Detection of Antibiotic Resistance in Swine Production

By:

SEPIDEH PAKPOUR

Department of Food Science and Agricultural Chemistry Macdonald Campus, McGill University Montreal, Quebec

A thesis submitted to the Office of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for the degree of Master of Science.

August, 2010

TABLE OF CONTENT

TABLE OF CONTENT I

LIST OF TABLES VII

LIST OF FIGURES VIII

LIST OF ABBREVIATIONS IX

ABSTRACT X

RÉSUMÉ XI

ACKNOWLEDGMENTS XIII

INTRODUCTION XV

Hypotheses XVI

Objectives XVII

Experimental Approach XVII

CONTRIBUTION TO RESEARCH XIX

LIST OF PUBLICATIONS AND PRESENTATIONS XX

CHAPTER 1. LITERATURE REVIEW 1

1.1 General Introduction to Antibiotics 1

1.1.1 Definition 1

1.1.2 History of Antibiotics 1

1.1.3 Classifications 2

1.1.4 How do Antibiotics Work? 2

1.1.5 Applications of Antibiotics 3

1.2 General Introduction to Antibiotic Resistance 4

1.2.1 Definition 5

1.2.2 Classification 6

1.2.2.1 Innate (Intrinsic) Resistance 6

1.2.2.2 Acquired (Extrinsic) Resistance 6

1.2.2.3 Adaptation 7

1.3 General Introduction to Swine Rearing 9

1.4 Antibiotic Resistance in Swine Production 11

1.5 Tetracyclines 12

1.5.1 Discovery and Development of Tetracyclines 12

1.5.2 Structure of Tetracyclines 14

1.5.3 Mode of Action 14

1.5.4 Resistance to Tetracyclines 17

1.5.4.1 Protection of the Ribosome 17

1.5.4.2 Efflux Proteins 19

1.5.4.3 Enzymatic Inactivation 19

1.5.4.4 Other/Unknown Mechanisms of Resistance 21

1.6 Macrolides 21

1.6.1 Discovery and Development of Macrolides 21

1.6.2 Structure of Macrolides 23

1.6.3 Mechanisms of Action of Macrolides 23

1.6.4 Resistance to Macrolides 23

1.6.4.1 Ribosomal Methylation 23

1.6.4.2 Efflux Systems 25

1.6.4.3 Enzymatic Inactivation 25

1.6.4.4 Mutational Resistance to Macrolides 25

1.7 General Introduction to Tylosin 26

1.8 Food-Borne Pathogens 27

CONNECTING STATEMENT TO CHAPTER 2 29

CHAPTER 2. PRELIMINARY STUDIES 29

2.1 Abstract 29

2.2 Introduction 30

2.3 Material and Methods 31

2.3.1 Swine Rearing and Sampling 31

2.3.2 Enumeration of Total Aerobic Bacteria on Solid 32 Media 2.3.2.1 Preparation of Aerobic Dilution Water 32

2.3.2.2 Preparation of Solid Media 32

2.3.2.3 Dilution of Fecal Samples 32

2.3.2.4 Inoculation of Solid Media by Spread-Plate 33

2.3.3 Enumeration of Total Anaerobic Bacteria on Solid 33 Media

2.3.3.1 Preparation of Anaerobic Dilution Water 33

2.3.3.2 Preparation of Solid Media 35

2.3.3.3 Dilution of Fecal Samples 35

2.3.3.4 Inoculation of Solid Media by Spread-Plate 35

2.3.4 DNA Extraction 36

2.3.4.1 Extraction of Total DNA From Bacterial 36

III

Strains Used as Positive Control for PCR

2.3.4.2 Extraction of Total Community DNA From 36

Swine Feces

2.3.4.3 DNA Integrity, Concentration and Purity 37

2.3.5 PCR for Bacteria 16S rDNA 37

2.3.6 Real-Time PCR for tet (O) 41

2.3.6.1 Primers and Probes 41

2.3.6.2 Preparation of DNA Dilution Series 41

2.3.6.3 Real-Time PCR for tet (O) 42

2.4 Results 44

2.4.1 Anaerobic Dilution Water 44

2.4.2 Enumeration of Total Aerobic and Anaerobic 44

Bacterial Populations

2.4.3 DNA Extraction 44

2.4.3.1 Extraction of Total DNA From Bacterial Strains 44

Used as Positive Control for PCR

2.4.3.2 Extraction of Total Community DNA From 46

Swine Feces

2.4.4 PCR for Bacteria 16S rDNA 46

2.4.5 Real-time PCR for tet (O) 48

2.5 Discussion 51

2.5.1 Anaerobic Dilution Water 51

2.5.2 Bacterial Enumerations 51

2.5.3 Extraction of Total Community DNA from Swine 52

Feces

2.5.4 PCR Reaction Mixture for Bacteria 16S rDNA 53

2.5.5 PCR Conditions for Bacteria 16S rDNA 54

2.5.6 Real_Time PCR for tet (O) 55

2.6 Conclusions 57

2.7 Acknowledgments 57

CONNECTING STATEMENT TO CHAPTER 3 58

CHAPTER 3. ANTIBIOTIC RESISTANCE IN SWINE 58 PRODUCTION 2.5 YEARS AFTER DISCONTINUATION OF ANTIBIOTIC USE.

3.1 Abstract 58

3.2 Introduction 59

3.3 Material and Methods 61

3.3.1 Swine Rearing and Sampling 61

3.3.2 Bacterial Enumerations 61

3.3.3 DNA Extraction 63

3.3.4 PCR Amplification 64

3.3.5 Standard for Real-Time PCR 65

3.3.6 Optimization of Real-Time PCR 65

3.4 Results 67

3.4.1 Bacterial Enumerations. 67

3.4.2 Antibiotic Resistance Genes 68

3.4.3 Optimization and Standard Curve for Real-Time 72 PCR

3.4.4 Real-Time PCR for tet (O) 74

3.5 Discussion 77

3.5.1 Bacterial Enumerations 77

3.5.2 Gender Effect 78

3.5.3 Antibiotic resistance Genes 80

3.5.4 Abundance of tet (O) 82

3.6 Conclusions 83

3.7 Acknowledgments 83

CHAPTER 4. GENERAL CONCLUSIONS 85

4.1 Antibioic Resistance in Swine Production 86

4.2 Experimental Approach 86

4.3 Methodology 87

4.3.1 Culture-Dependent Methods 87

4.3.2 Molecular Biology Techniques 88

4.3.2.1 Polymerase Chain Reaction 88

4.3.2.2. Quantitative Real-Time PCR 88

4.4 Conclusions 89

REFERENCES 90

APPENDIX. ANIMAL USE PROTOCOLS & BIOHAZARDS 102 CERTIFICATES

LIST OF TABLES Table 1.1 Principal members of the tetracycline class. 13

Table 1.2 Structures of the principal members of the tetracycline class 15

Table 1.3 Mechanisms of resistance for characterized tet and otr genes. 22 Table 2.1 Oligonucleotide primers, amplicon size, annealing temperatures 39 and positive used for PCR amplification of bacterial genes.

Table 2.2 Optimization of the PCR reaction mixture and conditions. 40

Table 2.3 Annealing temperatures and primer and probe concentration 43 used for real-time PCR amplification of tet (O).

Table 2.4 Abundance of total aerobic and anaerobic bacterial populations 45 in swine feces. Brain Heart Infusion Agar (BHIA) and Tryptic Soy agar (TSA) were compared.

Table 2.5 Yield and quality of total DNA extracted from bacterial strains 45 used as positive controls for PCR. Strains were preserved at -20 oC in 15% glycerol.

Table 2.6 Yield and quality of total community DNA extracted from swine 47 feces.

Table 2.7 Optimization of the PCR reaction mixture and conditions. 47

Table 2.8 Precision of standard curves during optimization of real-time 49 PCR reaction mixture and conditions for tet (O).

Table 2.9 Linearity and efficiency of standard curves during optimization 50 of real-time PCR reaction mixture and conditions for tet (O).

Table 3.1 Swine rearing and sampling. 62

Table 3.2 PCR detection of selected tetracycline [ tet (ABCDEKLMOSY)] 71 and macrolide [ erm (ABC)] resistance genes among bacterial populations in individual pigs during suckling, weanling, growing and finishing. Only genes detected are indicated.

Table 3.3 Accuracy of standard curves for the real-time PCR assay for 73 tet (O) quantification.

VII

LIST OF FIGURES

Figure 1.1 Transformation 8

Figure 1.2 Transduction 8

Figure 1.3 Conjugation 8

Figure 1.4 Pig inventories in Canada in quarterly year-to-year change 10

Figure 1.5 Uptake of tetracycline by Escherichia coli 16

Figure 1.6 Ribosome protection 18

Figure 1.7 Efflux proteins 20

Figure 1.8 Enzymatic inactivation 20

Figure 1.9 Chemical structures of some macrolide antibiotics 24

Figure 1.10 Food-borne illness 28

Figure 3.1 Enumeration of (A) Tot, (B) Tet R and (C) Tyl R anaerobic bacterial 69 populations in individual pigs during suckling, weanling, growing and finishing

Figure 3.2 Abundance (A and B), evolution (C and D) and percentage (E 70 and F) of Tot, Tet R and Tyl R anaerobic bacterial populations in males (average for 6 males in panels A, C, E) and females (average for 4 females in panels B, D, F) during suckling (S), weanling (W), growing (G) and finishing (F)

Figure 3.3 Abundance of tet (O) among bacterial populations in individual 75 pigs during suckling, weanling, growing and finishing.

Figure 3.4 Average abundance of tet (O) among bacterial populations in 6 76 males and 4 females during suckling (S), weanling (W), growing (G) and finishing (F).

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LIST OF ABBREVIATIONS

16S rRNA 16S subunit of ribosomal ribonucleic acid BHIA Brian-Heart Infusion Agar BSA Bovine Serum Albumin CFU Colony Forming Unit

CO 2 Carbon Dioxide DNA Deoxyribonucleic Acid dNTP Deoxyribonucleotide Triphosphate EU European Union FQRNT Fonds Quebecois de Recherche sur la Nature et les Technologies

H2 Hydrogen KCl Potassium Chloride LB Luria-Bertani

MgCl 2 Magnesium Chloride MIC Minimal Inhibitory Concentration mRNA Messenger Ribonucleic Acid

N2 Nitrogen

Na 2S.9H 2O Sodium Sulfide Nonahydrate NADPH Nicotinamide Adenine Dinucleotide Phosphate NSERC Natural Sciences and Engineering Research Council PCR Polymerase Chain Reaction rRNA Ribosomal Ribonucleic Acid Tet R Tetracycline-Resistant Tris-HCl Tris (hydroxymethyl) Aminomethane tRNA Transfer Ribonucleic Acid TSA Tryptic Soy Agar Tyl R Tylosin-Resistant USDA United States Department of Agriculture

ABSTRACT

Since antibiotics have been added to animal feed for decades, food animals and their wastes constitute a reservoir of antibiotic-resistant bacteria. At the Swine Complex of McGill University, the addition of antibiotics to swine feed for subtherapeutic applications has been discontinued since January 2007. The objective of this work was to assess the prevalence and short-term evolution of antibiotic resistance among bacterial populations in swine production 2.5 years after this discontinuation. Feces from ten healthy pigs (6 males and 4 females) born at the Swine Complex of McGill from the same sow and administered feed without antibiotics were sampled during suckling, weanling, growing and finishing. The percentage of chlortetracycline-resistant anaerobic bacterial populations (Tet R) was higher than that of tylosin-resistant anaerobic bacterial populations (Tyl R) at weanling, growing and finishing, with generally larger differences in males than in females. At the finishing stage, i.e. prior to the transportation of animals to the slaughterhouse, resistant populations varied between 3.1x10 6 and 2.5x10 9 CFU g -1 . In all pigs, tet (L), tet (O) and erm (B) were detected by PCR at suckling and weanling, whereas only tet (O) was detected at growing and finishing. Quantification of tet (O) by real-time PCR showed that at suckling, the abundance of this gene was 18 times higher in females than in males, was similar between the two genders at weanling and growing, and reached 5.1x10 5 and 5.6x10 5 copies of tet (O)/ $g of total DNA in the feces of males and females, respectively, at finishing. In this study, the high abundance and proportion of antibiotic-resistant populations, as well as the occurrence of resistance genes within these populations despite the discontinuation of antibiotic addition to feeds imply either that more time would be required for antibiotic resistance to decrease to lower levels, and/or that factors such as the presence of metals in feed impose a selective pressure that maintains antibiotic resistance genes among these bacterial populations.

RÉSUMÉ

Puisque des antibiotiques sont ajoutés aux moulées des animaux de ferme depuis des décennies, ces animaux et leurs déjections constituent un réservoir de bactéries résistantes aux antibiotiques. Au Complexe porcin de l'Université McGill, l’ajout d'antibiotiques dans les aliments pour porcs pour les applications sous-thérapeutiques a été interrompu en janvier 2007. L’objectif de ce travail était d'évaluer la prévalence et l’évolution à court terme de la résistance aux antibiotiques chez les populations bactériennes en production porcine 2,5 ans après cette interruption. Les matières fécales de dix porcs sains (6 mâles et 4 femelles) nés au Complexe porcin de McGill de la même truie et nourris avec des moulées sans antibiotiques ont été échantillonnées durant les phases d’allaitement, sevrage, croissance et finition. Le pourcentage de bactéries anaérobies résistantes à la chlortétracycline (Tet R) était généralement plus élevé que le pourcentage de bactéries anaérobies résistantes à la tylosine (TylR) lors des phases de sevrage, croissance et finition, avec des différences plus grandes chez les mâles que chez les femelles. Au stade de la finition, c’est à dire avant le transport des animaux vers l'abattoir, les populations résistantes variaient entre 3.1x10 6 et 2.5x10 9 UFC g-1 . Chez tous les porcs, les gènes tet (L), tet (O) et erm (B) ont été détectés par PCR lors des phases d’allaitement et de sevrage, alors que seulement tet (O) a été détecté en croissance et finition. La quantification de tet (O) par PCR en temps réel a montré que, à l’allaitement, l’abondance de ce gène était de 18 fois plus élevé chez les femelles que chez les mâles, était similaire entre les deux sexes en sevrage et en croissance, et a atteint 5.1x10 5 et 5.6x10 5 copies de tet (O)/ $g d’ADN total dans les excréments des males et des femelles, respectivement, à la phase de finition. La forte abondance et la proportion élevée de populations résistantes aux antibiotiques, ainsi que la présence de gènes de résistance au sein de ces populations malgré l'interruption de l’ajout d’antibiotiques aux moulées impliquent soit que plus de temps serait nécessaire pour que la résistance aux antibiotiques décroisse à des niveaux inférieurs, et/ou que des facteurs tel la

XI présence de métaux dans les moulées impose une pression sélective qui maintient les gènes de résistance aux antibiotiques parmi ces populations bactériennes.

XII

ACKNOWLEDGMENTS

I would like to extend my sincere gratitude to my supervisor, Dr. Martin Chénier (Assistant Professor, Department of Food Science), for his financial support, valuable time, ceaseless encouragement, professional advice, and endless help throughout masters. I am privileged to be his first master student. I would like to express my sincere thanks to Dr. Suha Jabaji (Department of Plant science, Macdonald Campus of McGill University) for her generosity, valuable guidance, expertise, valuable time throughout my work and providing some equipment used for the experiments. I would like to express my gratitude to my Scholarship sponsors, the Alexander Graham Bell Canada Graduate Scholarship M (NSERC), the Principal’s Graduate Fellowship (McGill) and the Macdonald Class of '44 Rowles Graduate Bursary (McGill) for financing of my study. My sincere thanks also go to Dr. Huilan Chen, Department of Plant Science (Macdonald Campus of McGill University) for her continuous guidance, advice, and encouragement throughout the course of my thesis; I also wish to express my sincere thanks to Dr. Selim Kermasha (Chair, Department of Food Science) for his excellent teaching skills, help and understanding; my committee member, Dr V. Yalayan (Professor, Department of Food Science), for his support and precious guidance, Dr. Benjamin K. Simpson (Professor, Department Food Science), Dr. Frederick R. van de Voort (Professor, Department of Food Science) and Dr. Hosahalli S. Ramaswamy (Professor, Department of Food Science), for their excellent teaching skills which benefited me a lot for my research and career life. I would also like to thank Mrs. Leslie Ann LaDuke, Mrs. Diane Chan- Hum, and Mrs. Deborah Martin, Administrative Assistants at the Department of Food Science, for all their administrative and secretarial help. Also my sincere thanks go to Dr. Lyle Whyte and Dr. Salwa Karboune for providing some equipment used in this study.

XIII

Special thanks are hereby extended to my friends Elham Azarpazhooh, Abbas Milani, Majid Karimi, Amir Omoumi, Fatemeh Zare, Hussein Hassan and Mohsen Gorji for their friendship and help during my graduate program. I am thankful to my colleagues Ms. Andrée-Anne Rouleau and Ms. Nema Boulis for helping me at the Swine Complex of McGill University and with anaerobic bacterial enumerations. I am thankful to my colleague and friends, Mr. Devin Holman, Mrs. Niloofar Hariri and Ms. Saghar Sefidbakht for sharing experiences and knowledge and useful suggestions and ideas for statistical analysis. Also I acknowledge my gratitude to Mr. Paul Meldrum, Manager of the Macdonald Campus Farm, and Mr. Denis Hatcher, employee at the Swine Complex, for their fruitful collaboration and valuable assistance in the research. Finally, I wish to give a huge thank you to my parents for always believing in me and for providing me with the encouragement and support that I needed. I’d like to thank my brothers (Farrokh Reza and Farbod) for their motivation, and my sister (Bahareh) for her support.

