Genotypes and Phenotypes of Staphylococci on Selected Dairy Farms in Vermont Robert Mugabi University of Vermont

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2018 Genotypes And Phenotypes Of Staphylococci On Selected Dairy Farms In Vermont Robert Mugabi University of Vermont

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GENOTYPES AND PHENOTYPES OF STAPHYLOCOCCI ON SELECTED DAIRY FARMS IN VERMONT

A Dissertation Presented

Robert Mugabi

The Faculty of the Graduate College

The University of Vermont

In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Specializing in Animal, Nutrition, and Food Sciences

May, 2018

Defense Date: December 13th, 2017 Dissertation Examination Committee:

John W. Barlow, DVM, PhD., Advisor Matthew Wargo, Ph.D., Chairperson David Kerr, PhD Douglas I. Johnson, Ph.D. Simon Dufour, DMV, PhD Cynthia J. Forehand, Ph.D., Dean of the Graduate College

ABSTRACT

The genus Staphylococcus contains at least 47 species and 23 subspecies. Bacteria in this genus are ubiquitous; many are commensals on human and animal skin and can be opportunistic pathogens. In dairy cattle, staphylococci are the leading cause of intramammary infections (IMI) and mastitis. Mastitis is the inflammation of the mammary gland, and is one of the leading infectious diseases causing production losses in the dairy industry. Based on the ability to clot blood plasma in vitro, members of the genus can be divided into two groups: coagulase positive staphylococci (CPS) and coagulase negative staphylococci (CNS). In the dairy industry, Staphylococcus aureus is the most common CPS causing mastitis and is considered a major mastitis pathogen compared to the CNS, which as a group have been described as minor mastitis pathogens. The CNS species are increasingly recognized as an important cause of bovine mastitis, although the relative role of some species is still uncertain. Our understanding of the local and global epidemiology of CNS mastitis is improving with application of more accurate DNA sequence-based species identification methods and techniques to discriminate between strains within species. These factors have led to a shift in perspective, with the CNS being recognized as a heterogeneous group where some species are more important than others in bovine mastitis. The major goals of this thesis were to describe Staphylococcus mastitis epidemiology, and to identify phenotypes that may contribute to persistence in various niches on selected dairy farms in Vermont. We conducted 2 field studies on 2 groups of farms in Vermont. In the first study, we collected S. aureus isolates from bulk tank milk of 44 certified organic dairy farms. In the second field study, we completed quarter milk, cow skin, and environmental sampling of 5 herds that make farmstead cheeses. In both studies, we used non-selective and selective agar medium to isolate staphylococci from the farm sources. From these studies, we collected 1,853 Staphylococcus spp. isolates. We used PCR-amplicon sequence-based species identification to describe Staphylococcus species diversity on these selected Vermont dairy farms. S. aureus isolates were strain- typed using an established Multilocus Sequence Typing (MLST) scheme. A novel MLST scheme was developed to investigate the molecular epidemiology of S. chromogenes, one of the leading CNS species causing bovine mastitis in this and other studies. We also evaluated antibiotic resistance and biofilm formation phenotypes and genotypes of staphylococci to test the hypothesis that these phenotypes may be associated with strain types. In the study of organic dairy farms, 20 S. aureus strain types (STs) were identified, including ten novel STs. The majority of STs belonged to lineages or clonal complexes (CCs) previously identified as cattle adapted (e.g. CC97 and CC151). Associations between ST and carriage of beta-lactam resistance and biofilm forming capacity were identified among the S. aureus isolates from these farms. In the 5-herd study, a total of 27 different staphylococci species were identified from various niches including humans, but only five species; S. chromogenes, S. aureus, S. haemolyticus, S. simulans, and S. xylosus were commonly identified to cause IMI. S. aureus and S. chromogenes strain types were niche specific.

ACKNOWLEDGEMENTS

This dissertation wouldn’t have been finished without the help from a lot of people over the past five years. First and foremost, I would like to acknowledge God for perfect health and wisdom. Secondly, I thank my advisor John Barlow for believing and accepting me to work in his laboratory even when he didn’t know me so much. I acknowledge his mentorship and desire to make me a better scientist who I am today, evidenced by discussions we have heard about data interpretation, statistics, reviewing manuscripts, grant writing, and availing resources for me to go to scientific conferences. I appreciate all the past and present undergraduate and graduate students, postdocs who have helped me in one way or another. I can’t forget our former laboratory technician

Amanda Ochoa who helped me get acclimatized to the laboratory in my initial years, as well as field sample collection. I also extend my sincere gratitude to my thesis committee members for their immense advice. I acknowledge Dr. George Sensabaugh who was influential in the development of the novel S. chromogenes MLST scheme. Last but not least, I extend my appreciation to my family, UVM office of international education, and friends for their immeasurable academic, emotional, social, and spiritual support during my five-year tenure in graduate school.

TABLE OF CONTENTS Page ACKNOWLEDGEMENTS ...... ii LIST OF TABLES ...... viii LIST OF FIGURES ...... viiii CHAPTER 1 : COMPREHENSIVE LITERATURE REVIEW ...... 1 1.1 Introduction ...... 2 1.2 Dairy farming systems ...... 7 1.3 Mastitis diagnosis and economic implication ...... 8 1.4 Mastitis epidemiology and control ...... 12 1.6 Genus Staphylococcus ...... 18 1.7 Staphylococci species identification ...... 21 1.8 Strain typing of staphylococci ...... 27 1.8.1 Phenotypic typing methods ...... 29 1.8.1.1 Biotyping ...... 29 1.8.1.2 Antibiogram typing ...... 30 1.8.1.3 Serotyping ...... 31 1.8.1.4 Phage typing ...... 32 1.8.1.5 Multilocus Enzyme Electrophoresis (MEE) ...... 33 1.8.2 Genotypic typing methods ...... 34 1.8.2.1 Restriction enzyme based methods ...... 34 1.8.2.1.1 Ribotyping ...... 34 1.8.2.1.2 Pulsed Field Gel Electrophoresis (PFGE) ...... 35 1.8.2.2 Polymerase chain reaction (PCR) based methods ...... 36 1.8.2.2.1 Random Amplified Polymorphic DNA (RAPD) ...... 36 1.8.2.3 Typing methods combining Restriction enzyme digests and PCR amplification ...... 37 1.8.2.3.1 Amplified Fragment Length Polymorphism (AFLP) ...... 37 1.8.2.4 Sequencing based typing ...... 37 1.8.2.4.1 Multilocus Sequence Typing (MLST) ...... 37 1.8.2.4.2 Multilocus Variable Number of Tandem Repeats Analysis (MLVA) ...... 41 1.8.2.4.3 Whole Genome Sequencing (WGS) ...... 42 1.9 Staphylococci virulence factors ...... 43 1.9.1 Adhesion to host cells and extracellular matrix ...... 44 1.9.2 Host tissue invasion and damage ...... 45 1.9.3 Evasion of host defense mechanisms ...... 47 1.9.3.1 Staphylococcal neutrophil evasion ...... 47 iii

