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The Swine Intestinal Microbiota: Localized Adaptations and Responses to In-Feed Antibiotics Torey P

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The Swine Intestinal Microbiota: Localized Adaptations and Responses to In-Feed Antibiotics Torey P Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations 2012 The swine intestinal microbiota: localized adaptations and responses to in-feed antibiotics Torey P. Looft Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/etd Part of the Animal Sciences Commons, Ecology and Evolutionary Biology Commons, and the Microbiology Commons Recommended Citation Looft, Torey P., "The swine intestinal microbiota: localized adaptations and responses to in-feed antibiotics" (2012). Graduate Theses and Dissertations. 12390. https://lib.dr.iastate.edu/etd/12390 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. The swine intestinal microbiota: localized adaptations and responses to in-feed antibiotics by Torey P. Looft A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Microbiology Program of Study Committee: Thaddeus Stanton, Co-Major Professor Gwyn Beattie, Co-Major Professor Nancy Cornick Alexandra Scupham Drena Dobbs Iowa State University Ames, Iowa 2012 Copyright © Torey Looft, 2012. All rights reserved. ii TABLE OF CONTENTS LIST OF FIGURES vii LIST OF TABLES ix ACKNOWLEDGEMENTS xi ABSTRACT xii CHAPTER 1. GENERAL INTRODUCTION 1 Introduction 1 Dissertation Organization 2 Literature Review 3 History of antibiotic use in agriculture 3 Bacterial diversity in the GI tract 5 Host mucosa and immune system 6 Bacterial specialists in the GI tract 8 Lactic acid bacteria 9 Butyrate-producing bacteria 9 Mucin-degrading bacteria 10 How antibiotics in feed lead to improved feed efficiencies 11 Collateral effects of in-feed antibiotics on the gut microbiota 12 On disease susceptibility 12 On beneficial microbes and functions 12 The GI antibiotic resistome 14 Alternatives to in-feed antibiotics 17 Antibiotic alternatives for improved feed efficiency 17 iii Antibiotic alternatives for disease treatment and prevention 18 Summary 19 Future directions with host-bacterial interactions in the gut 20 References: 21 CHAPTER 2. IN-FEED ANTIBIOTIC EFFECTS ON THE SWINE INTESTINAL MICROBIOME 30 Abstract 31 Introduction 32 Results 34 Shifts in Community Membership with ASP250 34 Shifts in Functional Gene Abundance with ASP250 35 Pervasive Antibiotic Resistance in the Absence of Antibiotic Exposure 36 qPCR and Metagenomic Analyses Reveal Shifts in Resistance Gene richness and Abundance in Medicated Pigs 37 Discussion 38 Conclusions 42 Materials and Methods 43 Swine. 43 DNA Sequencing. 43 Phylotype Analysis. 44 Metagenomic Analysis 44 Quantitative PCR. 45 Statistical Analysis of qPCR Results: Abundance and Diversity. 45 iv References: 47 CHAPTER 3. SWINE MICROBIAL COMMUNITIES, SUBDIVIDED BY INTESTINAL LOCATIONS AND ANTIBIOTICS 55 Abstract 56 Introduction 57 Methods 59 Swine 59 16S rRNA gene sequence analysis 60 Phylotype analysis. 61 Metagenomic analysis 62 Results and discussion 63 Swine intestinal bacterial diversity exhibits radial specificity 63 Distinct ileum-radial differences 64 Bacterial membership and functions exhibit longitudinal specificity. 65 The effect of antibiotics on bacterial community structure and function. 67 The effect of in-feed antibiotics is measurable at discrete gut regions. 68 Antibiotic resistance gene diversity 69 Conclusions 70 References 71 CHAPTER 4. CLOACIBACILLUS PORCORUM SP. NOV.,–A MUCIN-DEGRADING BACTERIUM FROM THE SWINE INTESTINAL TRACT 83 Abstract 84 Introduction 85 v Strain isolation 85 Strain CL-84 T cell morphology 86 16S rRNA gene sequence analysis 87 Substrate utilization 88 Fermentation Products 89 Growth Tolerance 90 Cellular fatty acid content 90 Resistance to antibiotics 91 Description of Cloacibacillus porcorum sp. nov. 91 References 93 CHAPTER 5. GENERAL CONCLUSIONS 100 Collateral impacts of in-feed antibiotics on the swine microbiota 100 Community Shifts 100 Resistance 101 The importance of spatial distribution of bacteria in the gut 102 Characterizing bacterial specialists in gut 102 Future directions 103 References 105 APPENDIX A. SUPPORTING INFORMATION FOR CHAPTER 2 106 APPENDIX B. SUPPORTING INFORMATION FOR CHAPTER 3 138 vi APPENDIX C. IN-FEED ANTIBIOTICS INDUCE PROPHAGES IN SWINE FECAL MICROBIOMES 144 APPENDIX D. TABLE OF MUCIN DEGRADERS ISOLATED FROM THE SWINE INTESTINAL TRACT 183 vii LIST OF FIGURES Figure 2.1. Shifts in fecal bacterial community membership with antibiotic treatment 52 Figure 2.2. Changes in diversity and abundance of antibiotic resistance genes (ARG) in swine feces with antibiotic treatment 53 Figure 3.1. Bacterial