Antibiotic Resistance in Poultry Gastrointestinal Microbiota and Targeted Mitigation
Dissertation
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
in the Graduate School of The Ohio State University
By
Yang Zhou, B.S.
Graduate Program in Food Science and Technology
The Ohio State University
2016
Dissertation Committee:
Hua Wang, Advisor
Monica Giusti
Michael Lilburn
Zhongtang Yu
Copyright by Yang Zhou 2016
Abstract
The rapid emergence and spread of antibiotic resistance (AR) is a major public health concern. The poultry industry worldwide represents the largest segment in food animal production. The prevalence and abundance of antibiotic resistant (ART) bacteria in poultry and poultry products have been a recognized food safety challenge. The large amount of ART bacteria-rich feces from industrial poultry production and its release further contaminate water and soil, impacting the environmental AR gene pool.
Therefore, revealing contributing factors to AR in poultry production and developing targeted control strategies has critical impacts on AR mitigation in the ecosystem. This study examined 1) the natural occurrence of AR in gastrointestinal (GI) tract of chicken without antibiotic exposure; 2) the impact of antibiotic administration route on AR ecology in chicken GI microbiota, and 3) the efficacy of commensal Lactobacillus crispatus CG-2 inocula in AR mitigation in poultry rearing. The results of this study contributed to an improved understanding of AR ecology in food-producing animals.
ii The first chapter is a literature review covering the origin, propagation, and dissemination of AR, as well as AR mitigation strategies. AR status in food-producing animals, particularly poultry, and recent achievements in AR mitigation were also reviewed to lay the foundation for research presented in this dissertation.
In the second chapter, the fecal microbiota of chickens from 1st to 4th week, grown in the teaching farm without any antibiotic treatment, were examined to assess the early establishment of AR gene pools and the constitution of natural microbiota in chicken GI
r r r r tract. At least 5.5 Log10 (gene copies/g) of Tet , Amp , Erm and Sul encoding gene pools were found in the chicken GI tract within the first week of life without exposure to antibiotics. The sizes of the AR gene pools varied among different sources of chickens. In the 4th week post-hatch, over 96% bacteria in layer chicken’s natural gut microbiota were
Firmicutes, and blaCMY-2 gene pool remained stable in the natural gut microbiota during
Week 4. These results suggest that the AR gene pools were established and remained stable in chicken gut microbiota without antibiotic intervention during the first 4 weeks of life.
iii In the third chapter, several culture-recovered commensal bacterial strains isolated from chicken feces were identified and examined for their potential contribution to AR ecology.
Three Ampr E. coli (E. coli CA-1, E. coli CA-4 and E. coli CA-20) strains were found resistant/insusceptible to β-lactam, erythromycin, daptomycin, vancomycin and linezolid, but susceptible to tetracycline and quinolones. A Lactobacillus crispatus strain designated
CG-12 was isolated and found susceptible to most antibiotics examined, but resistant/insusceptible to quinolone and daptomycin. The results were consistent with data by whole genome sequence analysis. The identified and characterized E. coli strains have been used in later studies as ART marker strains (Chapter 4), and the Lactobacillus crispatus was later examined for its efficacy in modulating GI microbiota (Chapter 5).
In the fourth chapter, the impact of oral resistant bacteria exposure and antibiotic administration methods on microbiota and AR gene pools in poultry GI tract was examined using leghorn chicken with natural gut microbiota. It was found that without
r antibiotic exposure, Amp gene (blaCMY-2) pool established in feces of chicks and persisted
+ in GI microbiota of chickens orally inoculated with the blaCMY-2 E. coli cocktail. Study also found that oral exposure to 300kg/mg of Amp in chickens inoculated with ART
iv bacteria led to rapid enrichment of the corresponding AR gene pool and phylum
Proteobacteria, and sharp decrease of phylum Firmicutes in feces. However, when administered via intramuscular injection, the same dosage of Amp, led to significantly less increase of Proteobacteria and decrease of Firmicutes. The Ampr marker strains were detected in certain blank control chickens in different cages in the same facility, indicating possible ART bacteria dissemination through environmental exposure. Shift of fecal microbiota and dominant bacterial population were consistent with the dynamics of the targeted AR gene pool. These results confirmed that the impact of certain antibiotics on gut microbiota can be significantly reduced by avoiding the mainstream oral antibiotic administration route in the chicken model. Our study also indicates that additional control strategies for the spread of bacteria in the environment may be also important to reduce
ART bacteria dissemination in food animal production.
In the fifth chapter, the growth inhibition activity of antibiotic-susceptible Lactobacillus crispatus strain CG-12 has been characterized both in vitro and in vivo. Results from in
+ vitro studies showed that the strain could inhibit the growth of the blaCMY-2 E. coli strains isolated from natural chicken fecal microbiota. In an in vivo study, Lactobacillus
v crispatus CG-12 was inoculated into chicken model to test its colonization resistance
+ against the blaCMY-2 E. coli strains in gut microbiota. This study found that Lactobacillus
crispatus CG-12 reduced the prevalence of blaCMY-2 gene in newly established GI microbiota. However, inoculation of Lactobacillus crispatus CG-12 had limited impact on the targeted ART E. coli strains from their colonization to proliferation. Data from this study suggested that Lactobacillus crispatus was prevalent in neonatal GI microbiota of chicken, and that antibiotic-susceptible Lactobacillus crispatus CG-12 could reduce early established AR gene pool. But its colonization resistant activity requires further evaluation against other ART populations.
Finally, future direction of AR mitigation in poultry GI microbiota was discussed.
vi Dedication
This dissertation work is dedicated to my family and many friends.
A special gratitude to my loving parents, who offered encouragement and support on every big decision I made in my life.
vii Acknowledgement
I would like to express my sincere gratitude to my advisor Dr. Hua Wang for her continuous support throughout my entire Ph. D study and related research, for her patience, inspiration and encouragement. Her guidance helped me throughout the research and her insight will continue to benefit my future work.
I also thank my committee members, Dr. Monica Giusti, Dr. Michael Lilburn and Dr.
Zhongtang Yu, for their support and encouragement throughout my Ph.D. program. Their insightful comments inspired me to broaden my knowledge from various perspectives.
My sincere thanks also go to my colleagues, Lu Zhang, Qianying Yao, Yu Li and Ying
Huang, for the stimulating discussions in the lab, for the unconditional help during experiment and for all the fun we have inside and outside the office. Also I thank the supportive staffs in OARDC Chicken Research Center for offering me help and advice for my study.
Last but not the least, I would like to thank my family, to my loving parents, aunts and uncles for supporting me throughout writing this dissertation and my life in general.
viii Vita
April 1980 ………………………… Yang Zhou
2012 ………………………………. B. S. Life Science, Fudan University
2012 – Present ………………………Graduate Research Associate,
Department of Food Science and Technology,
The Ohio State University
Publications
Lu Zhang,Ying Huang,Yang Zhou, Timothy Buckley, Hua H. Wang. 2013. Antibiotic
Administration Routes Significantly Influence the Levels of Antibiotic Resistance in Gut
Microbiota. Antimicrobial agents and Chemotherapy. 57(8):3659-3666
Zhou Y, Zhang L, Huang Y, Wang H. 2014. The Impact of Antibiotic Administration
Routes and Environmental Exposure on Antibiotic Resistance Ecology in Poultry Gut
ix Microbiota. ASM general meeting. Boston, MA (Peer-reviewed manuscript in preparation).
Zhou Y, Zhang L, Huang Y, Wang H. 2015. Antibiotic Administration Routes and
Environmental Exposure Influence Antibiotic Resistance Ecology in Poultry Gut
Microbiota. 4th Conference on Antimicrobial Resistance in Zoonotic Bacteria and
Foodborne Pathogens. Washington, D.C
Field of Study
Major Field: Food Science and Technology
x Table of Contents
Abstract ………………………………………………………………………… ii
Dedication ……………………………………………………………………… vii
Acknowledgements …………………………………………………………….. viii
Vita ……………………………………………………………………………… ix
List of Tables ……………………………………………………………………. xiv
List of Figures …………………………………………………………………… xv
Chapters
1. Literature Review………………………………………………………………. 1
1.1 The big picture……………………………………………………………….... 1
1.2 Antibiotic usage and antibiotic resistance in animal and poultry production … 5
1.3 Antibiotics and resistance …………………………………………….……… 12
1.4 Dissemination of antibiotic resistance……………………….……………….. 30
1.5 Commensal bacteria, gut microbiota and antibiotic resistance ………………. 38
1.6 Mitigation strategies for antibiotic resistance……………………….………... 43
2. Natural microbiota and Antibiotic Resistance Gene Pools in Chicken Gut……. 62
2.1 Abstract………………………………………………………………………... 62
2.2 Introduction…………………………………………………………………… 63
2.3 Materials and Methods………………………………………………………... 66
xi 2.4 Results………………………………………………………………………… 73
2.5 Discussion and conclusion……………………………………………………. 81
3. Strain identification of commensal Escherichia coli and Lactobacillus
crispatus strains………………………………………………………………… 85
3.1 Abstract………………………………………………………………………... 85
3.2 Introduction…………………………………………………………………… 86
3.3 Materials and Methods………………………………………………………... 88
3.4 Results………………………………………………………………………… 91
3.5 Discussion and conclusion……………………………………………………. 96
4. The Impact of Antibiotic Administration Routes on Development of Antibiotic
Resistance in Chicken Gut Microbiota…………………………………………… 99
4.1Abstract………………………………………………………………………... 99
4.2 Introduction…………………………………………………………………… 101
4.3 Materials and Methods………………………………………………………... 104
4.4 Results………………………………………………………………………… 114
4.5 Discussion and conclusion……………………………………………………. 137
5. The efficacy of Lactobacillus crispatus on resistance mitigation in poultry gut
microbiota……………………………………………………………………… 144
5.1 Abstract………………………………………………………………………... 144
5.2 Introduction…………………………………………………………………… 146
5.3 Materials and Methods………………………………………………………... 147
5.4 Results………………………………………………………………………… 156
5.5 Discussion and conclusion……………………………………………………. 170
xii 6. Future Direction……………………………………………………………… 173
Bibliography………………………………………………………………………. 176
xiii List of Tables
2.1 Primers and probes used in AR gene pool quantification in poultry GI
microbiota………………………………………...…………………………… 69
3.1 Primer used in strain identification …………………………………………... 90
3.2 The MIC of selected antibiotics in E. coli CA-1, E. coli CA-1, E. coli CA-1
and Lactobacillus crispatus CG-12. MIC values were expressed in µg/mL.… 94
4.1 Inocula of blaCMY-2 strains ………………………………………...………….. 106
4.2 Leghorn chicken groups subjected to marker cocktail inoculation and
antibiotic administration treatments…………………………………………... 108
5.1 List of modulated media used for growth inhibition test…………………...… 150
5.2 Leghorn chicken groups subject to inoculation and antibiotic administration
treatments ……………………………………………………………….…… 152
5.3 The growth of blaCMY-2 E. coli in modulated MRS media……………….…… 157
xiv List of Figures
2.1 Abundance of targeted AR gene pools in chicken feces at Day 5…………….. 74
2.2 Gene pool size of blaCMY-2 and 16S rRNA and the ratio of blaCMY-2 /16S rRNA from
individual chicken in Week 4.…………….…………….…………….……….… 76
2.3 The constitution of fecal microbiota of individual layer chickens in Week 4… 79
4.1 Natural shift of predominant 16S rRNA genes in total fecal DNA.……..……. 116
4.2 Real-time PCR quantification of blaCMY-2 gene pool in chicken GI microbiome upon
ampicillin exposure…………………………………………………………………… 120
4.3 Dynamic of predominant 16S rRNA genes in total fecal DNA extracts from
inoculated chicken administered with antibiotics ……………………………. 123
4.4 Composition of fecal microbiota after antibiotic treatment ………………… 127
4.5 Krona chart of the composition of fecal microbiota on Day 25 in pooled
samples ……………………………………………………………………… 129
4.6 Dynamic of predominant 16S rRNA genes in total fecal DNA extracts from
one chicken received neither inoculation nor antibiotic treatment ………….. 142
5.1 Predominant 16S rRNA genes in total fecal DNA from chicken after 3 days’
inoculation of Lactobacillus crispatus CG-12………………………………... 159
5.2 Predominant 16S rRNA genes in total fecal DNA from chicken after 4 days’
+ inoculation of blaCMY-2 E. coli following lactobacillus ……………………… 162
xv
5.3 The predominant bacterial population in chicken GI microbiota before,
during and after antibiotic administration.……………………………………. 165
5.4 The phylum distribution of GI microbiota post-antibiotic treatment…………. 169
xvi Chapter 1
Literature review
1.1 The big picture
Antibiotics are essential tools for human beings to combat bacterial infectious diseases in human and animals. However, the misuse of antibiotics worldwide contributed to the problem of antibiotic resistance (AR) seen today. For a long time, it is believed that the prophylactic and therapeutic uses of antibiotics inevitably lead to AR; therefore the primary strategy to control the problem has been to limit the applications of antibiotics in both human medicine and food animal production. However, results from innovative research in the past decade illustrated that AR is a very complicated issue, multiple risk factors contributed to the problem seen today, and a paradigm change in policy and practices for AR mitigation may become necessary. This section summarizes key concepts and advancements from literature regarding AR.
1 1.1.1 The public health impact of AR
Antibiotic resistant (ART) pathogens no longer responding to therapeutic antibiotic(s) are extremely problematic with major social and financial impacts. Patients infected by ART pathogens usually need more extensive and expensive treatments, and sometimes doctors even run out of options for therapy. According to Centers for Disease Control and
Prevention (CDC), each year in the U.S. at least 2 million people become infected with
ART pathogens and at least 23,000 people die as a direct result of these infections. The annual financial cost of AR to the U.S. economy is estimated to be as high as $20 billion in direct healthcare costs and another $35 billion in other societal cost (CDC, 2013).
1.1.2 The mainstream mitigation strategies.
In response to the AR crisis, regulations and antibiotic stewardship program (ASPs) have been developed to reduce unnecessary exposure to antibiotics (CDC, 2016; Fridkin and others, 2014; Avorn and others, 2001; Belongia and others, 2005). Several studies reported the success of ASPs in optimizing infection treatment and reducing hospital-based AR (Davey and others, 2013; Malani and others, 2013; Akpan and others,
2016). However, since new evidences suggest that the development, dissemination and
2 persistence of ART bacteria and the antibiotic resistance-encoding genes (AR genes) are very complicated with multiple risk factors, it becomes necessary to re-evaluate and update the ASPs with advanced science to properly address the AR challenge.
It has also been recognized that the food chain, particularly food-producing animals, contribute to AR development and dissemination. For decades, the government monitory systems, such as the National Antimicrobial Resistance Monitoring System for Enteric
Bacteria (NARMS) system in the U.S. by FDA, CDC and USDA, track the status of AR in several pathogens and opportunistic pathogens (Salmonella, Campylobacter,
Escherichia coli, Shigella and Vibrio) associated with foods. However, because foodborne pathogens only represent a tiny percentage of the foodborne microbiota, the data cannot reflect the real abundance and spectrum of AR in the food chain. Furthermore, once resistance emerged in pathogens, it is too late to get rid of due to various gene persistence mechanisms.
3 1.1.3 The innovative scope and approaches
Commensal microbiota of food-producing animal is a major reservoir for AR genes and key route for AR dissemination. Decades of application of antibiotics has improved the health and production of animals, but also introduced lasting changes in AR profiles in animal commensal microbiota and environmental micro-ecology (Götz and others, 1996;
Salyers and Amábile-Cuevas, 1997; Martínez, 2008; Zhang and others, 2011). Effective
AR control in commensal bacteria of food-producing animals is critical to AR mitigation in the entire ecosystem.
It is concerned that restrictions on antibiotic applications in food-producing animals is associated with deteriorations in animal health, contributing to the reduction of animal production as well as the increase in therapeutic use of antibiotic (Casewell and others,
2003). To resolve this dilemma, new perspective should be introduced to clarify the relationship between AR and agriculture practice, and novel strategies for AR control should be tested in field research.
4 1.2 Antibiotic usage and antibiotic resistance in animal and poultry production
Using antibiotics is a cost-effective way to improve the health and feed efficiency of food animals, especially in confined animal feeding operations (CAFO) (Cromwell, 2002;
Dibner and Richards, 2005; Aminov, 2010). Antibiotics are commonly used in food-producing animals to treat clinical diseases, to prevent and control potential disease events, and to enhance growth and production. Despite its benefits, decades of extensive use of antibiotic in animal farming contribute to the wide dissemination of antibiotic resistance in the microbial ecosystem.
1.2.1 History of antibiotic use in food-producing animals
The growth promoting effect of antibiotics was first reported in 1946 when streptomycin producing strain was added to the diet of chicks (Moore and others, 1946). This discovery was soon supported by a series of studies when the by-product of chlortetracycline fermentation was used as dietary supplement for livestock and poultry and significantly increased the feed-conversion efficiency (Dibner and Richards, 2005). At the same time, raising food-producing animals in large flock and herd was intensively practiced to meet the increasing protein consumption worldwide (Turner, 2000). Industrial livestock and
5 poultry production made the commercial implication of these studies quickly recognized and before long supplementing antibiotic became a common feeding practice. Another reason for the wide use of antibiotic in modern animal farming is to control endemic diseases in large population of animals. Intensive rearing enhances the development and transmission of infectious diseases, so prophylactic medication of the entire flock become necessary when just few animals show sickness. The tendency to provide prophylactic antibiotics as early as possible rather than after a fully developed disease spreads in the whole flock is also driven by producers’ anxiety to protect their large investment. Similar to human medication, antibiotics are also given to sick animals for therapeutic purpose usually with a higher dosage than that for growth-promotion and prophylactic purpose.
1.2.2 Current antibiotic use in food-producing animals
Antibiotics have been intensively given to food-producing animals for more than six decades. Nowadays the global consumption of antibiotic in livestock is conservatively estimated to be over 63,151 tons/year and is expected to increase with growing need of protein consumption (Van Boeckel and others, 2010). Although antibiotics were discovered primary to cure human infections at its discovery, the sum of antibiotics used
6 in animal farming has already exceeded human consumption. In the U.S., about 3.29 million kilograms of antibiotic were sold for human medication during year 2011 (USDA,
2012), while domestic sales and distribution of antimicrobials approved for use in food-producing animals was approximately 13.6 million kilograms (USDA, 2013). These data show that agricultural use of antibiotics accounts for over 80% of the total antibiotics usage in the U.S. And recent years still saw an increase of antibiotic consumption in food-producing animals according to recent reports (USDA, 2014; USDA, 2015a; USDA,
2015b).
The most common administrative route for antibiotics in food-producing animals is through the digestive tract. Over 90% of the total antibiotic was given to animal via feed and water, and this percentage reached 95% in 2014 (USDA, 2015b). Larger animals, such as horses, cattle, and pigs can be treated individually for many diseases, under which circumstance the antibiotic can be delivered via intramuscular/subcutaneous injection or through intramammary pathway. But for other intensive raised small animals, such as poultry and fish, therapeutic antibiotic is always extended to the entire flock or pond through feed and water, rather than spending extra work and cost to treat sick
7 animals individually. Growth-promoting and prophylactic antibiotics are targeted on an entire group of animals, so these antibiotics are usually administered through the feed or drinking water. Even the large livestock mentioned above may receive antibiotic treatment as a group through feed or water as well.
1.2.3 Antibiotic resistance in food-producing animals
Despite the obvious benefits of antibiotics to animal farming, antibiotic usage led to AR, which, demands for prudent use of antibiotics (Levy, 1978, Wegener and others, 1999).
The emergence of AR has been observed following the introduction of each new antibiotic to animal farming. Five years after the discovery of the growth-promotional effect of streptomycin, one of the first reports of AR in food animal after experimental feeding of streptomycin was published (Starr and Reynolds, 1951). The association of tetracycline resistance with feeding growth-promoting antibiotic to chickens was reported less than 10 years after the introduction of chlortetracycline (Elliott and Barnes, 1959).
Early concerns about the development of AR in human pathogen due to imprudent antibiotic use in animal farming was brought up by Swann in his report to the British
Parliament in 1969 (Wise, 2007). Indeed, later studies proved that AR can be transmitted
8 from animal to human directly and indirectly. Recent studies on environmental and manure microbiota revealed considerable quantity and diversity of antibiotic resistance genes in nature (Allen and others, 2010; Heuer and others, 2011). However, it is worth noting that none of the studies has considered the impact of antibiotic administration routes on AR ecology. Antibiotics introduce selective pressure that may lead to lasting changes in animal host and environmental microbiota. Reservoirs of AR genes have been shown to be stable in environmental and fecal microbiota, even in the absence of antibiotic exposure (Götz and others, 1996; Salyers and Amábile-Cuevas, 1997; Martínez,
2008; Zhang and others, 2011). It is estimated that as much as 25% to 75% of the antibiotics administered to food-producing animals are excreted unaltered through the hundreds of millions tons of animal waste generated in the U.S. annually (Roe and Pillai,
2003). It is not surprising that animal-derived antibiotic-resistant organisms are found contaminating soil, water, and food crops, expending the map of antibiotic resistance from the field of medication and clinical trials to the whole ecosphere, particularly to food chain and human.