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INTRODUCTION Antibiotic resistance is defined as the ability of a microorganism to counteract the effect of antibiotics (American Academy of Microbiology, 2001). Although some bacteria are naturally resistant to antibiotics, most of them can acquire resistance through mutations or insertion of extrinsic genes which can spread very rapidly among bacteria (Institute of food technologists, 2006). Some of the genes that provide resistance to different types of antibiotics can be co- located on the same chromosome or mobile genetic element, which might cause multidrug resistance (Simeoni et al. 2008). Pork is the most frequently consumed meat in the world (Guan and Holley, 2003). Swine production is one of the principal economic activities in Canada and has made this country very successful in the world’s pork export market (Statistics Canada, 2000). Over the last 50 years, world production of pork has risen dramatically, reaching 964 million pigs in the world, including 24 million pigs in Canada with 7 million pigs in the province of Québec alone, in 2006 (Statistics Canada, 2006), although year-to-year hog inventories have continued to decrease since 2006 (Statistics Canada, 2010). In the province of Québec (Canada), swine production is an important economic activity and a major source of environmental problems because of the large volume of swine wastes that it generates (Statistics Canada, 2000). In commercial swine production, antibiotics have been used for decades to treat infections, to prevent diseases or to promote growth (Jindal et al. 2006). In contrast, antibiotics are generally used in human for disease treatment (Silbergeld et al. 2008). Antibiotics applied in swine production, therapeutically or sub-therapeutically, are structurally similar or identical to the ones utilized in human medicine. The similarity between them means that some commonly used antibiotics for human medicine could become ineffective if resistant bacteria transfer from livestock to the human food chain and infect people. This phenomenon can contribute to the development of resistant strains of pathogenic bacteria in human populations (Silbergeld et al. 2008). In addition, resistance genes can be transferred from fecal organisms to indigenous soil and water bacteria (Chee-Sanford et al. 2009). Farmers,

XV slaughterhouse workers and swine waste products are important reservoirs from which antibiotics and antibiotic-resistant bacteria can be transferred from the farm to the environment (Guan and Holley, 2003). Moreover, poor hygiene, improper food handling and inadequate cooking can cause the transmission of drug resistance genes and resistant bacteria from animals to humans (Institute of food technologists, 2006). This creates the risk of infectious diseases caused by antibiotic-resistant pathogenic bacteria and increases food safety and health concerns (Schlundt et al. 2004). In the mammal gut, pathogens are greatly outnumbered by commensal bacteria that can harbour the same resistance determinants as their disease- producing counterparts. Since the oxygen level in the swine large intestine is below 1%, anaerobic bacteria, for which the culturable fraction can reach 10 10 to 10 11 CFU g -1 , dominate over aerobic bacteria by tens to hundreds (Jensen and Jorgensen, 1994). Since anaerobic commensal bacteria constitute the numerically and ecologically dominant sub-population in the swine large intestine, we hypothesize that they serve as a diverse and highly abundant reservoir of resistance genes that may be transferred to pathogenic bacteria. This implies that not only pathogenic bacteria, but mainly commensal bacteria, especially anaerobes, must be targeted applying a relevant, whole-population approach as described in this work.

Hypotheses The hypotheses underlying the objectives and methodology of this project are the following. (a) The enteric commensal bacteria, especially anaerobes, constitute a diversified and highly abundant reservoir of antibiotic resistance genes in the swine intestine. (b) In the absence of antibiotic additions to swine feed, antibiotic resistance levels in the swine intestine should remain at low levels throughout the lifetime of pigs.

XVI

Objectives At the Swine Complex of McGill University, the addition of antibiotics to swine feed for nutritional (sub-therapeutic) applications has been discontinued since January 2007. The general objective of this work was to assess the prevalence and short-term temporal evolution (i.e. within the lifetime of pigs at the farm) of antibiotic resistance among enteric anaerobic bacterial populations in swine production 2.5 years after this discontinuation, using complementary quantitative classical microbiology and molecular biology techniques.

The preliminary objectives were: 1. To determine which solid medium provides the highest recovery of total anaerobic bacterial populations. 2. To determine which commercial extraction kit provides the highest yield and quality of extracted DNA from fecal samples.

The main objectives are: 1. To determine the abundance of anaerobic bacteria (total and resistant) in the swine intestine; 2. To detect the resistance genes present among the anaerobic bacterial populations; 3. To determine the abundance of the resistance gene the most frequently detected among these anaerobic bacterial populations.

Experimental Approach In the past, culture-dependant methods were used and are still needed to study the diversity and quantify the activities of microorganisms involved in biodegradation processes and biogeochemical cycling in natural environments. Culture-dependent microbiology methods are limited to the study of microorganisms which are active and can be grown under laboratory conditions (Chenier and Juteau, 2009). A variety of culture-independent techniques such as

XVII polymerase chain reaction (PCR), competitive quantitative PCR, real-time PCR, denaturing gradient gel electrophoresis and constant denaturant capillary electrophoresis have been developed for rapid enumeration and identification of bacteria (Fu et al. 2006). Thus, a reasonable combination of molecular methods and culture-dependent methods would offer better chances to improve our knowledge of microbial ecology of complex ecosystems.

XVIII

CONTRIBUTION TO RESEARCH

Part of this work has been presented in a poster at the 60 th Annual Meeting of the Canadian Society of Microbiologists in Hamilton, ON, on June 16 th , 2010. A manuscript is also in preparation for submission to Applied and Environmental Microbiology, a journal with one of the highest impact factor in this field. Ms. Sepideh Pakpour, Dr. Martin Chénier and Dr. Suha Jabaji were involved at different levels in the thesis research and preparation of the thesis. The present work has been supported financially by a Discovery Grant from the Natural Science and Engineering Research Council of Canada (NSERC). Sepideh Pakpour is the M.Sc. candidate who participated actively in the planning of the experiments, and actually carried out all experiments, gathered data, analyzed the results and prepared the first draft of the thesis manuscript. Dr. Martin Chénier is the thesis supervisor, under whose guidance the thesis was planned and carried out and who critically reviewed and edited the manuscript and thesis to its final form. Dr. Suha Jabaji provided the technical supervision to set up the PCR and real-time PCR experiments.

XIX

LIST OF PUBLICATIONS AND PRESENTATIONS

Poster: Pakpour, S., Jabaji, S., Chenier, M.R. (2010) “Detection of Antibiotic Resistance in Swine Production”, 60 th Annual Meeting of the Canadian Society of Microbiologists, Hamilton, ON, Canada, June 14 th -17 th , 2010, poster # AE100.

Manuscript: Pakpour, S., Jabaji, S., Chenier, M.R. (2011) “Antibiotic resistance in swine production after discontinuation of antibiotic use’’. For submission to Microbial Ecology, 37 pages.

CHAPTER 1. LITERATURE REVIEW

1.1 General Introduction to Antibiotics

1.1.1 Definition

Antibiotics are powerful medicines that fight bacterial infections. Natural antibiotics are substances that are generated by bacteria and fungi into their environment to selectively restrain the growth of other organisms. Chemists alter the structure of natural antibiotics in order to produce synthetic antibiotics (Hammond and Lambert, 1978). Generally, the unique ecological role of antibiotics in natural, non-clinical environments is to prohibit the growth of competitors. However, recently it has been indicated that antibiotics have a concentration-dependent role. At low concentration, antibiotics are mediators of intercellular signalling, while at higher concentration (found occasionally in some specific natural environments and developed in clinical settings), they selectively inhibit the growth of microorganisms (Fajardo and Martinez, 2008).

1.1.2 History of Antibiotics In 1928, penicillin was isolated by Alexander Fleming from the mould Penicillium notatum . First record of disease treatment by penicillin was in 1930, a case in which an eye infection in a three-year old boy was cured by a crude extract. In 1939, Ernst Chain and Howard Florey began to separate and purify penicillin, which was very useful to treat war-related infectious diseases during World War II (Gottlieb and Shaw, 1967). Selman Waksman and colleagues isolated streptomycin from a soil bacterium Streptomyces griseus in 1944. Streptomyces bacteria have been the source of almost two-thirds of all known antibiotics, including tetracyclines and macrolides. More recently, UK scientists have sequenced the genome of Streptomyces coelicolor , which may help to produce new antibiotics (Chadwick and Whelan, 1992).

1.1.3 Classifications Antimicrobials can be classified by at least four different schemes. In the first scheme, antibiotics can be classified into two large groups based upon their effects on target cells. Antibiotics that essentially kill microorganisms are termed bactericidal, while those that only inhibit the growth of microorganisms are termed bacteriostatic. In another classification scheme, antibiotics can be divided into natural and synthetic products. Natural antibiotics are produced by microorganisms to fight natural enemies. Semi-synthetic products are natural products that have been chemically modified in the laboratory to enhance their efficacy, decreasing their side effects and expanding the range of bacteria that can be treated with it. Synthetic antibiotics, such as linezolid, have provided new avenues in the treatment of drug-resistant bacterial infections. The third scheme of classifying antimicrobials is by their ranges of activity, i.e. narrow, moderate and broad. Narrow spectrum antibiotics are only active and effective against a relatively small number of organisms, usually the Gram-positive bacteria. Moderate spectrum antibiotics are effective not only on the Gram-positive bacteria but also against the most systemic, enteric and urinary tract Gram-negative pathogens. Finally, broad spectrum antibiotics are effective against all prokaryotes, with two exceptions, namely Mycobacteria and Pseudomonas . The last classification scheme is by structure or major structural fragments

that are derivable mainly from amino acids, acetate and simple sugars (Abraham

and Newton, 1960).

1.1.4 How do Antibiotics Work?

Not all antibiotics work in the same way. Different groups or classes of antibiotics have different actions on bacteria. Antibiotics may be applied to cure bacterial disease by prohibiting the formation of bacterial cell walls. Some antibiotics like penicillin and cephalosporin prevent the synthesis of peptide links

2 between peptidoglycan molecules in bacterial cell walls. This makes the cell wall weak and it causes the bacterium to detonate. Another group of antibiotics inhibit DNA replication. For example, rifampicin sticks to RNA polymerase in bacteria and inhibits transcription. The anthracyclines prevents DNA synthesis in all organisms, but the greatest effect is in rapidly growing cancer cells. Some other antibiotics like streptomycin and tetracyclines bind to ribosomal subunits and interfere with protein synthesis. Finally, some antibiotics encourage the synthesis of abnormal proteins (Abraham and Newton, 1960).

1.1.5 Applications of antibiotics Antibiotics have been utilized broadly in the past 70 years to cure and prevent bacterial infections in humans and animals (Botsoglou, 2001). Additionally, in the last 50 years, antimicrobials have been applied in food animals (especially cattle, swine, and poultry) to treat, prevent, or control infectious illness, or to enhance efficiency of feed utilization and weight gain. Management of these veterinary medicaments to food animals is a crucial component of an overall administrative system that food animal producers apply to secure the health and welfare of their animals and to warrant the safety of the products that enter the food chain (Institute of Food Technologists, 2006). The late 1940’s was the great period of antimicrobial growth promoters; it began when scientists found that chicks fed a dried fermentation blend of Streptomyces aureofaciens grew and gained weight faster than those fed a diet supplemented with liver extract. The ingredient of the fermentation blend which stimulated growth was identified as chlortetracycline. Right after the confirmation of the ability of chlortetracycline to increase the growth in turkeys and swine, several other antibiotics were found and added to the list of the compounds that could improve growth and enhance feed efficiency (McEwen and Fedorka-Cray, 2002). Antimicrobial growth promoters in non-ruminating animals act mainly in the digestive tract, exerting a beneficial effect on the composition of microorganisms living in the gut. It has been known for a long time that a well-

3 balanced intestinal flora blocks the way of the pathogens that try to enter the body. Antimicrobials improve the availability of nutrients and increase intestinal absorption because they reduce the rate at which the intestinal flora breaks down feed proteins to substances such as ammonia and biogenic amines, which are toxic to the animals and interfere with the absorption of nutrients through the intestinal wall. They also have a positive effect on metabolism and increase the rate at which animals lay down protein, and consequently improve weight gain and feed efficiency (Botsoglou, 2001). In the case of ruminants, antimicrobial growth promoters affect the balance of microbial species inhabiting the rumen. A higher level of rumen propionate is produced in treated animals at the expense of acetate and sometimes of butyrate production, and there are considerable reductions in energy losses because of the ruminal production of methane. The total effect is to make rumen fermentation more efficient, thus increasing the metabolizable energy content available for lean meat production. The growth promotion in-feed antibiotic use is mostly done for young growing animals. The effect on older animals is less than the younger ones. Although using antibiotics for growth promotion reduces the amount of required feed for an animal to reach production weight and consequently reduces farmers’ costs, the use of antimicrobials for growth promotion has been a target for elimination (Institute of Food Technologists, 2006). Recently some large restaurant corporations in the United States (e.g. McDonalds, Oak Brook, Ill., U.S.A.) have developed policies for antibiotic use which exclude human use antibiotic classes for growth promotion reasons in herds and flocks of their poultry and beef product suppliers (Institute of Food Technologists, 2006).

1.2 General Introduction to Antibiotic Resistance Antibiotic resistance is defined as the ability of a microorganism to eliminate the effect of antibiotics (American Academy of Microbiology, 2001). Although some bacteria are naturally resistant to antibiotics, they can acquire

4 resistance through mutations or insertion of extrinsic genes which can spread very rapidly among bacteria (Institute of Food Technologists, 2006). Antibiotics applied in swine production, therapeutically or sub- therapeutically, are structurally similar or identical to the ones utilized in human medicine. The similarity between them means that some commonly used antibiotics for human medicine could become ineffective if resistant bacteria transfer from livestock to the human food chain and infect people. This phenomenon can contribute to the development of resistant strains of pathogenic bacteria in human populations (Silbergeld et al. 2008). In addition, resistance genes can be transferred from fecal organisms to indigenous soil and water bacteria (Chee-Sanford et al. 2009). Farmers, slaughterhouse workers and swine waste products are important reservoirs from which antibiotics and antibiotic- resistant bacteria can be transferred from the farm to the environment (Guan and Holley, 2003). Moreover, poor hygiene, improper food handling and inadequate cooking can cause the transmission of drug resistance genes and resistant bacteria from animals to humans (Institute of food technologists, 2006). This creates the risk of infectious diseases caused by antibiotic-resistant pathogenic bacteria and increases food safety and health concerns (Schlundt et al. 2004).

1.2.1 Definition In order to discuss antimicrobial resistance, it is important first to define resistance. Resistance can be defined from a functional perspective or from a laboratory perspective. The former perspective correlates with failure of a given antimicrobial treatment, whereas from a laboratory perspective, resistance is marked by a “Minimal Inhibitory Concentration” (MIC) value that exceeds a threshold value, which may or may not be connected with a clinical outcome. Minimal Inhibitory Concentration is the lowest concentration of an antimicrobial drug, expressed in )g/ml or mg/L, which under defined in-vitro conditions within a defined period of time inhibits growth of the microbial inoculum (Institute of Food Technologists, 2006).

1.2.2 Classification

1.2.2.1 Innate (intrinsic) resistance Innate resistance is connected to the general morphology or physiology of a microorganism and comes from pre-existing properties or mechanisms. Innate resistance might occur as a result of the complexity of the cell wall. For instance, Gram-negative bacteria are generally more resistant to antibiotics than Gram- positive bacteria due to the complexity of the cell walls (Russell and Chopra, 1996). More specifically, Gram-negative bacteria are innately resistant to penicillin G by virtue of their double membrane structure, which prevents the antibiotic from accessing the cell wall target. In the same way, Mycobacterium species have a higher level of resistance than general non-spore-forming bacteria because of the high lipid content in their cell walls and relatively high hydrophobicity (Institute of Food Technologists, 2006).

1.2.2.2 Acquired (extrinsic) resistance Extrinsic resistance involves changes in the genetics of the organism. These changes occur through either mutation in a chromosomal gene or the acquisition of new genetic material encoding resistance from another cell or the environments (Institute of Food Technologists, 2006).

A. Mutation A mutation is a process that occurs randomly and results in a permanent and heritable change in the nucleotide sequence of a gene, which can alter the amino acid sequence of the protein encoded by the gene (Institute of food technologists, 2006).

B. Horizontal transfer of genetic elements Genetic materials can be transferred from one bacteria to another through three different processes, including transformation, transduction and conjugation in the presence or absence of antibiotics. The most important difference between these three genetic events is the mechanism by which genetic material is exchanged between bacterial species (Institute of food technologists, 2006).

6 a) Transformation Transformation is a process discovered by Frederick Griffith in 1928. In this process, the recipient cell absorbs the deoxyribonucleotide molecule which is released by the donor cell ( Figure 1.1 ). The absorbed free DNA can be incorporated into the chromosome or plasmid of the recipient cell (Furuya and Franklin, 2006).

b) Transduction The second mode of gene transfer which was discovered by Norton Zinder and Joshua Lederberg in 1952 is transduction. During transduction, genetic material is exchanged among bacterial cells by a bacteriophage ( Figure 1.2 ). Then, the transfered free DNA can be integrated into the chromosome of the recipient cell (lysogeny) (Furuya and Franklin, 2006). c) Conjugation Conjugation was discovered by Joshua Lederberg and Edward Tatum in 1949 in E. coli cells. During conjugation, the donor cell and the recipient cell compose an intercellular channel known as Conjugation Bridge ( Figure 1.3 ). The genetic material passes through this bridge and transfers from one bacterium to another (Furuya and Franklin, 2006).

1.2.2.3 Adaptation For some specific types of antibiotics, bacteria can adapt to gradual increases of substance concentration. This kind of resistance is unstable, and the resistant microorganism returns to the sensitive phenotype in the absence of antibiotics, which is known as back-mutation (Russell, 1991).

Figure 1.1 Transformation (Furuya and Franklin , 2006)

Figure 1 .2 Transduction (Furuya and Franklin, 2006)

Figure 1 .3 Conjugation (Furuya and Franklin, 2006)

1.3 General Introduction to Swine Rearing Pork is the most frequently consumed meat in the world (Guan and Holley, 2003). Swine production is one of the principal economic activities in Canada and has made this country very successful in the world’s pork export market (Statistics Canada, 2000). Over the last 50 years, world production of pork has risen dramatically, reaching 964 million pigs in the world, including 24 million pigs in Canada with 7 million pigs in the province of Québec alone, in 2006 (Statistics Canada, 2006), although year-to-year hog inventories have continued to decrease since 2006 (Statistics Canada, 2010). Figure 1.4 illustrates the percentage of changes in pig inventories in Canda from 2005 to 2010. As can be seen, since 2006, swine production started to decrease annually, and in 2008 the largest decrease was occurred, 11.8% (Statistics Canada, 2010). In the province of Québec (Canada), swine production is an important economic activity and a major source of environmental problems because of the large volume of swine wastes that it generates (Statistics Canada, 2000). Swine waste introduces pathogens, natural hormones and metals into agricultural ecosystems such as farmland, crops and water resources (Institute of Food Technologists, 2000).

Figure 1.4 Pig inventories in Canada in quarterly year-to-year change. (Statistics Canada, 2010).