1.9.3.2 Inactivation of the complement ...... 49 1.9.3.3 Lysozyme Evasion ...... 49 1.9.4 Biofilm formation ...... 50 1.9.4.1 Micro-titer plate in vitro biofilm assay ...... 54 1.10 Staphylococci antimicrobial resistance ...... 57 1.11 Summary ...... 62 CHAPTER 2 : STAPHYLOCOCCUS AUREUS MULTI-LOCUS SEQUENCE TYPES FROM VERMONT ORGANIC FRARM BULK TANK MILK ARE ASSOCIATED WITH IN VITRO BIOFILM CAPACITY AND ANTIMICROBIAL SUSCEPTIBILITY ...... 63 2.1 Abstract ...... 64 2.2 Introduction ...... 65 2.3 Materials and Methods ...... 68 2.3.1 Study design and reporting ...... 68 2.3.2 Farm sampling ...... 69 2.3.3 Bacteriologic Culture ...... 70 2.3.4 Bacterial isolation and identification ...... 71 2.3.5 Selection of isolates for further genotypic and phenotypic analysis ...... 73 2.3.6 Multi-locus sequence typing ...... 74 2.3.7 Antimicrobial susceptibility testing ...... 74 2.3.8 Biofilm genotyping and in vitro assay ...... 75 2.3.9 Data analysis ...... 77 2.4 Results ...... 78 2.4.1 MLST ...... 78 2.4.3 Antibiotic susceptibility ...... 79 2.4.4 Biofilm phenotypes and genotypes ...... 80 2.5 Discussion ...... 81 2.6 Conclusion ...... 87 2.7 Acknowledgements ...... 87 2.8 References ...... 87 CHAPTER 3 : TUF GENE SPECIES IDENTIFICATION REVEALS UNIQUE STAPHYLOCOCCUS DIVERSITY ON SELECTED DAIRY FARMS PRODUCING FARMSTEAD CHEESE IN VERMONT ...... 100 3.1 Abstract ...... 101 3.2 Introduction ...... 102 3.3 Materials and Methods ...... 106 3.3.1 Herd and sample collection ...... 106 iv

3.3.2 Sample processing and isolation of staphylococci ...... 108 3.3.3 DNA extraction ...... 109 3.3.4 Polymerase Chain Reaction (PCR) ...... 109 3.3.5 Multi-locus Sequence Typing (MLST) ...... 112 3.3.6 Definition of staphylococci IMI ...... 112 3.3.7 Statistical Analysis ...... 112 3.4 Results ...... 113 3.4.1 Bacterial identification ...... 113 3.4.2 Bacteriologic Findings in Various Niches ...... 114 3.4.3 S. aureus MLST ...... 115 3.4.4 Association of Staphylococcus Species and Somatic Cell Count (SCC) ...... 116 3.7 Acknowledgments ...... 125 3.8 References ...... 125 CHAPTER 4 : A MULTILOCUS SEQUENCE TYPING SCHEME PROVIDES INSIGHTS INTO THE DIVERSITY OF STAPHYLOCOCCUS CHROMOGENES ISOLATED FROM DAIRY FARMS FROM THE UNITED STATES AND BELGIUM ...... 137 4.1 Abstract ...... 138 4.2 Introduction ...... 139 4.3 Materials and Methods ...... 141 4.3.1 Bacterial isolates ...... 141 4.3.2 Bacterial identification ...... 142 4.3.3 PCR Screening for the blaZ and mecA genes ...... 143 4.3.4 MLST ...... 144 4.3.5 Data analysis ...... 144 4.4 Results ...... 145 4.4.1 Strain Types ...... 145 4.4.2 Identification of clonal complexes (CCs) ...... 147 4.4.3 Prevalence of the blaZ and mecA genes ...... 148 4.5 Discussion ...... 148 4.5.1 MLST strain types geographical distribution ...... 148 4.5.2 Strain types niche specificity ...... 149 4.5.3 Phylogenetic analysis ...... 151 4.5.4 BlaZ and mecA genes ...... 152 4.6 Conclusions ...... 153 4.7 Acknowledgments ...... 153 4.8 References ...... 154

CHAPTER 5: ANTIBIOTIC RESISTANCE AND BIOFILM FORMATION OF STAPHYLOCOCCI ISOLATED FROM SELECTED DAIRY FARMS IN VERMONT ...... 164 5.1 Abstract ...... 165 5.2 Introduction ...... 166 5.3.1 Source of Isolates ...... 170 5.3.2 Antibiotic Susceptibility Testing ...... 170 5.3.3 Genetic screening for antibiotic resistance markers ...... 172 5.3.4 Biofilm genotyping and in vitro assay ...... 173 5.4 Results ...... 175 5.4.1 Detection of β- lactam antibiotic resistance genes ...... 175 5.4.2 Antimicrobial Susceptibility Testing ...... 176 4.4.3 Comparison of phenotypic resistance and presence of β-lactam antibiotic resistance genes ...... 178 5.4.4 Biofilm formation of the staphylococci ...... 178 5.5 Discussion ...... 179 5.6 Conclusion ...... 188 5.7 Acknowledgments ...... 189 5.8 References ...... 189 CHAPTER 6 : CONCLUSIONS AND FUTURE DIRECTIONS ...... 204 CHAPTER 7 : COMPREHENSIVE BIBLIOGRAPHY ...... 211