9 1.2.4 Antibiotic use and antibiotic resistance in poultry
Poultry is the largest sector of food-producing animal industry in the US (US Census
2011). Meanwhile, not only was antibiotic dietary supplement first used in poultry production historically (Moore, 1946), but also the poultry industry is still one of the largest consumers of antibiotics. It is common practice in large production facility to give all broilers antibiotic to prevent diseases, such as botulism and Stapylococcus infections, and promote feed efficiency. Information obtained from the 2016 Feed Additive
Compendium (Lundee, 2016) shows that a total of 25 antimicrobial compounds are approved for use in poultry feeds in the U.S. without a veterinary prescription. Eight of these compounds listed (chlortetracycline, lincomycin, neomycin, ormetoprim, oxytetracycline, sulfadimethoxine, tylosin and virginiamycin) are medically important antibiotics that also frequently used in human medicine.
Antibiotic uses pose an impact on both poultry commensal bacteria and environmental microbiota. Studies reported that conventional (oral) administration of antimicrobial agents has significant impact on the poultry gut microbiota by changing the size and composition of the microbiota, as well as AR profiles (Fairchild and others, 2005; Diarra
10 and others, 2007; Torok and others, 2011). Multiple studies have been conducted to examine certain groups of ART bacteria and genes in poultry gut microbiota. For example, multiple-antibiotic resistant Enterococcus spp. were isolated from poultry litter in commercial poultry production environments (Hayes et al., 2005). Tetracycline resistant
Escherichia coli were detected in chicken feces and was illustrated to transfer Tetr gene to bacteria in other animal host in vivo (Hart and others, 2006). In addition, large diversity and quantity of environmental ART bacteria have been detected inside and outside of poultry facilities (Price and others, 2007; Diarrassouba and others, 2007). ART bacteria were also detected in food-animal products (Antunes and others, 2003; Hasman and others, 2005; Waters and others, 2011), indicating the potential dissemination of poultry-derived AR into human food chain. With concerns over the AR in poultry production, there is an urgent need for efficient control strategies to mitigate the emergence, development and dissemination of AR in poultry farming practice.
11 1.3 Antibiotics and resistance
1.3.1 Currently approved antibiotics in food-producing animals
According to the latest FDA Summary Report on Antimicrobials Sold or Distributed for
Use in Food-Producing Animals (FDA, 2015), 18 classes of antimicrobial drugs including 41 active ingredients approved for use in food-producing animals were actively marketed in 2014. Two third of these 18 classes are medically important antibiotics currently used in clinical practice, including aminoglycosides, amphenicols, cephalosporins, diaminopyrimidines, fluoroquinolones, lincosamides, macrolides, penicillins, polymyxins, streptogramins, sulfonamides (sulfas) and tetracyclines.
Antibiotics are commonly classified depending on their chemical structure, mechanism of action (bactericidal/bacteriostatic) or spectrum of activity (broad-spectrum/narrow spectrum). Further characterization of antibiotics can be based on their metabolic and elimination pathway (renal/biliary).
12 Tetracycline
Tetracycline is the mostly used antibiotic in food animal production for treatment, prophylaxis and growth promotion, accounting for 43% of the total antimicrobial drugs usage (FDA, 2015). It is a broad-spectrum antibiotic originally produced by Streptomyces.
Common tetracyclines, such as tetracycline, chlortetracycline and oxytetracycline, exhibit bacteriostatic activity by inhibiting bacterial protein synthesis. These tetracyclines reversibly bind to ribosomal 30S subunit, preventing the association of aminoacyl tRNA with the bacterial ribosome (Chopra and Roberts, 2001). Some atypical tetracycline derivatives like chelocardin, 6-thiatetracycline and anhydrotetracycline are bactericidal, targeting cytoplasmic membrane rather than the ribosome (Schnappinger and Hillen,
1996). Tetracycline has good oral absorption in mammal, but the absorption in bird may be incomplete (Anadon and others, 1994). However, tetracycline administration via feed and water remains the most common practice in poultry production (Goetting and others,
2011). Absorbed tetracyclines are excreted through both renal and biliary systems in bird and mammal (Frazier and others, 1995).
13 Before the wide use of tetracycline starting from mid-1950’s, most medically relevant aerobic and anaerobic bacteria, both Gram-positive and Gram-negative, were susceptible to tetracycline. Tetracycline resistance is now observed broadly in many commensal and pathogenic bacteria due to the acquisition of various Tetr genes. Most common tet genes either encode an efflux pump (e.g. tet(A), tet(B), tet(C), otr(B) or a ribosomal protection protein (e.g. tet(M), tet(O), tet(S), otrA) (Chopra and Roberts, 2001). So far there are more than 50 tet genes been discovered.
β-lactam antibiotics
As the earliest discovered antibiotics, β-lactam antibiotics are still of importance in clinics today. Recent report showed that β-lactam antibiotics ranked the second in the mostly used antibiotics with medical importance in food-producing animals (FDA, 2015), even though many bacteria have developed resistance due to decades of extensive use of
β-lactam. Members of β-lactam antibiotics can be divided into several subgroups
(penicillin, cephalosporins, carbapenems, monobactam and ect.), among which amoxicillin, ampicillin, cloxacillin, penicillin and cephalosporins were mostly marketed antibiotics in food-producing animal according to the recent report (FDA, 2015).
14 β-lactam antibiotics are bactericidal, because they inhibit the formation of cell wall and cause the cell to die rapidly. β-Lactam antibiotics irreversibly bind to DD-transpeptidase, which is also referred to as penicillin-binding protein (PBP). This binding inhibits the formation of peptidoglycan cross-links, breaks the balance between cell wall formation and degradation and finally results in the cytolysis of the bacterial cell (Waxman and
Strominger, 1983). As the most popular β-lactam antibiotics, penicillin is administered during poultry production mainly through oral route for preventative and therapeutic purposes; while both oral and injective administrations are used in mammals (Goetting and others, 2011). Previous studies suggested that penicillin is excreted primarily through hepatic pathway in birds rather than kidney excretion (Dorrestein and others, 1984;
Frazier and others, 1995), while renal excretion is the major excretion pathway for penicillin in mammal (Vaden and Riviere, 2001).
The β-lactam resistance is one of the most distributed AR, reported worldwide in food-producing animals and animal products. There are three major mechanisms of
β-lactam resistance, including 1) reduced access of antibiotics into the cell, 2) altered
PBPs with lower binding affinity to antibiotics and 3) β-lactam hydrolysis by the
15 β-lactamases (Cardenas and Palzkill, 2015). Most commonly detected antibiotic resistance genes encode β-lactamases to hydrolyze β-lactam (Poole, 2004; Cardenas and
Palzkill, 2015). For example, blaTEM and blaSHV are Class A β-lactamases responsible for
penicillin resistance; blaAmpC and blaCMY-2 are class C β-lactamases responsible for ampicillin and amoxicillin resistance (Jacoby, 2009; Bauernfeind and others, 1996); and
blaOXA represent Class D β-lactamases that hydrolyze cloxacillin and oxacillin
(Majiduddin and others, 2002).
Macrolides
Macrolide is another class of clinically important antibiotics approved in food-producing animals, including erythromycin and tylosin. Macrolides are broad-spectrum antibiotics, effective against Mycoplasma and Gram-positive organisms such as Streptococcus and
Staphylococcus (Goetting and others, 2011). Macrolides antibiotics inhibit bacterial growth by blocking protein synthesis. Macrolides bind to the 50S subunit of the bacterial ribosome in the nascent peptide exit tunnel (NPET) close to the peptidyl transferase center (PTC), therefore hindering the passage of the newly synthesized polypeptides through the tunnel and interrupting peptide elongation (Kannan and Mankin, 2011).
16 However, study showed that macrolides’ blocking of the tunnel is incomplete (Tu and others, 2005), so macrolides are bacteriostatic rather than bactericidal. Macrolide may also associate with premature dissociation of the peptidyl-tRNA from the ribosome during translation (Tenson and others, 2003). In mammals most macrolides are metabolized by the liver and excreted through feces, with a small portion excreted in urine (Giguere, 2006). Tylosin, the most widely used macrolides in poultry, is primarily excreted through feces; however considerable portion is also excreted via urine (van
Leeuwen, 1991; Lewicki and others, 2008).
Bacteria develop several macrolides-resistant mechanisms, usually resulting in a cross-resistance against lincosamides and streptogramin B compounds
(Macrolide-Lincosamide-Streptogramin B (MLSB) Resistance). Post-transcriptional methylation of the 23S rRNA is the predominant mechanism of macrolides resistance, resulting in the conformational change in the ribosome (Leclercq and Courvalin, 1991).
This species-specific ribosomal modification is mediated by erm genes, which encoding a
23S rRNA methylase. Resistances against MLS antibiotic are also caused by the presence of multidrug efflux pumps, such as ATP-binding transporters MsrA, MsrB, VgaA, VgaB
17 and etc. (Ross and others, 1990; Allignet and others, 1992). Direct inactivation of macrolides by hydrolyzing ester binds (e.g EreA and EreB) or transferring phosphorus-containing groups (e.g. MphA, MphB and MphC) has been described in several studies (Ounissi and others, 1985; Yamamoto and others, 1983; Noguchi and others, 1995; Noguchi and others, 1996; Matsuoka and others, 1998).
Sulfonamides
Sulfonamide is a group of synthetic antibiotic compounds that share the sulfonamide group and a common mode of action. Medically important sulfonamides that are approved in food animal production include sulfadimethoxine, sulfamethazine and sulfaquinoxaline (2015 FDA). Sulfonamides are broad-spectrum antibiotic against both
Gram-positive and Gram-negative bacteria, even protozoa and coccidia. Sulfonamides inhibit the growth and multiplication of bacteria by hindering the synthesis of folic acid.
Sulfonamides act as competitive inhibitors of the bacterial enzyme dihydropteroate synthase (DHPS), which catalyzes the condensation reaction to form dihydropteroic acid, a precursor of dihydrofolic acid (Sköld, 2000). The inhibition of folic acid synthesis interferes with the synthesis of DNA and some amino acid, but does not rapidly kill
18 bacteria (Petri, 2006); therefore, mechanism of sulfonamide action is bacteriostatic rather than bactericidal. Sulfonamides are mainly administrated via oral route in animals, with a quicker absorption in bird than in mammal (Botsoglou and Fletouris, 2001). Renal excretion is the primarily pathway for sulfonamides both in bird and in mammal, although some fecal excretion also occurs (Frazier and others, 1995; Botsoglou and
Fletouris, 2001).
Resistance to sulfonamides occurred rapidly after their broad application (Lewis, 2013).
Bacteria develop sulfonamides resistance by producing alternative drug-resistant variants of the DHPS enzyme with an altered binding site, which sulfonamides cannot efficiently recognize. One type of sulfonamide-resistant DHPS enzyme is the product of spontaneous mutated chromosomal dhps (folP) gene, which was found in both
Gram-positive and Gram-negative bacteria (Sköld, 2000). In Gram-negative bacteria, sulfonamides resistance genes are frequently detected on plasmids and encode alternative drug-resistant variants of the DHPS enzymes, such as sul1, sul2 and sul3 (Sköld, 2001;
Perreten and others, 2003). The plasmid-born sulfonamides resistance genes are normally linked to other resistance genes via horizontal gene transfer (Antunes and others, 2005).
19 Aminoglycosides
Aminoglycosides are antibiotics produced by Streptomyces and Micromonospora and are among the earliest antibiotics reported to have growth promotional effects in food-producing animals (Moore and others, 1946). Aminoglycosides for use in food-producing animals include gentamicin, hygromycin B, neomycin and spectinomycin
(FDA, 2015). Aminoglycosides are effective against aerobic Gram-negative strains and some Gram-positive strains; but they don’t impair the growth of anaerobic bacteria
(Dowling, 2006). Most aminoglycosides have concentration-dependent bactericidal effect, but spectinomycin is bacteriostatic due to different mechanisms of action (Vogelman and
Craig, 1986). The primary antibiotic mechanism of aminoglycosides is to inhibit bacterial protein synthesis through binding to 30S subunit of ribosomes. This binding hinders the proofreading process of newly-synthesized peptide, leading to inaccurate peptide elongation (Melancon and others, 1992). The mistranslated proteins may insert into cell membrane and further facilitate the transport of aminoglycosides (Busse and others,
1992). Aminoglycosides are not well absorbed in the GI tract due to the high polarity, so feces are likely to be the main elimination route in both mammals and birds (Brown and
Riviere, 1991; Goetting and others, 2011). Because aminoglycosides exhibit
20 nephrotoxicity during intramuscular or subcutaneous administration in mammals and birds, it is suggested that renal pathway is more likely to be the main elimination pathway
(Botsoglou and Fletouris, 2001, Frazier and others, 1995).
Resistance to aminoglycosides is becoming prevalent (Dworkin, 1999, Fluit and Schmitz,
1999). Bacteria develop aminoglycoside resistance in three general ways: 1) reduction of intracellular concentration of the antibiotic via decreasing membrane permeability and express efflux pump (Chambers and others, 1995; Hatch and Schiller, 1998); 2) modification of the drug target, such as 16S rRNA methylation and ribosomal mutation
(Maravic, 2004; Meier and others, 1994); and 3) Enzymatic modification of aminoglycosides to reduce their antibacterial activity, mainly by aminoglycoside acetyltransferases, aminoglycoside nucleotidyltransferases and aminoglycoside phosphotransferases (Levings and others, 2005; Boehr and others, 2004; McKay and
Wright, 1995). Commonly detected aminoglycoside resistance genes include several multidrug efflux pumps such as AcrA, AcrB, AdeA, AdeB, AdeC, EmrE and TolC, aminoglycoside N-acetyltransferase aac gene family and some nucleotidylyltransferase
(Ant family) and phosphotransferase (Aph family) genes (Liu and Pop, 2009).
21 Lincosamides
Lincosamides for use in food-producing animals include lincomycin and pirlimycin
(FDA, 2015). Lincosamide is always discussed together with macrolide and streptogramin B class due to their similar antibiotic spectrum and mode of action. Like macrolides, lincosamides bind to the 50S subunit of the bacterial ribosomes near the PTC, blocking the passage of newly synthesized polypeptide and interrupting protein elongation, and thus inhibiting bacterial growth. Lincosamides form stronger binding to the peptide exiting tunnel, exhibiting concentration-dependent bactericidal effect (Tu and others, 2005; Byarugaba, 2010; Giguère, 2013). Lincosamides have good absorption in the GI tract of non-herbivorous mammal, although IM and IV injection are also applied for drug administratin. In mammal, lincosamides are primarily eliminated through hepatic pathway, but a considerable portion is excreted through urine in active form (Giguère,
2013). There is limited pharmacokinetic information on lincosamides in poultry.
Lincosamides resistance mechanisms also include target modification, active efflux pump and enzymatic drug inactivation. The erm gene family is the most common lincosamide resistant gene, which is also responsible for resistance to macrolides and streptogramin B.
22 Genes encoding Macrolide-Lincosamide-Streptogramin B efflux pump from the ABC transporter system are always involved in lincosamides resistance, such as msrACD, oleABC, srmB, tlrC and isaAB, (Roberts, 2008). Enzymes that specifically inactivate
Lincosamides have been reported in several bacterial genera. Lincosamide nucleotidyltransferases encoded by the lnu gene inactivate lincosamides by phosphorylating and adding nucleotide to the hydroxyl group of the antibiotic molecule
(Bozdogan and others,1999). Lincosamide resistance genes can be acquired through horizontal gene transfer mediated by plasmids and transposons.
1.3.2 Mechanisms of antibiotic resistance
Development of antibiotic resistance is essentially a Darwinian process of selection.
Resistance genes emerge from random mutation and exist in the environment long before the first discovery of antibiotics (D’Costa and others, 2011). Gene mutation is the major contributor to the emergence of AR genes. Antimicrobial producing strains are another potential source of antibiotic resistant genes, since they are exposed to the inhibitory compounds and thus have natural protective mechanisms to mediate self-immunity.
23 Bacteria develop or acquire resistance mechanisms to counteract the killing/inhibition activity of antibiotics. So far several mechanisms are known to lead to antibiotic resistance, including: 1) reduction of the intracellular concentration of antibiotic; 2) change/modification of the drug target; and 3) direct modification of antibiotic. Multiple mechanisms are often adopted by bacteria to develop resistance to single or multiple antibiotics.
1.3.2.1 Reduction of the intracellular concentration of antibiotic
Reduction of the intracellular antibiotics decreases the chance for drug to reach its target or threshold concentration. Decreas in cell membrane permeability and increase in efflux pumps are common mechanisms, which are always adopted by the resistant strains simultaneously.
Permeability reduction
Gram-negative bacteria are intrinsically less susceptible to many antibiotics than
Gram-positive bacteria due to their outer membrane. Large-molecule hydrophilic antibiotics, such as aminoglycoside and glycopeptide, are usually too large to pass the 24 outer membrane, so they have limited activity against Gram-negative bacteria. Small hydrophilic molecules like β-lactams diffuse through the non-specific porin protein to pass the outer membrane. Therefore, decreasing porins or replacing non-specific porin with selective channel can effectively reduce the permeability of the outer membrane
(Tamber and Hancock, 2003). Selective pressure from antibiotics favors the emergence of mutated porin genes and their regulatory genes, resulting in the fast accumulation of mutations in resistant strains (Lavigne and others, 2013; Tangden and others, 2013).
Increase in efflux
Bacteria efflux pumps are major contributors to resistance against many types of antibiotics. They export antibiotics via active transportation and reduce the intracellular drug concentration. Some efflux pump systems have narrow drug-specificity (such as Tet efflux family), whereas others may accommodate and transport multiple antibiotics and lead to the occurrence of multidrug resistance. Bacterial efflux pumps have five major families: major facilitator superfamily (MFS), ATP-binding cassette superfamily (ABC), small multidrug resistance family (SMR), resistance-nodulation-cell division superfamily
(RND) and multi antimicrobial extrusion protein family (MATE). Although efflux pumps
25 are commonly found in almost all bacteria due to its critical function in xenobiotic metabolism, their overexpression contributes to high level of antibiotic resistance.
Transcription of the efflux pump encoding gene is controlled by local regulators and global regulators. Mutation in the regulatory system and intergenic region that control gene expression often results in the overexpression of efflux pumps (Kaatz and others,
2005; Olliver and others, 2004; Webber and others, 2005). Overexpression of efflux pumps also occurs when small molecules binds to the gene repressors and inhibits the binding of repressor to the efflux DNA (Baucheron and others, 2014). Efflux pump system is also transmissible between strains via plasmids (Dolejska and others, 2013).
1.3.2.2 Change and modifications of the drug target
Most antibiotics bind to their molecular targets, usually the enzymatic centers, and inhibit or perturb the normal activity of the target. Structure change of the target can prevent efficient binding of antibiotics and maintain the normal function of the target, conferring resistance to the bacteria.
26 The targets of antibiotics, such as 23S rRNA, may be encoded by multiple gene copies in the same strain; if one of these copies has a point mutation that confers resistance, the mutated gene and strain will have better proliferation under antibiotic selective pressure
(Gao and others, 2010). The acquisition of exogenous DNA also contributes to the target change and resistance development (Unemo and others, 2012). Mosaic genes due to DNA recombination may lead to the expression of mosaic molecules with critical conformation change, which the antibiotic can no longer recognize. Bacteria can also obtain a drug-insensitive target from directly acquisition of gene homologous from other resistant strains, via horizontal gene transformation and recombination (Shore and others, 2011).
Change of the antibiotic target can take place without gene mutation and recombination.
There are several post-transcription strategies to protect the target from being recognized by the antibiotics. Point methylation on the target is a common strategy of target protection, which is often seen in MLS resistance and aminoglycoside resistance
(Gryczan and others, 1980; Fritsche and others, 2008). Some quinolone resistant bacteria have resistance gene that encodes a protective protein, namely pentapeptide repeat proteins (PRPs). The PRPs rescue the targeted topoisomerase from the binding of quinolones by promoting the release of the drug molecule (Vetting and others, 2011).
27 Recent researches also find that change in the charge of target reduces the antibiotic binding and confer resistance (Beceiro and others, 2011).
1.3.2.3 Direct modification of antibiotic.
Degradation and modification of antibiotics is another mechanism of resistance.
Βeta-lactamase represents antibiotic hydrolase that confer β-lactam resistance in a wide variety of bacteria. Βeta-lactamases have wide diversities and can be classified into four subgroups based on their nucleotide, amino acid sequences and function (Ehmann and others, 2012). Another concerning issue is the emergence of novel β-lactam with expended spectrum against latest generation of β-lactams. Early β-lactamase such TEM-1,
TEM-2, and SHV-1 only confer resistance to penicillins but not to expanded-spectrum
β-lactam like cephalosporins. Now extended-spectrum β-lactamases (ESBLs) that are responsible for resistance to last-resort β-lactam such as carbapenem have been isolated from several bacterial genera, indication the existence of “super” strains that are resistant to all β-lactam antibiotics (Voulgari and others, 2013; Lynch and others, 2013). Other antibiotic hydrolases include macrolide esterases and epoxidases (Barthelemy and others,
1984; Fillgrove and others, 2003). Enzymatic oxidation, reduction and lysis are
28 uncommon in antibiotic destruction in bacteria, whereas researches have confirmed the existence of these strategies in multiple isolates, indication the diverse of antibiotic resistance related enzymes (Wright, 2005).