1.4 Antibiotic Resistance in Swine Production Antibiotics are generally used in human for disease treatment (Silbergeld et al. 2008). In contrast, in intensive swine production, antibiotics have been used for decades to treat infections, to prevent diseases or to promote growth (Jindal et al. 2006). Two antibiotics, chlortetracycline and tylosin, are frequently used therapeutically or sub-therapeutically in swine production (Rajic et al. 2006). More than 88% of swine farmers in the United States added antibiotics in the feed of grower/finisher pigs as a growth promoter in 2000. It is estimated that only 25% of antibiotics are absorbed by animals and the rest is excreted in urine and feces. For instance, about a quarter of oral administration of tetracycline is excreted in feces, while 60% is excreted in urine where it remains unaltered and active. Moreover, 67% of oral dose of tylosin is excreted mainly in feces (Mackie et al. 2006). These antibiotics belong to the same classes of important antibiotics for the treatment of human infections (Heuer et al. 2006), so the intensive and extensive use of these antibiotics results in a selective pressure for the emergence and dissemination of antimicrobial-resistant bacteria (Adjiri-Awere and Van Lunen, 2005). Antibiotic resistance can occur in pathogenic or commensal bacteria which are present in food animals (Andremont, 2004). For example, investigation derived from different steps of the production chain of pork meat industries illustrated the wide distribution of multi-drug-resistant staphylococci (Simeoni et al. 2008). Moreover, resistant bacteria and resistance genes can be transferred from food animals, their waste and their meat to humans via the food processing chain or the environment (Silbergeld et al. 2008). For instance, transmission of resistance genes from animal to human enterococci happens in vivo in the human gut (Heuer et al. 2006). So far, 41 and 66 genes are known to confer resistance to tetracyclines and macrolides, respectively (Levy et al. 1999; Roberts et al. 1999). The spread of a new generation of infections in humans caused by resistant bacteria that derive from animal reservoirs is a great food safety and health concern (Heuer et al. 2006).

1.5 Tetracyclines

1.5.1 Discovery and Development of Tetracyclines Tetracyclines are a family of antibiotics which have been broadly applied to cure infections caused by a variety of Gram-positive and Gram-negative bacteria or protozoa, as well as for noninfectious conditions (Chopra and Roberts, 2001). The first members of the tetracyclines are chlortetracycline and oxytetracycline, the products of Streptomyces aureofaciens and S. rimosus , respectively, both discovered in the late 1940s (Chopra et al. 1992). Since then, new natural tetracyclines and tetracycline-synthesizing bacteria have been discovered, such as tetracycline from S. aureofaciens , S. rimosus and S. viridofaciens , and demethylchlortetracycline from S. aureofaciens . Semisynthetic tetracyclines, such as methacycline, doxycycline, and minocycline, have also been developed ( Table 1.1 ). The most recently discovered tetracyclines, glycylcyclines, which are products of semisynthetic approaches, include 9-(N,N- dimethylglycylamido)-6-demethyl-6-deoxytetracycline, 9-(N,N- dimethylglycylamido)-minocycline, and 9-t-(butylglycylamido)-minocycline (Chopra and Roberts, 2001). Because of the following desirable properties, tetracyclines have been used broadly for decades both therapeutically and sub-therapeutically: (1) they are broad spectrum antimicrobial agents which are active against a wide range of pathogens; (2) they show suitable oral absorption; (3) they demonstrate low toxicity with few allergic reactions, and; (4) they are relatively inexpensive (Moellering, 1990). Although tetracyclines still are among the most important antibiotics in both human and veterinary medicine, the prevalence of microbial resistance has narrowed their effectiveness (Donskey et al. 2000). Although the misuse of antibiotics in human medicine is the most important cause of antibiotic resistance in human pathogens, the intensive and extensive use of tetracylines in agri-food production is also believed to contribute to this global public health problem (Rajic et al. 2006).

Table 1.1 Principal members of the tetracycline class (Chopra and Roberts, 2001)

Chemical name Generic name Trade name Year of discovery Status Threrapeutic adminestration 7-Chlortetracycline Chlortetracycline Aureomycin 1948 Marketed Oral 5-Hydroxytetracycline Oxytetracycline Terramycin 1948 Marketed Oral and presental Tetracycline Tetracycline Achromycin 1953 Marketed Oral 6-Demethyl-7-chlortetracycline Demethylchlortetracycline Declomycin 1957 Marketed Oral 2-N-Pyrrolidinomethyltetracycline Rolitetracycline Reverin 1958 Marketed Oral 2-N-Lysinomethyltetracycline Limecycline Tetralysal 1961 Marketed Oral and presental N-Methylol-7-chlortetracycline Clomocycline Megaclor 1963 Marketed Oral 6-Methylene-5- Methacycline Rondomycin 1965 Marketed hydroxytetracycline 6-Deoxy-5-hydroxytetracycline Doxycycline Vibramycin 1967 Marketed Oral and presental 7-Dimethylamino-6-demethyl-6- Minocycline Minocin 1972 Marketed Oral and presental deoxytetracycline Minocycline 9-(t-butylglycylamido)-minocycline Tertiary-butylglycylamidominocycline Tigilcycline 1993 Phase II Clinical trials

1.5.2 Structure of Tetracyclines Tetracycline molecules consist of a linear complex tetracyclic nucleus (rings designated A, B, C, and D; Table 1.2 ) to which a variety of functional groups are attached (Chopra and Roberts, 2001). The clinically useful tetracycline (such as chlortetracydine, oxytetracycline, tetracycline, methacycline and doxycycline) are composed of an identical 4-ring carbocyclic structure as a basic skeleton, to which substituent variations at carbons 5, 6 or 7 make them different chemically (Chopra et al. 1992).

1.5.3 Mode of Action Tetracyclines can be divided into two groups according to their mode of action. Typical antibiotics which are bacteriostatic such as tetracycline, chlortetracycline, doxycycline, or minocycline, while some tetracycline like anhydrotetracycline, anhydrochlortetracycline, 6-thiatetracycline, chelocardin and 4-epi-anhydrochlortetracycline exhibits bactericidal activity (Chopra et al. 1992). Generally tetracyclines traverse one or more membrane systems of susceptible organisms and prohibit the association of aminoacyl-tRNA with the bacterial ribosome, thus inhibiting bacterial protein synthesis. For this reason, talking about the mode of action of tetracyclines needs the consideration of uptake and ribosomal binding mechanisms (Chopra and Roberts, 2001). There is an assumption that tetracyclines pass the outer membrane of Gram-negative bacteria through the porins OmpF and OmpC, most likely by chelating a M 2+ ion as [M- tc] + (Schnappinger and Hillen, 1996) ( Figure 1.5 ). It is followed by the attraction of the cationic metal ion-antibiotic complex by the donnan potential across the outer membrane which causes the accumulation of the complex in the periplasm. At this point, the metal ion-tetracycline complex possibly dissociates to free uncharged tetracycline which can diffuse through the lipid bilayer regions of the inner (cytoplasmic) membrane. In the same way, the electroneutral, lipophilic form is assumed to be the species transferred across the cytoplasmic membrane of Gram-positive bacteria.

Table 1.2 Structures of the principal members of the tetracycline class (Chopra and Roberts, 2001)

Figure 1.5 Uptake of tetracycline by Escherichia coli . (Schnappinger and Hillen , 1996).

Uptake of tetracycline across the cytoplasmic membrane requires energy and is supported by the pH component of the proton motive force (Chopra and Roberts, 2001). After diffusion of tetracycline, there is a single, high-affinity binding site for tetracyclines in the ribosomal 30S subunit, and several studies showed that protein S7 and 16S rRNA bases G693, A892, U1052, C1054, G1300, and G1338 contribute to the binding compartment (Aminov et al. 2001; Roberts 2005; Holzel et al. 2010).

1.5.4 Resistance to Tetracyclines Studies show that until the 1950s, most commensal and pathogenic bacteria were sensitive to tetracyclines, since only 2% of 433 isolates of Enterobacteriaceae collected between 1917 and 1954 were resistant (Chopra et al. 1992). Three different microbial strategies for resisting the effects of tetracyclines have been identified. They interfere with various aspects of the antibiotic activity of tetracycline: (1) modification of target site of the ribosome to protect them from the antibiotic effect, (2) efflux of the antimicrobial drug to decrease the intracellular concentration of tetracycline, and (3) inactivation of the antibiotic by degrading the drug before it reaches its target site (Mendez et al. 1980).

1.5.4.1 Protection of the ribosome Ribosomal protection is a strategy of tetracycline resistance which was discovered in Streptococci . Although, the mechanism of ribosomal modification has only been studied with tet (M), the mechanism of action may be similar for all protection proteins encoded by the other tet genes that have an amino acid sequence similarity of at least 40% to Tet(M) (Schnappinger and Hillen, 1996). As it is shown in Figure 1.6 , in this strategy, the intercellular concentration of tetracycline is similar to that in the sensitive cell, but the ribosome is modified in a way that the drug can no longer bind prolifically to the ribosome (Chopra et al. 1992).

Fig ure 1.6 Ribosome protection (Chopra et al. 1992)

1.5.4.2 Efflux proteins Since tetracyclines have a concentration-dependent activity, reducing the concentration of drug in the cytoplasm results in decreased susceptibility of the cell (Hammond and Lambert, 1978). Numerous tetracycline resistance genes encode for ~ 45 kDa proteins which cause high level resistance in bacteria by energy-dependent efflux of tetracyclines. There are two different strategies to reduce antibiotic concentration in the cytoplasm: (1) reducing the permeability of the cell, and (2) transferring tetracycline out of the cytoplasm in an energy- dependent fashion (Schnappinger and Hillen, 1996). During efflux pumping, as it is shown in Figure 1.7 , a cytoplasm membrane protein pumps tetracyclines out of the cell to keep the intracellular tetracycline concentration at low level. Therefore, tetracyclines cannot bind to ribosomes effectively anymore (Chopra et al. 1992).

1.5.4.3 Enzymatic inactivation of tetracycline Figure 1.8 illustrates the features of the enzymatic inactivation type of resistance. Active tetracycline (T) enters the cytoplasm where it is degraded to an inactive form (t) by a reaction that needs oxygen. Degraded tetracycline then diffuses out of the cell (Chopra et al. 1992). Enzymatic alteration of tetracyclines is encoded by one tetracycline resistance gene, tet (X). The tet (X) gene was discovered due to its linkage to erm (F), which encodes for a rRNA methylase gene. A 44 kDa cytoplasmic protein is encoded by tet (X) and can chemically alter tetracyclines in the presence of both oxygen and NADPH; thus the altered drug no more binds to the ribosome (Chopra and Roberts, 2001).

Figure 1.7 Efflux proteins (Chopra et al. 1992)

Figure 1.8 Enzymatic inactivation (Chopra et al. 1992)

1.5.4.4 Other/unknown mechanisms of resistance Among tetracycline resistance genes, the tetracycline resistance mechanism(s) conferred by tet (U) and otr (C) have not been identified yet (Table 1.3). Tet (U) causes low-level tetracycline resistance by itself. Although there is 21% similarity over the 105 amino acids between the Tet(U) and Tet(M) proteins, these similarities do not include the sequences which have the fundamental role in resistance in the Tet(M) and related proteins. Since the Tet(U) sequence has no similarity either with the efflux or ribosomal protection genes, the mechanism is listed as unknown in Table 1.3 . Also, the strategy of resistance of the otr (C) gene from Streptomyces has not been determined because it has not yet been sequenced (Schnappinger and Hillen, 1996).

1.6 Macrolides

1.6.1 Discovery and Development of Macrolides Macrolides play a considerable role in treating infectious diseases since 1952 when the first macrolide, erythromycin, was discovered (Brander et al. 1991). The majority of macrolide antibiotics are isolated from culture broth of Streptomyces strains. Mirosamicin is an exception, which is produced by Micromonospora . They are extremely efficient against a wide range of Gram- positive bacteria with narrow or no activity against most Gram-negative bacteria (Brander et al. 1991). Quantitative and qualitative activity of macrolides against bacterial pathogens was improved by modifying their structures (Retsema and Fu, 2001). In the 1980s, semi-synthetic products of erythromycin with improved properties were developed: these derivatives are much more active and stable; the intracellular and tissue penetration of these semi-synthetic macrolides has improved so that they can be better absorbed; fewer doses are required per day compared to erythromycin (Roberts, 2004).

Table 1.3 Mechanisms of resistance for characterized tet and otr genes (Chopra and Roberts, 2001).

Genes Efflux tet (A), tet (B), tet (C), tet (D), tet (E), tet (G), tet (H), tet (I), tet (J) tet (Z), tet (30), tet (31) tet (K), tet (L) otr (B), tcr3 tet P(A) tet (V) tet (Y)

Ribosomal protection tet (M), tet( O), tet (S), tet (W) tet (Q), tet (T) otr (A), tet P(B) Emzymatic, tet (X)

Unknown tet (U), otr (C)

1.6.2 Structure of Macrolides The term macrolides originates from their structure, a macrocyclic lactone ring to which different amino sugars are fastened, and can be categorized based on the number of carbon atoms in the macrocyclic ring (Retsema and Fu, 2001). The macrolide antibiotics are basic macrocyclic compounds composed of 14 (erythromycin and clarithromycin), 15 (azithromycin), or 16 (josamycin, spiramycin, and tylosin) membered macrocyclic lactone rings decorated with one or more deoxy sugars, often amino sugars, by glycoside bonding ( Figure 1.9 ) (Mankin, 2008).

1.6.3 Mechanisms of Action of Macrolides Macrolides reversibly link to the large subunit (50S) and prohibit protein synthesis and result in protein chain termination by inspiring dissociation of the peptidyl-tRNA molecule from the ribosomes during elongation ( Restama and Fu, 2001)

1.6.4 Resistance to Macrolides Resistant to macrolides can be inherent or acquired. Inherent resistance has been demonstrated in many Gram-negative bacteria due to the impermeability of their outer membrane to macrolides. Moreover, different strategies of acquired resistance have been reported, including methylation of ribosomes by methylase enzymes, drug efflux from bacteria, and enzymatic inactivation of macrolides either by destroying the macrocyclic nucleus or by attaching a conjugate onto the antibiotic (Brander et al. 1991).

1.6.4.1 Ribosomal methylation The most widespread mechanism of bacterial resistance to macrolides is the modification of the target site by adding one or two methyl groups to a single adenine (A2058 in Escherichia coli ) in the 23S rRNA. The majority of resistance genes were first found in Gram-positive species or Streptomycetes , but were not described in Streptomycetes with low G+C content. There are 30 different rRNA

Figure 1.9 Chemical structures of some macrolide antibiotics. (Mankin, 2008)

24 methylase genes which can be expressed constitutively or inducibly (Brander, Pugh et a. 1991).

1.6.4.2 Efflux systems In the efflux type of resistance, a cytoplasmic membrane protein transports macrolides out of the cell. Thus, the intracellular macrolide concentration remains too low for effective binding to ribosomes (Chopra et al. 1992). A number of different antibiotic resistance genes [ mef (A), mef (E), and lmr (A)] encode for many of these proteins, which have fundamental similarity to the major facilitator super family (MFS) of efflux proteins. Others [ car (A), msr (A), msr (B), ole (B), ole (C) srm (B), tlr (C), vga (A), and vga (B)] are reputed members of the ABC transporter super family (Roberts et al. 1999).

1.6.4.3 Enzymatic inactivation A common phenomenon, enzymatic degradation, is common strategy for emergence of bacterial resistance to macrolides. Enzymes which hydrolyze streptogramin B [vgb (virginiamycin factor B hydrolase), vgb (B) genes] or modify the antibiotic by adding an acetyl group (acetyltransferases) to streptogramin A [vat (virginiamycin, factor A acetylation), vat (B), vat (C), sat (A), and sat (G) genes] can be mentioned (Roberts, 2004).

1.6.4.4 Mutational resistance to macrolides According to the literature, between 1 and 4% of macrolide-resistant bacteria do not carry any of the known genes examined and their mechanism of resistance has not yet been determined. Surveys suggest that most of these isolates may have mutations in their innate genes that confer an increase in resistance instead of acquired genes (Brander et al. 1991). Over the past 10 years, an increasing number of macrolide-resistant isolates with mutations in the V domain of the 23S rRNA gene, and/or in the genes encoding the ribosomal proteins L4 and L22, have been identified (Roberts, 2004).

1.7 General Introduction to Tylosin Streptomyces fradiae produces tylosin A, desmycosin (tylosin B), macrocin (tylosin C), and relomycin (tylosin D). Tylosin A is the major product and the last three ones are minor compounds produced by this bacterium. Tylosin belongs to the macrolide antibiotics and is applied extensively in animal husbandry to treat diseases such as respiratory disease complex in chickens, infectious sinusitis in turkeys, bovine respiratory and swine dysentery diseases. Moreover, tylosin is also used as a growth promoter for pigs (Shimada et al. 2008). Tylosin can be administrated orally through drinking water or feed as an aid in stimulating growth and improving feed efficiency in swine starters, growers and finishers at concentrations of 44, 22 and 11 mg/kg of complete feed, respectively (CFIA, 2010). Tylosin generally demonstrates low toxicity with suitable oral absorption, and is excreted relatively slowly through the feces in the form of tylosin A, tylosin D, and dihydrodesmycosin. There is low level of tylosin residues in liver and kidney; the tissue in which the highest residue levels occur and the concentration of the residues in the tissues highly depends on the route of administration (Brander et al. 1991). For instance, higher residue levels are found in kidney by using injectable administration, while the highest residue concentrations are found in liver by using oral preparation. Moreover, studies show that oral administration results in lower residue concentrations than injections. Thus, detectable residues of parent tylosin cannot be detected in swine liver unless the medicated feed contains at least 1000 ppm of the drug (Brander et al. 1991). In growing and finishing swine, bacitracin, chlortetracycline hydrochloride, tylosin phosphate, and narasin are generally used therapeutically and sub-therapeutically in Canada (CFIA, 2010). Chlortetracycline and tylosin both result in cross-resistance to antibiotics currently used in human medicine, which is not the case for bacitracin due to the limited application of this drug in humans (Brander et al. 1991).