LIST OF TABLES

Table 1-1: Species in the genus Staphylococcus ...... 20 Table 1-2: Common CNS identification methods for epidemiologic purposes on dairy farms ...... 27 Table 1-3: Staphylococci virulence factors associated with biofilm formation identified in isolates obtained from dairy cattle ...... 50 Table 1-4: Common methods used for assessment of biofilm formation of staphylococci on dairy farms ...... 56 Table 1-5: Animals as potential reservoirs of bacteria with mec homologues ...... 61 Table 2-1: Allelic profile of the 20 strain types identified ...... 98 Table 2-2: Broth micro-dilution in vitro susceptibility testing of S. aureus ...... 98 Table 3-1: Distribution of staphylococci species by farm ...... 133 Table 4-1: Prevalence of blaZ gene presence within different strain types ...... 158 Table 4-2: Clonal complexes, strain types, and number of isolates in each country and niche of isolation ...... 162 Table 4-3: Allelic profile of 62 S. chromogenes STs ...... 163 Table 5-1: Source of isolates ...... 198 Table 5-2: Distribution of MIC for S. aureus and CNS ...... 199 Table 5-3: Antibiotic susceptibility categories of S. aureus and coagulase negative staphylococci ...... 201 Table 5-4: Comparison of phenotypic and genotypic β-lactam resistance among the staphylococci ...... 201

vii

LIST OF FIGURES

Figure 1-1: Differential hemolysis patterns of two S. aureus strains isolated from bovine subclinical mastitis ...... 23 Figure 1-2: Scheme for presumptive identification of staphylococci ...... 26 Figure 1-3: eBurst analysis of some S. aureus clonal groups ...... 41 Figure 2-1: Map of Vermont showing S. aureus geographic distribution of CCs (A) and a dendrogram showing phylogeny and frequency (Freq.) of STs, % penicillin resistance and number of farms a particular ST was isolated (B) ...... 96 Figure 2-2: eBurst analysis of the S. aureus sequence types ...... 97 Figure 2-3: Biofilm formation of S. aureus lineages from organic farms on (A) and biofilm categories (B) ...... 97 Figure 3-1: Box plot for association between Staphylococcus species and somatic cell count ...... 136 Figure 4-1: eBurst analysis of S. chromogenes strain types ...... 159 Figure 4-2: Dendrogram of the S. chromogenes STs ...... 160 Figure 4-3: Distribution of top four predominant strain types in different niches on five farms where whole herdd quarter milk sampling was done in Vermont (A) and number of strain types causing IMI (B) per farm ...... 161 Figure 5-1: Distribution of blaZ and mecA gene presence among the Staphylococcus species ...... 200 Figure 5-2: Overall biofilm formation of staphylococci (A) and top 3 species causing IMI...... 202 Figure 5-3: Biofilm categories by species ...... 203 Figure 6-1: Biofilm formation of S. aureus lineages from organic farms on untreated (white box plots) and treated (red box plots) surfaces (A) and STs within CC97 (B) ...... 207

viii

CHAPTER 1 : COMPREHENSIVE LITERATURE REVIEW

1.1 Introduction

Staphylococci are the most common cause of mastitis among domestic ruminants, including dairy cattle. Staphylococci are ubiquitous on dairy farms from which at least 19 species have been isolated from diverse sources, including the dairy farm environment

(Piessens et al., 2011, De Visscher et al., 2014). These bacteria are normal mammalian normal skin commensal organisms as well as opportunistic pathogens. Some

Staphylococcus species can be isolated from fermented food products including cheese and may positively contribute to cheese flavor and texture (Bockelmann W., 2001,

Bockelmann, 2002, Place et al., 2003). Some staphylococci have been proposed to be beneficial commensal organisms, contributing to a healthy microbiota that may prevent colonization by pathogenic species or strains (Braem et al., 2014, De Vliegher et al.,

2004). While it is generally accepted that S. aureus (classified as a major mastitis pathogen and a zoonotic pathogen) control is a worthy goal for dairy farms, it is less clear whether other Staphylococcus species should be targeted for control, and if so, which species should be targeted for control. One problem is identifying which Staphylococcus species or strains are beneficial commensal organisms that should be encouraged or promoted, and which may be opportunistic pathogens that should be avoided or limited.

The purpose of this research is to advance our understanding of Staphylococcus epidemiology on dairy farms. In these studies, molecular tools were applied to enhance our understanding of species and strain diversity in dairy farm systems. The research included field surveys conducted on Vermont farms marketing milk or milk products to specialty markets because it was recognized that staphylococci are the most common

cause of mastitis on these farms. At least in the case of farms making farmstead or artisan cheese, it was also recognized that some Staphylococcus species may be positively contributing to cheese flavor and texture. Therefore, an improved understanding of this group of organisms was the broad goal of this research. Quantifying antibiotic resistance and biofilm formation of the Staphylococcus species isolates from these farms was a secondary goal, as these phenotypes may contribute to environmental persistence, persistent colonization or infection, or treatment failures of Staphylococcus infections.

Staphylococci cause soft tissue infections, bone infections, pneumonia, septicemia, endocarditis, and urinary tract infections in humans and other animals

(Foster, 1996, Lowy, 1998, Becker et al., 2014, Tong et al., 2015a). In the dairy industry, staphylococci are the predominant bacteria isolated from cows with clinical and subclinical mastitis (Pyorala and Taponen, 2009). Staphylococcus aureus is generally coagulase positive and continues to be described as a major mastitis pathogen. In comparison, the coagulase-negative staphylococci (CNS), though often described as minor pathogens, have long been recognized as a common cause of mastitis in domestic ruminants (cattle, sheep and goats). Recent findings indicate that the CNS are becoming more important, especially in herds that have successfully controlled mastitis caused by the major contagious pathogens S. aureus and Streptococcus agalactiae (Pyorala and

Taponen, 2009; Schukken et al., 2009). Some authors have even gone as far as describing

CNS as “emerging mastitis pathogens” although these authors recognize that CNS have been isolated from mastitic bovine milk samples for decades (Pyorala and Taponen,

2009). Some species such as S. chromogenes, S. haemolyticus, S. simulans, S. epidermidis, and S. xylosus appear to be a common cause of mastitis (Taponen et al.,

2007, Sampimon et al., 2009, Supre et al., 2011, Fry et al., 2014), while for other species, their isolation from cases of clinical and subclinical bovine mastitis is rare. Farm environment and body surfaces have been shown to be some of the sources of CNS bacteria causing bovine mastitis (Piessens et al., 2011). A study done by White and colleagues suggested that CNS IMI may prevent infection by the major pathogens (White et al., 2001). In a challenge study, only 47% of the cow quarters previously infected with

S. chromogenes became infected upon a subsequent S. aureus intrammamary challenge, suggesting a possible S. chromogenes protective effect (Matthews et al., 1990). This concept is still under debate, as other studies did not find a protective effect of CNS IMI on the risk of infection with major mastitis pathogens (Zadoks et al., 2001, Compton et al., 2007), and some CNS might actually be more pathogenic than previously thought

(Taponen et al., 2006), or could increase the odds of subsequent infection with S. aureus

(Reyher et al., 2012a). Some CNS species seem to affect udder health more than others

(Supre et al., 2011, De Visscher et al., 2016). The negative or positive effect might be species dependent (Reyher et al., 2012b), or even strain specific (Breyne et al., 2015;

Piccart et al., 2016; Souza et al., 2016). The variable results and limitations of prior data highlight the need to identify staphylococci mastitis infections to the species level, and to obtain data that might help describe why certain species persist in different niches or cause mastitis.