Another enzymatic resistant mechanism is the addition/transfer of chemical groups to antibiotic. Group transferases alter the antibiotic structure by adding chemical groups covalently, which impairs the affinity of antibiotic molecule to its original target and leads to a reduction of antibiotic activity. A variety of chemical groups can be transferred, including acyl, phosphate, nucleotidyl and ribitoyl groups. Acyltransferases are commonly found in resistant bacteria insensitive to aminoglysides, chloramphenicols, and streptogramins (Dyda and others, 2000; Wright, 2005; Schwarz and others, 2004).
Phosphotransferases/kinases modify antibiotics by transferring phosphate from a nucleoside trinucleotide, typically ATP, to the antibiotic molecule, which confers resistance against aminoglycoside and some macrolides (McKay and Wright, 1995;
O’Hara and others, 1989). Aminoglycoside antibiotics are also inactivated by nucleotidyl- transferases (Cameron and others, 1986), and similar inactivation has been reported in
29 lincomycin resistance (Bozdogan and others, 1999). Other groups of transferases include thioltransferases, ADP-ribosyltransferases and glycosyltransferases (Wright, 2005).
1.4 Dissemination of antibiotic resistance
Resistance to antimicrobials can be caused by genetic changes. AR encoded genes may be transmitted to progenies via vertical transmission and to other bacteria by horizontal gene transfer (HGT) mechanisms.
1.4.1 Vertical transmission of AR
Intrinsic and acquired AR genes can be passed from parental strains to progenies by vertical gene transmission. Errors in DNA synthesis, low-fidelity DNA reparation and error-prone replication bypass all contribute to the natural emergence of AR genes
(Davies, 2008; Norton and others, 2013). Because mutation frequency is only 10-6 -10-10 per bacterial generation (Davies, 1994), without selective pressure spontaneous AR genes may be lost due to subsequent mutation or genetic drift. However, it is noteworthy that even without antibiotic selective pressures, a single site mutation is able to confer high resistance together with niche fitness. Luo and his colleagues reported a 30 fluoroquinolone-resistant Campylobacter jejuni strain with resistance-conferring point mutation in gyrA gene that exhibited fitness advantage in poultry gut (Luo and others,
2005). With exposure to antibiotics, bacterial population with AR-conferring mutations is selectively preserved and the AR genes propagate through generations.
1.4.2 Horizontal transmission of AR
Resistance to antibiotics can be innate (intrinsic) and acquired. While gene mutation produces new AR genes, the majority of ART bacteria develop AR as a result of horizontal gene transfer. Gene exchanges between microbes greatly expand resistance profile, leading to the rapid and wide spread of AR genes and the occurrence of multi-drug resistant strains. Three classic bacterial HGT mechanisms are conjugation, transduction and transformation. There are several mobile elements that frequently mediate HGT between bacteria, such as plasmid, transposons and integrons. The presence of these mobile elements in the microbiome could be an indicator of HGT incidence.
31 1.4.2.1 Horizontal gene transfer mechanisms
Three classic bacterial HGT mechanisms are conjugation, transduction and transformation. Conjugation is the predominant process due to its broader host range than the other two (Smillie and others, 2010). Bacterial conjugation is the process of transferring genetic materials between bacterial cells through direct cell-to-cell contact or by pili-mediated connection. Conjugation process involves a donor cell that provide a mobile genetic element (plasmid or transposon in most case) and a recipient cell that are compatible to the acquired genetic elements. The mobile gene elements usually contain
AR determinants. Bacterial transformation entails direct uptake and incorporation of exogenous genetic elements from the environment across the cell membranes.
Spontaneous transformation happens in nature at low frequency, but this HGT process can be significantly accelerated under artificial condition, for example the heat-pulse and electroporation transformation. Bacterial cells have to be in a state of competence to receive exogenous DNA through transformation, which might happen as a general stress response (Claverys and others, 2006). Bacterial transduction recruits bacteriophage or other viral vectors to introduce exogenous DNA into a cell. Direct contact is not required during transduction. Bacteriophage and virulent vectors are generally inserted to bacterial
32 genome during infections, and their translation, transcription and replication extremely rely on the bacterial host cell. However, the packaging of viral DNA has low fidelity.
Small pieces of bacterial DNA might also be included into the new phage particles or viral vectors and some viral sequence might be left behind in the original host’s genome.
In this manner, AR genes can also spread through phages.
1.4.2.2 Mobile genetic elements
Plasmids are extrachromosomal genome that replicates autonomously. AR genes that act against major classes of antibiotics have been observed on plasmids, including β-lactams, aminoglycosides, tetracyclines, chloramphenicol, sulfonamides, macrolides and quinolones (Carattoli, 2011). In addition, plasmid may harbor other mobile genetic elements, such as insertion sequence and transposon, which further facilitate the accumulation and dissemination of AR genes. It is estimated that most acquired resistance is plasmid-mediated (Alanis, 2005). Plasmids are classified into homogenous groups based on their replicon. Several plasmid families are prevalently detected in the
ART bacteria, indicating their contribution to the dissemination and persistence of AR.
For example, IncA/C plasmid family are most frequently reported to be associate with
33 multidrug resistance in gram-negative bacteria; IncN, IncA/C, IncL/M and IncH plasmids
are common carrier of carbapenem resistance gene blaNDM; rolling-cycle replication
(RCR) plasmids are frequently observed with quinolone resistance genes (Johnson and
Lang KS, 2012; Carattoli, 2013). Plasmids conferring antibiotic resistance, particularly multi-drug resistance, are usually large in size (>50kb) and low in copy numbers. These resistant plasmids develop sophisticated mechanisms to persist and spread in bacterial hosts. Toxin-antitoxin system is a common addiction module that plasmids recruit to maintain persistence and stable inheritance. This module is usually composed of a stable toxin and an unstable antitoxin. If bacteria lose this type of plasmids, the cured cells are killed because the remaining antitoxin is degraded faster than the toxin and there is no de novo synthesis of it (Kroll and others, 2010). Broad-host plasmids may express anti-restriction protein (Ard protein family) to inhibit the host restriction endonucleases from degrading the heterogeneous plasmid DNA (Delver and others, 1991). Instead of randomly distributed to daughter cells, some plasmids, particularly large-size-low-copy plasmid, have an auto-regulated partition system to ensure stable inheritance during cell division. The partition system has three elements: centromere-like DNA site, centromere binding protein and motor protein. This system directs the movement of plasmid along
34 nucleoid DNA and attaches plasmid to specific cell location, such as the opposite cell poles (Dmowski and Jagura-Burdzy, 2013). Another mechanism for plasmid to maintain is to provide useful traits to the bacteria cells. For example, IncI1 plasmids have AR determinants together with a cluster encoding the type IV pili that contributes to the adhesion and invasion of Shiga-toxigenic E. coli (STEC) (Kim and Komano, 1997).
These peculiar pili are considered a virulence factor, and in association with resistance determinants it support of the STEC cells’ survival during invasion and persistence. The bacterial cells are likely to retain this plasmid to maintain its colonization advantage.
Plasmid may also express its own restriction enzyme to recruit more useful genes into its restriction sites. These sites are prone to transposons and integrons (Carattoli, 2013). This is an important mechanism for the development to multi-drug resistant plasmid. In general plasmid promotes the horizontal transfer and hereditary persistence of resistance determinants among bacteria.
Transposable elements (TEs or transposons) are DNA sequences that can change position within a genome. Bacterial transposons can be basically divided into two categories: 1) insertion sequence (IS) elements and their composite transposons and 2) non-composite
35 drug resistance transposons. Further classifications are based on their insertion mechanism, structure, encoded proteins, and replication strategy. All of these elements are able to move both intra and inter-molecularly, such as from plasmid to plasmid, from plasmid to chromosome and vice versa. Generally, the transposition activity does not require DNA homology between transposons and the insertion sites (Craig, 1997).
Insertion sequence is short DNA sequence (800-2000 bp) that contains a gene encoding transposase and a short terminal inverted repeat for the transposase to act on. Generally, single IS only mediates the transposition of itself, but two inverted IS elements can cooperate to move genes. Such a pair of IS elements and the intervening sequence constitute a composite transposon. Since the IS elements are universal located, the transposition is performed in a manner of homogenous recombination. AR determinants are of the most prevalent intervening genes detected on this type of transposon (Kopecko,
1980). There are a number of different transposons unrelated to the IS-based composite transposons. These transposons, such as Tn3 and Tn5 and Tn7 superfamily, are usually more complex and large, and are commonly associated with the transposition of AR determinants. Generally, these transposons encode their own recombinase in addition to transposase, and insert into more specific recombination sites such as att site (Nagy and
36 Chandler, 2004). In addition, bacteriophage Mu and its relatives can mediate gene transposition as well (Leach and Symonds, 1979).
Bacterial integron is a gene capture system that incorporates gene cassettes using site-specific recombination mechanisms. Integron has a specialized recombination system comprised with a site-specific recombination enzyme (integrase) and corresponding combination site. A gene cassette is a small mobile genetic element made up with single gene and a downstream site-specific recombination sequence. Both integration and excision are catalyzed by the integrase encoded by the integron, so gene cassette can move in or out. More than one cassette can be inserted into the same integron (Bennett,
2008). Integron and cassettes are particularly important in the emergence of multi-drug resistant bacteria. There are more than 400 AR gene cassettes reported by now (Tsafnat and others, 2011[accessed in Jul 2016]) Integrons carrying antibiotic AR gene cassettes are often associated with mobile elements, such as plasmid.
37 1.5 Commensal bacteria, gut microbiota and antibiotic resistance
Commensal bacteria are non-pathogenic bacteria habitat in food, environment and animal hosts, including microbes that present on the surfaces of gastrointestinal and respiratory tract, vagina and skin. The population of commensal bacteria is huge, for example, there are approximately 1014 microbes in human commensal microbiota while an individual only have about 1013 mammalian cells (Hu and others, 2013). Due to the extremely large population, as well as diversified growth and genetic background, lack of rationale for targeted investigation and investment, and also lack of proper methods for detection, commensal bacteria have long been a mystery with very limited knowledge. For years
AR research has been much focused on clinically relevant bacterial species, although they represent minor portion in the ecosystem, whether host or environment. The searching result in PubMed shows that peer review articles on “antibiotic resistant pathogens” (8874 results) outnumbers the “antibiotic resistant commensal bacteria” (527 results) by numbers of times.
In the past decade, the importance of commensal bacteria has been gradually recognized.
For instance, foodborne commensal bacteria were found as the key avenue transmitting
38 antibiotic resistance to the general public, independent from clinical drug exposure
(Wang et al, 2006; Duran and Marshall, 2005, Li and Wang 2009). Commensal bacteria also have key roles in antibiotic resistance ecology from development, amplification, dissemination, to persistence (Zhang and others, 2011; Zhang and others, 2013).
The GI microbiota, mostly of commensal bacteria, represent a complex ecosystem in the digestion tract, significantly impact immune system, nutrient processing and a broad range of other host activities, as well as the AR ecology (Hooper, 2001). The recent developments of high-throughput sequencing and metagenomics have shed light on comprehensive analysis of complex micro-ecology like GI commensal microbiota.
Gut microbiota as breeding ground for AR
GI commensal bacteria are important in the emergence of antibiotic resistance. GI bacteria have large quantity and diverse genetic background, so the chance to develop AR mutation is much higher than the limited number of pathogens. Once exposure to the selective pressure conferred by consumption and excretion of antibiotics in the GI tract,
AR mutation in the commensal bacteria is selectively preserved and amplified. 39 GI microbiota are reservoirs for ART bacteria, AR genes and mobile genetic elements.
Various ART bacteria and AR genes have been detected in hosts without direct exposure to antibiotics, including animal and human GI and fecal microbiota. It has been reported that the GI commensal microbiota of human and animal establish within a week after birth and the neonatal GI microbiota are significantly influenced by the environmental bacteria (Hooper, 2004; Adlerberth and Wold, 2009; Zhang and others, 2011). Without antibiotic administration, AR genes against commonly used therapeutic antibiotics, such as ampicillin, tetracycline, sulfonamide and etc., have been detected in high density in food-producing animals, agriculture related location as well as human gut (Marshall and others, 2009; Zhou and others, 2012; Hu and others, 2013; Huang and others, 2015).
In animal models, in-feed/water antibiotics increase the population of ART bacteria
(Depaola and others, 1995; Bager and others, 1997). AR genes in GI/fecal microbiota are simultaneously increased both in abundance and diversity (Looft and others, 2012;
Wegener and others, 1999). The administration of antibiotic even enriches genes that confer resistance to other antibiotics that are not used in the same trail (Looft and others,
2012). Similar increase in resistant population and resistant gene pool has been reported
40 in human gut/fecal samples after antibiotic chemotherapy. The human studies have also demonstrated an increase in multi-drug resistant bacteria after clinical exposure to antibiotics (Graham and Fischbach, 2010; Levy and others, 1988).
Furthermore, the gut microbiota has large microbial population suitable for horizontal gene transfer. Transfer of AR gene has been detected inside a genus and between
Gram-positive and Gram-negative bacteria (Shoemaker and others, 2001; Rolain, 2013).
The application of antibiotics is found to enrich the phage sequences and expend bacteria species that interacts with phage in gut. The highly connected phage–bacterial network indicates an increased efficiency of gene exchange (Modi and others, 2013). Efficient AR gene transfer further confers persistence of AR in gut microbiota in the absence of antibiotic selection.
Gut microbiota also contributes to the dissemination of AR, which is best illustrated in the agricultural use of antibiotics (Van den Bogaard and others, 2001). It is estimated that as much as 30–90% of antibiotics administrated to food-producing animals are excreted through the GI tract and ended up in manure, selectively enriching the AR profile in the
41 GI and fecal microbiota (Sarmah and others, 2006). The AR enriched manure microbiota passes into waste lagoons and spread on agriculture field as fertilizer, leading to the dissemination of ART bacteria and mobile AR elements, such as resistance-encoding plasmid, cassettes and integrons, into surface and groundwater as well as the soil
(Jongbloed and Lenis, 1998). The AR contaminated food-animal products and vegetables are likely to further introduce AR into the food chain. For example, ART commensal E. coli has been detected in raw meat, shellfish and fresh produce (Egea and others, 2012;
Van and others, 2008; Duffy and others, 2005). Considerable size of AR gene pools has been reported in ready-to-consume food, such as salad and deli (Wang and others, 2006;
Li and Wang, 2011), indicating the dissemination of AR into the general public through conventional food consumption. Once the ART bacteria and AR determinants from food enter the digestive tract, another round of enrichment and dissemination might start. The gut commensal microbiota therefore has a critical role linking the microbiota among food, hosts and the environment, and therefore AR circulation in the ecosystem.
In conclusion, the gut commensal microbes are of great significance in AR ecology, from emergence, accumulation, persistence to dissemination. Effective AR control strategies
42 should take serious consideration of the commensal bacteria, especially the gut microbiota of human and food-producing animals.
1.6 Mitigation strategies for antibiotic resistance
Mitigation of AR is a major practical goal, which should recruit efforts from various social institutes. Currently reducing the general overuse of antibiotics and thus the exposure of bacteria to high-intensity antibiotic selective pressure has been the primary strategy. Now antibiotics are prescribed drugs in many countries, clinical application is monitored and instructed by medical practitioners so that unnecessary and overdosed uses of antibiotics are minimized in clinical practices. In the field of agriculture, for fear of the potential risk of ART bacteria transmitting to human, the World Health Organization and the Economic and Social Committee of the European Union drew conclusion in late
1990s that the use of antimicrobials in food animals is a public health issue (WHO, 1997;
Economic and Social Committee of the European Union, 1998). However as early as
1986, Sweden had prohibited the use of in-feed antibiotics as growth-promoter. In 2006,
EU-wide ban on the use of antibiotic feed-additive was into effect and antibiotic growth promoters were deleted from the Community Register of authorized feed additives
43 (European Commission, 2005). In the US, the Department of Agriculture has released several guidelines to reduce the antibiotic usage in food animal production (USDA, 2011;
USDA, 2013a; USDA, 2013b). FDA also published annual review on antibiotics production, sales and distribution to better monitor the use of antibiotics. However administrative intervention is far from sufficient to control the increasing AR. Recent studies have reported that a 2-year discontinuation of trimethoprim use in Sweden had little influence on the resistant rates in Escherichia coli (Sundqvist and others, 2010). AR determinants might integrate into multi-drug resistant integrons or plasmids and maintain its persistence without antibiotic selection. In regions where antibiotic growth-promoters are prohibited, decreased animal yields and increased needs for veterinary antibiotics counteract the potential benefit of antibiotic restriction (Casewell and others, 2003).
Another classic approach to control AR dissemination is the improvement of general hygiene and infection control measures, to reduce nosocomial AR infection (Bonten and others, 2001; Bootsma and others, 2006). Hygiene improvement is obviously important to reduce the emergence of ART infections in individual patient and medical institution, but regional practice has yet limited impacts on the existing AR profile in community and ecosystem (Smith and others, 2005; Bouchers and others, 2009).
44 With increased understanding of the complexity of the AR problem and the demonstration of multiple contribution factors, new perspectives and strategies should be investigated and adopted for effective AR mitigation. Ecological and evolutionary
(eco-evo) concept was firstly introduced to explain bacterial evolution and pathogenicity on a broader perspective rather than isolates level (Wang et al, 2006; Pallen and Wren,
2007; Dethlefsen and others, 2007). The eco-evo concept also applies to the development and spread of AR as well as novel AR mitigation practices (Baquero and others, 2011).
One very successful example is the effective reduction of the largest foodborne AR gene pool through targeting the AR risk factor(s) in dairy fermentation, and removing problematic starter culture and probiotics from the market (Li and others, 2011). Simply within 3-4 years, the largest AR gene pool in food products was reduced to mostly detection limit. In addition, new intervention strategies have been proposed, and tested in research or practical trails. For example, quorum sensing inhibitors that are effective in disabling the expression of virulence and reducing antibiotic tolerance has been tested in several in vitro and in vivo trails, indicating their potential as novel broad-spectrum antimicrobials (Bjarnsholt and others, 2010; Rasko and others, 2008). Inhibition of the conjugation process is another potential strategy to prevent the dissemination of AR
45 determinants. Reported inhibition targets have covered various elements required in conjugation, such as pili, relaxase, and NTPase, to prevent HGT from cell connection, intercellular DNA relocation and gene integration (Novotny and others, 1968;
Hilleringmann and others, 2006; Lujan and others, 2007).
Using AR-free bacteria to compete with the ART population in a common niche is a promising strategy to decontaminate high-risk clones from the established ecosystem. For example, probiotic strain E. coli Nissle 1917 profoundly elevate the resistance to microbial pathogens in gut barrier of gnotobiotic pigs. The antagonistic functions of E. coli strain Nissle 1917 rely on its good colonization fitness, expression of microcin and antimicrobial peptides and immunomodulation activities, indicating that effectiveness against ART bacteria might also be achieved by probiotic intervention (Trebichavsky and others, 2010). Although current antibiotic policies and prescription practice have made limited success in AR control, it is undoubtable that they contribute to the reduction of antibiotic selective pressure. While therapeutic antibiotic is still necessary in infection treatment, changing antibiotic administrative pathway is an applicable method to reduce unnecessary AR selective pressure. Reduced AR gene pool and ART population has been
46 demonstrated in mouse model with alternative antibiotic administration pathway (Zhang and others, 2013).
1.6.1 Administration pathway
Oral administration is a convenient and labor-free method for drug delivery. But in the case of antibiotic, oral administration exposes the GI microbiota directly under selective pressure. According to FDA report, about 90% of the veterinary and agricultural uses of antibiotics are administrated through digestive tract (FDA, 2015). Antibiotic selective pressure in GI tract favors the emergence and enrichment of ART bacteria in commensal microbiota, which is an unneglectable risk factor to the increasing crisis of AR. Oral administration of antibiotic inevitably casted unnecessary selective pressure on gut microbiota. In a recent study carried out in our lab, oral administration was compared to injective antibiotic in their impacts on the AR profile in mouse feces (Zhang and others,
2013). The results demonstrated that by changing the administrative method from oral to injection, the perspective AR gene poor and ART bacteria population was considerably reduced (5 logs to almost not detectable). This reductive effect is more significant when
47 the antibiotic has renal exertion, which can entirely/partially bypass the digestive tract and reduce direct contact with GI microbiota.