1.8 Food-Borne Pathogens The consumption of food containing toxins or pathogens can cause food poisoning or food-borne illness, which is a major concern for both public health and veterinary communities (Schlundt et al. 2004; Abubakar et al. 2007). Foodborne infection is not a simple problem in need of a solution; it is a complex combination of factors including the pathogen, the host, and the environment in which they exist and interact all together ( Figure 1.10 ). Each of these factors plays a role in the changing nature of foodborne diseases, opening new niches and creating new vulnerabilities (Institute of food technologists, 2000). There are two main groups of infectious food-borne diseases: penetration of pathogenic microbes into the lining of intestines, causing an immune response that results in gastrointestinal symptoms (e.g. salmonellosis), and toxin-induced food poisoning, because of the presence of a preformed toxin resulting from bacterial growth (e.g., Bacillus cereus ) in the food. These toxins can be already present in the consumed food or produced in vivo after microbial ingestion (e.g., Clostridium perfringens ) (Abubakar et al. 2007). More than 200 infectious illnesses can be propagated through food (Wells and Bennik, 2003). It has been estimated that foodborne diseases cause approximately 76 million illnesses, 325,000 hospitalizations, and 5,000 deaths and billions of dollars of costs annually in the United States (Mead et al. 1999, McNamara et al. 2007). The most common bacterial causes of food-borne illness are Salmonella and Campylobacter , which account for 26 % of all foodborne infections and 17 % of hospitalizations in the United States. Major bacterial foodborne pathogens are Salmonella (non-typhoidal), Listeria monocytogenes , Campylobacter , and enterohaemorrhagic Escherichia coli (Mead et al. 1999). Annual costs of human infections for food-borne pathogens ranges from $2.9 and $6.7 billion (1993 dollars) annually, with meat and poultry accounting for 80% of costs in the United States (McNamara et al. 2007). Among major bacterial foodborne pathogens, Salmonella is the most important one in the case of pork which 40% of the pork-associated outbreaks were due to Salmonella . (Mead et al. 1999).

Figure 1.10 Food- borne illness (Institute of Food Technologists, 2000)

CONNECTING STATEMENT TO CHAPTER 2

In this chapter, optimal conditions for faecal collection and preservation, total aerobic and anaerobic bacterial enumerations, and DNA extraction were determined. Moreover, various PCR and real-time PCR reaction mixtures and conditions were assessed to optimize these methods for analyzing pig fecal samples. The work presented in this chapter is the first step to further investigations regarding the bacterial ecology of antibiotic resistance in swine production. All experimental work and data analysis were carried out by the candidate under the overall supervision of Dr. M. Chénier.

CHAPTER 2. PRELIMINARY STUDIES 2.1 Abstract Fecal samples from weanling pigs were used to optimize methods and procedures for bacterial enumerations, DNA extraction, polymerase chain reaction and real-time PCR for the detection and quantification of selected antibiotic resistance genes in swine feces. For bacterial enumerations, BHIA (Brain Heart Infusion Agar) and TSA (Tryptic Soy Agar), which are both rich media for general purpose in bacteriology (Gerhardt et al. 1994), were tested to determine which solid medium allows the highest quantitative microbial growth. For total genomic DNA extraction, the QIAamp DNA Stool Mini kit (QIAgen, Ontario, Canada) and the Ultra Clean DNA kit (MoBio, California, USA) were compared to determine which kit provides the highest yield and quality of DNA. Hot start PCR and real-time PCR reaction mixtures and conditions were optimized for the detection and quantification, respectively, of resistance genes. BHIA allowed the highest and fastest quantitative bacterial growth from the swine faecal samples, whereas the Qiagen QIAamp DNA Stool Mini kit provided better total DNA recovery and purity, as well as relatively little PCR inhibition, especially for samples preserved at -80 oC. Classical microbiology and molecular biology techniques could be optimized and successfully applied to the

29 investigation of complex microbial communities in a technically challenging matrix.

2.2 Introduction Antibiotic resistance is defined as the ability of a microorganism to counteract the effect of antibiotics ,American Academy of Microbiology 2001). Although some bacteria are naturally resistant to antibiotics, most of them can acquire resistance through mutations or insertion of extrinsic genes which can spread very rapidly between bacteria (Institute of food technologists, 2006). Some of the genes that provide resistance to different types of antibiotics can be co- located on the same chromosome or mobile genetic element, which cause multidrug resistance (Simeoni et al. 2008). In animal production, antibiotics are commonly applied sub- therapeutically (e.g., for growth promotion) and therapeutically at higher concentrations (e.g., for the treatment of various infections and to stimulate appetite during period of stress) (Furuya and Lowy, 2005; Jindal et al. 2006). Applications of antibiotics in animal production contribute to the selection and dissemination of antibiotic resistance in pathogens that can get into contact with humans through several routes (Jindal et al. 2006), including livestock-human transmission during animal care (Heuer et al. 2006), contamination of agricultural ecosystems (farmlands, surface waters, ground waters, soils, and crops), equipment and facilities by animal wastes, and through animal carcasses and wastes at slaughter and in the meat processing chain (US FDA 1998; Rosser and Young, 1999; Aminov et al. 2001). The subsequent emergence of infections in humans and animals caused by resistant bacteria that originate from the animal reservoir is of great concern to veterinary and public health authorities (Heuer et al. 2006). Although, it is not easy to demonstrate a straight link between agricultural applications of antibiotics and increased levels of resistance in pathogenic and commensal microorganisms, the potential consequences are so serious that the World Health Organization has recommended that antibiotics that are currently

30 utilized or are under development for human therapy be eliminated as animal growth promoters (Jindal et al. 2006). In the past, culture-dependant methods were used and are still needed to study the diversity and quantify the activities of microorganisms involved in biodegradation processes and biogeochemical cycling in natural environments. Culture-dependent microbiology methods are limited to the study of microorganisms which are active and can be grown under laboratory conditions (Chenier and Juteau, 2009). A variety of culture-independent techniques such as polymerase chain reaction (PCR), competitive quantitative PCR, real-time PCR, denaturing gradient gel electrophoresis and constant denaturant capillary electrophoresis has been developed for rapid enumeration and identification of bacteria (Fu et al. 2006). Thus, a reasonable combination of molecular methods and culture-dependent methods would offer better chances to improve our knowledge of microbial ecology of complex ecosystems. The aim of this chapter was to optimize complementary microbiology and molecular biology methods, i.e. bacterial enumerations, DNA extraction, end-point PCR and real-time PCR, for reliable analysis of the bacterial ecology of antibiotic resistance in swine faeces.

2.3 Material and Methods

2.3.1 Swine Rearing and Sampling Pigs were reared at the Swine Complex of McGill University between June and December 2009. They were given antibiotic-free pelleted equilibrated cereal-based diet specific for each production stage, as well as water, ad libitum (Agribrands-Purina Canada Inc.). Fresh fecal samples from healthy pigs (20±2 kg mean live body weight) were collected from the ground using sterile instruments, taking care not to touch the ground in order to avoid cross-contamination, within minutes after defecation. Samples were kept on ice until arrival to the laboratory, and then divided into two subsamples. Samples from the first group were kept on ice and used to perform bacterial enumerations (the same day), while samples

31 from the second group were immersed in liquid nitrogen and stored either at - 20 0C or -80 0C for subsequent molecular analyses.

2.3.2 Enumeration of Total Aerobic Bacteria on Solid Media

2.3.2.1 Preparation of aerobic dilution water -1 In a 1 liter-cylinder, 1.25 ml of phosphate buffer (0.25 mol KH 2PO 4 l , pH -1 7.2) and 5 ml of magnesium chloride hexahydrate (0.4 mol MgCl 2.6H 2O l ) were added in about 500 ml of distilled deionized water. The volume was completed to 1 l with distilled deionized water to obtain final concentrations of 313 )mol -1 -1 KH 2PO 4 l and 2 mmol MgCl 2.6H 2O l . With a 50 ml cylinder, 47 ml of dilution water were distributed into 125 ml glass bottles to obtain 45 ± 2 ml after 15 min of autoclaving. All the tubes were autoclaved at 121°C-15 psi for 15 minutes and were preserved at 4 °C.

2.3.2.2 Preparation of solid media BHIA (Brain Heart Infusion Agar) and TSA (Tryptic Soy Agar), which are both rich media for general purpose in bacteriology (Gerhardt et al. 1994), were tested to determine which solid medium allows the highest quantitative microbial growth. 25 g and 26 g of dehydrated BHIA and TSA, respectively, were added to 500 ml of distilled deionized water in a 1 L Pyrex bottle containing a magnetic bar. Media were heated and agitated on a magnetic stirrer to get dissolved, and autoclaved at 121 °C-15 psi for 15 min. After autoclaving, media were distributed into pre-identified Petri dishes under sterile conditions in a class II biosafety cabinet (Labconco Corporation, Kansas City, MI, USA). Media in Petri dishes were kept for 45 min in the biosafety cabinet to solidify and then kept at 4 °C in inverted position until use.

2.3.2.3 Dilution of fecal samples In the biosafety cabinet, 5 g of feces were weighed using sterile spatula and a leveled balance (model AS-120, Ohaus Corporation, Florham Park, NJ,

USA), and then transferred into a glass bottle containing 45 ml of aerobic dilution water. After homogenizing dilution 10 -1 by vigorously shaking 25 times up-and- down over a 2-foot vertical movement, 5 ml of this dilution were transferred into another bottle to prepare dilution 10 -2 . The last two steps were repeated for desired dilutions, usually 10 -2 through 10 -10 .

2.3.2.4 Inoculation of solid media by spread-plate For bacterial enumerations, a range of dilutions (usually 10 -5 to 10 -10 ) were used. After homogenizing dilution 10 -1 by vigorously shaking 25 times up-and- down over a 2-foot vertical movement, 0.1 ml of the highest (10 -10 ) to the lowest (10 -5 ) dilution were measured and were put onto the corresponding solid media into an identified Petri plate. Three replicate Petri plates were inoculated for each dilution. Using sterile hockey or spreader and the inoculating turn-table, inocula were uniformly were distributed onto the surface of the solid medium by ‘streaking’ and rotating the turn-table for 20-30 seconds. All plates were kept for 20 min in the biosafety cabinet and incubated in inverted position at 37 °C. Petri plates were periodically observed until no additional colonies could be visually detected.

2.3.3 Enumeration of Total Anaerobic Bacteria on Solid Media

2.3.3.1 Preparation of anaerobic dilution water

A. Test 1 In two loosely capped 1 l-Pyrex bottles, two volumes of 600 ml of distilled deionized water were boiled for 15 min. At the end of the 15 min, about 600 ml of boiled distilled deionized water were transferred to a 1 l-graduated cylinder, and

0.001g of resazurin (an indicator of redox potential), 1.25 ml of 0.25 mol KH 2PO 4 -1 -1 l (pH 7.2) and 5 ml of 0.4 mol MgCl 2.6H 2O l were added. Volume was completed to 1 l with boiled distilled deionized to obtain complete dilution water -1 -1 -1 (313 )mol KH 2PO 4 l , 2 mmol MgCl 2.6H 2O l , 0.001 g resazurin l , pH 7.2).

Dilution water was distributed back into the original Pyrex bottles (each containing about 500 ml of dilution water) containing a magnetic stirrer, and each Pyrex bottle was transferred into an anaerobic jar which was connected to suction and a cylinder of mix gases (10% H 2, 10% CO 2, 80% N 2, Megs, St-Laurent, Canada). While homogenizing on a magnetic stirrer, the air in the jar was vacuumed for one minute. This was followed by introducing the gas mixture into the jar and letting rest for 5 min. These two last steps were repeated for 3 cycles. When these three cycles were completed, anaerobic jars were transferred into an anaerobic chamber (Coy Drive, Grass Lake, USA) to distribute 9.2 ml aliquots of anaerobic dilution water into a series of 50 ml glass tubes, in order to obtain 9.0 ± 0.2 ml after 15 min of autoclaving. Once distribution was completed, tubes were taken out of the anaerobic chamber, placed in a vessel containing 2-3 ml water, and autoclaved at 121°C-15 psi for 20 min. After cooling down to room temperature, tubes were returned into the anaerobic chamber, and 40 µl of sterile

1.125% w/v Na 2S.9H 2O (reducing agent to maintain anaerobic conditions) was added to obtain a final concentration of 0.2 mmol l-1 (Chénier and Juteau 2009). Tubes were cooled down at room temperature for 24 hours and kept at 4 °C.

B. Test 2

Test 2 was identical to test 1 except that distilled deionized water was initially boiled for 30 min (instead of 15 min), and boiled again for 1 min (to keep its temperature high) prior to transferring Pyrex bottles into anaerobic jars for flushing. Moreover, Pyrex bottles containing about 500 ml of dilution water and a magnetic stirrer was transferred into an anaerobic jar which was connected to suction and a cylinder of pure nitrogen (Megs, St-Laurent, Canada) instead of mix

gases (10% H 2, 10% CO 2, 80% N 2, Megs, St-Laurent, Canada).

C. Test 3 Test 3 was identical to test 2 except that autoclaved dilution water (313 -1 -1 -1 )mol l KH 2PO 4, 2 mmol l MgCl 2.6H 2O, 0.001 g resazurin l , pH 7.2) were

34 transferred into the anaerobic chamber right after autoclaving in order to cool -1 down prior to adding Na 2S.9H 2O at a final concentration of 0.2 mmol l .

2.3.3.2 Preparation of solid media BHIA and TSA were prepared as described in section 2.3.2.2, except that Petri plates were transferred into the anaerobic chamber 24 h before performing bacterial enumerations to assemble an anaerobic atmosphere.

2.3.3.3 Dilution of fecal samples In the biosafety cabinet, 5 g of feces were weighed directly into an autoclaved glass tube using sterile spatula and a leveled balance. The tube containing the sample was transferred into the anaerobic chamber, where 45 ml of anaerobic dilution water was added to the sample. After homogenizing dilution 10 -1 by vigorously shaking, 5 ml of this dilution were transferred into another bottle to prepare dilution 10 -2 . The last two steps were repeated for desired dilutions, usually 10 -2 through 10 -10 .

2.3.3.4 Inoculation of solid media by spread-plate For bacterial enumerations, a range of dilutions (usually 10 -5 to 10 -10 ) were used. After homogenizing dilution 10 -1 by vigorously shaking 25 times up-and- down over a 2-foot vertical movement, 0.1 ml of the highest (10 -10 ) to the lowest (10 -5 ) dilution were measured at about 2.5 cm underneath the surface and were put onto the corresponding solid media into an identified Petri plate. Three replicate Petri plates were inoculated for each dilution. Using s sterile hockey or spreader and the inoculating turn-table, inocula were uniformly distributed onto the surface of the solid medium by ‘streaking’ and rotating the turn-table for 20-30 seconds. All the plates were kept for 20 min in the biosafety cabinet transferred into an anaerobic jar, and incubated in inverted position at 37 oC. Petri plates were periodically observed until no additional colonies could be visually detected.

2.3.4 DNA Extraction

2.3.4.1 Extraction of total DNA from bacterial strains used as positive control for PCR Bacterial strains used as positive controls for PCR analyses are described in Table 2.1 and were preserved at -20 oC in 15% glycerol. For each strain, 500 )l of a fresh, turbid culture in Luria-Bertani broth (LB, Becton Dickinson, Sparks, NJ, USA) containing either chlortetracycline HCl (Sigma-Aldrich, St-Louis, MO, USA) at 25 µg/ml or tylosin tartrate (Sigma-Aldrich, St-Louis, MO, USA) at 200 µg/ml were used for DNA extraction with the Qiagen QIAamp kit according to the protocol supplied by the manufacturer (Qiagen, City, Ontario, Canada). The bacterial DNA was recovered in 100 )l of elution buffer supplied with the extraction kit. Subsequently extracted DNA was purified by using the QIAquick PCR Purification Kit (Qiagen, Ontario, Canada).

2.3.4.2 Extraction of total community DNA from swine feces Since feces have various PCR inhibitors such as bile salts, hemoglobin degradation products and complex polysaccharides (Ruiz and Rubio, 2009), a certain number of test-kits have been developed specifically for the analysis of fecal samples. In this experiment, optimal conditions for faecal collection and preservation, as well as for DNA extraction and preservation were determined. Each freshly collected fecal sample was divided into 3 sub-samples in 1.5 ml tubes. The first sub-sample was kept at 4 oC and immediately used for DNA extraction. The second sub-sample was kept at -20 oC until analysis. The third sub- sample was soaked in liquid nitrogen and stored at -80 oC until analysis. For each sub-sample, DNA was extracted using either the Qiagen QIAamp DNA Stool Mini kit (QIAgen, Ontario, Canada) or the Ultra Clean DNA kit (MoBio, California, USA) according to the manufacturers’ instructions. These kits utilize a lysis buffer which contains a detergent to disrupt cellular membranes and a protease (proteinase K) for digestion of periplasmic and intracellular proteins.

2.3.4.3 DNA integrity, concentration and purity DNA was checked for integrity (shearing) by agarose gel electrophoresis with Lambda DNA HindIII Digest standards (New England BioLabs, Ipswich,

MA, USA). DNA concentration and purity (A 260/230 and A 260/280 ) of each extract was determined using the NanoDrop ND-1000 UV-visible spectrophotometer. Ratio of absorbance at 260/280 nm is used to assess the purity of DNA and RNA. A ratio of 1.8 is generally accepted as pure for DNA and a ratio of 2 is accepted as pure for RNA. A ratio lower than 1.8 may indicate the presence of protein, phenol or other contaminants that absorb strongly at or near 280 nm. Ratio of 260/230 is a secondary measure of nucleic acid purity and 260/230 values for pure nucleic acid are often higher than the respective 260/280 values. They are commonly in the range of 1.8-2.2. The ratio out of this range may indicate the presence of co-purified contaminants.

2.3.5 PCR for Bacteria 16S rDNA The PCR reaction mixture and conditions were optimized for efficient and specific amplification of the V3 region of Bacteria 16S rDNA. Optimized reaction mixture and conditions were subsequently used for the detection of 14 genes conferring resistance either to tetracyclines ( tet genes) or macrolides ( erm genes) via ribosomal protection or efflux. PCR amplifications were carried out in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, USA) using DNA extract at 5 $g/µl from individual pig’s fecal sample as template The PCR reaction mixture (25 )l) contained 1.5 )mol l -1 of each primer (Table 2.1 ), 250 )mol l -1 of each dNTP (Amersham Biosciences Corp., Piscateway, NJ), 1.25 U of Taq DNA polymerase (Invitrogen, CA, USA), and the PCR buffer supplied with the enzyme (10 mmol l -1 Tris-HCl pH 9, 50 mmol l -1 2+ -1 KCl). The impacts of Mg (MgCl 2.6H 2O, 1.5 mmol l , Invitrogen, CA, USA) and BSA (Bovine Serum Albumine, 0.4 g l −1 , Sigma Chemical Cy, St-Louis, MO, USA) additions to the reaction mixture on the efficiency and specificity of PCR amplifications were assessed ( Table 2.2 ). The positive control is described in

Table 2.1 . A negative control, consisting of the reaction mixture without DNA, was used in each PCR run. Regular and hot start PCR conditions were compared for efficient and specific amplification of the Bacteria 16S rDNA ( Table 2.2 ). Regular PCR conditions were 5 min of denaturation at 94°C, 30 cycles of 1 min at 94°C (denaturation), 1 min at 55°C (annealing), 2 min at 72°C (extension), and finally an extension period of 10 min at 72°C. Hot start PCR conditions were 5 min of denaturation at 99°C, followed by 10 min at 80°C during which the Taq DNA polymerase was added (hot start), 2 cycles of 5 min at 94°C, 5 min at 55°C, 2 min at 72°C, then 28 cycles of 1 min at 94°C, 1 min at 55°C, 2 min at 72°C, and finally an extension period of 10 min at 72°C. The size ( Table 2.1 ), specificity (unique band) and abundance of PCR products were determined by comparison with DNA standards (GeneRuler 100 bp DNA Ladder, MBI Fermentas, Burlington, ON, Canada) after agarose gel electrophoresis (Chenier and Juteau, 2009).