Although, CNS species have long been recognized to cause mastitis, their relative importance appears to be increasing. This change has paralleled the successful control of the major contagious pathogens Staphylococcus aureus and Streptococcus agalactiae on well-managed farms. The practices that have contributed to control of these major pathogens might be less effective for CNS species, and it appears the ecology of mastitis causing organisms is shifting (Vanderhaeghen et al., 2015). New approaches are needed to advance mastitis control and milking hygiene. Definitive identification and a better understanding of the epidemiology of pathogens is the foundation to developing effective control practices (Zadoks and Schukken, 2006). Understanding the potential role of beneficial commensal bacteria may also advance mastitis control, milk quality and food safety.

It is noteworthy that historically, in most diagnostic laboratories, CNS from IMI or bulk tank milk samples were not identified to the species-level (Bes et al., 2000,

Irlinger, 2008). CNS have been known historically as minor pathogens compared to the major mastitis pathogens like S. aureus, Streptococci and coliforms. More recently, the introduction of high-throughput methods for bacterial species identification, such as matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-

TOF MS), is changing the extent of species level information available from some laboratories. Historically, staphylococci species identification was done using biochemical/phenotypic methods (Kloos and Schleifer, 1975). Studies done in the past decade comparing genotypic and phenotypic methods have demonstrated that phenotypic methods are less accurate compared to genotypic/molecular methods (Capurro et al.,

2009, Zadoks and Watts, 2009). Despite potential inaccuracies of biochemical methods, they are still being used in some epidemiologic studies. Conclusions made on CNS epidemiologic studies using biochemical species identification should be interpreted with caution, as they might be incorrect. The CNS group is heterogeneous and within species heterogeneity might also exist in some CNS, like that seen in S. aureus. For instance, S. aureus strain typing using unambiguous methods like multilocus sequence typing

(MLST) has revealed high diversity. Since the development of S. aureus MLST in 2000

(Enright et al., 2000), at least 4,324 strain types (STs) (pubmlst.org) have been identified, with most lineages being host specific while others have broad host tropism. These data have played a critical role in understanding local and global epidemiology of S. aureus.

The extent of strain diversity among CNS mastitis pathogens is currently unknown or limited in scope, and some species/strains might be good biofilm formers or antibiotic resistant (Tremblay et al., 2013; Tremblay et al., 2014; da Costa et al., 2015). The CNS species are believed to be reservoirs of antibiotic resistance gene markers, which can be horizontally transferred to major pathogens like S. aureus (Woodford, 2005).

The purpose of this literature review is to highlight the general knowledge on this topic and point out some knowledge gaps that are partly addressed in this dissertation.

This review describes staphylococci identification and typing methods highlighting their advantages and disadvantages and some knowledge gaps as well as current knowledge about staphylococci bovine mastitis. Some current knowledge on antibiotic resistance with a major focus on β-lactam antibiotic resistance among the staphylococci is also reviewed. Virulence determinants that may contribute to the pathogenesis or persistence

of staphylococci within or outside the host, for example biofilm formation, are also reviewed.

1.2 Dairy farming systems

In the United States, dairy farms can be pasture based or in confinement. These farms are either organic or conventional. Consumer demand for organic dairy products has increased over the years (Organic Trade Association, 2015). This demand has led to an increase in number of organic dairy cows. For instance, the number of certified organic cows increased from 249,766 to 254,771 between 2008 and 2011 in USA (USDA

Economic Research Service, 2013). There is a perceived safety concern of conventional dairy products as compared to the organic which is driving the demand for organic products (e.g. antimicrobial residues, pesticides residues, and lack of animal welfare.

However, on US organic farms, antimicrobial use is not allowed so this limits one potential practice for the control of contagious pathogens for example, S. aureus and

Streptococcus agalactiae. Preventive measures like dry cow therapy are not practiced.

This may explain why S. aureus is more prevalent on organic than conventional dairy farms (Ruegg, 2009a, Cicconi-Hogan et al., 2013). Farming practices may also influence

CNS epidemiology. There is an opportunity to study staphylococci epidemiology and antimicrobial resistance on organic farms where there is limited antibiotic use compared to conventional farms. A previous study showed that isolates from organic dairy farms were more susceptible to some antibiotics as compared to conventional dairy farms, though information on strain diversity was not provided (Tikofsky et al., 2003).

Some conventional and organic farms harvest milk for farmstead or artisan cheese

production, including raw milk cheeses. These farms may have simultaneous goals of encouraging or maintaining beneficial bacterial communities on the teat skin and in raw milk, while limiting the risk for intramammary infections (IMI) and of raw milk contamination with potential human pathogens such as S. aureus (Tsegmed et al., 2007,

D'Amico and Donnelly, 2010). Raw milk is the common route for introducing human pathogens like S. aureus in the cheese production chain, most of which are from cows with mastitis (D'Amico D and Donnelly, 2011, Kummel et al., 2016). Previous work on artisan cheese farms in Vermont focused on S. aureus epidemiology (D'Amico and

Donnelly, 2010, D'Amico D and Donnelly, 2011). In addition, understanding CNS epidemiology on artisan cheese farms is crucial given their relative high abundance in cheese (Wolfe et al., 2014). Some CNS species found in raw milk may be part of the consortium of ripening bacteria that contribute to flavor or other attributes of finished cheeses (Bockelmann W., 2001, Bockelmann, 2002, Place et al., 2003). In particular, S. equorum is one of the most common nonpathogenic Staphylococcus species isolated in cheese (Kastman et al., 2016), it has been proposed as a potential starter culture, and it has been shown to have anti-listerial effects (Carnio et al., 2000, Place et al., 2003). A better understanding of the reservoirs of both the beneficial and the mastitis pathogenic bacteria on these farmers is beneficial and may improve farmers’ economies.