1.6.2 Probiotic
Probiotics are now commonly referred to as microorganisms that provide benefit to host when consumed. Although the use of health-promoting microorganisms could date back to early history of food fermentation, it was not until late 1980s when the term ‘probiotic’ started to describe beneficial microorganisms instead of substances (Fuller, 1992). The official definition and application guideline of antibiotic were published by the Food and
Agriculture Organization of the United Nations and the WHO (FAO/WHO) in 2001 and
2002. Since then there has been a rapid increase of research interests and achievements on probiotics in terms of mode of action and development of new strains/strain combinations, thus the term ‘probiotic’ is under continuously development as well. In
2013, an expert panel convened by the International Scientific Association for Probiotics and Prebiotics (ISAPP) gave the updated definition of probiotic as “live microorganisms that, when administered in adequate amounts, confer a health benefit on the host”. This new definition comes along with a series of recommendations for the scope of probiotics,
48 regarding the most recent achievements in meta-analysis and microbiota transplant (Hill and others, 2014). The mode of actions of probiotic is closely related to digestive tract and gastro-intestinal microbiota. Because knowledge on biochemistry and physiological functions of both digestive tract and GI microbiota are still under rapid expansion, there is no fixed explanation of probiotic mechanisms or a standard definition of probiotic benefits. In fact, the history of research on probiotic is an on-going accumulation of evidence and discovery. And the scope of probiotic is likely to continuously evolve with deeper understanding of its mode of actions.
1.6.2.1 Antimicrobial Activity
The earliest hypothesis on the positive impact of consumed beneficial bacteria was proposed by the Nobel Prize winner Élie Metchnikoff. During his journey in early 1870s to the Steppes of Astrakhan and Stavropol, residence of rural population in Europe,
Metchnikoff found that the native tribespeople had exceptionally long life. As these people had the habit of drinking fermented milk, Metchnikoff attributed the longevity to consumption of the starter culture, which he called ‘Bulgarian Bacillus’ and was later named as ‘Lactobacullus delbrueckii subsp. bulgaricus’. At that time, it was known that
49 lactic-acid bacteria lower pH during lactose fermentation and inhibit the growth of some
‘toxin producing’ proteolytic bacteria. Based on these evidences, Metchnikoff proposed that ‘seeding’ the intestine with harmless acid-producing lactobacillus would reduce the intestinal pH, inhibit the growth of proteolytic bacteria and suppress the production of toxic substances that contribute to aging (Vaughan, 1965). Although Metchnikoff over-simplified the relationship between aging and intestinal bacteria largely due to limited understanding of both areas at that time, his opinion represents the early comprehensions of probiotic mechanisms: competitive colonization of intestinal tract, production of antagonistic substances against harmful microorganisms and improve GI microbiota. These mechanisms are considerably parallel to the concept of colonization resistance.
The antimicrobial activity of probiotic has been demonstrated in varies clinical trials, although how probiotic interacts with host GI microbiota still requires further clarification. As early as 1917, the German physiologist, microbiologist, and physician
Alfred Nissle isolated a strain of Escherichia coli from the feces of an officer who was not affected by any of the intestinal disorders then highly prevalent. Nissle used this E.
50 coli strain, later named E. coli Nissle 1917, as an ‘antagonistic’ strain to treat acute gastrointestinal infectious (Nissle, 1916; Nissle, 1918). The following years there were considerable number of studies demonstrating the positive effects of probiotics in disease remission, especially in the treatment of inflammatory bowel disease (IBD).
Consumption of Lactobacillus spp. has been demonstrated to control and prevent colitis in the IL-10-deficient mice, which spontaneously develops colitis similar to Crohn’s disease. Not only prophylaxis inoculation of Lactobacillus shown positive effect on the prevention of colitis (Schultz and others, 2002), post-infection consumption of this genus of probiotic was able to attenuate the recurrence of this inflammation as well (Madsen and others, 1999). The anti-colitis function of Lactobacillus was confirmed in rat model as several Lactobacillus spp. displayed beneficial effects in the prevention and attenuation of the disease onset (Mao and others, 1996; Fabia and others, 1993). The effects of probiotic on human IBD cannot be measured under well-controlled condition as easily as in animal studies, due to relatively small number of patients, small number of events and the high risk of bias in the analysis. Therefore, previous reviews for IBD were unable to make solid conclusions about the value of probiotics for IBD prevention and treatment (Gionchetti and others, 2006). A recent meta-analysis includes twenty-three
51 randomized controlled trials (RTCs) with a total of 1763 participants aiming at comparing probiotics with controls in human IBDs. The results indicate that probiotics, particularly
VSL#3 probiotic mixture, exhibit additional benefit in inducing remission of patients with active ulcerative colitis and pouches (Shen and others, 2014). Other health effects of probiotics in human are reviewed and analyzed by many well-conducted RCTs and meta-analyses as well as systemic reviews (AlFaleh and Anabrees, 2014; Hao and others,
2011; Johnston and others, 2012; Hempel and others, 2012; Hoveyda and others, 2009).
Although there is a lack of definitive mechanism of probiotic, several antimicrobial strategies have been confirmed in probiotic mediated microbiota-modification. In vitro measurement and genome analysis demonstrates that probiotic trains secret antimicrobial compounds, such as bio-acid and microcin, to inhibit pathogenic infections (Asahara and others, 2004; Grozdanov and others, 2004; Rea and others, 2007). Another antagonistic strategy of probiotic is to block bacterial adhesion to epithelial cells and inhibit bacterial invasion (Tuomola and others, 1999; Sherman and others, 2005; Collado and others, 2007;
Boudeau and others, 2003; Resta-Lenert and Barrett KE, 2003). Usually these two mechanisms work together to inhibit bacterial invasion. For example, Lactobacillus species inhibit Helicobacter pylori infection of gastric mucosa by releasing of
52 bacteriocins and decreasing its adhesion to epithelial cells (Gotteland and others, 2006).
So far, most results and conclusions of antimicrobial activity of probiotic rely largely on in vitro cell lines. The in vivo interaction between probiotic and invasive bacteria is likely much more complicated.
1.6.2.2 Enhancement of epithelial barrier function
Probiotics exhibit enhancement activity towards the intestinal barrier by influencing the mucosal cell-cell interaction and epithelial integrity. The integrity and normal function of intestinal barrier is not only important in digestion and nutrient absorption, but also critical in resistant to enteric infections and inflammations. Probiotic enhancement has been observed in epithelial cell line, excised intestinal tissue and live animal model
(Sherman and others, 2005; Madsen and others, 2001; Madsen and others, 1999). How probiotics enhance mucosal barrier integrity and function remains unclear, but the evidences indicate that it may relate to mucus secretion and expression of tight junction protein. For example, Lactobacillus plantarum 299v, probiotic mixtureVSL#3 and E. coli
Nissle strain were observed to increase the expression of MUC genes (mucin encoded gene in human) when incubated with the intestinal epithelial cell line (Mack and others,
53 1999; Otte and Podolsky, 2004). VSL#3 probiotic mixture was also reported to maintain the expression of tight junction protein (zonula occludens-1, ZO-1) and prevent harmful redistribution of these proteins induced by pathogenic bacteria (Mennigen and others,
2009; Otte and Podolsky, 2004), implying its potential function in stabilizing the cytoskeleton architecture of intestinal barrier. Other cytoskeleton structure that positively affected by probiotic include F-actin, actinin, occluding and actin (ZO-2) (Mennigen and others, 2009; Otte and Podolsky, 2004; Resta-Lenert and Barrett, 2003; Lievin-Le Moal and others, 2002; Zyrek and others, 2007).
1.6.2.3 Immunomodulation
Despite the direct antimicrobial activity and mucosal enhancement actions, probiotic is involved in stimulation and education of the immune system, particularly in mucosal immunity response. Consumption of probiotic has been reported to reduce intestinal inflammation, prevent and alleviate allergic reactions (Esposito and others, 2009; Furrie and others, 2005; Kuitunen and others, 2009; Dotterud and others, 2010). The mode of actions and molecular mechanism of probiotic immunomodulation has been intensively reviewed (Isolauri and others, 2001; Ng and others, 2009; Ashraf and Shah, 2014).
54 Although clear explanation of probiotic immunomodulation is yet to be made, possible mechanisms include promotion of non-immunologic epithelial defense barrier by modulation enteric permeability and altered GI microbiota, and promotion of immunologic defense via stimulation of intestinal immunoglobulin A (IgA) and inflammatory responses (Isolauri and others, 2001). In general probiotic impacts both intrinsic and acquired immunity, via interaction with epithelial cells, dendritic cells, monocytes/macrophage and a series of lymphocytes include B lymphocytes, T lymphocytes and natural killing (NK) cells (Ng and others, 2009). However, the immune response triggered by probiotic is strain-specific, with distinguished cytokines, immune cells and signal pathway involved (Ashraf and Shah, 2014).
1.6.2.4 Reduction of antibiotic resistance
In order to control the rapid emergence and dissemination of antibiotic resistance, international consensus has been achieved on limiting unnecessary antibiotic application, especially the antibiotic growth-promoters in food-producing animal farming. Probiotic is suggested as a potential alternative to antibiotic, with the expectation to perform
55 antimicrobial activity, improve host health and promote food-animal production without increase antibiotic resistance.
Reduction of the antibiotic use
The antimicrobial and microbiota-modulation activity of probiotic could be used as strategy to hinder the colonization of pathogenic bacteria, improve overall gut health and thus potentially reduce the applied dosage of antibiotic by improving its action (Vuotto and others, 2014). High-valued meta-analysis studies and systematic reviews have demonstrated the effectiveness of various probiotics as promising therapies for antibiotic-associated diarrhea (D'Souza and others, 2002; McFarland, 2006; Hempel and others, 2012). This therapeutic function of probiotic is likely to decrease the need for further antibiotic chemotherapy, because it reduces the risk of intestinal infections and disorders due to the diarrhea.
Probiotic has been intensively studied as an antibiotic alternative, in the perspective of improve food-animal welfare and production without introducing antibiotic selective pressure. As a matter of fact, the growth-promotion effect of antibiotic was first 56 discovered when extra weight-gain was observed in animals fed with dried mycelia of
Streptomyces aureofaciens, which contained chlortetracycline residues (Moore and others,
1946). Microbial interventions have been introduced in animal farming for several decades, and many studies observed improved production performance in food-producing animals receiving probiotic supplement (Musa and Seri, 2009). However, the growth promotion effect of probiotic is still controversial, as quite a few researchers declared insignificance between probiotic treatment and control (Pelicano and others, 2004; Nunes and others, 2012; Bryan and others, 2015). It is likely that the improvement of performance is strain-dependent and growth enhancement is not a prerequisite for probiotic treatment (Musa and Seri, 2009).
In general, the use of probiotic as adjunct or alternative of antibiotic in disease treatment and agricultural production potentially reduce the use of antibiotic, indirectly and partially release the antibiotic selective pressure that contribute to antibiotic resistance.
Developing probiotic for direct decontamination of AR has been proposed lately and tested in several recent studies (Baquero and others, 2011).
57 Reduction of antibiotic resistance
Probiotic is observed to have direct effect on reducing antibiotic resistance via increasing strain susceptibility, inhibiting resistant gene transfer and performing antagonistic activity against ART strains. Moubareck and colleagues tested and demonstrated the inhibitory activity of five probiotic bifidobacteria strains on the transfer of genes encoding extended-spectrum-lactamases between enterobacteria (Moubareck and others, 2007). In vitro transfer frequencies of the tested resistant genes were significantly decreased in the presence of Bifidobacterium longum, Bifidobacterium bifidum, and Bifidobacterium pseudocatenulatum. In vivo transfer frequency was also analyzed in the digestive tract of gnotobiotic mice, showing a significant decrease in the transconjugant levels in the presence of either Bifidobacterium bifidum or Bifidobacterium pseudocatenulatum. The results indicated that bifidobacteria inhibit transfer of antibiotic resistance genes, while this inhibitory effect might be strain-dependent. In another study, probiotic Enterococcus faecium was investigated to evaluate its influence on the virulence and antibiotic resistance of clinical enteropathogenic E. coli strains (Ditu and others, 2011). The soluble and cellular portions of probiotic (co-cultivated with either Bacillus cereus or E. coli O28) both increased susceptibility to aminoglycosides, β-lactams and quinolones, although the
58 susceptibility to amoxicillin-clavulanic acid was reduced. This research demonstrates that modulating antibiotic susceptibility might be an anti-infective mechanism of probiotic.
The general antagonistic effects of probiotics on multidrug-resistant bacteria were assessed in an in vitro study using supernatants of lactobacillus culture as probiotic
(Naderi and others, 2014). Inhibitory effect was observed in E. coli, which were resistant to 8-9 antibiotics, but no effect was detected on reducing the prevalence of plasmid carrying ampicillin resistant gene. Little antagonistic activity of the cell free supernatants was detected against the tested Enterococcus, Enterobacter and Klebsiella pneumoniae.
The exclusion of probiotic cell in this study is likely to undermine the real agnostic activity, but the results still shed light on the potential reduction of antibiotic resistance.
On the other hand, results on the colonization elimination function of probiotic against
ART bacteria are controversial. In a clinical study, the administration of probiotic
Lactobacillus F19 during antibiotic treatment didn’t affect the emergence of resistant isolates in Enterococci, Enterobacteria and Bacteroides from stool specimens (Sullivan and others, 2004). Although the result shown a limited resistance-reducing effect of
Lactobacillus F19 in certain bacterial genera, it is worth noting that the probiotic was
59 administrated simultaneously during chemotherapy and was likely to be inhibited by the antibiotics before performing any probiotic activity. Furthermore, the resistant status was evaluated in limited range of bacteria, which might be a poor representative of the whole resistome. Similar ineffectiveness of probiotic intervention was reported in another trial, when a multi-strain probiotic was administrated before the challenge of enterotoxigenic E. coli in order to decrease its colonization (Ten Bruggencate and others, 2015). Since none of the strains in the probiotic mixture is E. coli, the different origin of probiotic and target bacteria might occupy varied ecological niches and resulted in the failure of effective exclusion of resistant strains. In a human study, probiotic E. coli Nissle 1917 was administrated to exclude intrinsic quinolone-resistant E. coli, hypothesizing that probiotic strain occupying the same ecological niche would exclude the resistant one. However, no decreased persistence of the resistant strains was detected with the probiotic therapy
(Tannock and others, 2011). In conclusion, the prevention and exclusion activity of probiotic against resistant strains remains uncertain.
The role of probiotic in mitigating antibiotic resistance is not fully established. Although there are some studies achieving positive results, the current data is insufficient to draw
60 any solid conclusions. Current trend of probiotic development is to recruit novel candidates from commensal bacteria in gut microbiota, which might have better colonization fitness and individual-specific benefits (Hill and others, 2014). It is noteworthy that GI microbiota and resistome are acquired at very early stage of life, and this microbiota-establishing stage might be a promising window for effective probiotic intervention.
Novel perspective and strategies might be promising supplement to classic AR control practices, but it is noteworthy that most of them remain highly speculative, achieved in vitro or research-scale success only. Field test in animal model and even in human studies are still needed to confirm the efficacy.
61 Chapter 2
Natural microbiota and Antibiotic Resistance Gene Pools in Chicken Gut
2.1 Abstract
Poultry as the largest segment in food animal production worldwide produce large quantity of manure every year. Besides its importance in poultry growth and overall health, gut microbiota is a critical link in the occurrence and dissemination of antibiotic resistant (ART) bacteria and antibiotic resistance (AR) genes. Previous studies shown that in-feed antibiotics introduce significant changes in poultry gut microbiota by altering its size, constitution and AR profiles. To better understanding the impact of antibiotics and occurrence of AR in poultry gut microbiota, this study monitored the early establishment of AR gene pools and the constitution of microbiota in chicken gut. Chicken were raised on a study farm with controlled temperature, sanitized water and feed. Fresh feces were collected from broilers and layers at Day 5 post-hatch, and from layers at Day 21, Day 25 and Day 28 post-hatch, and then subjected to qPCR and 16S rDNA high-throughput
62 r sequencing assessment. Results shown that: 1) at least 5.5 Log10 (gene copies/g) of Tet ,
Ampr, Ermr and Sulr gene pools were established within a week after hatch; 2) vendor-hatched broilers had larger Sulr gene pool; 3) Firmicutes is predominant phylum in layer chicken’s natural gut microbiota during Week 4 (Day 21, Day 25, Day 28), accounting for over 96% of the total microbial population, while Proteobacteria only
took up less than 1%; 4) blaCMY-2 gene pool remained relatively stable in the gut microbiota during Week 4. These results suggest that AR gene pools were established in the chicken gut at early stage of growth and likely impacted by handling and transport of chicks; gut microbiota and AR gene pool stayed stable without antibiotic intervention during Week 4 post-hatch.
2.2 Introduction
Gastrointestinal (GI) microbiota plays an important role in the overall health of animal hosts, contributing to nutrient extraction, immune system and epithelium development as well as the defense against pathogens (Zoetendal and others, 2004). Meanwhile, GI microbiota may also serve as the breeding ground for ART bacteria, playing critical role in AR development and dissemination (Shoemaker and others, 2001; Sengeløv and others,
63 2003 Karami and others, 2007; Lu and others, 2011). Due to the wide spread of AR, nowadays, ART bacteria are commonly detected in the GI microbiota of food-producing animal (Van den Bogaard and others, 2001; Mathew and others, 2007). Animal manure rich in ART bacteria further impacts AR in the ecosystem through AR circulation among soil, water, food and hosts (Sengeløv and others, 2003; Wang, 2009; Heuer and others,
2011).
Poultry as the largest food animal sector in the US provides 49.2 billion pounds of broiler,
7.1 billion pounds of turkey and 91.4 billon eggs annually to the food supply (US Census
2011), as well as hundreds of millions of pounds of manure daily. Studies on poultry GI tract have made valuable observations towards illustrating the importance of GI microbiota in growth performance of hosts (Brisbin and others, 2008). Using culture-dependent and -independent approaches, diversified profiles of bacteria from chicken GI tract were identified (Mead, 1989; Lu and others, 2003). While poultry GI microbiota shifts naturally during growth (Barnes and others, 1972; Baenes, 1979; Lu and others, 2003), it is considerably impacted by diet (Apajalahti and others, 2001). In poultry production, antibiotics are normally given through the oral routes, i.e., mixed in feed or
64 water. Studies reported that antibiotic administration (either via feed or water) had significant impact on the poultry gut microbiota by changing the microbial population size and constitution, as well as AR profiles (Fairchild and others, 2005; Diarra and others, 2007; Torok and others, 2011). Multiple studies have also examined certain groups of ART bacteria and AR genes in poultry gut microbiota. For example, multiple-antibiotic resistant Enterococcus spp. was isolated from poultry litter in commercial poultry production environments (Hayes and others, 2004). Tetracycline resistant E. coli was detected in chicken feces and was proved to transfer Tetr gene to bacteria in other host in vivo (Hart and other, 2006). In addition, large diversity and quantity of environmental ART bacteria have been detected inside and outside of poultry facilities (Price and others, 2007; Diarrassouba and others, 2007). However, there has been a lack of comprehensive understanding of risk factors, including but not limited to the contributions of commensal microbiota, in the overall AR ecology in the production chain.
In this study, we examined the establishment of AR gene pools at early growth stage of chicken, in the absence of antibiotic exposure. We also monitored the constitution of GI
65 th microbiota and the blaCMY-2 gene pool within the 4 week post-hatch. The results of this study will contribute to an improved understanding of the establishment and persistence of AR gene pools, and can potentially provide valuable information to explain the impact of antibiotic applications on GI microbiota and the direction for effective mitigation.
2.3 Materials and methods
2.3.1 The chicken model.
The study was conducted using procedures approved by the Institutional Animal Care and
Use Committee (protocol No. 2012A00000061, The Ohio State University, Columbus,
OH). One batch of Broiler chicken (50 subjects) was purchased from external vendor,
Broiler and Leghorn chicken used in the 2nd trial (60 subjects) and 3rd trial (80 subjects) were hatched on-site at the Ohio Agricultural Research and Development Center
(OARDC) poultry research teaching farm. Chickens were maintained at the teaching farm in standard battery brooder pens (two birds per cage with individual feed and water supply, controlled temperature, filtered air in the room, sanitized feed and distilled water).
Fresh feces were collected on-site and subjected to microbiota and AR gene pool assessments. Chickens had no exposure to antibiotics throughout the study.
66 2.3.2 Sample collection.
Fresh feces were collected from each chicken on-site in the rearing facility. On Day 5 post-hatch, fresh fecal samples were collected on site from 5 randomly selected chickens from each of the three repeated trails at Day 4 post-hatch. On Day 21, Day 25 and D28, among 16 layer chicken (Leghorn chicken) subjects raised for AR profile assessment without antibiotic exposure, 4 chickens were randomly selected for further analysis of fecal microbiota composition. AR gene pools were assessed separately in each sample.
2.3.3 DNA extraction.
Total DNA from chicken fecal samples for real-time quantitative PCR (qPCR) and denaturing gradient gel electrophoresis (DGGE) analyses were extracted according to published method (Yu and Morrison 2004).