genera that have significantly different representation between mucosa and lumen environments to mucosa or lumen association 76 Figure 3.2. Swine intestinal bacterial communities differentiate along longitudinal and radial axes 77 Figure 3.3. Bacterial community structure, based on OTU assignments 78 Figure 3.4. Nonmetric Multidimensional Scaling analysis of OTU-based bacterial 16S rRNA gene sequence abundances in individual pig intestinal samples 79 Figure 3.5. Bacterial genera that are differentially present due to antibiotic treatment 80 Figure 3.6. Spindle diagram of COGs with differential representation (adjusted p<0.01) between the medicated and nonmedicated metagenomes 81 Figure 4.1. Morphology of CL-84 T 95 Figure 4.2. Neighbor-joining phyogentic tree of proposed species Cloacibacillus porcorum 96 Appendix figures Figure A1. E. coli enumerations from swine gut contents in a repeated ASP250 study 113 Figure A2. Microbial functions encoded by the swine metagenomes 114 Figure A3. Tetracycline efflux abundance trends for each treatment animal 115 Figure B1. Total assigned reads from metagenomes, averaged by intestinal location and treatment 139 Figure B2. Stress Response assignments among the locations (non-medicated) 140 Figure C1. Electron micrographs of virions isolated from swine feces 168 Figure C2. Community structure based on taxonomic inference of phages from swine feces 169 viii Figure C3. Community structure based on taxonomic inference of bacteria (16S rRNA sequences) from swine feces 170 Figure C4. Population dynamics of bacteria and phages in swine fecal microbiomes 171 Figure C5. Box plot of integrase-encoding gene abundance in nonmedicated ( n = 10) And medicated ( n = 5) swine viromes ( P < 0.01) 172 Supplemental Figure C1. GAAS was used to infer phylogeny of the phage-derived Sequences from the subtherapeutic and therapeutic carbadox experiments 175 Supplemental Figure C2. Schematic of swine fecal phage metagenomic study 176 Supplemental Figure C3. Clusters of orthologous groups (COGs) identified by CAMERA in assignable virome reads 177 ix LIST OF TABLES Table 2.1. Antibiotic resistance genes differentially represented ( P < 0.05) in the medicated vs. nonmedicated pig fecal samples as detected by metagenomics 54 Table 3.1. Antibiotic resistance of differential abundance in swine medicated versus nonmedicated metagenomes 82 Table 4.1. Fermentation of substrates that support growth of strain CL-84 T 97 Table 4.2. Cellular fatty acid profiles (%) of strain CL-84 T and C. evryensis , grown on BHIAH medium 98 Table 4.3. Differential characteristics of the species Cloacibacillus porcorum and related species genera in the phylum Synergistetes 99 Appendix tables Table A1. Phylotypes based on 16S analysis, by treatment 116 Table A2. Clusters of orthologous groups (COGs) that are differentially represented in the ASP250 (n=1) vs. unmedicated (n=3) swine fecal metagenomes 118 Table A3. Individual COGs of the energy production and conversion COG category That were significantly more prevalent in the medicated metagenome (n = 1) than the nonmedicated metagenomes (n = 3) 125 Table A4. Primer sets targeting antibiotic resistance genes (specificity classified by ARDB) 126 Table A5. Primer sets targeting antibiotic resistance genes (specificity classified by NCBI) 131 Table A6. Quantitative PCR primers used in validation of the antibiotic resistance primer set 135 Table B1. Most abundant bacteria from the intestinal samples of swine fed ASP250 and their nonmedicated counterparts 141 Table C1. Antibiotic resistance genes detected more than twice across all viromes, as annotated by the antibiotic resistance gene database 173 Supplemental Table C1. Mean and standard error (SE) of the most abundant bacteria in the feces of swine fed ASP250 and their nonmedicated counterparts 178 x Supplemental Table C2. Estimated operational taxonomic unit diversity of 16S rRNA gene sequences in the ASP250 experiment 179 Supplemental Table C3. Summary of swine fecal phage metagenomic (virome) data 180 Supplemental Table C4. Barcodes used in this study for parallel 16S rRNA gene sequencing 181 Table D1. Taxonomic assignments of partial 16S rRNA gene sequences 183 xi ACKNOWLEDGEMENTS I would like to thank the members of my Program of Study Committee: Drs. Thad Stanton, Gwyn Beattie, Nancy Cornick, Alexandra Scupham, and Drena Dobbs for their time and effort towards my graduate education. Dr. Thad Stanton provided a wonderful research environment with the support and knowledge to cultivate ideas and an excitement for science that is contagious. I have been fortunate to work with many talented people and would like to
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