Table 2.1 Oligonucleotide primers, amplicon size, annealing temperatures and positive controls used for PCR amplification of bacterial genes.

Amplicon size Annealing temp. Target gene Primers Sequence (5’ 3’) Positive control Reference (bp) ( oC) Pseudomonas 16S rDNA 341-F CCT ACG GGA GGC AGC AG ~ 233 55 aeruginosa (Majdoub R, Côté C et al. 2004) 518-R ATT ACC GCG GCT GCT GG tet (A) tetA-F GCG CGA TCT GGT TCA CTC G ~ 164 61 Strain SAS 1393 (Aminov, Chee-Sanford et al. 2002) tetA-R AGT CGA CAG YRG CGC CGG C tet (B) tetB-F TAC GTG AAT TTA TTG CTT CGG ~ 206 Strain Ct4afooB (Aminov, Chee-Sanford et al. 2002) tetB-R ATA CAG CAT CCA AAG CGC AC tet (C) tetC-F GCG GGA TAT CGT CCA TTC CG ~ 207 63 pBR322 (Am inov, Chee-Sanford et al. 2002) tetC-R GCG TAG AGG ATC CAC AGG ACG tet (D) tetD-F GGA ATA TCT CCC GGA AGC GG ~ 187 58 Strain D7 -5 (Aminov, Chee-Sanford et al. 2002) tetD-R CAC ATT GGA CAG TGC CAG CAG tet (E) tetE-F GTT ATT ACG GGA GTT TGT TGG ~ 199 61 pSL1504 ( Aminov, Chee-Sanford et al. 2002) tetE-R AAT ACA ACA CCC ACA CTA CGC tet (K) tetK-F TTA TGG TGG TTG TAG CTA GAA A ~ 348 55 pAT102 (Huys, D’Haene et al. 2005) tetK-R AAA GGG TTA GAA ACT CTT GAA A tet (L) tetL-F GTM GTT GCG CGC TAT ATT CC ~ 696 57 pVB.A15 (H uys, D’Haene et al. 2005) tetL-R GTG AAM GRW AGC CCA CCT AA tet (M) tetM-F ACA GAA AGC TTA TTA TAT AAC ~ 171 53 pJ13 (Aminov, Garrigues-Jeanjean et al. 2001) tetM-R TGG CGT GTC TAT GAT GTT CAC (Aminov, Garrigues-Jeanjean et al. tet (O) tetO-F ACG GAR AGT TTA TTG TAT ACC ~ 171 57 pU0A1 2001) tetO-R TGG CGT ATC TAT AAT GTT GAC tet (S) tetS-F GAA AGC TTA CTA TAC AGT AGC ~ 169 50 pAT451 (Aminov, Garrigues-Jeanjean et al. tetS-R AGG AGT ATC TAC AAT ATT TAC (Aminov, Garrigues-Jeanjean et al. tet (Y) tetY-F ATT TGT ACC GGC AGA GCA AAC ~ 181 56 AF070999 2001) tetY-R GGC GCT GCC GCC ATT ATG C (Aminov, Garrigues-Jeanjean et al. erm (A) ermA-F TCT AAA AAG CAT GTA AAA GAA ~ 645 54 CCRI-993 0 2001) ermA-R CTT CGA TAG TTT ATT AAT ATT AGT erm (B) ermB-F GAA AAG GTA CTC AAC CAA ATA ~ 639 52 CCRI-131 7 (Sutcliffe, Grebe et al. 1996; Sutcliffe, Tait-Kamradt et al. 1996) ermB-R AGT AAC GGT ACT TAA ATT GTT TAC

erm (C) ermC-F TCA AAA CAT AAT ATA GAT AAA ~ 642 47 CCRI-131 7 (Sutcliffe, Grebe et al. 1996; Sutcliffe, Tait-Kamradt et al. 1996) ermC-R GCT AAT ATT GTT TAA ATC GTC AAT

Table 2.2 Optimization of the PCR reaction mixture and conditions.

PCR conditions Test # Mg 2+ (mmol l -1) BSA (g l -1) 1 0 0 2 0 0.4 Regular 3 1.5 0 4 1.5 0.4

5 0 0 6 0 0.4 Hot start 7 1.5 0 8 1.5 0.4

2.3.6 Real-Time PCR for tet (O) Since tet (O) was detected in all pigs at all production stages, and as it can be horizontally transferred among bacterial populations via different mechanisms (Smith et al. 2004), this gene was selected for further quantitative analysis by real-time PCR based on protocols described before (Smith et al. 2004). The tet (O)-bearing plasmid pU0A1 was extracted and purified from E. coli using the QIAquick PCR Purification Kit and used as standard to determine the number of copies of tet (O) in the samples by real-time PCR. Following extraction and purification of pU0A1, tet (O) was amplified by conventional PCR, using the reaction mixture and conditions described above, and the concentration of the amplified product (~ 171bp) was determined spectrophotometrically with the NanoDrop ND-1000 UV-visible spectrophotometer. Subsequently, serial ten-fold dilutions of the tet (O) PCR product were prepared in triplicate in EB solution (1 mM Tris-HCl pH 8). Dilutions ranged from 3x10 3 copies per $g total DNA (lower precision limit) to 3x10 7 copies per $g total DNA (upper precision limit) and included a negative control (containing no target DNA).

2.3.6.1 Primers and probes Sequences of primers (forward (5'AAGAAAACAGGAGATTCCAAAACG), reverse (5'CGAGTCCCCAGATTGTTTTTAGC) and probe (5'FAM ACGTTATTTCCCGTTTATCACGG-Tamra) for detection of tet (O) were derived from Smith et al. (Smith et al. 2004) . The Taqman probe was labeled with 6-carboxyfluorescein (FAM) and 6-carboxytetramethyl-rhodamine (TAMRA).

2.3.6.2 Preparation of DNA dilution series

DNA was extracted from liquid bacterial cultures containing the tet (O)- bearing lasmid pU0A1. Subsequently, from extracted DNA, a 10-fold dilution series of target DNA was prepared in triplicate. Each series ranged from 3x10 3 to 3x10 7 tet (O) copies per $g total DNA

2.3.6.3 Real-time PCR for tet (O) Real-time PCR amplifications were carried out in a Mx3000P (Stratagene,

Cedar Creek, TX, USA). For optimization of the real-time PCR reaction mixture and conditions, different concentrations of forward primer

(5’AAGAAAACAGGAGATTCCAAAACG; 600 to 900 $mol l -1 ), reverse primer

(5’CGAGTCCCCAGATTGTTTTTAGC; 600 to 900 $mol l -1 ), Taqman fluorogenic probe [5’FAM-ACGTTATTTCCCGTTTATCACGG-Tamra, labeled with 6-carboxyfluorescein (FAM) at its 5’ end and with 6-carboxytetramethyl- rhodamine (TAMRA) at its 3’ end; 450 and 900 $mol l -1 ] and tet (O) DNA standard (3x10 3 to 3x10 7 tet (O) copies per $g total DNA), as well as a range of annealing temperatures (53 to 59 oC) were assessed ( Table 2.3 ).

The upper and lower precision limits of each standard curve were determined by the highest and lowest (respectively) tet (O) concentration at which the relative standard deviation on the average of triplicate C t (threshold cycle) was

< 5%. A standard curve was considered linear if R 2 was > 0.98. The percentage efficiency of the real-time PCR amplification for a standard curve was considered satisfactory if higher than 90% and lower than 105% (Bio-Rad Laboratories Inc

2006). Finally, successive standard curves were considered accurate if the relative standard deviation on the average of their R 2, percentage efficiency and slope were < 5%, respectively. These quantitative criteria were applied to the optimization experiments to determine the optimal real-time PCR reaction mixture and conditions, as described above, and to each standard curve used thereafter for the determination of tet (O) concentrations in samples.

Table 2.3 Annealing temperatures and primer and probe concentration used for real-time PCR amplification of tet (O).

Annealing temperature Primer concentration (nmol Probe concentration (nmol Experiment ( C) l-1 ) l-1 ) 1 53 900 450 2 55 900 450 3 57 900 450 4 59 900 450 5 55 900 900 6 55 800 450 7 55 700 450 8 55 600 450 9 55 800 800

2.4 Results 2.4.1 Anaerobic Dilution Water Resazurin is an indicator of redox potential and depending on the concentration of oxygen, the color of solution changes from blue (high concentration of oxygen) to pink (medium concentration of oxygen) and colorless (low concentration of oxygen).

Dilution waters remained blue after deoxygenating steps for test one, while most of them became pink after second experiment by increasing the boiling time followed by flushing pure nitrogen instead of mixed gases. Finally, the third experiment provided colorless dilution waters by transferring dilution bottles into the anaerobic chamber right after autoclaving in order to cool down -1 prior to adding Na 2S.9H 2O at a final concentration of 0.2 mmol l .

2.4.2 Enumeration of Total Aerobic and Anaerobic Bacterial Populations Since enumerations of both aerobic and anaerobic total bacterial populations were slightly higher using BHIA than TSA, and as anaerobic populations could be enumerated faster using BHIA than TSA ( Table 2.4 ), the former was used in all subsequent experiments for the enumeration of total and antibiotic-resistant anaerobic bacterial populations.

2.4.3 DNA Extraction 2.4.3.1 Extraction of total DNA from bacterial strains used as positive control for PCR Table 2.5 shows the yield and quality of total DNA extracted from bacterial strains used as positive controls for PCR. DNA concentrations ranged between 167 and 609 $g/µl. The A 260/230 and A 260/280 ratios for some genes is not in range, which indicates the presence of either proteins, phenol or other

contaminants that absorb strongly at or near 280 nm, or of co-purified contaminants. Table 2.4 Abundance of total aerobic and anaerobic bacterial populations in swine feces. Brain Heart Infusion Agar (BHIA) and Tryptic Soy agar (TSA) were compared.

Aaerobic Anaerobic Media Incubation Incubation (CFU g -1 ) (CFU g -1 ) (Days) (Days) BHIA 7.7. *10 8 7 1.19*10 9 10

TSA 5.2*10 8 7 8.8*10 8 14

Table 2.5 Yield and quality of total DNA extracted from bacterial strains used as positive controls for PCR. Strains were preserved at -20 oC in 15% glycerol.

Positive control Target gene DNA conc. A260/230 A260/280 ($g µl -1 ) Pseudomonas Bacteria 16S 254 2.17 1.85 aeruginosa rDNA tet(A) Strain SAS1393 609 1.78 1.98 Strain Ct4afooB (Tn10) tet(B) 321 1.94 2.02 pBR322 tet(C) 277 2.01 1.62 Strain D7-5 tet(D) 220 1.93 1.63 pSL1504 tet(E) 277 1.62 2.01 pAT102 tet(K) 254 1.12 1.85 pVB.A15 tet(L) 346 1.73 1.96 pJ13 tet(M) 257 1.84 1.62 pU0A1 tet(O) 302 1.93 1.99 pAT451 tet(S) 239 1.63 1.98 AF070999 tet(Y) 302 1.39 1.93 CCRI-9930 erm(A) 235 1.00 1.82 CCRI-1317 erm(B) 264 1.93 1.49 CCRI-1317 erm(C) 167 1.30 1.93

2.4.3.2 Extraction of total community DNA from swine feces The QIAamp DNA Stool Mini kit provided larger volumes of extracts and better total DNA concentrations than the Ultra Clean DNA kit, especially for samples preserved at -80 oC, as well as much less PCR inhibition ( Table 2.6 ). Ratio of absorbance at 260/280 nm and 260/230 nm are used to assess the purity of DNA and RNA. A ratio of 1.8 is generally accepted as pure for DNA and ratio of 2 is accepted as pure for RNA. Hence, the DNA extracts used for the detection and quantification of resistance genes by PCR and real-time PCR were those obtained with the QIAamp DNA Stool Mini kit and preserved at -80 oC in EB solution (1 m mol l -1 Tris-HCl pH 8).

2.4.4 PCR for Bacteria 16S rDNA Consistent specific amplification of a ~ 233 bp PCR product corresponding to a segment of the Bacteria 16S rDNA was obtained using a PCR reaction mixture with MgCl 2 and without BSA, and hot start PCR conditions (Table 2.7 ). Hence, the optimal PCR reaction mixture (25 µl total volume) for amplification of the Bacteria 16S rDNA contained 1.5 )mol l -1 of each primer (Table 2.1), 250 )mol l -1 of each dNTP (Amersham Biosciences Corp., Piscateway, NJ), 1.25 U of Taq DNA polymerase (Invitrogen, CA, USA), the PCR buffer supplied with the enzyme (10 mmol l -1 Tris-HCl pH 9, 50 mmol l -1 2+ -1 KCl) and Mg (MgCl 2.6H 2O, 1.5 mmol l ). Optimal hot start PCR conditions were 5 min of denaturation at 94°C, 30 cycles of 1 min at 94°C (denaturation), 1 min at 55°C (annealing), 2 min at 72°C (extension), and finally an extension period of 10 min at 72°C.

Table 2.6 Yield and quality of total community DNA extracted from swine feces. Final volume DNA Test kit Storage A A of conc. 260/280 260/230 (supplier) extract (µl) temp. ( oC) ( $g µl -1 ) Ultra Clean 4 19 2.05 0.17 DNA kit 50 -20 17 1.93 0.22 (Mo-Bio) -80 11 1.73 0.34

QIAamp DNA 4 12 1.90 1.80 Stool Mini 200 -20 19 1.79 1.88 (Qiagen) -80 142 1.91 1.95

Table 2.7 Optimization of the PCR reaction mixture and conditions.

PCR Test Mg 2+ BSA Amplification Specificity conditions # (mmol l -1 ) (g l -1 )

1 0 0 _ Not applicable 2 0 0.4 _ Not applicable Regular 3 1.5 0 + Multiple bands 4 1.5 0.4 + Multiple bands

5 0 0 + Multiple bands 6 0 0.4 _ Not applicable Hot start 7 1.5 0 + Single band 8 1.5 0.4 _ Not applicable

2.4.5 Real-time PCR for tet (O) For all optimization experiments, the relative standard deviation on the 3 average of triplicate C t was < 5% for tet (O) concentrations ranging from 3x10 copies per $g total DNA (lower precision limit) to 3x10 7 copies per $g total DNA (upper precision limit) ( Table 2.8 ). Thus, this real-time PCR assay is precise for tet (O) concentrations included within this range. Optimization experiments also showed that quantitative criteria for linearity of standard curves (R 2 > 0.98) and efficiency of amplification (percentage higher than 90% and lower than 105%) were met only when the annealing temperature was 55oC, the Taqman fluorogenic probe concentration was 450 $mol l -1 , and the concentration of each primer was between 700 to 900 $mol l -1 ( Table 2.9 ). Since optimal linearity (R 2 = 0.987) and amplification efficiency (102.1%) were obtained at 55 oC with Taqman fluorogenic probe concentration at 450 $mol l -1 and primers concentration at 800 $mol l -1 , these conditions were selected for further quantification of tet (O) abundance in samples. Agarose gel electrophoresis of tet (O) real-time PCR products showed only one band, which confirms the absence of non-specific amplification. Thus, this tet (O) real-time PCR assay is robust and reliable.

Table 2.8 Precision of standard curves during optimization of real-time PCR reaction mixture and conditions for tet (O). Relative Anealing Primer Probe tet (O) conc. Average standard temp. conc. conc. (copies/ $g Q Ct deviation ( C) ($mol l -1 ) ($mol l -1 ) total DNA) (%)

53 900 450 3x10 3 20.53 0.65 3x10 5 28.57 0.89 3x10 7 35.87 0.89

55 900 450 3x10 3 19.00 0.33 3x10 5 27.57 0.92 3x10 7 31.87 1.75

57 900 450 3x10 3 20.77 0.43 3x10 5 28.05 0.46 3x10 7 35.47 0.49

59 900 450 3x10 3 20.77 0.43 3x10 5 28.03 0.46 3x10 7 35.47 0.49

55 600 450 3x10 3 21.60 0.93 3x10 5 28.60 0.88 3x10 7 34.07 0.71

55 700 450 3x10 3 19.67 0.68 3x10 5 28.13 0.63 3x10 7 33.20 0.76

55 800 450 3x10 3 19.80 1.34 3x10 5 27.87 0.29 3x10 7 32.57 4.85

55 900 450 3x10 3 20.10 2.69 3x10 5 27.90 2.02 3x10 7 33.67 1.30

55 800 900 3x10 3 20.87 1.09 3x10 5 28.87 0.03 3x10 7 36.30 0.89

Table 2.9 Linearity and efficiency of standard curves during optimization of real-time PCR reaction mixture and conditions for tet (O).

Primer conc. Probe conc. Anealing temperature (°C) R 2 % Efficiency ($mol l -1 ) ($mol l -1 )

53 900 450 450 0.997 82.3 59 900 450 450 0.997 82.3 55 600 450 450 0.998 108.2 55 700 450 450 0.983 97.5 55 800 450 450 0.987 102.1 55 900 450 450 0.987 97.0 55 900 900 900 0.999 81.9

2.5 Discussion In this chapter, optimal conditions for faecal collection and preservation, total aerobic and anaerobic bacterial enumerations, and DNA extraction were determined. Moreover, various PCR and real-time PCR reaction mixtures and conditions were assessed to optimize these methods for analyzing pig fecal samples. The work presented in this chapter is the first step to further investigations regarding the bacterial ecology of antibiotic resistance in swine production.