2.3.4 Real-time quantitative PCR.
TaqMan real-time PCR protocol was used to assess blaCMY-2, tetL, tetM, tetS, sul1, sul2, ermB and 16S rRNA gene pools in total DNA extracted from chicken fecal samples as
67 described previously (Zhang, 2013). The sequences of the primers and probes were listed in Table 1. The primers were synthesized by Sigma-Aldrich (St. Louis, MO) and the probe was synthesized by Biosearch Technology Inc. (Novato, CA). Each sample was assessed and analyzed in duplicates on a CFX96 system (Bio-Rad, Hercules, CA).
68 Primer and
Probe Sequence (5'-3') Reference
Zhang and others, blaCMY-2 FP GCCGTTGATGATCGAATC 2013
Zhang and others, blaCMY-2 RP GCGTATTGGCGATATGTAC 2013
Zhang and others, blaCMY-2 probe AGTTCAGCATCTCCCAGCCTAATCC 2013 tet(S) FP GTATGTTCATCTTTCTAAG Li and Wang, 2010 tet(S) RP GCAATAACATCTTTTCAAC Li and Wang, 2010 tet(S) probe CCATGTGTCCAGGAGTATCTAC Li and Wang, 2010 tet(L) FP CGTCTCATTACCTGATATTGC Li and Wang, 2010 tet(L) RP AGGAGTAACCTTTTGATGCC Li and Wang, 2010 tet(L) probe AACCACCTGCGAGTACAAACTGG Li and Wang, 2010 tet(M) FP GAACATCGTAGACACTCAATTG Li and Wang, 2010 tet(M) RP CAAACAGGTTCACCGG Li and Wang, 2010 tet(M) probe CGGTGTATTCAAGAATATCGTAGTG Li and Wang, 2010
Continued
Table 2.1 Primers and probes used in AR gene pool quantification in poultry GI microbiota. FP: forward primer; RP: reversed primer.
69 Table 2.1 continued
Zhang, 2012 sul1 FP CACCTTCGACCCGAAG (unpublished)
Zhang, 2012 sul1 RP TTGAAGGTTCGACAGCACG (unpublished)
Zhang, 2012 sul1 probe TCGACGAGATTGTGCGGTTCTTCG (unpublished)
Zhang, 2012 sul2 FP GATATTCGCGGTTTTCCAGA (unpublished)
Zhang, 2012 sul2 RP CAAAGAACGCCGCAATGT (unpublished)
Zhang, 2012 sul2 probe ATCATCTGCCAAACTCGTCGTTATGC (unpublished)
Zhang, 2012 ermB FP GAAAGCCRTGCGTCTGACATC (unpublished)
Zhang, 2012 ermB RP CGAGACTTGAGTGTGCAAGAGC (unpublished)
Zhang, 2012 ermB probe ACCTTGGATATTCACCGAACACTAG (unpublished)
Continued
70 Table 2.1 continued
Nadkarni and others,
16s FP TCCTACGGGAGGCAGCAGT 2010
Nadkarni and others,
16s RP GGACTACCAGGGTATCTAATCCTGTT 2010
Nadkarni and others,
16s probe CGTATTACCGCGGCTGCTGGCAC 2010
2.3.5 16S Metagenomic Analysis.
Among 16 chickens raised for AR profile assessment without antibiotic exposure, 4 chickens were randomly selected for further analysis for fecal microbiota composition.
Fecal DNA of Day 21, Day 25 and Day 28 from each chicken was extracted and subjected to the analysis. The V3/V4 portions of the 16S rRNA genes of the microbiota were amplified and sequenced on an Illumina Miseq sequencer, following the standard protocol of 16S Metagenomic Sequencing Library Preparation (Illumina support, 2013).
Paired-end joining and quality filtering were performed with Qiime (Caporaso and others,
2010). Only sequences longer than 450bp with Phred quality score higher than 19 were used
71 for phylotype analysis. Operational Taxonomic Units (OTUs) were picked using open-reference OTU picking process with 97% sequence similarity. And 10% of the sequences that failed to hit the reference database were subjected to de novo clustering. Other quality control perimeters were set as default (Caporaso and others, 2010). Phylogenetic analysis and taxonomic assignments of the V3 and V4 portion of the 16S rRNA gene were made using Greengenes database (version 13_8). Additional phylotype comparisons and analysis were performed with the QIIME diversity analyses module.
2.3.6 Statistics
One-way ANOVA analysis of the population size of AR gene pools was performed in
SAS (version 9.4), to compare the difference between the three batches of chickens.
Significance was declared at P < 0.05.
72 2.4 Results
2.4.1 The prevalence of AR in chicken GI microbiota at early stage
Fresh feces from 5 Vendor-hatched broilers, 5 farm-hatched broilers and 5 farm hatched layers were analyzed. Total DNA was extracted from all chickens recruited and AR gene pools were assessed individually by Taqman real-time (Figure 2.1).
The average 16S rRNA gene pool was similar across three groups (10.9±0.5, 10.5±0.8
and 11.4±0.5 log10 (gene copies/g), P=0.109), indicating a comparable microbial population in the fecal microbiota. The largest differences detected were the sizes of sul1
and sul2 gene pools, with up to 10.4 log10 (gene copies/g) in the vendor-hatched broilers
but under detection limit (6.0 log10 (gene copies/g) for sul1 and sul2 genes) in either group of chickens hatched on-site in the teaching farm. It is noteworthy that the sul1 gene
pool in the vendor-hatched broiler was large, reaching (9.8±0.5 log10 (gene copies/g)). In
r general, large sizes of tet gene pools were detected across all three groups (above 8 log10
(gene copies/g)), especially the tetM gene pool (10±0.9, 9.9±1.4 and 10.6±0.6 log10 (gene copies/g), P=0.569). Farm-hatched broiler had relatively smaller tetL gene pool (8.3±1.7
vs. 10.3±0.9 and 10.6±0.7, P=0.019 log10 (gene copies/g)) but larger tetS gene pool
73 (10.9±0.5 vs. 8.8±1.3 and 9.4±0.5 log10 (gene copies/g)). There was no significant
difference in ermB (8.5±1.3, 7.1±0.9 and 8.5±0.4 log10 (gene copies/g)) and blaCMY-2
(7.5±1.0, 6.4±0.5 and 6.9±0.9 log10 (gene copies/g)) gene pools.
Figure 2.1. Abundance of targeted AR gene pools in chicken feces at Day 5. ☆Bacteria count or size of gene pool is below detection limit.
74 2.4.2 The dynamic of 16S and blaCMY-2 gene pools in Week 4.
r Among all assessed AR genes, blaCMY-2 (Amp gene) had low abundance and is a convenient indicator of AR proliferation. Besides, ampicillin has good solubility in water and is easy to be delivered to poultry. In this case, ampicillin was chosen as target
antibiotic and blaCMY-2 as target AR gene in the following analysis.
Fresh feces from 4 farm-hatched layers were collected separately on Day 21, Day 25, and
Day 28 post-hatch. Total DNA was extracted from the above fecal samples and 16S and
blaCMY-2 gene pools were assessed individually by Taqman real-time (Figure 2.2). Shifts of 16S gene pool were observed across all the subjects during the study period, but the range of shift remained within 2 logs (Figure 2.2A). Except for the sample collected on
Day 21 from subject CS5-23, blaCMY-2 gene pool in all other samples remained blow 8
log10 (gene copies/g). The blaCMY-2 gene pool was too low to be detected in subject
CS5-37 on DAY 21 and Day 28 (Figure 2.2B). The percentage of blaCMY-2 gene in 16s gene copies was below 2.3% across all samples (Figure 2.2C).
75 A
Continued
Figure 2.2 Gene pool size of blaCMY-2 and 16S rRNA and the ratio of blaCMY-2 /16S rRNA from individual chicken in Week 4. A. The change of 16S rRNA gene pools. B. The
change of blaCMY-2 gene pools, the gene pool of subject CS5-37 on Day 21 and Day 28
was under detection limit (6.5 log10 (gene copies/g)). C. The ratio of blaCMY-2 gene copies
versus 16S rRNA gene copies ((blaCMY-2/16s) %).
76 Figure 2.2 continued
B
C
77 2.4.3 The change of microbiota during week 4
Total fecal DNA extracted from the 4 chickens for AR gene pool analysis were further subjected to total microbiota composition and phylotyping analysis. A total of 136,063 sequences were used for analysis, clustered into 1,648 OTUs (1,186 de nove clustered).
The distribution of bacteria at phylum level (Figure 2.3 A) showed that, without intervention, Firmicutes was most abundant in all subjects during the study period, taking up over 96% of the total sequences. Other identified phyla had less than 1% of the total sequence counts. The distribution at genus level (Figure 2.3B) indicated that
Lactobacillus was predominant in most samples on Day 21 and Day 25, while some unclassified genera from Lachnospiraceae (in order Clostridiales) replaced Lacrobacillus and become the largest portion in some samples (on D21 in CS5-27, on D28 in both
CS5-21 and CS5-23). Blautia, Enterococcus and some Clostridium had moderate population in some samples. It is worth noting that the genus Escherichia was barely observed during the study period, with only 1 or 2 readings if detected.
78 A
Continued
Figure 2.3 The constitution of fecal microbiota of individual layer chickens in Week 4. A.
Microbiota constitution at phylum level. B. Microbiota constitution at genus level. D21,
D25, and D28: samples collected on Day 21, Day 25 and Day 28, respectively.
79 Figure 2.3 continued
B
80 2.5 Discussion and conclusion
The rapid spread of ART bacteria and AR genes has been a major public health hazard.
ART bacteria and AR gene pools have been routinely detected in food-producing animals and around related agricultural facilities. Even in the region where antibiotic feed-additives are restricted, large AR gene pools remain in animals without exposure to antibiotics (Casewell, 2003). Gastrointestinal bacteria are the most important part of commensal microbiota, influencing the overall health of animal host (Zoetendal and others, 2004). Despite its impact on nutrition utilization, immunomodulation and etc., GI microbiota plays critical role in AR proliferation and dissemination. Spontaneous colonization and persistence of AR in GI microbiota of food-producing animals represent a hurdle for AR mitigation. In this case, a better understanding of the establishment and change of AR, as well as the natural constitution of commensal bacteria in the GI tract, is of significance for future development of AR control strategies.
The GI tract is sterile in neonate animals and becomes quickly colonized by bacteria within hours after birth (Benno and Mitsuoka, 1986). Environmental bacteria are the most convenient source of neonatal GI microbiota. So the AR profile in the young animal is a
81 good indication of the distribution of ART bacteria and AR determinants. In this study,
AR gene pools were detected in all three groups of chickens within a week after birth, without any exposure to antibiotics. The early establishment of large Tetr –encoding gene pools in chickens came from varied source implies that the Tetr gene might be prevalent in the environment, which is consistent with previous observations (Chopra and Roberts,
2001). However, the difference between Sulr gene pool between retail chicks and on-site hatched ones might suggest the impact from different environment or operation on the gut microbiota. The purchased chicks are likely exposed to multiple environments through hatching, transportation and relocation into new breeding rooms, so they have more chance to be exposed to various ART bacteria and AR genes. The farm-hatched chicks were raised under a much controlled condition from the very first day of life (sterilized hatcher, filtered air, sterilized feed and water), yet AR gene pools still established very quickly in large population. One on hand, early establishment of AR gene pool indicts that the breeding facility might have intrinsic AR populations that are hard to eliminate but easy to proliferate in animal host, and/or that the workers and researchers might also be carriers of the ART bacteria. On the other hand, these results further confirmed that GI
82 microbiota is like a “breeding bed” for AR, harboring large AR profile even in absence of antibiotic exposure.
Dramatic change of gut microbiota has been reported during the 2nd and 3rd week after birth (Lu and others, 2003), possibly due to the fast maturation of the GI tract during the
same period. After the significant shift of microbiota, intrinsic blaCMY-2 gene pool
remained in detectable size. The persistence of blaCMY-2 gene pool might result from good
niche-fitness of the intrinsic ART bacteria; while it is also possible that the blaCMY-2 gene is interchangeable through horizontal gene transfer and remains in various bacterial populations. Repeated pick of the environmental ART bacteria might also contribute to the persistence of AR in GI tract.
The analysis of microbial constitution of GI tract during Week 4 in layers indicates that the GI microbiota is stable at phylum level during this period of growing stage. Without intervention, bacteria from Firmicutes are the most dominant population, especially the genus Lactobacillus. But the GI microbiota is not a stable system; the prevalence of each population within the Firmicutes can differ significantly, even within short period. Many
83 frequently reported ART bacteria in poultry, such as Salmonella, Campylobacter and E. coli, belong to Proteobacteria. But this phylum only takes small portion of the natural chicken GI microbiota. In this case, AR surveillance only on these bacterial populations may result in a loss of whole landscape of AR development.
In conclusion, this study found that AR resistance gene pool established at early stage of chicken life without exposure to antibiotics. Environmental exposure might affect the
early establishment of AR profile in chicken gut. Intrinsic blaCMY-2 gene pool remained in detectable size after the 3 weeks of growth. GI microbiota of layer chicken was stable in phylum level during Week 4, Firmicutes being the most dominant population. Further analysis of AR profile in GI microbiota should take into consideration of the natural establishment of AR gene pools, the environmental factors and the constitution of microbiota.
84 Chapter 3
Strain identification of commensal Escherichia coli and Lactobacillus crispatus
strains
3.1 Abstract
Gastrointestinal microbiota consists of large number of bacterial cells, but less than 1% are cultivable. Nevertheless, cultivable bacteria provide important information of the GI ecology, including the profile of antibiotic resistance. The aim of this study is to identify several culture-recovered commensal bacterial strains isolated from chicken feces, and examine their potential contribution to AR ecology. Three Ampr E. coli (E. coli CA-1, E. coli CA-4 and E. coli CA-20) strains were found resistant/insusceptible to β-lactam, erythromycin, daptomycin, vancomycin and linezolid, but susceptible to tetracycline and quinolones. Lactobacillus crispatus CG-12 was isolated and susceptible to most antibiotics examined, but resistant/insusceptible to quinolone and daptomycin. The result was consistent with data by whole genome sequence analysis. The identified and
85 characterized E. coli strains will be used in later studies as ART marker strains, and the
Lactobacillus crispatus strain will be examined for its efficacy in modulating GI microbiota.
3.2 Introduction
The impact of antibiotics on GI tract is complicated partially due to the complexity of GI microbiota and the lack of appropriate target to track. While pathogens have been the focus for antibiotic resistance studies for decades, these bacteria count for a very small percentage in GI microbiota (Laxminarayan and others, 2013). Targeting certain group of commensal bacteria and tracking their dynamics during antibiotic treatment is a more promising strategy to explore the antibiotic-GI tract interaction.
Results from our previous study showed that during early development of chickens hatched in the teaching farm, among all background AR gene pools of fecal samples
examined, ampicillin resistance encoding blaCMY-2 gene has low abundance, and thus it was chosen to be the marker for further assessment of the impact of antibiotic intake on
86 + AR in gut microbiota. In this study, three blaCMY-2 strains were isolated from poultry feces, identified and characterized for further application as ART marker strains.
It has also been well recognized that the composition of GI microbiota is dynamic, affected not only by antibiotics but also by microorganisms ingested through the oral routes (such as food, feed, water, etc.), as well as other host factors (Scott and others,
2013; Looft and others, 2012). Since antibiotic resistant bacteria are found in poultry gut microbiota with or without direct exposure to antibiotics, the large quantity of AR-rich feces from poultry production represents an important contamination source impacting the environment AR gene pool. Thus targeted strategies to minimize the prevalence of antibiotic resistance in poultry GI microbiota become essential for effective mitigation of
AR in the poultry production system. In this study, additional commensal bacteria isolated from poultry feces were identified and characterized for further application as
AR modulating strain.
87 3.3 Materials and methods
3.3.1 Bacterial strains
Multiple Ampr strains from feces of broiler chicken without antibiotic treatment were recovered on Columbia blood Agar base (Becton, 100 Dickinson and Company, Franklin
Lakes, NJ) supplemented with 5% defibrinated sheep blood (Thermo Scientific™, Grand
Island, NY). The strains were maintained in Columbia broth (Becton Dickinson and
Company, Franklin Lakes, NJ), and propagated by aerobic growth at 37°C, and further subjected to strain identification and Minimum Inhibition Concentration (MIC) assessments.
Multiple commensal bacterial strains from chicken feces were recovered from Columbia blood Agar base (Becton, 100 Dickinson and Company, Franklin Lakes, NJ) supplemented with 5% defibrinated sheep blood (Thermo Scientific™, Grand Island,
NY), and maintained in Columbia broth (Becton Dickinson and Company, Franklin
Lakes, NJ) and propagated by anaerobic growth at 37°C. The strains were subjected to antibiotic susceptibility assessment followed by strain identification.
88 Screening of antibiotic susceptible commensal strains
Recovered commensal strains isolates (over 1000 colonies) were spotted on Columbia broth (Becton, 100 Dickinson and Company, Franklin Lakes, NJ) agar plates containing each of the four antibiotics for rapid assessment of their phenotypic resistance profile.
Screened antibiotics include 16 μg/mL of tetracycline (Sigma–Aldrich, St. Louis, MO,
USA), 100 μg/mL of erythromycin (Fisher Scientific, Waltham, MA, USA), 32 μg/mL of ampicillin (Sigma–Aldrich) and 152 μg/mL of sulfamethoxazole (Sigma–Aldrich) with 8
μg/mL of trimethoprim (Sigma–Aldrich).
3.3.2 Strain identification
The phylotype identity and AR determinants were examined by conventional PCR.
Primers used for identification and gene screening are listed in Table 3.1 and synthesized by Sigma-Aldrich. The sequence of the 16S rRNA amplicon was confirmed by DNA sequencing at the Plant Microbe Genomics Facility of the Ohio State University and compared with published AR gene sequences deposited in the NCBI database.
API® 50CH (Biomerieus, Durham, NC, US) identification strip was used for further identification of Lactobacillus.
89
Primer Sequence size Amplicon size Reference blaCMY-2 FP GACAGCCTCTTTCTCCACA 1,143 bp (Zhao and blaCMY-2 RP TGGAACGAAGGCTACGTA others, 2001)
16S-357F-GC CGCCCGCCGCGCGCGGCGG 233 bp (Muyzer and
GCGGGGCGGGGGCACGGGG others, 1993)
GGCCTACGGGAGGCAGCAG
16S-518R ATTACCGCGGCTGCTGG
Table 3.1 Primers used in strain identification. FP: forward primer; RP: reversed primer.
3.3.3 Minimum inhibition concertation (MIC) assessment
TREK Sensititre diagnostic system (Thermo scientific, Oakwood Village, OH, USA) was used to assess the AR phenotype and MIC of the isolated strains. Protocol to use this system can be found on www.trekds.com. Cation-adjusted Mueller Hinton Broth (Becton,
Dickinson and Company, MD, USA) was used as basic medium.
90 3.3.4 Shotgun whole genome sequencing, assembly and annotation
DNA of Lactobacillus crispatus CG-12 was extracted from a colony using UltraClean®
Microbial DNA Isolation Kit (Mo Bio Laboratories Inc; Carlsbad, CA, USA). DNA was sent to the Nationwide Children’s hospital (Columbus, OH. USA) for sequencing on an
Illumina HiSeq 2500 system (Illumina Inc; San Diego, CA, USA). Assembly of bacterial genome was performed using CLC Genomics Workbench 9.0 (CLC bio; Katrinebjerg,
Denmark). Reference mapping of reads was performed using the genome of the
Lactobacillus crispatus ST1 (GenBank accession no. FN692037.1). The assembled contigs were aligned to the Comprehensive Antibiotic Resistance Database (CARD) to search for AR determinants (McArthur and others, 2013). Annotation of the assembled contigs was performed on the RAST (Rapid Annotation using Subsystem Technology) server (Aziz and others, 2008; Overbeek and others, 2014; Brettin and others, 2015).
3.4 Results
3.4.1 Identification and characterization of the E. coli strains
NCBI blast result of the 16S rRNA sequence from the Ampr strains showed that, all three strains had 100% query coverage and over 98% sequence identity to the E. coli 16S 91 rRNA sequences in NCBI database. Three strains were designated as E. coli CA-1, E. coli
+ CA-4, E. coli CA-20. All three E. coli strains were blaCYM-2 by conventional PCR. MIC assessments results of the E. coli strains were listed in Table 3.2. The MIC profiles of E. coli CA-1 AND E. coli CA-4 were highly identical. Three Ampr E. coli had high resistance to β-lactam antibiotics (except for ceftriaxone), for example penicillin, ampicillin and oxacillin. Only E. coli CA-20 had some resistant to ceftriaxone. The E. coli strains were also resistant/insusceptible to erythromycin and some peptide antibiotics
(daptomycin, vancomycin and linezolid). But they had low MIC for tetracycline and quinolones, indicating their susceptibility to these two categories of antibiotics.
