend that time traveling home, so she brought home to me. I also have friends that would listen to me talk about my research, even though it was outside of their fields, for hours. Kailey Troller, Nick Chagnon, Nate Edwards, Joe Durant, Paige Howard, and Ray D’Entremont were my rocks to the outside world. Despite my cancelling plans to work on writing or having to go home early from any version of a social gathering so I could do work in the morning for the past two years, they have v stuck by my side. Nick Chagnon attended every public speaking event I presented at, proof read my papers, and endured my occasional tears. He was there through all of it. Thank you. Dr. Cheryl Andam once told me that you make your life-long friends in grad school. I could not agree more. The connections that I made are invaluable. I am humbled to have been educated by my brilliant professors, peers, and others who have helped me along the way. Finally, thank you to the resources that funded my research at UNH, including the UNH Student Teaching Fellowship, the New Hampshire Agricultural Experiment Station (NHAES) grant number NH00653 to CPA, National Cancer Institute grant number K22-CA190674 to BMB, and the UNH Core Pilot Research Partnership to CPA and BMB. vi TABLE OF CONTENTS ACKNOWLEDGEMENTS .......................................................................................................... iii LIST OF TABLES ....................................................................................................................... vii LIST OF FIGURES ...................................................................................................................... vii ABSTRACT .................................................................................................................................. ix INTRODUCTION: THE ROLE OF THE MICROBIOME IN CANCER AND THE DEVELOPMENT OF IMPROVED CANCER THERAPEUTICS ............................................... 1 GENOME MINING OF BIOSYNTHETIC AND CHEMOTHERAPEUTIC GENE CLUSTERS IN STREPTOMYCES BACTERIA AND INSIGHTS TO POPULATION-LEVEL DRUG DISCOVERY STRATAGIES ...................................................................................................... 19 IDENTIFICATION OF STREPTOMYCES AKAC8 FOR THE MODIFICATION OF URSOLIC ACID ............................................................................................................................................ 40 FUTURE DIRECTIONS REGARDING PRODUCTION OF NOVEL CHEMOTHERAPEUTIC COMPOUNDS BY STREPTOMYCES ........................................................................................ 57 APPENDIX .................................................................................................................................. 59 BIBLIOGRAPHY ........................................................................................................................ 74 vii LIST OF TABLES Table 1. Summary of bacterial strains and their role in the development and/or treatment of cancers ………………….…………......……………………………………………………….................16 Table S1. Accession numbers of the 1,110 Streptomyces genomes used in this study…………....59 Table S2. List of CGCs used in Figure 3. Sequences were obtained from DoBISCUIT (Ichikawa et al, 2013)………………………..........………………………………………..................……..73 LIST OF FIGURES Chapter 2 Fig. 1. Phylogenetic distribution of the 34 major classes of BGCs in 1,110 Streptomyces genomes…………………………………………………………………….…………………....26 Fig. 2. Frequency and diversity of BGCs……………………………………...………………….28 Fig. 3. Phylogenetic distribution of the CGCs that encode antitumor compounds………………..31 Fig. 4. Inter-strain differences in the distribution of BGCs and CGCs…………………………....33 Chapter 3 Figure 1. (a) Mass spectrometry results of acetone extract of NLT (b) MTS PMS viability assay after AML cell line exposure to quercetin or UA for 48 hours…………...……………………….42 Figure 2. Fecal Sample Collection and Streptomyces Isolate Isolation, Purification, and Identification…………………………………………………………………………………......45 Figure 3. 16S Genomic Distribution of Primary Submission of Whole Genome Sequencing viii ……………………………………………………………………………………………………49 Figure 4. Comparative Analysis of the Primary and Secondary Genome Sequencing of Streptomyces akac8………………………………………………………………………...…….50 Figure 5: Media Optimization Protocol Results…………………………………………………..51 Figure 6. Minimum Inhibitory Concentration Testing of Streptomyces Grown with UA…...........52 Figure 7. Biosynthetic Gene Cluster
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