2.5.1 Anaerobic Dilution Water Resazurin is an indicator of redox potential and depends on the concentration of oxygen the color of solution change from blue (high concentration of oxygen) to pink (medium concentration of oxygen) and colorless (Low concentration of oxygen). In order to obtain colorless anaerobic dilution waters, sufficient boiling time, flushing pure nitrogen inside the anaerobic jars and, and cooling down the autoclaved bottles inside the anaerobic chamber are necessary to perform.

2.5.2 Bacterial Enumerations Brain Heart Infusion Agar ( BHIA) and Tryptic (Trypticase) Soy Agar (TSA) have been proven to be effective in the cultivation of a wide variety of microorganisms, including many types of pathogens. The nutritional composition of BHIA is brain heart infusion, peptone and dextrose components. The peptones and infusion are sources of organic nitrogen, carbon, sulfur, vitamins and trace substances. Dextrose is a carbohydrate source that microorganisms utilize by fermentative action. The medium is buffered through the use of disodium phosphate. TSA is made of soybean-casein digest agar medium in the USP for the total microbial count portion of the microbial limit testing procedures (Gerhardt et al 1994).

Since enumerations of both aerobic and anaerobic total bacterial populations in this research study were slightly higher using BHIA than TSA, and as anaerobic populations could be enumerated faster using BHIA than TSA (Table 2.5 ), the former was used in all subsequent experiments for the enumeration of total and antibiotic-resistant anaerobic bacterial populations.

2.5.3 Extraction of Total Community DNA from Swine Feces Fecal samples are chemically and microbiologically complex matrices that present technical challenges for the extraction and PCR amplification of nucleic acids (Monteiro et al. 1997). For example, feces contain potent inhibitors of DNA polymerases such as bile-salts (Lantz et al. 1997) and complex polysaccharides (Monteiro et al. 1997). Moreover, reagents used for DNA purification such as salts, guanidine, proteases and organic solvents, are other potent inhibitors of DNA polymerases (Weyant et al. 1990; Loffert D. et al. 1997). Other important sources of inhibitors are the materials and reagents that come into contact with samples during DNA extraction and purification such as inorganic salts (KCl, NaCl), detergents (including sodium dodecyl sulfate), chelating agents (such as EDTA) and others (Weyant et al. 1990). Successful PCR amplification also depends on DNA template quantity and quality. Commercial test kits are developed specifically for the extraction and purification of DNA from fecal samples. Ideally, a test kit should remove PCR inhibitors, preserve the quality (integrity) of nucleic acids, and provide a high recovery of nucleic acids. Results showed that the QIAamp DNA Stool Mini kit better performed in all three aspects than the Ultra Clean DNA kit ( Table 2.7 ). However, the limited information available about the exact composition and concentration of the reagents used in these kits make explanations of these results difficult.

2.5.4 PCR Reaction Mixture for Bacteria 16S rDNA The Polymerase Chain Reaction, which is a sensitive technique for the amplification of specific DNA segments in vitro, can be affected by the chemistry of the reaction mixture and the thermal conditions used during logarithmic amplification. For example, batch-related variability in the quality of primers and Taq DNA polymerases, as well as mismanipulation of the thermal cycler can cause the amplification reaction to fail. General considerations for the optimization of PCR reaction mixtures include DNA template quality and quantity, PCR primer design and concentration, DNA polymerase type and concentration, and concentration of Mg 2+ and PCR enhancers such as BSA (Promega Corporation 2007). The temperature used to optimize the specific annealing of oligonucleotide primers with the target region of template DNA is a critical factor for successful PCR analyses. Thus, PCR reaction mixture and conditions were optimized for consistent specific amplification of a ~ 233 bp PCR product corresponding to the V3 region of the Bacteria 16S rDNA (section 2.4.4). This optimized PCR reaction mixture was also used for PCR amplification of 14 genes conferring resistance either to tetracyclines ( tet genes) or macrolides ( erm genes) via ribosomal protection or efflux ( Table 2.2 ). PCR primers define the target region to be amplified and generally range between 15 and 30 bases in length. Primer design has an important role to optimize the specificity and efficiency of amplification reactions (Rabinow 1996). The primers synthesized by AlphaDNA ( Table 2.2 ) and their concentration have been optimized before by Chenier and Juteau (2009) and were found to be optimal with the swine matrix investigated in this study. The choice of DNA polymerase can have a significant impact on resistance to inhibition (Katcher and Schwartz, 1994). Taq DNA Polymerases from two different companies (Amersham, Piscateway, NJ and Invitrogen, CA, USA) were tested and were found to be similar in their activity. The Taq DNA Polymerase from Invitrogen was chosen for future work. Recommended enzyme concentration is 1-1.25 units in a 50 µl amplification reaction mixture (Chenier and Juteau, 2009). Adding more enzyme will not significantly increase product

53 yield (Katcher and Schwartz, 1994), and in fact will increase the likelihood of generating artifacts associated with the intrinsic 5a3a exonuclease activity of Taq DNA polymerases, resulting in smeared bands in an agarose gel (Bell and DeMarini, 1991; Longley M.J et al. 1990). Magnesium is a required cofactor for Taq DNA polymerases, and magnesium concentration is a crucial factor that can affect amplification success. Chenier and Juteau (2009) amplified 16S rDNA and tet genes in the absence of extra magnesium in the reaction mixture. In contrast in the present research, adding magnesium at a final concentration of 1.5 mmol l -1 was necessary for amplifying 16S rDNA and all tet and erm genes (section 2.4.4). This might be due to differences in the chemical composition between samples. Usually template DNA concentration, chelating agents present in the sample like EDTA or citrate, and the presence of proteins can reduce the amount of free magnesium in the reaction. Consequently, Taq DNA polymerase is inactive in the absence of adequate free magnesium (Eckert and Kunkel, 1990). Studies showed that the addition of stabilizing agents such as Bovin Serum Albumin (BSA) can overcome amplification failure and that such additives can enhance DNA polymerase stability and decrease the loss of reagents through adsorption to the tube walls (Klebe et al. 1999). However, BSA acted as an inhibitor for amplification of DNA in fecal samples in this study (section 2.4.4). This could be due to the quality of BSA, because BSA quality can vary greatly between sources and material should be rigorously quality-tested (Promega Corporation 2007).

2.5.5 PCR Conditions for Bacteria 16S rDNA With regular PCR conditions, 16S rDNA amplification occurred with nonspecific amplification ( Table 2.8 ). Excess free magnesium reduces enzyme fidelity and may increase the level of nonspecific amplification (Ellsworth DL. et al. 1993). Improper PCR annealing temperature and conditions can also lead to non-specific amplification. Hot-start PCR for amplification of 16S rDNA of fecal samples significantly reduced nonspecific priming, the formation of primer

54 dimers, and enhanced product yields (Promega Corporation, 2007) ( Table 2.8 ). For resistant genes, the most commonly altered cycling parameter was annealing temperature. Table 2.2 shows the sequence of primers and optimized annealing temperature for each specific gene. Primer sequence is a major factor that determines the optimal annealing temperature, which is often within 5°C of the melting temperature of the primer.

2.5.6 Real-Time PCR for tet (O) Quantitative PCR has resulted in radical changes in our ability to quantify nucleic acid concentrations. In a classic reaction, the amount of PCR product increases exponentially (Bio-Rad Laboratories Inc, 2006). Because it takes several cycles for enough amplicons to be readily detectable, the plot of fluorescence vs. cycle number exhibits a sigmoidal appearance. At later cycles, the reaction substrates become depleted, the amount of PCR product no longer doubles at every cycle, and the curve begins to flatten. The point on the curve at which the amount of fluorescence begins to increase rapidly, usually a few standard deviations above the baseline, is termed the threshold cycle (C t value).

The plot of C t versus template concentration is linear, thus a comparison of C t values between multiple reactions enables one to calculate the concentration of the target nucleic acid. The slope of this plot provides a measure of PCR efficiency (Shenng and Russell D. Fernald, 2005). For each optimization experiment for the quantification of tet (O) by real- time PCR, 10-fold dilutions of the tet (O) plasmid standard (three different sets: sets = dilutions) were run in parallel with PCR reactions. Stringent criteria were applied to evaluate the precision, linearity and efficiency of real-time PCR optimization experiments. The precision of each experiment was assessed by the relative standard deviation on the average of triplicate C t for a specific dilution of standard. In the present work, it was arbitrarily established that a relative standard deviation below 5% shows the precision of calculations and preparation of solutions and standard, and of experimental work. This criterion was met for all dilutions of all standard curves during optimization ( Table 2.7 ). The linearity of

55 each standard curve was assessed by the coefficient of determination (R 2) of its regression. The R 2 is a statistical measure of how well the regression plot approximates the real data points. An R 2 of 1.0 indicates that the regression plot and the data fit perfectly. In this research study, a standard was considered linear, hence reliable, when R 2 was higher than 0.98 (Bio-Rad Laboratories Inc, 2006). During optimization experiments, 8 of the 9 standard curves met the criterion above ( Table 2.8 ). The amplification efficiency (E) is determined by data from serially diluted samples and is related to the slope of the standard curve. It can be calculated by using the following equation: E = 10 (-1/slope)

E can be converted into percentage by using the following equation: E = 100*(10 (-1/slope)-1 ) which determines the increase in the amount of PCR product after each cycle. In an ideal reaction, the efficiency is close to 100% (Bio-Rad Laboratories Inc, 2006). Amplification efficiency above 90% shows that the real-time PCR reaction mixture (including primer design and concentration) and conditions (including annealing temperature) are optimal, whereas amplification efficiency below 105% shows the absence of non-specific amplification (Bio-Rad Laboratories Inc, 2006). During optimization experiments, only 4 of the 9 standard curves met these criteria above ( Table 2.8 ).

2.6 Conclusions Brain Heart Infusion Agar allowed the highest and fastest quantitative bacterial growth from the swine faecal samples in comparison to Tryptic Soy Agar. QIAamp DNA Stool Mini kit (Qiagen) provided better total DNA recovery and purity, as well as less PCR inhibition than the Ultra Clean DNA kit (MoBio), especially for samples preserved at -80 oC. A PCR reaction mixture with magnesium at 1.5 mmol l -1 , without BSA was optimal for the amplification of 16S rDNA of fecal samples. Hot-start PCR conditions significantly eliminated nonspecific priming, the formation of primer dimers, and enhanced product yields for the amplification of 16S rDNA. Classical microbiology and molecular biology techniques could be optimized and successfully applied to the investigation of complex microbial communities in a technically challenging matrix. The work presented in this chapter is the first step to further investigations regarding the bacterial ecology of antibiotic resistance in swine production.

2.7 Acknowledgments This research was supported by the National Sciences and Engineering Research Council of Canada (NSERC) and the Fonds Québécois de Recherche sur la Nature and les Technologies (FQRNT) to M.R.C. S.P. benefited from the Alexander Graham Bell Canada Graduate Scholarship M (NSERC), the Principal’s Graduate Fellowship (McGill) and the Macdonald Class of '44 Rowles Graduate Bursary (McGill). We acknowledge Dr. Huilan Chen for generously sharing her expertise about real-time PCR. We thank Dr. Josée Harel (Faculty of Veterinary Medicine, Université de Montréal), Dr. Luke Masson (Biotechnology Research Institute, National Research Council Canada, Montreal) and Dr. Marilyn C. Roberts (University of Washington, USA) for providing positive control strains for PCR.

CONNECTING STATEMENT TO CHAPTER 3

In this chapter, optimized methods and conditions were applied to assess the prevalence and short-term temporal evolution of antibiotic resistance among enteric anaerobic bacterial populations in swine production 2.5 years after discontinuation of adding antibiotics for nutritional purposes, using complementary quantitative classical microbiology and molecular biology techniques. A manuscript is being prepared for publication based on the studies highlighted in this chapter. All experiment work and data analysis were carried out by the candidate under the overall supervision of Dr. M. Chenier.

CHAPTER 3. ANTIBIOTIC RESISTANCE IN SWINE PRODUCTION 2.5 YEARS AFTER DISCONTINUATION OF ANTIBIOTIC USE.

3.1 Abstract At the Swine Complex of McGill University, the addition of antibiotics to swine feed for subtherapeutic applications has been discontinued since January 2007. The objective of this work was to assess the prevalence of antibiotic resistance among bacterial populations in swine production 2.5 years after this discontinuation. Feces from ten pigs born from the same sow and administered feed without antibiotics were sampled during suckling, weanling, growing and finishing. The percentage of chlortetracycline-resistant anaerobic bacterial populations was higher than that of tylosin-resistant anaerobic bacterial populations at weanling, growing and finishing, with generally larger differences in males than in females. Prior to the transportation of animals to the slaughterhouse, resistant populations varied between 3.1 ×10 6 and 2.5 ×10 9 CFU g -

1. In all pigs, tet (L), tet (O) and erm (B) were detected at suckling and weanling, whereas only tet (O) was detected at growing and finishing. At suckling, the abundance of tet (O) was 18.2 times higher in females than in males, was similar between the two genders at weanling and growing, and reached 5.1 ×10 5 and 5.6 ×10 5 copies of tet (O)/ $g of total DNA in males and females, respectively, at finishing. The high abundance and proportion of antibiotic-resistant populations, as well as the occurrence of resistance genes within these populations despite the discontinuation of antibiotic addition to feeds imply either that more time would be required for antibiotic resistance to decrease to lower levels, and/or that factors such as the presence of metals in feed impose a selective pressure that maintains antibiotic resistance genes among these bacterial populations.

3.2 Introduction Antibiotics have been utilized broadly in the last 50 years in food animals to treat, prevent, or control infectious illness, or to enhance efficiency of feed utilization and weight gain (Institute of food technologists 2006). In Canada, swine production is an important economic activity and a major source of environmental problems because of the large volume of swine wastes that it generates (Girard et al. 2009). In this country, tetracyclines and macrolides are the first and third most abundantly distributed antibiotics for use in animals (http://www.phac-aspc.gc.ca/cipars-picra/2007-eng.php), and are classes of antibiotics that are also important for the treatment of human infections. Intensive and extensive use of these antibiotics creates a pressure for the selection and dissemination of both pathogenic and commensal antimicrobial-resistant bacteria in swine husbandry and subsequently along the food processing chain (Adjiri- Awere and Van Lunen, 2005). Investigation derived from different steps of the production chain of pork meat industries illustrated the wide distribution of multidrug resistant staphylococci (Simeoni et al. 2008). Moreover, resistant bacteria and resistance genes can be transferred from food animals, their waste and their meat to humans via the food processing chain or the environment (Silbergeld et al. 2008). Studies showed that human diseases and deaths caused by strains of

multi-drug resistant pathogenic Salmonella enterica serotype typhimurium DT104 in Denmark (Molbak et al. 1999) and Enterococcus faecium in China (Lu et al. 2002) originated from swine herds. The selection of antibiotic-resistant bacteria in swine husbandry and the subsequent dissemination of such bacteria from animal reservoirs to humans increase the occurrence of infectious diseases that become more and more difficult to treat with currently available antibiotics. This represents a major food safety and human/animal health concern because of the the increasing emergence of antibiotic resistance phenotypes both in strains of clinical/veterinary significance and in usual commensal bacteria (Heuer et al. 2006). In the mammal gut, pathogens are greatly outnumbered by commensal bacteria that can harbor the same resistance determinants as their disease- producing counterparts. Since the oxygen level in the swine large intestine is below 1%, anaerobic bacteria, for which the culturable fraction can reach 10 9 to 10 10 CFU g -1 , dominate over aerobic bacteria by tens to hundreds, dominate over aerobic bacteria by tens to hundreds (Jensen and Jorgensen, 1994). Since anaerobic commensal bacteria constitute the numerically and ecologically dominant sub-population in the swine large intestine, we hypothesize that they serve as a diversified and highly abundant reservoir of resistance genes that may be transferred to pathogenic bacteria. This implies that not only pathogenic bacteria, but mainly commensal bacteria, especially anaerobes, must be targeted applying a relevant, whole-population approach as described in this work. At the Swine Complex of McGill University, the addition of antibiotics to swine feed for nutritional (sub-therapeutic) applications have been discontinued since January 2007. The objective of this work was to assess the prevalence and short-term temporal evolution (i.e. within the lifetime of pigs at the farm) of antibiotic resistance among enteric anaerobic bacterial populations in swine production 2.5 years after this discontinuation, using complementary quantitative classical microbiology and molecular biology techniques.

3.3 Material and Methods

3.3.1 Swine Rearing and Sampling

Pigs were reared at the Swine Complex of McGill University between June and December 2009. They were given antibiotic-free pelleted equilibrated cereal-based diet specific for each production stage, as well as water, ad libitum (Agribrands-Purina Canada Inc.). During each stage, fresh fecal samples were collected from ten healthy pigs (six males: pigs 1 to 6; four females: pigs 7 to 10) born from the same sow (Landrace x Yorkshire, mated with a Duroc boar) on June 17 th , 2009 ( Table 3.1 ). Fresh fecal samples were collected from the ground using sterile instruments, taking care not to touch the ground in order to avoid cross-contamination, within minutes after defecation. Samples were kept on ice until arrival to the laboratory, and then divided into two sub-samples. Samples from the first group were kept on ice and used to perform bacterial enumerations (the same day), while samples from the second group were soaked in liquid nitrogen and preserved either at -20 0C or -80 0C for subsequent molecular analyses.

3.3.2 Bacterial Enumerations -1 Phosphate buffer (313 )M KH 2PO 4, 2 mmol l MgCl 2.6H 2O, 0.001 g resazurin l -1 as an indicator of redox potential, pH 7.2) was made anaerobic by boiling water for 30 min to reduce the oxygen concentration, transferring into an anaerobic jar, vacuuming for 1 min and flushing for 5 min with a 10% H 2, 10%

CO 2 and 80% N 2 gas mixture (Megs, St-Laurent, Canada). The last two steps were repeated three times. Anaerobic phosphate buffer was distributed in glass test tubes with screw caps inside the anaerobic chamber. Glass test tubes were

screwed, autoclaved, and sterile Na 2S.9H 2O (reducing agent to maintain anaerobic conditions) was added at a final concentration of 0.2 mmol l -1 (Chénier and Juteau 2009).

Table 3.1 Swine rearing and sampling.