3.4.2 Identification and characterization of the commensal Lactobacillus strains
Among over 1000 strains examined, a strain CG-12, susceptible to ampicillin, tetracycline, erythromycin and sulfonamide/trimethoprim, originated from Leghorn chicken, was isolated. The strain was identified to be Lactobacillus by 16S rRNA gene sequence assessment without confirmed species. The API® 50CH result indicated the tested susceptible strain had 99.9% possibility to be Lactiobacillus crispatus. This strain was designated as Lactiobacillus crispatus CG-12. Lactobacillus crispatus CG-12 was
92 - blaCYM-2 by PCR. Lactobacillus crispatus CG-12 had low MIC to most tested antibiotics
(Table 3.2), but was resistant/insusceptible to daptomycin and quinolone (levofloxacin, gatifloxacin and ciprofloxacin).
93 L. crispatus E.coli CA-1 E.coli CA-4 E.coli CA-20 CG-12
ERY > 4 > 4 > 4 < 0.25
CLI > 2 > 2 > 2 < 0.12
SYN > 4 > 4 > 4 0.25
DAP > 8 > 8 > 8 4
VAN > 128 > 128 > 128 < 1
TET < 2 < 2 < 2 < 2
AMP >16 >16 >16 0.5
GEN 4 4 8 16
LEVO < 0.25 < 0.25 < 0.25 > 8
Continued
Table 3.2 The MIC of selected antibiotics in E. coli CA-1, E. coli CA-1, E. coli CA-1 and
Lactobacillus crispatus CG-12. MIC values were expressed in µg/mL. ERY: erythromycin; CLI: clindamycin; SYN: quinupristin/dalfopristin; DAP: daptomycin; VAN: vancomycin; TET: tetracycline; AMP: ampicillin; GEN: gentamicin; LEVO: levofloxacin;
LZD: linezolid; AXO: ceftriaxone; STR: streptomycin; PEN: penicillin; RIF: rifampin;
GAT: gatifloxacin; CIP: ciprofloxacin; SXT: sulfamethoxazole/trimethoprim; OXA+: oxacillin+2%NaC.
94 Table 3.2 continued
LZD > 8 > 8 > 8 2
AXO < 8 < 8 16 < 8
STR < 1000 < 1000 < 1000 < 1000
PEN > 8 > 8 > 8 0.5
RIF 4 > 4 4 1
GAT < 1 < 1 < 1 4
CIP < 0.5 < 0.5 < 0.5 > 2
SXT < 0.5/9.5 < 0.5/9.5 < 0.5/9.5 2/38
OXA+ >8 >8 8 < 0.25
3.4.3 Whole genome sequence assessment of Lactobacillus crispatus CG-12
A total of 63 contigs longer than 1,000 bps were assembled from the sequence data with a total length of 2,046,783 bp. Further steps are required to fill the gaps between contigs and compile the scaffold genome into a continuous genome sequence. Compared to the
Genebank reference strain (Lactobacillus crispatus ST1, Genebank sequence No.
FN692037.1) full length chromosomal genome (2,043,161 bp), the sequence coverage was nearly complete.
95 Two AR-related gene sequences were detected in the scaffold genome when compared to
CARD database. A 346 bp sequence that had 77% identities to Staphylococcus aureus parE gene was observed on Contig 11 (153,379 bp). It encoded DNA topoisomerase IV subunit B which conferring resistance to aminocoumatin and fluoroquinolones. The other
737 bp sequence that had 73% identities to Staphylococcus aureus rpoC was located on
Contig 22 (65,018 bp). It encoded DNA-directed RNA polymerase β-subunit and confers resistance to distamycin. These results were consistent with the MIC test.
Besides, the annotation from RAST server indicated that there were phage-related genes in the genome of Lactobacillus crispatus CG-12. Phage related gene include phage replication initiation protein, phage anti-repressor protein, phage integrase, phage immunity repressor and etc.
3.5 Discussion and conclusion
Strain identification is important in the study of antibiotic resistance in commensal microbiota. The prevalence and AR profile of strains might be a good indication of the overall AR status in the microbiota. 96 In this study, three Ampr isolates were identified to be Escherichia coli. The target AR
gene blaCMY-2 was detected in all three strains. These strains had high resistance to
β-lactam antibiotics according to the MIC test. Similarity in MIC profile observed between E. coli CA-1 and E. coli CA-4 indicated these two strains might be identical. But further analysis is required for confirmation.
The susceptible strain CG-12 was identified as Lactobacillus crispatus. Lactobacillus crispatus is a commensal bacterial species prevalent in neonatal GI microbiota, and certain strain of this species has been commercialized as probiotic. Lactobacillus crispatus CG-12 is susceptible to most tested antibiotics, but has relative high resistant to quinolone antibiotics and daptomycin. This result is consistent with whole genome sequence analysis, as sequences with high homology to parE gene and rpoC were observed in the genome. Other AR gene against beta-lactam was not observed. The presence of phage-related genes indicates that gene transfer activity is possibly involved during the evolution of this strain. But deeper analysis of the genome sequence is required to build a comprehensive understanding of Lactobacillus crispatus CG-12.
97 + In conclusion the three blaCMY-2 E. coli strains have high resistance to β-lactams and can be used as indicators in responding to ampicillin selective pressure. The commensal
- blaCMY-2 Lactobacillus crispatus CG-12 has low resistance to most commonly used antibiotics and no Ampr gene was detected on its genome. The susceptibility of this strain makes it a promising replacement of the ART strain in GI microbiota.
98 Chapter 4
The Impact of Antibiotic Administration Routes on Development of Antibiotic
Resistance in Chicken Gut Microbiota
4.1 Abstract
The rapid emergence of antibiotic resistant (ART) bacteria poses a serious threat to public health. Selective pressure due to antibiotic applications certainly contributed to the rapid development of antibiotic resistance (AR). However, it is now recognized that AR is a complicated issue and more risk factors contributed to the problem seen today. This study examined the impact of oral resistant bacteria exposure and antibiotic administration methods on microbiota and AR gene pools in host gastrointestinal (GI) tract using
Leghorn chicken with natural gut microbiota. Chickens inoculated with a mixture of
+ blaCMY-2 Escherichia coli were treated with ampicillin sodium (Amp), which was delivered via oral gavaging or intramuscular (IM) injection. Chicken fecal samples were recovered and subjected to qPCR, denaturing gradient gel electrophoresis (DGGE) and
99 16S rDNA high-throughput sequencing assessment. This study found that: 1) the
r emergence of Amp gene (blaCMY-2) was found in feces of young chicks in the absence of
Amp treatments; 2) orally inoculated ART bacteria persisted in GI microbiota without antibiotic selective pressure; 3) oral exposure to 300mg/Kg of Amp in chickens inoculated with ART bacteria led to rapid enrichment of corresponding AR gene pools and phylum Proteobacteria and sharp decrease of phylum Firmicutes in feces; 4) the same dosage of Amp, when administered via IM injection, led to significantly less increase of Proteobacteria and decrease of Firmicutes; 5) The Ampr marker strains were detected in certain blank control chickens in different cages in the same facility, indicating possible ART bacteria dissemination through environmental exposure. Shift of fecal microbiota and dominant bacterial population were consistent with the dynamics of the targeted AR gene pool. These results confirmed that the impact of certain antibiotics on gut microbiota can be significantly reduced by avoiding the mainstream oral antibiotic administration route in the chicken model. Our study also indicates that additional control strategies for the spread of bacteria in the environment may be also important to reduce
ART bacterial dissemination in food animal production.
100 4.2 Introduction
For decades gastrointestinal (GI) microbes were primarily studied as the source of pathogens and pollutants. With increasing evidences from studies using animal models, it is now widely recognized that GI microbiota play an important role in modulating host metabolism, influencing organ and immune development and maintaining normal homeostasis (Sommer & Backhed 2013). Besides interaction with hosts, GI microbiota is of significance in the development and dissemination of antibiotic resistance (AR).
GI microbiota are constantly exposed to and react with the substances that enter the GI tract, laying the foundation for dietary interventions to optimize the GI microbiota and achieve better production (Patterson and Burkholder, 2003; Dibner and Richards, 2003).
Dietary supplements of antibiotics are popular in food animal production and perhaps have been the most effective practice to improve feed conversion efficiency and ensure animal health (FDA, 2014). Although the exact growth-promotion mechanism of antibiotics is unclear, significant changes in GI microbiota composition and metabolism have been reported in swine, mouse and poultry models (Zhang and others, 2013; Looft and others, 2012; Videnska and others, 2013; Lin and others, 2013; Singh and others,
101 2013). However, such antibiotic feed-supplements have been severely criticized due to its association with high frequency of antibiotic resistant (ART) strains and AR genes detected in farm environment and animal products (Lakhotia and Stephens, 1973;
Bensink and Botham, 1983; Aarestrup and others, 1998; Hagedorn and others, 1999).
Besides dietary interventions, GI antibiotic resistome is intensively impacted by environmental and foodborne microbes, resulting in the succession and dissemination of
ART stains among individuals and between species (Smith, 1970; Van den Bogaard and others, 2001; Zhang and others, 2011). Once established, ART bacteria and the corresponding AR genes can maintain a significant level in the host GI tract in the absence of antibiotic exposure (Zhang and others, 2011). In this case, food chain serves as a critical route for the establishment of GI resistome (Threlfall and others, 2000; Wang and others, 2006; Duran and Marshall 2005), because foodborne AR genes and ART bacteria has easy access into the GI microbiota. In conclusion, serious attention should be paid on the roles of GI microbiota and food chain in AR ecology.
The poultry industry provides a large portion of protein production with global annual stocks of over 19 billion heads (FAO, 2013), producing hundreds of millions’ tons of
102 manure annually (Moore and others, 1995; Collins and others, 1999; Williams and others,
1999). After the first discovery that in-feed dried mycelia of Streptomyces aureofaciens
(containing chlortetracycline) improved animal growth performance in 1940s, antibiotic growth promoter quickly gained popularity in poultry industry (Castanon, 2007). Early studies on AR in poultry from1950s reported intestinal bacteria resistant to tetracycline and streptomycin from poultry receiving dietary chlortetracycline (Elliott and Barnes,
1959). After decades of agricultural and veterinarian antibiotic applications, resistance to sulfonamides, penicillin, bacitracin, erythromycin and other clinically important antibiotics has been detected in strains related to poultry and farm environment. One of the primary concerns of AR in poultry is the transmission of resistance to pathogens
(Martínez, 2008) and dissemination via the food chain. While ART bacteria in poultry affect food safety, proper processing (e.g. sterilization and cooking) should be able to minimize AR prevalence in poultry products. But the impacts of AR-rich feces on the environmental AR gene pool and the health of farm workers can be very significant. In fact, the possibility of AR transmission from poultry to other farm animals and farm workers has been demonstrated in multiple studies (Smith, 1970; Van den Bogaard and others, 2001).
103 Culture independent methods, such as high-throughput sequencing techniques, have been employed to study the impact of in-feed antibiotics on poultry GI microbiota in recent years. While some studies reported insignificant change of population diversity of intestinal microbiota after antibiotic administration (Fairchild and others, 2005), most studies showed rapid and significant changes in composition of GI microbiota upon antibiotic administration, including reduced inter-bird variability in ileal microbiota
(Torok and others, 2011), changed diversity in the phylum Firmicutes and phylum
Bacteroidetes (Videnska and others, 2013; Lin and others, 2013; Singh and others, 2013) and increased representatives of particular genera (Videnska and others, 2013). Here we presented a study using a combination of culture dependent and culture independent methods to evaluate the impact of antibiotic administration routes on the development of
AR and microbial composition in poultry fecal microbiota.
4.3 Materials and Methods
4.3.1 Bacterial strains and culture preparation.
+ Three blaCMY-2 Escherichia coli strains were isolated from feces of two 4-day-old broiler chickens (Table 4.1). All strains were incubated separately in Columbia Broth (Becton,
104 100 Dickinson and Company, Franklin Lakes, NJ) at 37°C. Bacterial cells from 1 mL of overnight culture were collected by centrifugation (8000 ×g, 1 minute), washed (once) and re-suspended in 1 mL saline. A cocktail of three E. coli strains for inoculation was prepared by mixing the cell suspension of designated strains and standardized to 106
CFU/mL per each strain.
105 MIC DGGE Cocktail Strain ID Resistance AR gene (μg/mL) Cluster
Ampr 512 Escherichia coli r Axo < 8 blaCMY-2 1 CA-1 Rifr 4
Ampr 512 Escherichia coli r 1 Axo < 8 blaCMY-2 1 CA-4 Rifr > 4
Ampr 512 Escherichia coli r Axo 16 blaCMY-2 1 CA-20 Rifr 4
+ Table 4.1. Inocula of blaCMY-2 strains. Amp: ampicillin; Axo: ceftriaxone; Rif: rifampin.
4.3.2 The chicken model.
The experiment was conducted following approved animal protocol No. 2012A00000061, by the Institutional Animal Care and Use Committee, The Ohio State University,
Columbus, OH. Leghorn chickens were hatched and maintained at the Ohio Agricultural
Research and Development Center (OARDC) poultry research teaching farm (two birds
106 per cage with separate feed and water supply, controlled temperature, filtered air in the room and sterilized feed and water). Chicken fecal samples were collected on-site and
examined for the presence of blaCMY-2 gene pools. Since the Day 5 post-hatching, chicks
+ 6 were inoculated with the blaCMY-2 E. coli cocktail (0.2mL/bird, 10 CFU/mL) every 24 hours for 4 consecutive days via gavage feeding using 20ga X 1.5 in animal feeding needle (Fine Science Tools, Foster City, CA). Chicks in non-inoculated control groups were fed with 0.2 mL of saline by the same method. Chicks were then set in cages for 11 days before antibiotic treatment, allowing the microbiota to stabilize.
4.3.3 Antibiotic administration.
In poultry, clinical ampicillin dosage is applied at a range of 30-300mg/kg, while feed-additive ampicillin is below 30mg/kg. In this proof-of-concept study, high antibiotic dosage (300 mg/kg body weight per day for Amp, respectively) was selected. Chickens were grouped and treated as shown in Table 4.2.
107 Antibiotic administration AR carrier Group Oral IM Oral IM inocula Ampicillin 300mg/kg Saline (control)
Amp-PO Escherichia coli. + - - -
Amp-IM Escherichia coli. - + - -
Saline-PO Escherichia coli. - - + -
Saline-IM Escherichia coli. - - - +
NI-Amp-PO - + - - -
NI-Amp-IM - - + - -
NI-Saline-PO - - - + -
NI-Saline-IM - - - - +
Table 4.2. Leghorn chicken groups subjected to marker cocktail inoculation and antibiotic administration treatments
Each of the four groups receiving antibiotic treatment contained 8 chickens (2 chickens/cage), whereas the four control groups each contained 10 chickens (2 chickens/cage). Antibiotics were administered via gavage feeding using 20ga X 1.5 in animal feeding needle or breast intramuscular injection using 1 mL insulin syringe
108 (Becton, Dickinson and Company, Franklin Lakes, NJ). Chicks were administered with ampicillin or saline once a day for 5 consecutive days.
4.3.4 Sample collection.
Fresh feces were collected from each broiler subject on-site in the rearing facility. Fecal samples were collected once a week before antibiotic treatment, once a day during the antibiotic administration period, and once every three days during antibiotic withdrawal period up to 14 days from initial antibiotic exposure.
4.3.5 Culture-recovery of gut microbiota.
Fecal microbiota in chicken GI tract were recovered on Columbia blood agar base (CBA,
Becton Dickinson and Company, Franklin Lakes, NJ) supplemented with 5% defibrinated sheep blood (Fisher Scientific, Hampton, NH) and 100 μg/mL cycloheximide
(Sigma-Aldrich). CBA plates supplemented with 32μg/mL of ampicillin sodium (Life
Technologies, Grand Island, NY) were used to recover ART bacteria. Chicken fecal samples were homogenized in stomacher bags by stomacher (Seward Stomacher 80 Lab
109 Systerm, UK). Homogenized samples were serially diluted in sterile saline and plated on corresponding agar plates. The plates were incubated at 37°C for 48 h in a GasPak 150 anaerobic system with GasPak EZ anaerobe container system sachets (Becton Dickinson and Company). The upper and lower detection limit of the plate counting enumeration
method is 10 log10 CFU/g and 2 log10 CFU/g respectively.
4.3.6 DNA extraction.
Total DNA from chicken fecal samples for real-time quantitative PCR (qPCR) and denaturing gradient gel electrophoresis (DGGE) analyses were extracted according to published method (Yu and Morrison 2004).
4.3.7 Real-time quantitative PCR.
TaqMan real-time PCR protocol was used to assess blaCMY-2 and 16S rRNA gene pools in total DNA extracted from chicken fecal samples as described previously (Zhang and others, 2013). The sequences of the primers were 5’-GCCGTTGATGATCGAATC-3’ and
5’-GCGTATTGGCGATATGTAC-3’, with blaCMY-2 probe 5’-6FAM
110 AGTTCAGCATCTCCCAGCCTAATCC-BHQ1-3’ (Zhang and others, 2013). The primers were synthesized by Sigma-Aldrich (St. Louis, MO) and the probe was synthesized by and Biosearch Technology Inc. (Novato, CA). Each sample was assessed and analyzed in duplicates on a CFX96 system (Bio-Rad, Hercules, CA, USA).
4.3.8 DGGE analysis.
The 16S rRNA V3 region was used for amplification of partial 16S rRNA gene following previous procedure (Muyzer et al. 1993). The sequences of PCR primers used were
16S-357F-GC and 16S-518R PCR; products were loaded on to an 8% acrylamide gel with a urea gradient from 40% to 60%. Electrophoresis was performed at 60°C, 83 V for
16 h using the Dcode system for DGGE (Bio-Rad, Hercules, CA, USA). The finishing gel was stained with 0.01% ethidium bromide and imaged under ChemiDoc XRS system
(Bio-Rad, Hercules, CA). The dominant DNA band was recovered and sequenced. For persistence analysis of oral-inoculated ART bacteria, fecal DNA of 3 randomly selected chickens from NI-Saline-PO and NI-saline-IM (C1, C2 and C3 respectively) at Day 5
(D5) and Day 20 (D20) post-hatch were used as the template to amplify the 16S rRNA gene V3 region. For microbiota analysis during antibiotic treatment, fecal DNA of
111 chickens from Amp-PO and Amo-IM collected on Day 5, 20, 21, 23, 25, 28 and 24 were used as the template to amplify the 16S rRNA gene V3 region.
4.3.9 16S Metagenomic Analysis.
For general microbiota analysis, extracted total DNA samples of Day 25(the end of treatment), were pooled by treatment groups (3 samples from each group of Amp-PO,
Amp-IM, Saline-PO, Saline-IM NI-Amp-PO, NI-Amp-IM, NI-Saline-PO and
NI-Saline-IM) and subjected to metagenomics assessment. In addition, the shift of microbiota in individual chicken was also examined. In this case, a total of 20 chickens were randomly selected from treatment groups (3 from each Amp-PO, Amp-IM,
NI-Amp-PO, NI-Amp-IM, and 2 from each Saline-PO, Saline-IM and NI-Saline-PO and
NI-Saline-IM). Fecal DNA samples of D20, D21, D25 and D28 from each chicken were subjected to analysis.
The V3/V4 portion of the 16S rRNA gene of the samples were amplified by PCR following the standard protocol for 16S Metagenomic Sequencing Library Preparation
(Illumina support, 2013), and the products were sequenced on Illumina Miseq sequencers 112 at DNA Facility of the Iowa State University Office of Biotechnology (pooled samples) and OARDC Molecular and Cellular Image Center (individual samples). Paired-end joining and quality filtering were performed with Qiime (Caporaso and others, 2010).
Only sequences longer than 450bp with Phred quality score higher than 19 were used for phylotype analysis. Operational Taxonomic Units (OTUs) were picked using open-reference OTU picking process with 97% sequence similarity. And the sequences that failed to hit the reference database were subjected to de novo clustering. Other quality control perimeters were set as default. Phylogenetic analysis and taxonomic assignments of the V3/V4 portion of the 16S rRNA gene were made using Greengenes database (version 13_8). Additional phylotype comparisons and analysis were performed with the QIIME diversity analyses module. Krona chart of the microbiota composition in
8 pooled samples were generated from the sequence obtained from QIIME (Ondov and others, 2011)
4.3.10 Statistics.
The population size of blaCMY-2 and the percentage of AR gene carriers were analyzed in completed randomized model with repeated measurements in time using the MIXED
113 procedure of SAS (version 9.4). The model included the fixed effects of inoculation (1 df), treatments (1 df), administrative route (1 df), time (2 df), and the random effects of animals. Various covariance structures of errors were fitted; the Huynh-Feldt structure was selected based on the lowest Bayesian information criterion (BIC). Degrees of freedom and tests were adjusted using the Kenward-Roger option. Significance was declared at P < 0.05.
4.4 Results
4.4.1 Early colonization of ART bacteria
Intrinsic pools of 11.4±0.5 log10 (copies/g) of 16S rRNA gene and 6.9±0.9 log10 (copies/g)
of blaCMY-2 gene were detected in all of the 46 chickens examined on the 5th day after birth. Fresh fecal samples (from 46 examined individuals) were used for culturing, and
8.0±0.6 log10 CFU/g cultivable bacteria were recovered on CBA plates from feces of 20
r randomly picked chickens, with up to 7.4 log10 CFU/g Amp bacteria detected in 42% of the chickens examined. The detection of significant background Ampr bacteria population
and blaCMY-2 gene pool in chicken fecal samples suggested that the establishment of AR in chicken GI tract is a natural process in early development, likely related to
114 environmental exposure or even vertical transmission from the hen (Cox and others,
2012), but certainly independent from direct antibiotic exposure.