1.3 Mastitis diagnosis and economic implication

Mastitis is defined as the inflammation of the mammary gland, which can occur in humans and animals. It is usually caused by bacterial IMI. Generally, mastitis cases in cattle are categorized as clinical and subclinical. Clinical mastitis presents with visible

signs of inflammation, which may include swelling of the udder, reddening, pain, heat, and abnormal milk consistency. Clinical mastitis ranges from mild to severe, and can become systemic causing fever, depression, loss of appetite, and possibly in severe cases, death of an animal. In subclinical mastitis, there are no visible signs of inflammation and the milk looks normal visually.

Diagnosis of clinical mastitis is relatively straight forward; it is generally based on visual assessment of inflammation (Contreras and Rodriguez 2011). Diagnosis of subclinical mastitis is based on two common methods. First is a bacteriologic culture of milk to determine the presence of an infectious agent. This is the reference method for

IMI and mastitis diagnosis (Koskinen et al., 2010). Staphylococci generally grow well on non-selective media like blood agar and, are therefore, easy to isolate. The second method is based on quantifying cow or quarter somatic cell count (SCC) as a measure of inflammation. The SCC increase is due to the infiltration of leukocytes into the mammary gland, and is generally presumed to be due to an immune response to IMI. In dairy cows, a SCC higher than 200,000 cells/mL was proposed to define a subclinical mastitis case as per National Mastitis Council (NMC) guidelines, although cut point ranges between

100,000 to 300,000 cells/mL are common in literature (Schukken et al., 2003, Bansal et al., 2005, Deluyker et al., 2005). Increase in SCC is correlated with the severity of the inflammatory response. S. aureus tends to induce a severe inflammatory response compared to CNS. A meta-analysis by Djabri and colleagues showed a geometric mean

SCC of 138, 000 and 357,000 cells/mL in CNS and S. aureus infected cow quarters, respectively. While, uninfected quarters had a mean of 68,000 cells/mL (Djabri et al.,

2002). Other diagnostic techniques include: N-acetyl-beta-D-glucosamindase activity, pH change, lactose content, electrical conductivity change, milk flow measurement, quantification of acute phase proteins (milk amyloid A, serum amyloid A, and haptoglobin), and the level of pro-inflammatory cytokines (interleukin or TNFα)

(Pyorala, 2003, Simojoki et al., 2011, Kalmus et al., 2013). Some PCR based diagnostic techniques using extracted DNA from whole milk have been evaluated to diagnose IMI due to major mastitis pathogens (Koskinen et al., 2010). Recently a commercial real-time

PCR kit (PathoProof Mastitis PCR Assay, Thermo Fisher Scientific) was used directly on milk samples without culture. The assay showed a higher sensitivity and was faster (4hrs) than bacterial culture (Koskinen et al., 2010). Application of PCR based assay to CNS might be challenging given the heterogeneity of the group. Nevertheless, targeting a few common CNS species causing IMI would be feasible.

In addition to the clinical and subclinical mastitis categories described above, an

IMI can be further categorized depending on the duration of an infection. Persistent IMI is generally defined as the presence of a given infectious agent in cow quarter milk in a given period for example, the dry period, and part of or entire lactation period

(Vanderhaeghen et al., 2014), whereas in a transient IMI, the duration of infection is no more than a few days and the infection is usually self-limiting (Barlow, 2011, Contreras and Rodriguez, 2011, Sordillo, 2011, Middleton et al., 2014). There is no established definition of persistent infection, but distinguishing persistent and transient IMI requires repeated sampling. Repeated (serial) milk SCC measurements can be used to define chronic or transient IMI (Schukken et al., 2003). There is no clear dichotomy of which

Staphylococcus species cause transient or persistent IMI, it is likely to be species strain dependent. Pathogen-host interaction and the quality of the host’s immune response likely play a role in the probability of persistence. For example, as recently reviewed, in several studies, certain CNS strains were found to cause persistent IMI in some cows and transient IM in others (Vanderhaeghen et al., 2014). The identification of persistent subclinical mastitis or IMI is economically relevant, as total economic losses per cow per year for subclinical mastitis are estimated to be higher for chronic subclinical cases compared to clinical mastitis, primarily due to the increased production losses associated with subclinical mastitis (Huijps et al., 2008). Previous authors have described the importance of strain typing in defining chronic IMI from serial samples (Barlow et al.,

2013; Veh et al., 2015)). A current limitation is the lack of repeatable and transferable strain typing scheme for CNS species.

In the United States, mastitis is the leading cause of production losses in the dairy sector and is a major condition affecting farm economics worldwide. The losses are mainly due to lost or reduced milk production, increased veterinary and treatment costs, increased labor, low product quality resulting in low premiums, and herd replacement costs due to culling (Bar et al., 2008). Even after recovery, the udder of a cow may not be functional to its optimal capacity (Akers and Nickerson, 2011), resulting in prolonged production losses. On average, a case of clinical and subclinical mastitis costs USD

367case-year and USD 130/case-year, respectively (Halasa et al., 2007). Although recent national data is lacking, estimates from the 1990s showed that mastitis losses were between $1.5-2.0 billion per year in the United States (Middleton et al., 2014). The cost

estimates did not include all the costs incurred by preventive measures e.g. teat disinfection, dry cow therapy, and others. The true cost generally varies depending on the pathogenic organism causing the IMI, the type of infection (clinical vs subclinical), and severity or duration of an infection (Bar et al., 2008). The severity of or the duration of an infection may be influenced by the interaction between the host, the pathogen, and the environment.