Stage Period (weeks) Dates (2009) Sampling (2009)

Suckling 1 to 3 June 17 - July 8 June 22

Weanling 4 to 11 July 9 – September 1 July 14

Growing 12 to 16 September 2 - October 7 September 2

Finishing 17 to 21 October 8 – November 12 October 26

Bacterial enumerations were completed in an anaerobic chamber (Coy Drive, Grass Lake, USA). Serial dilutions (10 -1 to 10 -10 ) of fresh fecal samples kept on ice were performed in anaerobic phosphate buffer. For each sample, anaerobic bacterial populations were determined using a spread-plate procedure (three replicate Petri plates per dilution for each sample). Brain Heart Infusion Agar (BHIA, Becton Dickinson, Sparks, NJ) was utilised as it allowed the highest quantitative bacterial growth from the swine faecal samples in comparison to Tryptic Soy Agar (Becton Dickinson, Sparks, NJ) (results not shown). Total bacterial populations (Tot) were enumerated using BHIA, chlortetracycline- resistant bacterial populations (Tet R) were enumerated using BHIA supplemented with 20 mg chlortetracycline HCl l -1 (Sigma-Aldrich, St-Louis, MO, USA), and tylosin-resistant populations bacterial populations (Tyl R) were enumerated using BHIA supplemented with 10 mg tylosin tartrate l -1 (Sigma-Aldrich). Chlortetracycline and tylosin were added at concentrations 25% higher than MIC breakpoints for tetracycline-resistant ( 116 mg l -1 ) and macrolide-resistant ( 18 mg l-1 ) bacteria isolated from animals (Edwards et al. 1989). Petri plates were incubated in an anaerobic incubator in the dark at 37°C. Growth was observed periodically in the anaerobic chamber, because of the oxygen sensitivity of anaerobic bacteria, until no additional colonies could be visually detected (10 days of incubation). Triplicate Petri plates (from a specific dilution) containing 30 to 300 colony forming units (CFU) were selected to determine the abundance, evolution (fold change) and proportion of Tot, Tet R and Tyl R anaerobic bacterial populations in swine feces.

3.3.3 DNA Extraction DNA was extracted from fresh samples and from samples preserved either at -20 oC or -80 oC. Qiagen QIAamp DNA Stool Mini kit (QIAgen, Ontario, Canada) provided better total DNA recovery than the Ultra Clean DNA kit (MoBio, California, USA), especially for samples preserved at -80 oC, and relatively little PCR inhibition (results not shown). Hence, the DNA extracts

analyzed were those obtained with the QIAamp DNA Stool Mini kit and preserved at -80 oC in EB solution (1 mM Tris-HCl pH 8). DNA was checked for integrity by agarose gel electrophoresis with Lambda DNA HindIII Digest standards (New England BioLabs, Ipswich, MA, USA), and DNA concentration of each extract was determined spectrophotometrically with the NanoDrop ND- 1000 UV-visible spectrophotometer. The total DNA from pure cultures was also extracted, purified, quantified and preserved in the same manner in order to be used as positive controls in PCR and real-time PCR experiments (see below).

3.3.4 PCR Amplification PCR amplifications were carried out in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, USA) using 5 $g of DNA extracted from individual pig’s fecal sample as template. Targets were the Bacteria 16S rDNA gene and 14 genes conferring resistance either to tetracyclines ( tet genes) or macrolides ( erm genes) via ribosomal protection or efflux (Table 2) (Chenier and Juteau 2009). The PCR reaction mixture contained 1.5 )mol l -1 of each primer (Table 2.1 ), 250 )mol l -1 of each dNTP (Amersham Biosciences Corp., Piscateway, NJ), 1.25 U Taq DNA polymerase (Invitrogen, CA, USA), and the PCR buffer supplied with the enzyme (10 mmol l -1 Tris-HCl pH 9, 50 mmol l -1 -1 KCl, 1.5 mmol l MgCl 2). Positive controls for each target gene are described in Table 2. A negative control, consisting of the reaction mixture without DNA, was used in each PCR run. The PCR conditions for antibiotic resistance genes started with an initial DNA denaturation (94 oC for 5 min), followed by 30 cycles of 1 min at 94 oC (denaturing), 1min of annealing at the temperatures specified in Table 2.1 , and 1 min at 72 oC (extension), followed by a final extension of 7 min at 72 oC. For the 16S rDNA gene ( Table 2.1 , the V3 region was targeted with the Bacteria universal primers 341-F and 518-R (Muyzer et al. 1993). The PCR conditions for 16S rDNA genes were 5 min of denaturation at 99°C, followed by 10 min at 80°C during which the Taq DNA polymerase was added (hot start), two cycles of 5 min at 94°C, 5 min at 55°C, 2 min at 72°C, then 28 cycles of 1 min at 94°C, 1 min at

55°C, 2 min at 72°C, and finally an extension period of 10 min at 72°C (Chénier and Juteau 2009). The size ( Table 2.1 ), specificity (unique band) and abundance of PCR products were determined by comparison with DNA standards (GeneRuler 100 bp DNA Ladder, MBI Fermentas, Burlington, ON, Canada) after agarose gel electrophoresis (Chénier and Juteau, 2009).

3.3.5 Standard for Real-Time PCR Since tet (O) was detected in all pigs at all production stages, and as it can be horizontally transferred among bacterial populations via different mechanisms (Smith et al. 2004), this gene was selected for further quantitative analysis by real-time PCR based on protocols described by Smith et al. (Smith et al. 2004). The tet (O)-bearing plasmid pU0A1 was extracted and purified from its E. coli host using the QIAquick PCR Purification Kit (QIAgen, Ontario, Canada) and used as a standard to allow for the determination of the number of copies of tet (O) in the samples by real-time PCR. Following extraction and purification of pU0A1, tet (O) was amplified by conventional PCR, using the reaction mixture and conditions described above, and the concentration of PCR products (~ 171bp) was determined spectrophotometrically with the NanoDrop ND-1000 UV-visible spectrophotometer. Subsequently, serial ten-fold dilutions of the tet (O) PCR products were prepared in triplicate in EB solution (1 mmol l -1 Tris-HCl pH 8). Dilutions ranged 3x10 3 copies per $g total DNA (lower precision limit) to 3x10 7 copies per $g total DNA (upper precision limit) and included a negative control (containing no target DNA).

3.3.6 Optimization of Real-Time PCR Real-time PCR amplifications were carried out in a Mx3000P (Stratagene, Cedar Creek, TX, USA). For optimization of the real-time PCR reaction mixture and conditions, different concentrations of forward primer (5’AAGAAAACAGGAGATTCCAAAACG; 600 to 900 $mol l -1 ), reverse primer (5’CGAGTCCCCAGATTGTTTTTAGC; 600 to 900 $mol l -1 ), Taqman fluorogenic probe [5’FAM-ACGTTATTTCCCGTTTATCACGG-Tamra, labeled

with 6-carboxyfluorescein (FAM) at its 5’ end and with 6-carboxytetramethyl- rhodamine (TAMRA) at its 3’ end; 450 and 900 $mol l -1 ] and tet (O) DNA standard (3x10 3 to 3x10 7 tet (O) copies per $g total DNA), as well as a range of annealing temperatures (53 to 59 oC) were assessed. The optimal real-time PCR reaction mixture (25 µl) contained 10 $g of DNA extracted from individual pig’s fecal sample as template, 800 $mol l -1 of each forward and reverse primers, 450 $mol l -1 of Taqman fluorogenic probe, and the Taqman Universal PCR Master Mix (Stratagene, CA, USA) (Smith et al. 2004). A negative control, consisting of the reaction mixture without DNA, was used in each PCR run. The optimal real-time PCR conditions for tet (O) started with an initial DNA denaturation (95°C for 10 min), followed by 40 cycles of 30 sec at 95°C (denaturing), 1 min at 55°C (annealing), and 30 sec at 72°C (extension), followed by a final extension of 7 min at 72°C. PCR products were analyzed by the Mx3000P software and checked for nonspecific PCR amplification by comparison with DNA standards (GeneRuler 100 bp DNA Ladder, MBI Fermentas, Burlington, ON, Canada) after agarose gel electrophoresis (Chénier and Juteau, 2009). The upper and lower precision limits of each standard curve were determined by the highest and lowest (respectively) tet (O) concentration at which the relative standard deviation on the average of triplicate C t (threshold cycle) was < 5%. A standard curve was considered linear if its R 2 was > 0.98. The percentage efficiency of the real-time PCR amplification for a standard curve was considered satisfactory if higher than 90% and lower than 105% (Bio-Rad Laboratories Inc, 2006). Finally, successive standard curves were considered accurate if the relative standard deviation on the average of their R 2, efficiency and slope were < 5%, respectively. These quantitative criteria were applied to the optimization experiments to determine the optimal real-time PCR reaction mixture and conditions, as described above, and to each standard curve used thereafter for the determination of tet (O) concentrations in samples.

3.4 Results

3.4.1 Bacterial Enumerations Figure 3.1 illustrates the abundance of Tot, Tet R and Tyl R anaerobic bacterial populations in individual pigs during suckling, weanling, growing and finishing. The temporal evolution of the abundance of Tot and Tet R populations was identical for all animals but pig 7, whereas only pigs 1, 2, 3 and 4 had identical trends for Tot, Tet R and Tyl R populations throughout their lifetime. Anaerobic bacterial populations varied between 3.13x10 6 and 2.48x10 10 CFU g -1 . In order to assess if gender has an impact on the short-term temporal evolution of the gut microflora, the abundance and percentage of Tot, Tet R and Tyl R anaerobic bacterial populations were averaged separately for males and females ( Figure 3.2 ). The abundance of Tot populations remained stable throughout the pigs’ lifetime both in males ( Figure 3.2A ) and females ( Figure 3.2B ), with the exception of a 7-fold increase in males at weanling ( Figure 3.2C ). In males, the abundance of Tet R and Tyl R populations increased at weanling and decreased thereafter ( Figure 3.2A ), especially Tyl R populations, which decreased by 7 and 19 times at growing and finishing, respectively ( Figure 3.2C ). In contrast, in females, Tet R and Tyl R populations decreased at weanling and increased thereafter, with the exception of Tyl R at finishing ( Fig. 3.2B ). At growing and finishing, the abundance of total and resistant populations between males and females were similar. The percentage of Tet R populations was higher than that of Tyl R populations at weanling, growing and finishing, with generally larger differences in males ( Figure 3.2E ) than in females ( Figure 3.2F ). The opposite trend was observed at suckling both for males and females. In males, the percentage of Tyl R populations steadily decreased over time, whereas the percentage of Tet R populations generally increased. In females, no trend regarding the percentage of resistant populations could be observed. At the finishing stage, i.e. prior to the transportation of animals to the slaughterhouse, resistant populations varied between 3.13x10 6 and 2.46x10 9 CFU

g-1 , Tet R populations averaged at 69% and about 100% of bacterial populations in males and females, respectively, whereas Tyl R populations accounted for only 2% and 5% of the communities in males and females, respectively.

3.4.2 Antibiotic Resistance Genes Among the 14 selected resistance genes that were monitored by PCR, only tet (O) and tet (L) were detected in the sow (from which the ten piglets were born) during suckling and weanling. The genes tet (L), tet (O) and erm (B) were detected in all pigs at suckling and weanling, whereas only tet (O) was detected at growing and finishing ( Table 3.2 ). Tet (S) was detected only once in male 5 at weanling.

11 A) Tot Suckling Weanling 10 Growing Finishing 9

6 B) Tet R 10 1 -

10 8 Log CFU g LogCFU 7

6 C) Tyl R 10

6 Pig 1 Pig 2 Pig 3 Pig 4 Pig 5 Pig 6 Pig 7 Pig 8 Pig 9 Pig 10 Males Females

Figure 3.1 Enumeration of (A) Tot, (B) Tet R and (C) Tyl R anaerobic bacterial populations in individual pigs during suckling, weanling, growing and finishing.

Figure 3.2 Abundance (A and B), evolution (C and D) and percentage (E and F)

of Tot, Tet R and Tyl R anaerobic bacterial populations in males (average for 6

males in panels A, C, E) and females (average for 4 females in panels B, D, F)

during suckling (S), weanling (W), growing (G) and finishing (F).

Table 3.2 PCR detection of selected tetracycline [ tet (ABCDEKLMOSY)] and macrolide [ erm (ABC)] resistance genes among bacterial populations in individual pigs during suckling, weanling, growing and finishing. Only genes detected are indicated. Males Females Phase 1 2 3 4 5 6 7 8 9 10

tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) Suckling erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B)

tet (LO) tet (LO) tet (LO) tet (LO) tet (LOS) tet (LO) tet (LO) tet (LO) tet (LO) tet (LO) Weanling erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B) erm (B)

Growing tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O)

Finishing tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O) tet (O)

3.4.3 Optimization and Standard Curve for Real-Time PCR For all optimization experiments, the relative standard deviation on the

average of triplicate Ct was < 5% for tet(O) concentrations ranging from 3x10 3 copies per $g total DNA (lower precision limit) to 3x10 7 copies per $g total DNA

(upper precision limit) (data not shown). Thus, this real-time PCR assay is precise for tet(O) concentrations included within this range. Optimization experiments also showed that quantitative criteria for linearity of standard curves (R 2 > 0.98)

and efficiency of amplification (percentage higher than 90% and lower than

105%) were met only when the annealing temperature was 55 oC, the Taqman fluorogenic probe concentration was 450 $mol l -1 , and the concentration of each primer was between 700 to 900 $mol l -1 (data not shown). Since optimal linearity

o (R 2 = 0.987) and amplification efficiency (98.7%) were obtained at 55 C with

Taqman fluorogenic probe concentration at 450 $mol l -1 and primers

concentration at 800 $mol l -1 , these conditions were selected for further

quantification of tet(O) abundance in samples. Amplification efficiency above

90% shows that the real-time PCR reaction mixture (including primer design and

concentration) and conditions (including annealing temperature) are optimal,

whereas amplification efficiency below 105% shows the absence of non-specific

amplification (Bio-Rad Laboratories Inc, 2006). Agarose gel electrophoresis of

tet(O) real-time PCR products showed only one band, which confirms the absence

of non-specific amplification (results not shown). Thus, this tet(O) real-time PCR

assay is robust and reliable. The standard curves for this real-time PCR assay

were accurate since the relative standard deviation on the average of R 2, efficiency and slope for 3 replicate experiments were below 5% ( Table 3.3 ).

Table 3.3 . Accuracy of standard curves for the real-time PCR assay for tet (O) quantification.

Standard curve R 2 Slope Efficiency 1 1 -3.35 1.99 2 1 -3.38 1.98 3 0.99 -3.62 1.89

Average 0.99 -3.45 1.95 Standard deviation 0.01 0.14 0.05 Relative standard deviation (%) 0.55 4.19 2.71

3.4.4 Real-Time PCR for tet (O) For most pigs, the abundance of tet (O) increased from suckling to weanling, decreased from weanling to growing, and increased again from growing to finishing ( Figure 3.3 ). Exceptions were observed for females 3 and 10, for which tet (O) levels were higher at suckling than at weanling. Generally, the abundance of tet (O) remained at high levels throughout the lifetime of pigs, despite the absence of antibiotic additions to swine feed. Figure 3.4 illustrates that at suckling, tet (O) abundance was 18.2 times higher in females than in males, but was similar between the two genders at weanling, growing and finishing. Ten-fold and 16-fold decreases in tet (O) abundance were observed at growing in males and females, respectively. At the finishing stage, i.e. prior to the transportation of animals to the slaughterhouse, 5x10 5 and 6x10 5 copies of tet (O)/ $g of total DNA were detected in the feces of males and females, respectively. Abundance of tet (O) was significantly different (p<0.05) between genders. In addition to the influence of genders, there was a definite age effect on the tet (O) abundance (p<0.05).

Figure 3.3 Abundance of tet (O) among bacterial populations in individual pigs

during suckling, weanling, growing and finishing.

Figure 3.4 Average abundance of tet (O) among bacterial populations in 6 males

and 4 females during suckling (S), weanling (W), growing (G) and

finishing (F).

3.5 Discussion

3.5.1 Bacterial Enumerations Our starting hypothesis was that enteric commensal bacteria, especially anaerobes, constitute a diversified and highly abundant reservoir of antibiotic resistance genes in the swine intestine. Despite the discontinuation of subtherapeutic applications of antibiotics at the Swine Complex 2.5 years prior to the beginning of the study, and even in the absence of therapeutic applications during this study, high abundances of Tet R and Tyl R anaerobic bacterial populations were observed in swine feces throughout the rearing period (Figure 3.1). This is of environmental and public/animal health significance since antibiotic-resistant bacteria can be transmitted among pigs reared in intensive production systems, as well as to farm employees (Akwar et al. 2007) and facilities (Sapkota et al. 2006). Also, the spreading of swine manure to fertilize agricultural fields can introduce resistant bacteria, whether commensal or pathogenic, into: farmlands (Agersø and Sandvang, 2005; Agersø et al. 2004; Sengeløv et al. 2003) and crops (US FDA, 1998) produced for animal feed or human consumption; field equipment, buildings and workers (Langvad et al. 2006); as well as surface (Rosser and Young, 1999) and subsurface (Chee- Sanford et al. 2001) (Mackie et al. 2006) water resources used for drinking, irrigation, aquaculture or recreation. At finishing, i.e. prior to the transportation of animals to the slaughterhouse, resistant populations varied between 3.13x10 6 Tyl R CFU g -1 (Figure 3.1C, male 2) and 2.46x10 9 Tet R CFU g -1 (Figure 3.1B, female 10). Such high resistant populations represent another source of concern for public health and food safety. Opportunities for the dissemination of antibiotic-resistant bacteria among animals and to trucks and trailers during transportation to slaughterhouse are provided through confinement of pigs, increased fecal shedding due to stress, and co-mingling of animals from different farms at slaughterhouse (Institute of Food Technologists, 2000). At slaughter and during meat processing, hides and coats contaminated with intestinal contents contact

carcasses (Leener et al. 2005), resulting in the introduction of antibiotic-resistant bacteria, whether commensals or pathogens, onto pork meat and into food processing facilities (Molbak et al. 1999; Schouten et al. 1997). This suggests that swine production and pork meat processing are one of the several factors contributing to the dynamic evolution of antibiotic resistance in agricultural (Isaacson and Torrence, 2002), environmental (Séveno et al. 2002) and industrial (Institute of Food Technologists, 2006) ecosystems, making antibiotics less effective to treat animal and human infections. Antibiotic resistance is considered as an emerging global health issue that, if not addressed, may evolve into one of the most significant public health challenges worldwide (Witte, 1998). Our findings support previous observations regarding a higher abundance of Tet R anaerobic populations than Tyl R in a swine farm effluent (Chénier and Juteau, 2009). Accordingly, it was reported that 71% of Enterococcus faecalis isolates from a farrowing house effluent were resistant to tetracycline (Haack BJ and RE. 2000), whereas 4%–32% of bacteria isolated from swine feces and manure storage pits were resistant to tylosin (Cotta MA et al. 2003). However, in a recent investigation of the impact of land application of swine manure on antibiotic resistance levels in soils, spreading of manure from farms with tetracycline use did not result in increased levels of Tet R and Tyl R in the soil microbial communities in comparison to soils fertilized with swine manure from organic farms (i.e. without antibiotic applications) (Zhou et al. 2010).