4.4.2 Persistence of oral-inoculated antibiotic resistant bacteria during microbiota shift in the absence of antibiotic selective pressure.
Three controlled chickens without inoculation of ART marker strains were randomly picked to study the development of dominant bacterial population. DGGE analysis showed the occurrence of population shift in chicken GI microbiota, with Enterococcus being the dominant bacterial genera on the Day 5 post-hatch and Lactobacillus becoming the dominant genera by the Day 20 (Figure 4.1). DGGE analysis of the amplicons indicated natural shifts in chicken fecal microbiota between Day 5 (Lane 2，3，4) and Day
20 (Land 5, 6, 7).
115
Figure 4.1 Natural shift of predominant 16S rRNA genes in total fecal DNA extracts.
Lane 1: 100 bp DNA ladder; Lane 2, 3, 4: poultry fecal microbiota of D5; Land 5, 6, 7:
+ poultry fecal microbiota of D20; Lane 8: blaCMY-2 marker strains. Residential strain symbols: a: Enterococcus sp.; b: Enterococus sp.; c: Lactobacillus sp.; d: Lactobacillus sp.; e: Lactobacillus sp.; f: Faecalibacterium sp.; g: Lactobacillus sp.; M: Inoculated
Escherichia coli.
116 At the end of two weeks’ stabilization period after inoculation of the Ampr marker strains,
5.9±0.7 log10 CFU/g of total cultivable bacteria were recovered on the corresponding
CBA plates from 11 inoculated chickens (from Group Amp-PO, Amp-IM, Saline-PO and
Saline-IM). Meanwhile, 6.1±0.8 log10 CFU/g of total bacteria was found in feces from 9 non-inoculated chickens (NI-Amp-PO, NI-Amp-IM, NI-Saline-PO and NI-Saline-IM.
These data illustrated that inoculation of blaCMY-2 carriers (Table 4.1) did not significantly change the sizes of total cultivable bacteria population in chicken GI microbiota. In accordance with the plate count result, the size of 16S rRNA gene pools was found to be
9.8±0.8 log10 copies/g and 10.2±0.9 log10 copies/g in non-inoculated and inoculated chickens, indicating that the magnitude of total GI microbiota in chickens was not significantly impacted by the inoculation of the AR maker strains employed in the study.
Ampr bacteria were recovered from 100% of the inoculated chickens at a level of 4.5±0.7
r log10 CFU/g in feces. Meanwhile, cultivable Amp bacteria were recovered from 56% of
the non-inoculated chickens (5 out of 9) in 4.08±0.7 log10 CFU/g. The blaCMY-2 gene pool
was 7.8±0.6 log10 copies/g in inoculated group and 6.5±0.9 log10 copies/g in non-inoculated group. Plate counting results indicated that inoculation of the Ampr
117 marker strains increased the number of chickens that carried cultivable Ampr bacteria, but
the average blaCMY-2 gene pool was only slightly increased in inoculated subjects.
4.4.3 Impact of Amp administration on blaCMY-2 gene pool in feces
Real-time qPCR was used to analyze the 16S rRNA and blaCMY-2 gene pools during antibiotic administration. As shown in Figure 4.2B, 16S rRNA gene pool from all
treatment groups were relatively stable, with a level between 9 and 11 log10 copies/g in chicken feces. Compared to non-inoculated groups, inoculated groups (Amp-PO,
Amp-IM, Saline-PO, Saline-IM) had larger blaCMY-2 gene pool before Amp treatment, due to the persistence of marker strains in chicken GI tract (Figure 4.2A). Administration of
300 mg/kg of Amp in chickens inoculated with AR gene carriers led to rapid
amplification of the blaCMY-2 gene pool starting from the second day of antibiotic
administration (Day 21). The increased blaCMY-2 gene pool was maintained during Amp
administration period. Meanwhile no significant change of blaCMY-2 pool was observed in
inoculated chickens that received saline placebo. A small intrinsic blaCMY-2 pool was found to maintain in non-inoculated chickens during the experiment, regardless whether the subjects were subjected to Amp administration (P=0.104).
118 As illustrated in Figure 4. 2A, the change of Amp administrative route did not cause
significant difference on the size or dynamic of the blaCMY-2 pool in fecal microbiota
(P=0.054) in this study.
119 A
Continued
Figure 4.2 Real-time PCR quantification of blaCMY-2 and 16s rRNA gene pool in chicken GI microbiome upon ampicillin exposure (300 mg/kg body weigh/day). The
detection limit of blaCMY-2 and 16S rRNA gene pools in this study is 5 log10 copies/g. (A)
blaCMY-2 gene pool with Amp treatment. (B) 16S rRNA gene pool with Amp treatment.
The error bars represent standard deviations of the data from animal subjects used in the study. The vertical dashed lines indicate the last day of Amp administration.
120 Figure 4.2 Continued
B
4.4.4 Impact of Amp administration on GI bacterial population in poultry.
Predominant bacterial populations in chicken GI tract were analyzed by assessing 16S rRNA gene V3 region using DGGE. As illustrated in Figure 4.3, the inoculation of
+ blaCMY-2 E. coli marker strains did not significantly change the profile of chicken fecal microbiota in chickens (Figure 4.3A-B, Lane 3). It is noteworthy that oral exposure to
Amp induced rapid amplification of E. coli strains that had identical band to the marker E.
121 coli strains on DGGE gel. By the end of oral Amp administration, the E. coli became the dominant strains in GI tract of chicken from Group Amp-PO; in contrast, the profile of dominant fecal microbiota in chickens from Group Amp-IM did not change significantly before and after Amp exposure (Figure 4.3B, Lane 4,5and 6).
122 A
Continued
Figure 4.3 Dynamic of predominant 16S rRNA genes in total fecal DNA extracts from inoculated chicken administered with antibiotics. A: Amp-PO, and B: Amp-IM. Lane 1:
100 bp DNA ladder; Lane 2: before inoculation of marker strain; Lane 3: after inoculation but before Amp administration; Lane 4-6: 1st, 3rd, and 5th days with Amp exposure;
+ Lane 7 & 8: 3rd and 9th days with Amp lifted; Lane 9: blaCMY-2 marker strains
123 Figure 4.3 continued
B.
Chicken GI microbiota was further investigated by 16S metagenomic analysis. A totally of 3,019,513 sequences from the 8 pooled samples were subjected to phylotype analysis, clustered into 13,608 OTUs (11788 from de novo clustering). For the individual analyses, 124 1,699,211 sequences were collected from the 80 samples and were clustered into 6,652
OTUs (5,326 from de novo clustering).
Firmicutes were found as the most abundant phylum in chicken natural GI microbiota
(Day 20), counting for more than 97% of total bacterial population group in 9 out of 10 of the non-inoculated subjects; while Proteobacteria only account for less than 1% in all these 9 subjects (57.7% Firmicutus and 42.2% Proteobacteria in the last sample). The prevalence of Firmicutes in chicken GI microbiota is in agreement with results by Wei et al (2013). In the inoculated group, 5 out of 10 still have over 97% Firmicutus and less than 1% Proteobacteria in total bacterial population, while the other half has a numerically larger portion of Proteobacteria (3.4%, 6.1%, 12.5%, 44.5%, 44.7%) and correspondingly small Firmicutus population (96.5%, 93.8%, 87.5%, 55.5% ,52.2%).
Inoculation of Ampr marker strains increased the Proteobactria population significantly in some chickens, but overall the impact of inoculation itself was statistically insignificant, which is in accordance with plate count and qPCR data.
125 After antibiotic treatment (Day 25), data from pooled samples indicated that Firmicutes remained the most abundant phylum in control groups (NI-Saline-PO and NI-Saline-IM), counting more than 99% in total bacterial population; while Proteobacteria counted less than 1%. Inoculated chickens receiving oral Amp showed increased abundance of
Proteobacteria (63.2% in total population after oral exposure to Amp) in GI microbiota, including a significant amplification of genera Escherichia/Shigella (57.9% in total population); and a corresponding decreased Firmicutes (35.7%) (Figure 4.4A-B). In contrast, the same dosage of Amp, when delivered via IM injection, only induced a moderate increase of Proteobacteria (13.6%) in GI microbiota from inoculated chickens, mostly attributed by the increase from genus Escherichia/Shigella (12.6%). Similarly, in the absence of marker strains inocula, oral Amp induced significantly amplification of
Proteobacteria (27.4%) compared to IM injection group (remained <1%). And it appeared that such increase of Proteobacteria in oral group was contributed to genus
Klebsiella (21.7% in Figure 4.5),
126 A
Continued
Figure 4.4. Composition of fecal microbiota after antibiotic treatment. Fecal samples were collected at Day 25 post hatching. A) Phylum-level composition of fecal microbiota. Abundance of phyla is shown as percentage of total sequence. B) The abundance of genus Escherichia/Shigella in fecal microbiota, shown as percentage of total sequence.
127 Figure 4.4 continued
B
128 A
Continued
Figure 4.5. Krona chart of the composition of fecal microbiota on Day 25 in pooled samples. (A) Amp-PO; (B) Amp-IM; (C) Saline-PO; (D) Saline-IM; (E) NI-Amp-PO;
(F) NI-Amp-IM; (G) NI-Saline-PO; (H)NI-Saline-IM.
129 Figure 4.5 continued
B
Continued
130 Figure 4.5 continued
C
Continued
131 Figure 4.5 continued
D
Continued
132 Figure 4.5 continued
E
Continued
133 Figure 4.5 continued
F
Continued
134 Figure 4.5 continued
G
Continued
135 Figure 4.5 continued
H
136 4.5 Discussion and conclusion
Antibiotics have been used in food animal production for 70 years (Dibner and Richards,
2005). However, the rapid emergence of AR has become serious threat to social welfare and part of the problem is contributed by such practice. Restricting the use of antibiotics is the mainstream strategy for AR mitigation nowadays, though the outcomes remain a complicated issue sometimes (Casewell 2003). Recent studies suggested that the development and dissemination of AR involves multiple risk factors in addition to antibiotic exposure (Smith and others, 2004; Wang, 2009; Knapp and others, 2009; Heuer and others, 2011; Allen and others, 2010), including significant contribution from commensal bacteria and host digestive system (Threlfall and others, 2000; Li and Wang,
2010; Zhang and others, 2011). Studies on AR in GI tract highlighted the importance of
GI microbiota in picking up environmental ART bacteria, amplifying AR traits and disseminating AR determinants to the environment through manure (Jernberg and others
2007; Looft and others, 2011; Zhang and others, 2011; Hu and others, 2013). The identification of additional risk factors of AR provided new targets for AR mitigation.
Our previous study showed that different antibiotic administration routes led to significantly difference in the magnitude of AR amplification in mouse GI tract (Zhang
137 and others, 2013). Here we presented a similar study in poultry, the most impactful food-producing animal, to examine the applicability of the concept in a second animal model, and its potential impact on food animal production industry.
Gastrointestinal microbiota is established at early growth stage of chicken (Barnes and others, 1980; Coloe and others, 1984; Amit-Romach and others, 2004). Large AR gene pools were also found established in GI microbiota without any antibiotic exposure in
+ this study. During the study, we selected blaCMY-2 E. coli marker strains, which is one of the intrinsic ART bacteria in chickens previously studied. The impact of antibiotic treatment on AR gene pool in our chicken model was complicated due to other intrinsic
+ blaCMY-2 strains (including those uncultivable). Considering the complexity of natural GI microbiota and the high chance of environmental contamination introduced by common practice, AR gene pool amplified during antibiotic treatment was likely carried by several
Ampr populations. By assessing the AR gene pool, the impact of antibiotic treatment was
+ not fully revealed. For example, our data showed that the inoculated blaCMY-2 E. coli
+ strains amplified more significantly than intrinsic blaCMY-2 strains upon Amp exposure,
but the blaCMY-2 gene pool of Amp-PO and Saline-PO was not significantly different. In
138 the absence of marker strains inocula, intrinsic genus Klebsiella amplified significantly instead of genus Escherichia/Shigella. Nonetheless, in both cases oral exposure to Amp led to greater change of GI microbiota in chickens (inverting the ratio of Proteobacteria and Firmicutes) compared to when Amp was delivered through IM injection. The injection route also caused mild population shift, but mostly retained the abundance of
Firmicutes in GI microbiota, indicating less selective pressure on the GI tract. This result was consistence with previous study (Zhang and others, 2013) and provided further support to our hypothesis that antibiotic administration approaches have critical influence on AR development and amplification in gut microbiota, and can be employed to mitigate
AR. By changing the antibiotic administration route from oral-intake to injection the selective pressure was significantly reduced, which may lead to much lesser extent of AR amplification in host GI tract.
In food animal production, antibiotics are delivered mainly through feed or water for growth promotional, prophylaxis, or therapeutic purposes. Oral delivery of antibiotic not only exposed gut microbiota to unnecessary antibiotic selective pressure, but also has a lower antibiotic bioavailability (Ziv and others, 1979; Frazier and others, 1995; Goetting
139 and others, 2011). Therefore, higher drug dosage is needed in feed/water than IM/IV treatment in order to achieve the same effective antibiotic concentration in the target infection sites (Goetting and others, 2011). In addition, animal manure is widely used as fertilizer nowadays, therefore serving as an important link in the circulation of AR in the ecosystem (Wang, 2009; Heuer and others, 2011). Our study showed that oral antibiotic administration practices commonly applied in food animal production is likely one of the most critical risk factors contributed to the rapid rise of AR worldwide. While further studies are required to assess the impact of additional antibiotics and administration routes, recognizing the current antibiotic administration practices may be a key risk factor for AR is of importance for further development of effective AR control strategy.
Besides antibiotic administration methods, environmental ART bacteria may be part of the AR circulation problem in poultry production. A parallel study spotted significant prevalence of the marker strains in feces from chickens kept in the same room with experiment groups but never exposed to inocula or antibiotic treatment (Figure 4.6). As cages, food and water supplies were not shared, aerosol spread is likely the cause of dissemination of the marker strains among chickens. This result is consistent with
140 previous discovery of concentrated ART bacteria inside poultry house (Brooks 2010).
Aerosol ART bacteria settled in the feeds and water supply are likely to enter the host gut microbial community through conventional food intake, and was later amplified and further spread via poultry manure.
Poultry gut contents transit fast and have short retention time, which may contribute to the fast renewal of GI/fecal microbiota. After lift of the antibiotic selective pressure, the
AR gene pools and the resistant population gradually decreased in both cases. Natural shifting of gut microbiota without antibiotic selective pressure effectively reduced the population of the inoculated ART marker bacteria, making them subdominant and even below detection limit after a short period of time. However, the resistant population became part of the residential population in chicken GI tract, and contributed to the increased of AR in the gut microbiota when the chickens were subjected to antibiotic selective pressure.
141
Figure 4.6. Dynamic of predominant 16S rRNA genes in total fecal DNA extracts from one chicken received neither inoculation nor antibiotic treatment. V3 region of 16S rRNA from the total fecal DNA was amplified. DGGE analysis of the amplicons indicated the accumulation of Eschrichia.coli between D5 to D25 even when this individual had no directly contact to inocula. Inoculated strain clusters (Lane 1) were included. M:
Inoculated Escherichia coli.
142 The development of antibiotic resistance in animal production is a complicated issue involving multiple risk factors. Our study provided an alternative explanation for the major contribution of the food animal production practices on the rapid rise of AR, and thus shed light on potential targeted mitigation strategies.
143 Chapter 5
The efficacy of Lactobacillus crispatus on resistance mitigation in poultry gut
microbiota
5.1 Abstract
Lactobacillus spp. strains have found broad applications as beneficial bacteria including probiotics and as a promising alternative for antibiotic to modulate animal growth. In this study, an antibiotic-susceptible Lactobacillus crispatus strain CG-12 has been isolated and characterized for antibiotic susceptibility profiles and whole genome sequencing.
+ Results from in vitro studies showed that the strain can inhibit the growth of the blaCMY-2
E. coli strains, isolated from natural chicken fecal microbiota. In an in vivo study,
Lactobacillus crispatus CG-12 was examined using a chicken model to test its
+ colonization resistance against the blaCMY-2 E. coli strains in gut microbiota. Chickens
-+ inoculated with a mixture of blaCMY-2 E. coli were treated with ampicillin sodium (Amp) via oral gavaging. Lactobacillus crispatus CG-12 was administrated via oral gavaging
144 before E. coli inoculation, before or after antibiotic treatment. Chicken fecal samples were recovered and subjected to qPCR, denaturing gradient gel electrophoresis (DGGE) and 16S rDNA pyrosequencing assessment. This study found that: 1) Lactobacillus
crispatus CG-12 reduced the prevalence of blaCM-2 gene in newly established GI microbiota; 2) pre-inoculation of Lactobacillus crispatus CG-12 at early stage didn’t significantly prevent the colonization of ART E. coli; 3) 10 days of inoculation of
Lactobacillus crispatus CG-12 had little effect on eliminating the particularly targeted
(inoculated) ART bacteria and reducing AR proliferation during antibiotic challenge; 4) post-antibiotic administration of Lactobacillus crispatus CG-12 didn’t significantly recover the diversified constitution of GI microbiota. These results demonstrated that
Lactobacillus crispatus CG-12 had limited impact on the targeted ART E. coli from colonization to proliferation. However, administration of Lactobacillus crispatus CG-12
significantly reduced the early establishment of blaCMY-2 gene pool. This study demonstrated that the Lactobacillus crispatus was prevalent population in neonatal GI microbiota of chicken, and that antibiotic-susceptible Lactobacillus crispatus CG-12 could reduce early established AR gene pool. But its clonal decontamination activity requires further evaluation against other ART populations.
145 5.2 Introduction
The rapid emergence and dissemination of antibiotic resistance is a critical threat to public health. International consensus has been achieved on limiting unnecessary antibiotic application, especially the antibiotic growth-promoters in food-producing animal farming. Probiotic is suggested as one of the potential alternatives to antibiotic.
The antimicrobial and microbiota-modulation activity of probiotics could be used as strategy to hinder the colonization of pathogenic bacteria, improve overall gut health and thus potentially reduce the applied dosage of antibiotic by improving its action (Vuotto and others, 2014). Probiotic strains can directly reduce the colonization of ART bacteria, for example, probiotic E. coli Nissle 1917 was observed to prevent the colonization of multidrug-resistant E. coli in human gut (Tannock and others, 2011). Other observed AR reduction activities include reducing antibiotic resistance via increasing strain susceptibility, inhibiting resistant gene transfer and performing antagonistic activity against ART strains (Moubareck and others, 2007; Ditu and others, 2011; Naderi and others, 2014). But the mechanisms of probiotics in mitigating AR are not fully established.
146 Current trend of probiotic development is to recruit novel candidate from commensal bacteria in gut microbiota, which might have better colonization and individual-specific benefits (Hill and others, 2014). GI microbiota and resistome established at very early stage of life, which might be a desirable stage for effective probiotic intervention. In previous studies, we isolated an antibiotic-susceptible Lactobacillus crispatus strain
CG-12 from chicken GI tract. In this study, we examined its impact on the growth of
+ blaCMY-2 E. coli strains by in vitro and in vivo studies, for its potential application as a new probiotic,
5.3 Materials and methods
5.3.1 Bacterial strains and culture preparation
+ Three blaCMY-2 Escherichia coli strains were isolated from feces of two 4-day-old broiler chickens (Table 5.1). E. coli strains were incubated separately in Columbia Broth (Becton,
100 Dickinson and Company, Franklin Lakes, NJ) at 37°C. Lactobacillus crispatus
CG-12 was isolated from feces of 3-week-old Leghorn chickens, and was incubated in
MRS broth (Becton, 100 Dickinson and Company, Franklin Lakes, NJ) at 37°C. For inocola preparation, 1 mL of overnight culture was precipitated by centrifugation
147 (8000×g , 1 minute), washed (once) and re-suspended in 1 mL saline. A cocktail of three E. coli strains for inoculation was prepared by mixing the cell suspension of designated strains and standardized to 106 CFU/mL per each strain.
5.3.2 Growth inhibition assessments
5.3.2.1 Agar diffusion
Bacterial competition assays were performed in a 1-by-3 matrix format by an agar diffusion technique (Durso and others, 2004). Supernatant producer and receptor strains were grown overnight in MRS at 37°C anaerobically. Producer strain culture was centrifuged at 10000 ×g for 5 min, and the supernatants were filtered by 0.22mm filter to remove remaining cells. Receptor strain cells were inoculated into tempered soft
Columbia agar (20 µl of cells culture into 3 mL of soft agar) and overlaid onto Columbia agar plates. Three sterile 6-mm-diameter paper disks were placed on the agar in each plate, and 25 µl of each supernatant was inoculated onto each disk. Plates were incubated anaerobically overnight at 37°C. Zones of clearing were recorded in millimeters.