1.4 Mastitis epidemiology and control

Mastitis is a complex disease, which occurs through an interaction between the causative agent factors, the host factors, and the environment. Most cases of mastitis are associated with bacterial infections, which are acquired by bacteria entering the teat of the mammary quarter (Akers and Nickerson, 2011; Contreras and Rodriquez, 2001). The causative agent factors include the ability to survive within the host and adhere to mammary gland epithelium. Host factors like breed, physiological state of the mammary gland, teat canal anatomy, sphincter tone and presence of teat lesions may predispose an animal to mastitis (Francis, 1984). Environmental factors include milking practice, housing system, and bedding (Kibebew, 2017). Mastitis pathogens can be classified according to their epidemiologic behavior, either contagious or environmental (Contreras and Rodriguez 2011). The main reservoir for contagious pathogens is the udder of a cow and bacteria spread from cow to cow, or between quarters in the same cow. Cow to cow transmission can occur through a carrier such as hands of herdsmen during milking or through fomites for example, milking equipment, and towels. In contrast, the reservoirs for environmental pathogens are: cow bedding, soil and pasture, and other inanimate 12

objects (Contreras and Rodriguez, 2011, Gomes and Henriques, 2016). Research has highlighted that certain microbial, host, and environmental factors may influence environmental pathogens to behave contagiously or vice versa (Zadoks et al., 2001,

Pyorala and Taponen, 2009). Within the genus Staphylococcus, S. aureus is a well- defined contagious pathogen. It is difficult to conclude that CNS are environmental or contagious pathogens based on current limited species specific knowledge (Pyorala and

Taponen, 2009). Additional research is needed to understand transmission dynamics of individual CNS (Reksen et al., 2012). More data on epidemiologic nature (contagious vs environmental) of CNS species involved in mastitis may help in designing better control strategies. It has been suggested that some CNS species might have a contagious transmission mode while others might be environmental (Piessens et al., 2012). The question would be whether some species are behaving both like contagious or environment pathogens and this might be yardstick to determine which control strategy to use. A critical requirement to describing within herd transmission dynamics is the development and validation of methods to discriminate between strains within each species of CNS, as has been demonstrated for other species of mastitis pathogens including S. aureus, Escherichia coli, Klebsiella species, and Streptococcus agalactiae

(Zadoks et al., 2011; Barlow et al., 2013)

The quest to develop measures to control mastitis pathogens, led to the development of the five-point mastitis control plan. The five point mastitis control plan is the basic program that has been used to control mastitis (Hillerton et al., 1995), it includes:

1. Good husbandry and milking practice with regular testing and maintenance of the

milking machine;

2. Application of a teat disinfection immediately after removal of the milking

machine;

3. Routine antibiotic therapy for all cows after the last milking of each lactation (Dry

cow therapy);

4. Treatment and documentation of all quarters with clinical mastitis;

5. Culling of cows with chronic and recurrent mastitis.

This program led to the control of the contagious pathogens S. aureus and

Streptococccus agalactiae, the primary pathogens of concern first described in the

United Kingdom (Smith et al., 1966; Bramley and Dodd, 1984). The principles of the plan are built on the basic principles of contagious disease epidemiology and transmission dynamics, where the prevalence of infection within a population (e.g. a herd) is a function of the incidence (or rate) of new infections and the duration of infection (Barlow et al., 2009; Reksen et al., 2012). In the case of contagious pathogens, the incidence of infection is a function of the number of infected individuals in the population, the probability of contacts between infected and susceptible individuals, and the probability of transmission upon contact (Barlow et al., 2009). The principles of the 5-point plan focus on preventing new infections and limiting the duration of existing infections. Hygiene (e.g. teat disinfection) interventions reduce the risk of new infection. Successful treatment of cases (lactating or dry cow therapy) reduces the duration of infection and like culling reduces the

force of infection within a population (White at al., 2001; Barlow et al., 2011). It is

possible that the source of new infections caused by some CNS infections can be

other infected udders or cows in the herd and CNS species may demonstrate

contagious transmission dynamics (Reksen et al., 2012). The source of CNS

infections might also be extended to teat skin transmission from colonized skin

surfaces. In comparison, the risk of new infections from environmental sources is

generally described as being independent of the number of the infected individuals in

a herd, and where post-milking disinfection may be less effective in reducing

pathogen exposure (Lam et al., 1996). This may help explain why the 5-point plan

has proven to be less effective at controlling pathogens where the primary source of

new infections is the environment (Hilleton et al., 1995; Bramley and Dodd, 1984).

Inclusion of environment pathogen control led to the introduction of ten-point

mastitis control plan issued by the National Mastitis council, a detailed recent update

is available (http://www.nmconline.org/resources). In addition to the five measures,

the ten-point plan places additional emphasis on environmental management.

Additional research is needed to better understand the sources of new CNS infections

and the role that CNS skin colonization may play in mastitis epidemiology.

1.5 Mastitis etiology

Although mastitis can be non-infectious, most mastitis cases are due to an intramammary bacterial infection (Djabri et al., 2002, Oliveira et al., 2013). Over 137 microorganisms are estimated to cause mastitis in cattle (Watts, 1988, Radostits, 2007).

Other non-bacterial pathogens have been rarely reported including: viruses (Wellenberg

et al., 2002), and fungi (Williamson and di Menna, 2007). Many bacterial genera, Gram- positive and-negative organisms, have been isolated from cases of mastitis in cattle

(Watts 1988), though some genera predominate, for example, Staphylococcus,

Streptococcus, and Escherichia. Depending on the severity of an infection, some bacterial species can be described as major or minor mastitis pathogens. Major pathogens are defined as pathogens that tend to elicit a severe inflammatory response with visible clinical signs, and mainly comprise S. aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, and coliforms. Minor pathogens on the other hand, are those that elicit moderate inflammatory response with subclinical signs, for example;

CNS and Corynebacterium bovis (White et al., 2001).

Among the Gram-positive bacteria, the staphylococci are most commonly isolated from cases of mastitis. The introduction of unambiguous strain typing techniques like

Multilocus Sequencing Typing (MLST) has improved our knowledge of S. aureus including: its local and global epidemiology, mode of transmission, and potential reservoirs, as well as lineages important in humans and animals. This information is not entirely clear for most CNS, mainly due to a lack of available unambiguous strain typing schemes for most species. The CNS are a heterogeneous group of at least 47 species and are considered minor mastitis-causing pathogens because the inflammatory response is less severe and the inflammatory responses are usually subclinical compared to S. aureus

(Ruegg, 2009b, Schukken et al., 2009). Research over the years shows an increasing role of some CNS species in mastitis. The CNS species have been recently described as

“emerging mastitis-causing pathogens” with some species such as: S. simulans, S.

chromogenes, and S. xylosus able to induce an inflammatory response comparable to that of S. aureus (Pyorala and Taponen, 2009, Supre et al., 2011). This suggests that during an

IMI some CNS species may behave like major pathogens. The top five CNS species commonly isolated in mastitis cases include: S. chromogenes, S. xylosus, S. epidermidis,