3.5.2 Gender Effect To our knowledge, there is the first report describing the effect of gender on the temporal evolution of the abundance of antibiotic-resistant bacterial populations in pigs. At weanling, an increase in the abundance of Tet R and Tyl R populations was observed in males (Figure 3.2C), whereas a decrease was observed in females (Figure 3.2D). Reasons for such opposite trends remain unclear. The abundance (Wise and Siragusa, 2007) and composition (Minelli et al. 1993; Vaahtovuo et al. 2001) of intestinal bacterial populations is influenced by a combination of factors including host physiology, host-microbe interactions,

interactions among microorganisms, environmental factors, and antenatal environment (Rettedal et al. 2009). A common and significant environmental factor disturbing the normal intestinal microflora is the administration of antimicrobial agents (Nord et al. 2006). Since, as mentioned previously, subtherapeutic applications of antibiotics have been discontinued prior to this study, and even in the absence of therapeutic applications during this study, other factor(s) might explain the differences observed at weanling between males and females. Weanling is a particularly crucial stage for piglets because they encounter different stresses, including separation from the sow, end of lactational immunity, a new environment and a major change in diet, i.e. from sow’s milk to pelleted feeds based on cereals, legumes or other sources of proteins (Straw et al. 1991; Su et al. 2008). However, this does not explain the differential evolution of the abundance of resistant populations between males and females at weanling. At suckling, growing and finishing, the abundance of total and resistant populations between males (Figure 3.2A) and females (Figure 3.2B) were similar. At the Swine Complex of McGill, pigs are reared for 21 weeks (4.5 months) before transportation to the slaughterhouse, i.e. before females can reach puberty. In female swine, the age at puberty varies between 4.5 and 6 months depending on breed, indoor versus outdoor production, nutrition, and boar exposure (Holden and Ensminger, 2006). Thus, hormonal cycles in females, which could have an impact on the abundance and composition of microbial populations hosted by these animals, were not initiated during this study. The fact that males and females were reared under identical environmental conditions in the same room, and that the pigs monitored in the present study were born from the same sow, are other explanations for the similarities observed between males and females at suckling, growing and finishing. Overall, our results show that stresses at weanling (as described above) have more impact than gender on the evolution of the abundance of enteric bacterial populations. Accordingly, in an investigation of the enteric microflora in healthy women of various ages, differences were observed between premenopausal and postmenopausal women (Minelli et al. 1993). The authors suggested that modifications of the steroid sex hormone

pattern may be the cause for the observed differences. Further work on the temporal evolution of enteric bacterial populations in the breeding sows and boars of the Swine Complex would shed light on gender-based differences. Statistically significant differences between males and females were not observed in the Tot, Tet R and Tyl R anaerobic bacterial populations in samples collected at different stages (p> 0.05, ANOVA) implying that gender does not affect enteric populations in pre-pubert pigs. A previous study done with mice showed that the composition of the enteric bacterial flora changes with age but remains unaffected by gender, although the impact of weanling has not been specifically addressed (Vaahtovuo et al. 2001; Vaahtovuo et al. 2001). This is in agreement with our quantitative results at suckling, growing and finishing, but not with those for weanling (Figures 3.2A and 3.2B). In contrast, the composition of the fecal microbiota of rats clustered according to gender, and temporal variations were less significant than variations between individuals (Bernbom et al. 2006).

3.5.3 Antibiotic Resistance Genes The experimental approach of this study is based on the hypothesis that enteric anaerobic bacterial populations constitute a diversified and highly abundant reservoir of antibiotic resistance genes in the swine intestine. Despite the absence of antibiotic use prior to and during this study, 3 out of 14 selected resistance genes [ tet (O), tet (L) and erm (B)] were detected in swine feces at suckling and weanling, although only tet (O) was detected at growing and finishing (Table 3.3). In a survey done by Jindal et al ., several tetracycline resistance determinants, including tet (O), were present in the swine waste of 4 conventional farms and 1 organic farm (Jindal et al. 2006). Although tylosin was not used sub-therapeutically in the present study, erm (B) was detected at suckling and weanling (Table 3.3). This gene is one of the most frequently macrolide- resistance genes detected in bacteria of animal and human origin (Roberts et al. 1999; Jackson et al. 2004). The occurrence of antibiotic resistance genes in the absence of usage of a specific antibiotic can result from the co-localization of resistance determinants on genetic vectors, such as the linkage of genes conferring

resistance to macrolides, streptogramins, and glycopeptides (Jensen et al. 2000; Jackson et al. 2004). Since no antibiotics have been used subtherapeutically and medicinally in this study, there are two plausible explanations regarding the detection of resistance genes in swine feces. First, it may be that more time would be required for the diversity of resistance genes to decrease. We monitored the short-term temporal evolution (~ 20 weeks, i.e. within the lifetime of pigs at the farm) of antibiotic resistance shortly after (2.5 years) the discontinuation of subtherapeutic applications. Only few investigations reported a lower occurrence of antibiotic resistance in swine farms without antibiotic applications in comparison to farms where antibiotics are used (Jackson et al. 2004). Further work is required to investigate the medium-term (i.e. for successive herds of pigs) and long-term (over several years) temporal evolution of the diversity and abundance of resistance genes in swine production. Second, it may be that some selective pressure maintains antibiotic resistance genes among these enteric bacterial populations. One possible selective pressure originates from metals included in the feeds given to pigs, which contain 125 mg of copper per kg and between 80 and 200 mg of zinc per kg, depending on pig age (Agribrands Purina information documents). Since it is known that antibiotic and metal resistance genes can be co-located on mobile genetic elements (Summers, 2006), the metal concentrations mentioned above are likely sufficient to exert a selective pressure for maintaining both antibiotic and metal resistance genes in swine husbandry despite the absence of any antibiotic application (Gul-Seker and Mater, 2009; Nakipoglu et al. 2009). Until now, at least 42 genes are known to confer resistance to tetracyclines, and at least 67 genes were reported to confer resistance to macrolides ( http://faculty.washington.edu/marilynr/ ). These genes are widely distributed among Gram-positive and Gram-negative bacteria, pathogenic and commensal bacteria, aerobes and anaerobes, and are found in several natural and agricultural ecosystems (Roberts, 2005; Roberts, 2008). It is likely that tetracycline- and macrolide-resistance genes other than those sought by PCR are

present in the microflora of pigs at the Swine Complex, which may explain the high abundance of resistant populations (Figures 3.1 and 3.2).

3.5.4 Abundance of tet (O) Despite the absence of antibiotic additions to swine feed, the abundance of tet (O) remained at high levels throughout the lifetime of pigs (Fig. 3). Tet (O), which confers resistance against tetracyclines through ribosomal protection (Sougakoff et al. 1987), was first identified on plasmids of Campylobacter spp. (Sougakoff et al. 1987; Taylor et al. 1987), and was later found in ruminal bacteria (Barbosa et al. 1999). It is now distributed in at least 10 Gram-negative genera, including 3 anaerobic, and 12 Gram-positive genera, including 5 anaerobic ( http://faculty.washington.edu/marilynr/ ). This gene, as well as other resistance determinants, are likely present in other species in agricultural ecosystems like swine production, for which much remains to be elucidated in terms of bacterial biodiversity (Leser et al. 2002). A theoretically wide species distribution of tet (O) in the pigs monitored in the present study is another potential explanation for the high abundance of TetR populations (Fig. 1) and tet (O) (Figure 3.3). Mobile genetic elements, such as plasmids, transposons and integrons, contribute to the horizontal transfer of resistance genes among related or unrelated species through transformation, bacteriophage-mediated transduction, and cell-to- cell conjugation (Furuya and Lowy, 2005). Since tet (O) can be located on plasmids, it is subject to be horizontally transferred among bacterial species in various environments and hosts, including swine farms (Aminov et al. 2001; Chee-Sanford et al. 2001; Yu et al. 2005). Interestingly, neither tet (O) nor any of the other 13 resistance genes monitored by PCR were detected in feces of the two employees working at the Swine Complex (data not shown), suggesting a ‘species barrier’ between hosts of Tet R bacteria. Some variations were observed in the abundance of tet (O) between pigs and over time. For example, at suckling, the abundance of this gene ranged from 2.17x10 3 copies/ $g total DNA (male 4) up to 6.00x10 5 copies/ $g total DNA

(female 8) (Figure 3.3). Statistically significant differences between males and females were also observed in the abundance of tet (O) in samples collected at all stages (p<0.05, ANOVA). Such discrepancies could be the result of differences in microenvironmental conditions such as pH, temperature, and mucin composition or concentration, which would supply a variety of niches and affect the types of antibiotic-bearing bacteria that can successfully compete for nutrients and space in the intestine (Lumpkins et al. 2008).

3.6 Conclusions The high abundance and proportion of antibiotic-resistant anaerobic bacterial populations, as well as the occurrence of resistance genes within these populations despite the discontinuation of antibiotic addition to feeds imply either that more time would be required for antibiotic resistance to decrease to lower levels, and/or that factors such as the presence of metals in feed impose a selective pressure that maintains antibiotic resistance genes among these bacterial populations. Some differences between males and females regarding the abundance of resistant populations at weanling and of tet (O) at suckling suggest that animal physiology may have an influence on the temporal evolution of antibiotic resistance in swine production. Further work is required to investigate the impact of time, age, gender, antibiotics and metals on the evolution of antibiotic resistance in swine production.

3.7 Acknowledgments This research was supported by the National Sciences and Engineering Research Council of Canada (NSERC) and the Fonds Québécois de Recherche sur la Nature and les Technologies (FQRNT) to M.R.C. S.P. benefited from the Alexander Graham Bell Canada Graduate Scholarship M (NSERC), the Principal’s Graduate Fellowship (McGill) and the Macdonald Class of '44 Rowles Graduate Bursary (McGill). We acknowledge Dr. Huilan Chen for generously sharing her expertise about real-time PCR. We thank Dr. Josée Harel (Faculty of

Veterinary Medicine, Université de Montréal), Dr. Luke Masson (Biotechnology Research Institute, National Research Council Canada, Montreal) and Dr. Marilyn C. Roberts (University of Washington, USA) for providing positive control strains for PCR.

CHAPTER 4. GENERAL CONCLUSIONS

Food safety researchers assess that foodborne pathogens cause billions of dollars of expenses annually to society (Wells and Bennik, 2003). In 2002, the U.S. Centers for Disease Control and Prevention (CDC) estimated that more than 45,000 deaths a year in the United States could be attributed to infections caused by bacteria resistant to at least one commonly used antibiotic for human therapy (Taubes 2008). It is generally acknowledged that the three main sources contributing to the increase in antibiotic resistance are the use of antibiotics in agriculture ,Furuya and Franklin, 2006), over-prescription of drugs by physicians, and misuse by patients (Institute of food technologists, 2000). In a model design concerning food safety in pork production and consumption, the farm level is the first stage of this model (McNamara et al. 2007). The goal of this research study was to determine the level of resistance at the Swine Complex of McGill University in the post-antibiotic era, i.e. 2.5 years after the discontinuation of antibiotic applications for nutritional purposes in this facility. This level of resistance will also serve as a baseline on which all further studies in our laboratory will be compared. For these reasons, culture-independent molecular techniques were employed to broaden and deepen the understanding of the abundance of bacteria and their resistance genes in a complex ecosystem. Instead of focusing on specific bacterial species, we have used another approach to detect over-all changes in the swine intestinal flora. A better understanding of the microbial ecology of antibiotic resistance, using molecular level investigations, can lead to significant improvements in the prevention and control of antibiotic resistance in swine production, thus contributing to food safety in the pre-harvest environment.

4.1 Antibiotic Resistance in Swine Production Antibiotics have been utilized broadly in the past 70 years to cure and prevent bacterial infections in humans and animals (Botsoglou, 2001). Additionally, in the last 50 years, antimicrobials have been applied in food animals (especially cattle, swine, and poultry) to treat, prevent, or control infectious illness, or to enhance efficiency of feed utilization and weight gain. During animal production, antibiotics are commonly applied sub-therapeutically for growth promotion and therapeutically at higher concentration to treat various infections and to stimulate appetite during periods of stress (Furuya and Lowy, 2005; Jindal et al. 2006). These agricultural uses of antibiotics could result in the selection of resistant genes and contribute to increased antibiotic resistance in human pathogens through several routes (Jindal et al. 2006), including human consumption of antimicrobial residues in animal products (Guan and Holley, 2003), human health hazard from antimicrobial-resistant microorganisms during animal care (Heuer et al. 2006), and contamination of farmlands and surface waters, ground waters, soils, and crops by wastes containing antimicrobials and resistant microorganisms(US FDA, 1998; Rosser and Young, 1999; Chee-Sanford et al. 2001). The subsequent emergence of infections in humans caused by resistant bacteria that originate from the animal reservoir is of great concern (Heuer et al. 2006). Although, it is not easy to demonstrate a straight link between agricultural applications of antibiotics and increased levels of resistance in pathogenic and commensal microorganisms, the potential consequences are so serious that the World Health Organization has recommended that antibiotics that are currently utilized or are under development for human therapy be eliminated as animal growth promoters (Jindal et al. 2006).

4.2 Experimental Approach Culture-dependent microbiology methods are limited to the study of microorganisms which are active and can be grown under laboratory conditions (Chenier and Juteau, 2009). Molecular biology techniques like PCR and real-time PCR were developed for rapid enumeration and identification of bacteria (Fu et al. 2006). Thus, a reasonable combination of molecular methods and culture- dependent methods would offer better chances to improve our knowledge of the microbial ecology of complex ecosystems. Several authors emphasized the value of applying complementary methods in the study of the abundance, diversity and activity of microorganisms in complex ecosystems as a means to overcome the limitations inherent to specific techniques, whether they be microbiological or molecular (Amann et al. 1995; Whyte et al. 2002; Barranguet et al. 2004). In order to characterize the microbial and molecular ecology of antibiotic resistance in the swine intestine, the integrated experimental approach of this research program is based on the application of complementary molecular biology and classical microbiology techniques.

4.3 Methodology

4.3.1 Culture-Dependent Methods Culture-dependant microbiological methods are used for over a century and are still needed to describe the abundance, diversity and activity of microorganisms in complex ecosystems such as animal wastes. However, these investigations are limited to the study of microorganisms, which are active and can be grown under laboratory conditions (Amann et al. 1995). Indeed, it is estimated that, in various habitats, less than 1% of bacteria are culturable (Ferguson et al. 1984). In chapter 3, BHIA and TSA, which are both rich media for general purpose in bacteriology (Gerhardt et al. 1994), were tested to determine which solid medium allows the highest quantitative microbial growth in the swine feces. In chapter four, for anaerobic analyses, total bacterial

populations were enumerated using the appropriate medium (BHIA), chlortetracycline-resistant bacterial populations were enumerated using BHIA supplemented with 20 mg l -1 chlortetracycline HCl (Sigma-Aldrich, St-Louis, MO), and tylosin-resistant bacterial populations were enumerated using BHIA supplemented with 10 mg l -1 tylosin tartrate (Sigma-Aldrich). Chlortetracycline and tylosin were added at concentrations 25% higher than MIC breakpoints for tetracycline-resistant ( 116 mg l -1 ) and macrolide-resistant ( 18 mg l -1 ) bacteria isolated from animals (Farzan et al. 2008).

4.3.2 Molecular Biology Techniques Over the last twenty years or so, culture-independent techniques have been developed and applied to the study of microbial ecology. Molecular techniques are employed to describe the abundance, diversity and activity of microorganisms in complex ecosystems (Amann et al. 1995), including those involved in antibiotic resistance (Yu et al. 2005).

4.3.2.1 Polymerase chain reaction

PCR is a relatively simple and sensitive technique for amplification of specific DNA template to produce specific DNA fragments in vitro. Different factors such as batch-related variability of primers and Taq polymerase, mismanipulation of the thermal cycler can cuase the amplification reaction to fail. Moreover, some specific reagents like, EDTA, sodium dodecyl sulfate and chaotropes such as guanidinium HCl prohibits the enzymes used for amplification (Monteiro et al. 1997). For the 16S rDNA amplification of fecal samples, hot-start PCR reduced nonspecific amplification. Hot-start PCR also can decrease the amount of primer-dimer synthesized by enhancing the stringency of primer annealing (Promega Corporation, 2007).

4.3.2.2. Quantitative real-time PCR Detection and quantification of a PCR product by using fluorescently labeled oligonucleotide probes or primers or fluorescent DNA-binding dyes

allows quantitative PCR to be performed in real time {Promega Corporation, 2007 #177}. Normally, quantitative PCR needs that measurements be taken before the plateau phase so that the relationship between the number of cycles and molecules is relatively linear (Bio-Rad Laboratories Inc, 2006). Chapter 4 showed some variations in the abundance of tet (O) between pigs and over time. Such discrepancies could be the result of differences in micro environmental conditions such as pH, temperature, and mucin composition or concentration, which would supply a variety of niches and affect the types of antibiotic-resistant bacteria that can successfully compete for nutrients and space in the intestine (Lumpkins et al. 2008).

4.4 Conclusions In this research study, instead of focusing on specific bacterial species, we have used a whole-population approach to detect over-all changes in the swine intestinal flora. This research study illustrates that enteric commensal bacteria, especially anaerobes, constitute a diversified and highly abundant reservoir of antibiotic resistance genes in the swine intestine. This is partially supported by the high abundance of antibiotic-resistant bacterial populations in faecal samples despite the absence of antibiotics. Although adding antibiotics to the swine feed for nutritional purposes have been discontinued since 2007, still at different stages tetracycline and tylosin resistance genes were detected. This implies either that more time would be required for antibiotic resistance to decrease to lower levels, and/or that factors such as the presence of metals in feed impose a selective pressure that maintains antibiotic resistance genes among these bacterial populations. Significant differences regarding the abundance of resistant populations and of tet (O) between males and females suggest that animal physiology may have an influence on the temporal evolution of antibiotic resistance in swine production.

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