148 5.3.2.2 Efficacy of inhibition by metabolites
Overnight cultures of three E. coli strains (106 CFU/mL) were mixed at equal volume as the E. coli mix. Overnight culture of Lactobacillus crispatus CG-12 (106 CFU/mL, 10 µl) were inoculated into 10 mL MRS broth and incubated anaerobically overnight at 37°C.
The culture was centrifuged at 10,000×g for 5 min, and the supernatant was filtered by
0.22mm filter to remove remaining cells. The inhibition volume of this supernatant against the ART E. coli culture was tested in a series of modulated MRS media listed in
Table 5.2. The media was modulated based on an assumption that 40% nutrient in the supernatant was depleted. Another set of 1× MRS media was modified in pH. The pH was identical to each supernatant-modified media. This set of media was used to evaluate the impact of pH on the inhibition activity.
149 Supernatant% Supernatant 3× MRS 1× MRS pH Total
(mL) (mL) (mL) (mL)
0% - - - 6.42 5
5% 0.25 0.05 4.7 5.87 5
10% 0.5 0.1 4.4 5.49 5
20% 1 0.2 3.8 5.03 5
40% 2 0.4 2.6 4.58 5
50% 2.5 0.5 2 4.42 5
Table 5.1 List of modulated media used for growth inhibition test.
5.3.3 The chicken model.
All procedures were approved by the Institutional Animal Care and Use Committee
(protocol No. 2012A00000061, The Ohio State University, Columbus, OH). Leghorn chicken were hatched and maintained at the Ohio Agricultural Research and
Development Center (OARDC) poultry research teaching farm (two birds per cage with separate feed and water supply, controlled temperature, filtered air in the room and sterilized feed). Chicken fecal samples were collected on-site and examined for the
presence of blaCMY-2 gene pools and microbial profile. Since the Day 5 post-hatch, 150 + 6 chicken were inoculated with blaCMY-2 E. coli cocktail (0.2mL/bird, 10 CFU/mL) every
24 hours for 4 consecutive days via gavage feeding using 20ga X 1.5 in animal feeding needle (Fine Science Tools, Foster City, CA, USA). Chickens in non-inoculated control groups were fed with 0.2 mL of saline by the same method. Chicken were then set in cages for 11 days before antibiotic treatment, allowing the microbiota to stabilize.
5.3.4 Lactobacillus crispatus and antibiotic administration.
The Lactobacillus crispatus CG-12 was susceptible to ampicillin. In order to monitor its impact on AR profile during common ampicillin administration practice, low veterinary
Amp dosages (30 mg/kg body weight per day) were selected instead of 300mg/kg/day.
Lactobacillus crispatus CG-12 was administrated in three periods: 1) Day 2 ~ Day 4 post-hatch; 2) throughout the stabilization and 3) post antibiotic challenge on Day 25 ~
Day 28. During these periods, chickens were inoculated with Lactobacillus crispatus
CG-12 suspension (0.2mL/bird, 106 CFU/mL) every 24 hours for 4 consecutive days via gavage feeding using 20ga X 1.5 in animal feeding needle (Fine Science Tools, Foster
City, CA, USA). Chickens were grouped and treated as shown in Table 5.1. Each groups contained at least 6 chickens.
151 Pre-AR Pre-antibioti Post-antibot
+ inoculation blaCMY-2 c Amp ic Group L. crispatus E. coli inocula L. crispatus (30mg/kg) L. crispatus
inocula inocula inocula
Lc-Saline + + - - -
Saline-saline - + - - -
Lc-Amp - + + + -
Saline-Amp - +. - + -
Amp-Lc - + - + +
Amp-Saline - + - + -
Table 5.2. Leghorn chicken groups subject to inoculation and antibiotic administration treatments. - : saline administrated at same column.
5.3.5 Sample collection.
Fresh feces were collected from each chicken on-site in the rearing facility. Fecal samples were collected at the 1st and last day of Lactobacillus inoculation, once a day during the
152 antibiotic administration period, and once every three days during antibiotic withdrawal period up to 14 days from initial antibiotic exposure.
5.3.6 DNA extraction.
Total DNA from chicken fecal samples for real-time quantitative PCR (qPCR) and denaturing gradient gel electrophoresis (DGGE) analyses were extracted according to published method (Yu and Morrison 2004).
5.3.7 Real-time quantitative PCR.
TaqMan real-time PCR protocol was used to assess blaCMY-2 and 16S rRNA gene pools in total DNA extracted from chicken fecal samples as described previously (Zhang and others, 2013). The sequences of the primers were 5’-GCCGTTGATGATCGAATC-3’ and
5’-GCGTATTGGCGATATGTAC-3’, with blaCMY-2 probe 5’-6FAM
AGTTCAGCATCTCCCAGCCTAATCC-BHQ1-3’ (Zhang and others, 2013). The primers were synthesized by Sigma-Aldrich (St. Louis, MO, USA) and the probe was
153 synthesized by and Biosearch Technology Inc. (Novato, CA, USA). Each sample was assessed and analyzed in duplicates on a CFX96 system (Bio-Rad, Hercules, CA, USA).
5.3.8 DGGE analysis.
The 16S rRNA V3 region was used for amplification of partial 16S rRNA gene following previous procedure (Muyzer and others, 1993). The sequences of PCR primers used were
16S-357F-GC and 16S-518R; products were loaded on to an 8% acrylamide gel with a urea gradient from 40% to 60%. Electrophoresis was performed at 60°C, 83 V for 16 h using the Dcode system for DGGE (Bio-Rad, Hercules, CA, USA). The finishing gel was stained with 0.01% ethidium bromide and imaged under ChemiDoc XRS system
(Bio-Rad, Hercules, CA, USA).
For analysis of the impact of Lactobacillus crispatus CG-12 on AR establishment (Day 5)
+ and blaCMY-2 colonization in GI microbiota (Day 9), and fecal DNA of 6 chickens from
Saline-Saline group (SS1-SS6), 4 chicken from Lc-Saline group (LS1-LS4) and 1 control subjects (C) at Day 5 post-hatch were used as the template to amplify the 16S rRNA gene
V3 region. 154 To analyze the predominant bacterial population in GI microbiota after antibiotic administration, chickens exposed to 30 mg/kg body weight/day Amp via the oral route were used as the template to amplify the 16S rRNA gene V3 region. The fecal DNA of 4 chickens from Lc-Amp group (LA1~LA4), 4 chickens from Saline-Amp group
(SA1~SA4) were used as the template to amplify the 16S rRNA gene V3 region.
5.3.9 16S Metagenomic Analysis.
For microbiota analysis, 3 chickens were randomly selected from group Amp-Lc and
Amp-Saline. Fecal DNA of Day 25 and Day 28 from each chicken was subjected to analysis. The V3/V4 portion of the 16S rRNA gene of the subjects were amplified by
PCR following the standard protocol of16S Metagenomic Sequencing Library
Preparation (Illumina support, 2013), and the products were sequenced on an Illumina
Miseq sequencer at OARDC Molecular and Cellular Image Center. Paired-end joining and quality filtering were performed with Qiime (Caporaso and others, 2010). Only sequences longer than 450bp with Phred quality score higher than 19 were used for phylotype analysis. Operational Taxonomic Units (OTUs) were picked using open-reference OTU picking process with 97% sequence similarity. And 10% of the
155 sequences that failed to hit the reference database were subjected to de novo clustering.
Other quality control perimeters were set as default. Phylogenetic analysis and taxonomic assignments of the V3 and V4 portion of the 16S rRNA gene were made using
Greengenes database (version 13_8). Additional phylotype comparisons and analysis were performed with the QIIME diversity analyses module.
5.3.10 Statistics
One-way ANOVA analysis of the population size of AR gene pools was performed in
SAS (version 9.4), to compare difference between the three batches of chickens.
Significance was declared at P < 0.05.
5.4 Results
3.4.4 Growth inhibition assessments
The supernatant of Lactobacillus crispatus CG-12 formed inhibition zones with 8-9mm in diameters on all E. coli plates, while no inhibition zone of E. coli supernatant was observed on the cultured plates of Lactobacillus crispatus CG-12 (Table 5.3).
156 % Supernatant pH CFU/mL Log10(CFU/mL)
Control 0 6.4 6.7✕108 8.8
20% Supernatant 20 5.3 5.7✕105 5.8
pH 5.3 0 5.3 2.7✕106 6.4
40% Supernatant 40 4.6 <10 <1
pH 4.6 0 4.6 7.8✕102 2.9
50% Supernatant 50 4.4 <10 <1
pH 4.4 0 4.4 <10 <1
+ Table 5.3 The growth of blaCMY-2 E. coli (CFU/mL) in modulated MRS media. CFU: colony forming unit.
In the 0% supernatant-modified media, overnight culture of E. coli had a total count of
8.8 log10 CFU/mL. The 20% supernatant supplement reduced E. coli count by 3 logs,
ending up in 5.8 log10 CFU/mL. The corresponding 1× MRS (pH 5.0) had 6.4 log10
CFU/mL of E. coli. With 40% supernatant, less than 1 log10 CFU/mL was detected in the
157 supernatant-modified media, while 2.9 log10 CFU/mL was observed in the corresponding pH-modified media.
5.4.1 Early colonization of Lactobacillis crispatus and reduced AR gene pool in GI tract of chicks
Six chickens from Saline-Saline group, four chickens from Lc-Saline group and one free of any treatment were randomly picked to study the constitution of gut microbiota.
DGGE analysis showed Lactobacillus crispatus was among the most predominant populations at Day 5 post-hatch, regardless of Lactobacillus crispatus CG-12 inocula.
(Figure 5.1).
158 1 2 3 4 5 6 7 8 9 10 11 12 13
Lactobacillus crispatus CG-12
ART E.coli maker strain
L M C LS1 LS2 LS3 LS4 SS1 SS2 SS3 SS4 SS5 SS6
Figure 5.1 Predominant 16S rRNA genes in total fecal DNA from chicken after 3 days’
inoculation of Lactobacillus crispatus CG-12. Lane 1: Lactobacillus crispatus CG-12;
+ Lane 2: blaCMY-2 E. coli marker strain. Lane 3: sample from control group; Lane 4-7: 4
individual samples from Lc-Saline group; Lane 8-13: 6 individual samples from
Saline-Saline group.
The blaCMY-2 gene pool and 16S rRNA pool was analyzed via qPCR. Seven chickens
from Saline-saline group and eight from Lc-Saline group were subjected to assessment.
159 The ratio of blaCMY-2 copies vs. 16S rRNA copies was calculated ((blaCMY-2 /16S) %) to
show the prevalence of blaCMY-2 in total bacterial load. In the Saline-Saline group, 6 out
of 7 has a (blaCMY-2 /16S) % ration larger than 0.77, with only one exception (0.12). There
were two subjects in this group had extremely high prevalence of blaCMY-2 gene, accounting for 7.14% and 54.96% of the total 16S copies. In the Lc-Saline groups,
however, the (blaCMY-2/16S) % ration was generally low in all subjects: A (blaCMY-2 /16S) % ration lower than 0.20 was detected in 7 out of 8 subjects; the highest one was 0.55, still lower than the average ration in Saline-Saline group.
+ 5.4.2 Insignificant inhibition of the colonization of blaCMY-2 marker strains
Six chickens from Saline-Saline group, four chickens from Lc-Saline group and one free of any treatment were randomly picked to study the constitution of gut microbiota on Day
+ 9, right after the inoculation of blaCMY-2 E. coli. DGGE analysis showed the
Lactobacillus crispatus population was better maintained in Lc-Saline group, but the
+ colonization of blaCMY-2 E. coli was not affected by pre-inoculation of the Lactobacillus
strain (Figure 5.2). AR gene pool was increased from 8.8±0.3 log10(gene copies/g) to
9.9±0.6 log10(gene copies/g) in Saline-Saline group, and from 8.2±0.2 log10(gene
160 copies/g) to 9.8±1.0 log10(gene copies/g) in Lc-Saline group. Overall, the blaCMY-2 gene pool had about 1 log increase from Day 5 to Day 9 regardless of the inoculation of the
+ blaCMY-2 E. coli, and the E. coli inocula didn’t significantly increase its prevalence in gut microbiota.
161 1 2 3 4 5 6 7 8 9 10 11 12 13
Lactobacillus crispatus CG-12
ART E.coli maker strain
L M C LS1 LS2 LS3 LS4 SS1 SS2 SS3 SS4 SS5 SS6
Figure 5.2 Predominant 16S rRNA genes in total fecal DNA from chicken after 4 days’
+ inoculation of blaCMY-2 E. coli following lactobacillus inocula. Lane 1: Lactobacillus
+ crispatus CG-12; Lane 2: blaCMY-2 E. coli marker strain. Lane 3: sample from control
group; Lane 4-7: 4 individual samples from Lc-Saline group; Lane 8-13: 6 individual
samples from Saline-Saline group.
162 5.4.3 Insignificant reduction of AR gene pool during antibiotic treatment
Four chickens from Saline-Amp group and eight from Lc-Amp group were subjected to
assessment of the blaCMY-2 and 16S rRNA gene pool, to show the prevalence of blaCMY-2
on Day 21(during treatment) and Day 25 (after treatment). Large prevalence of blaCMY-2
gene pool was detected in both groups on Day 21: blaCMY-2 and 16S rRNA gene pool was
8.7±0.8 log10(gene copies/g) and 8.5±0.7 log10(gene copies/g) in Saline-Amp group;
while in Lc-Amp group blaCMY-2 and 16S rRNA gene pool was 10.0±1.0 log10(gene
copies/g) and 9.2±1.07 log10(gene copies/g). On Day 25, blaCMY-2 and 16S rRNA gene
pool was 9.8±0.9 log10(gene copies/g) and 10.5±1.0 log10(gene copies/g) in Saline-Amp
group; while in Lc-Amp group blaCMY-2 and 16S rRNA gene pool was 9.2±0.9 log10(gene
copies/g) and 10.4±0.8 log10(gene copies/g). The overall prevalence of blaCMY-2 decreased from Day 21 to Day 25, but no significant difference was observed between this two treatment groups.
+ The predominance of blaCMY-2 E. coli marker was not reduced by pre-antibiotic inoculation of Lactobacillus crispatus CG-12 (Figure 5.3). The selective enrichment of E. coli on Day 21 was more significant in Lc-Amp group.
163 A possible explanation is that because the Lactobacillus crispatus CG-12 was susceptible to Amp, very likely that this strain was selectively eliminated during antibiotic treatment and therefore made no contribution in the treatment groups.
164 A
Continued
Figure 5.3 The predominant bacterial population in chicken GI microbiota before, during and after antibiotic administration. Predominant GI bacterial population on A) Day 20, before antibiotic treatment; B) Day 21, during antibiotic treatment. C) Day 25, after
+ antibiotic treatment. Lane 1: Lactobacillus crispatus CG-12; Lane 2: blaCMY-2 E. coli marker cocktail; Lane 3-6: 4 individual samples from Lc-Amp group; Lane 7-10: 4 individual samples from Saline-Amp group.
165 Figure 5.3 Continued
B
Continued
166 Figure 5.3 Continued
C
167 5.4.4 The post-antibiotic change of microbiota constitution
Three randomly selected chickens from Amp-Lc and Amp-Saline group was subjected to the 16S rRNA phylotyping analysis, to illustrate the impact of post-antibotic inoculation of Lactobacillus crispatus CG-12 (Figure 5.4).
168
Figure 5.4 The phylum distribution of GI microbiota post-antibiotic treatment. Sets of columns on the left and middle left: 3 samples from Amp-Saline (AS) group on Day 25
(left) and Day 28(middle left); sets of columns in middle right and right: 3 samples from
Amp-Lc (AL) group on Day 25 (middle right) and Day 28 (right).
169 5.5 Discussion and conclusion
In this study, we evaluated the in vitro and in vivo colonization resistant of Lactobacillus
+ crispatus CG-12 against blaCMY-2 E. coli in poultry GI microbiota.
The bacteria competition test shows that Lactobacillus crispatus CG-12 has good in vitro
+ inhibition ability against the blaCMY-2 E. coli. The inhibition is largely due to its ability to produce lactic acid and reduces the pH, because media modified into the same pH exhibited similar growth inhibition. Except for lactic acid, Lactobacillus crispatus CG-12 might also produce other inhibitive substances, which contributed to the extra reduction of E. coli in 20% and 40% supernatant-modified media compared to corresponding pH-modified media.
+ The in vivo colonization of Lactobacillus crispatus CG-12 against blaCMY-2 E. coli in was further evaluated in poultry GI microbiota. Lactobacillus crispatus CG-12 is a commensal bacteria isolated from chicken GI microbiota, which should have good colonization fitness in chicken gut. Analysis of the constitution of GI microbiota on Day
5 shown that Lactobacillus crispatus was predominate population at early growth stage of 170 chicken, which is constant with previous isolate-based research (Lu and others, 2003).
The predominance implied a favored environment for Lactobacillus crispatus in chicken
GI tract at this stage of growth. The decrease of blaCMY-2 gene pool indicates the
- successful colonization of blaCMY-2 Lactobacillus crispatus CG-12 in the GI microbiota.
- It is possible that the blaCMY-2 , well-colonized Lactobacillus crispatus CG-12 compete with homogeneous and heterogeneous bacteria and contribute to a reduction of ART bacteria and AR genes.
Lactobacillus crispatus losses its prevalence during chicken maturation, and other
Lactobacillus and Firmicutes population will take dominance during the natural transition of GI microbiota (Lu and others, 2003). The ineffectiveness of Lactobacillus crispatus
CG-12 to reduce AR gene pool and ART bacteria during Week 2-3 might result from loss of predominance in the GI microbiota. As Lactobacillus crispatus CG-12 was susceptible to ampicillin, it was also likely selective eliminated by antibiotic treatment in Week 4.
Furthermore, the targeted ART bacteria, E. coli, were distantly related to Lactobacillus crispatus CG-12. They might locate in distant niches in the gut, making it more difficult for Lactobacillus crispatus CG-12 to eliminate. Early study on displacement of
171 indigenous ART E. coli was achieved by using susceptible strains from the same species
(Linton and others, 1978). Future trails to use commensal or probiotic stains for clonal decontamination should take consideration of the ecological position of the targeted strains.
The constitution of GI microbiota recovers fast once the antibiotic selective pressure was removed. The dominance of Firmicutes was recovered within three days without any intervention. The inoculation of Lactobacillus crispatus CG-12 didn’t accelerate the recovery; instead the prevalence of Proteobacteria was even higher in the inoculated group. Further analysis should be conducted to explain such phenomenon. It is worth noting that the numbers of subjects used in the study may be a factor to consider.
In conclusion, inoculation of Lactobacillus crispatus CG-12 could be a promising strategy to reduce early colonization of AR in chicken GI microbiota. But its effectiveness of AR elimination is limited as the chicken matures.
172 Chapter 6
Future Direction
Effective antibiotic resistance mitigation in food-producing animals is important for food safety and public health. Our study on chicken gastrointestinal/fecal microbiota illustrated that AR gene pool established at early stage of life, and persisted in GI tract without antibiotic exposure. By changing the antibiotic administration route from gavage feeding to intramuscular injection, the impact of antibiotic on GI microbiota composition was significantly reduced. AR mitigation in GI tract was also observed when susceptible commensal bacteria were inoculated at young age. This study further confirmed that oral antibiotic administration and gut microbiota of digestive tract of food-producing animals have critical roles in AR ecology. Commensal microbiota in digestive tract and feces of food-producing animal are likely promising targets for future AR mitigation strategies.
173 6.1 Prevention of horizontal gene transfer in GI microbiota via genetic modified strains.
The GI commensal microbiota is a good source for selecting beneficial strains, such as probiotics and therapeutic strains (Kassam and others, 2012). Free of AR determinants should be a safety criteria of new additional strains. Current sequencing techniques allows for the genome-wide search for AR determinants in potential strains. Using genetic modification tools, such as CRISPR-Cas9 system, AR determinants and gene transfer elements can be efficiently eliminated via DNA level gene silencing and knock-out.
The whole genome sequence data of Lactobacillus crispatus CG-12 indicates the presence of multiple AR genes, which limited its beneficial applications. Knock-out of the AR genes as well as gene transfer elements, such as integron and phage sequences, might further reduce AR by minimizing horizontal gene transfer. Compare to classic AR control practices, genetic modification might be a direct and targeted strategy for AR mitigation.
174 6.2 Colonization resistant against ART bacteria by strain mixtures
The bacterial hosts of AR determinants have high diversity and might occupy different ecological niche in GI tract. Besides, the AR profile might have large difference between individual hosts. In this case, replacing ART populations by a single susceptible strain is far from sufficient. Finding a combination of susceptible commensal strains that cover major populations of GI microbiota, and using the strain mix to eliminate their ART counterparts is likely a promising AR control strategy. This strategy may require a comprehensive analysis of the original AR profile in the host, in order to generate a host-specific combination of susceptible strains. The resulting strain-mixture should have a higher AR elimination efficacy than single strains.
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