S. simulans, and S. haemolyticus, though their prevalence varies between studies

(Taponen et al., 2007, Sampimon et al., 2009, Supre et al., 2011, Fry et al., 2014), and these species tend to cause persistent IMI (Thorberg et al., 2009, Fry et al., 2014). S. epidermidis, in addition to causing bovine mastitis, is one of the leading causes of nosocomial infections in humans with indwelling medical devices and is considered a human adapted species. Human commensal and bovine S. epidermidis strains are closely related (Savijoki et al., 2014), suggesting that humans could be reservoirs of bovine mastitis associated strains. Some CNS have been isolated from the dairy farm environment, whereas, S. chromogenes is extremely rare in the environment and rarely colonizes humans, and so it’s considered a host adapted species (Pyorala and Taponen,

2009, De Visscher et al., 2014). Whether extramammary cow sites are the reservoirs of these bacteria requires more accurate species identification and unambiguous strain typing. It has been speculated that each dairy herd might have a unique extramammary

CNS microbiota (De Visscher et al., 2014), and the microbiota is speculated to protect the udder from pathogenic microbes. However, the protective effect is not conclusive and still debatable, for example, S. chromogenes strains isolated from teat apex showed inhibitory or bacteriocin-like effect against S. aureus and S. agalactiae (De Vliegher et al., 2004, Braem et al., 2014), yet, it’s the most prevalent CNS species causing IMI.

Another important genus is Streptococcus; Streptococcus agalactiae (Group B streptococci; GBS) is an intramammary pathogen of cattle causing contagious mastitis

(Keefe, 1997). Other Streptococcus species involved in mastitis include; Streptococcus uberis and Streptococcus dysgalactiae, which are considered environment pathogens however; contagious transmission for S. dysgalactiae has been reported (Bradley, 2002,

McDougall, 2002). Some minor Gram-positive bacterial species may occasionally cause mastitis and these include: Corynebacterium bovis, Trueperella pyogenes, Enterococcus faecium, Enterococcus faecalis and Bacillus spp (Devriese et al., 1999, Nieminen et al.,

2007, Hawkes et al., 2008, Tenhagen et al., 2009).

Among the Gram-negative bacteria, Escherichia coli is a common cause of mastitis in lactating and non-lactating cows. Escherichia coli and Klebsiella spp. tend to cause severe acute IMI. Other Gram-negative bacteria isolated in mastitis cases are mainly in the genera Pasturella, Proteus, Pseudomonas, and Serratia. These s are considered environmental pathogens and may cause severe acute clinical mastitis that can be life threatening. The severity of Gram-negative mastitis cases is at least partially due to the release of bacterial cell-wall derived endotoxins during the immune response (Ohnishi et al., 2011). Mycoplasma species including, Mycoplasma bovis, M. californicum, and M. bovigenitalum can cause contagious mastitis in cattle (Fox et al., 2005a).

1.6 Genus Staphylococcus

Bacteria in the genus Staphylococcus are Gram-positive, catalase-positive cocci with low guanine-cytosine (G+C) content, approximately 0.5-1µm in diameter, and are salt tolerant. They usually grow in clusters, pairs, and sometimes in chains (Foster, 1996).

The Staphylococcus genus contains some species that are usually animal and human skin commensals, and some can be pathogenic and cause disease, whereas others are predominant in the environment and can be isolated from fermented foods and rarely cause disease (De Visscher et al., 2014, Wolfe et al., 2014, Kastman et al., 2016). In cattle, they’re the leading cause of IMI that lead to mastitis (Taponen and Pyorala, 2009).

There are at least 47 species and 23 subspecies in the genus as of 2014 (Becker et al.,

2014), with two more species (S. schweitzeri and S. argenteus) closely related to S. aureus having been proposed recently (Tong et al., 2015c). Staphylococci have been broadly divided into two groups based on their ability to coagulate blood plasma: coagulase-positive staphylococci (CPS) and coagulase-negative staphylococci (CNS).

The CPS include: S. aureus, S. intermedius, S. pseudintermedius, S. delphini, S. hyicus, S. lutrae, S. agnetis, S. schweitzeri and S. argenteus with the remaining considered CNS

(Table 1-2). Staphylococcus schleiferi contains coagulase negative and positive subspecies, S. schleiferi subsp. schleiferi and S. schleiferi subsp. coagulans, respectively

(van Duijkeren et al., 2011,Becker et al., 2014, Tong et al., 2015c). A coagulase test is routinely done in research and diagnostic laboratories for presumptive differentiation of

CPS from CNS (Figure 1-2). Grouping of these species into CPS and CNS is not clear- cut in that some CNS species strains have blood plasma clotting activity. For instance, recently strains of S. chromogenes (23 of 42 isolates with initial ambiguous species identification) isolated from buffalos (Bubalus bubalis) with subclinical mastitis in Brazil were demonstrated to clot blood plasma, though authors didn’t mention their relative prevalence among all S. chromogenes submitted to their laboratory (Dos Santos et al.,

2016). Not all S. aureus strains are coagulase positive (Mlynarczyk et al., 1998).

Although, this phenotype is rare, it can complicate S. aureus diagnosis in laboratories that rely on coagulase test, emphasizing the use of molecular identification methods that have high accuracy. Some researchers group staphylococci into S. aureus, and non-aureus staphylococci (NAS) to avoid ambiguity (Condas et al., 2017a, Condas et al., 2017b).

Based on DNA sequences from four gene (16S rRNA, dnaj, rpoB, and tuf), staphylococci were recently classified into 15 groups clustered into six species groups: Auricularis,

Hyicus-Intermedius, Epidermidis-Aureus, Saprophyticus, Simulans, and Sciuri (Lamers et al., 2012).

Table 1-1: Species in the genus Staphylococcus

Species groups

Auricularis Hycus-Intermedius Epidermidis-Aureus Saprophyticus Simulans Sciuri References S. chromogenes S. epidermidis S. xylosus S. simulans Thorberg et al., J. Dairy Sci. 92:4962–4970 S. hyicus S. haemolyticus De Visscher et al., Vet. Microb. 172 (2014) 466–474

S. aureus Supre et al., J. Dairy Sci. 94:2329–2340 Piessens et al., 2011. J. Dairy Sci. 94:2933–2944 Smith et al, JCM, Sept. 2005, p. 4731–4736

S. auricularis S. hominis S. equorum Sciuri De Visscher et al., Vet. Microb. 172 (2014) 466–474 S. cohnii S. fleurettii Piessens et al., 2011. J. Dairy Sci. 94:2933–2944

S. muscae S. saccharolyticus S. nepalensis S. piscifermentans S. stepanovicii S. microti S. capitis S. saprophyticus S. carnosus S. vitulinus S. rostri S. simiae S. gallinarum S. condimenti S. pulvereri

S. agnetis S. caprae S. succinus S. lentus S. felis S. warneri S. arlettae

S. intermedius S. pasteuri S. kloosi S. lutrae S. devriesei S. pettenkoferi S. schleiferi S. lugdunensis S. massiliensis S. pseudintermedius S. jettensis S. delphini S. petrasii

S. argenteus S. schwitzeri

Blue and Red are species commonly isolated from IMI cases and dairy farm environment respectively. Species like S. simulans and S. haemolyticus have been shown to be dominant in the environment as well suggesting an environmental reservoir (Piessens et al., 2011). For the remaining species (black), there is no enough data but some are occasionally isolated from cow milk or environment at relatively low frequency (Piessens et al., 2012)

1.7 Staphylococci species identification

A lot of attention has been given to S. aureus since it was identified in the 1880s, partly because of its clinical relevance in humans and animals compared to CNS. In fact, some diagnostic microbiology laboratories do not identify CNS to the species level

(Irlinger, 2008, Pyorala and Taponen, 2009), yet their relative role in causing nosocomial infections and bovine mastitis seem to have increased over the years. In order to better understand the role of these bacteria in bovine mastitis and in clinical medicine, accurate identification to the species or subspecies level is paramount. Improved understanding of the impact, source, and transmission mechanisms is important in designing control measures targeting CNS mastitis. Field study data from a broad distribution of farm types will provide a broad perspective on the epidemiology of these bacteria species. Many species identification methods have been applied and a description of all methods is beyond the scope of this review. Examples include; matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) (Carbonnelle et al., 2007,

Dupont et al., 2010, Spanu et al., 2011; Cameron et al., 2017a; Cameron et al., 2017b ), nucleic acid hybridization and others (Phillips and Kloos, 1981, Hensley et al., 2009).

This portion of the review focuses on the earlier and latest literature on a fraction of phenotypic and genotypic/molecular based identification methods of staphylococci.

These are the most commonly used methods in bacterial species identification in general and some are routinely available for research and diagnostic purposes.

Before the invention of molecular-based species identification, staphylococci identification was performed using phenotypic methods. Biochemical methods are based

on expression of traits that are genetically encoded by the bacteria. These traits include: growth characteristics, morphology, antibiotic resistance, ability to metabolize certain substrates, and other features not based on detection of bacterial DNA. The initial identification method described by Kloos and Schleifer (1975) was complex, taking three days to process samples. Commercial test systems were developed based on this method for rapid phenotypic identification of staphylococci and have been used for the past three decades such as: API 20 Staph system, AP ID 32 Staph, Vitek 2 (Biomerieux) and others

(Kloos and Wolfshohl, 1982, Doern et al., 1983, De Paulis et al., 2003, Zadoks and

Watts, 2009, Becker et al., 2014). However, these phenotypic commercial systems lack accuracy in identification of some species, which leads to misclassification (Grant et al.,

1994, Ieven et al., 1995). This is partly due to the variability in expression of the phenotypic traits in isolates of the same species. Some strains within a species may not express or lack a particular gene defining a given phenotype, for example, both hemolytic and non-hemolytic S. aureus strains from bovine mastitis cases do exist (Figure 1-1).

Interpretation of phenotypic data is also subjective affecting reproducibility and typeability (Carretto et al., 2005, Zadoks and Watts, 2009). Some commercial systems may not have all the species and subspecies in their databases, limiting identification of novel species or Staphylococcus species with unique characteristics (Capurro et al.,

2009). Further, these commercial identification systems were designed and validated using human isolates, producing more accurate results with human isolates compared to animal-associated isolates (Ruegg, 2009b). The misidentification using these commercial systems is not limited to the species level. For example, the Vitek 2 system misidentified

clinical CNS isolates as Kocuria (Ben-Ami et al., 2005, Boudewijns et al., 2005).

Bacteria in the genus Kocuria are believed to be mere contaminants compared to some

CNS that are indeed pathogenic, resulting in potential misidentification and delay of treatment to patients (Ben-Ami et al., 2005). On the other hand, genotypic methods are more reliable and misidentifications are very minimal especially with sequence-based identification methods.

Figure 1-1: Differential hemolysis patterns of two S. aureus strains isolated from bovine subclinical mastitis The two strains were grown on blood agar at 370C for 24 and 48 hours, ST151 and ST3028 showed hemolysis and non-hemolysis patterns respectively.

Genotypic methods rely on DNA as a basis of staphylococci identification to the species or subspecies level. Some methods include: amplified-fragment length polymorphism (AFLP) (Taponen et al., 2006, Taponen et al., 2007), tDNA intergenic length polymorphism (tDNA-ILP) analysis (Lee and Park, 2001, Rossi et al., 2001, 23

Stepanovic et al., 2005), ribotyping (Carretto et al., 2005), and DNA sequencing

(Drancourt and Raoult, 2002, Mellmann et al., 2006, Hwang et al., 2011).

The 16S rRNA gene sequencing is the most common sequence-based method used for bacterial identification across different bacterial genera (Becker et al., 2004).

However, among the staphylococci, some species have less than 1% sequence divergence in the 16S rRNA gene, limiting accurate discrimination of closely related species (Shah et al., 2007). This was made apparent in studies where 16S rRNA sequencing could not discriminate between species including: S. caprae and S. capitis (Ghebremedhin et al.,

2008, Park et al., 2011), S. intermedius and S. delphini, or between S. pulvereri and S. vitulinus (Becker et al., 2004). This necessitated exploration of alternative genes that are discriminative and accurate in staphylococci identification.

Other housekeeping genes have been tested where some have proven to have better discriminatory power than the 16S rRNA gene. These include the: tuf gene

(elongation factor Tu) (Heikens et al., 2005), rpoB gene (β subunit of RNA polymerase)

(Drancourt and Raoult, 2002), sodA gene (manganese-dependent superoxide dismutase

A) (Poyart et al., 2001), hsp60 gene (heat shock protein 60)(Kwok et al., 1999), the dnaJ gene (heat shock protein 40) (Shah et al., 2007), gap gene (glyceraldehyde 3 phosphate dehydrogenase) (Yugueros et al., 2000), and femA gene (aminoacetyltransferase)

(Vannuffel et al., 1999). The mean sequence similarity of 16S rRNA, rpoB, hsp60, sodA, tuf, and dnaj genes reported within staphylococci is 97.4%, 86%, 82%, 81%, 86-97% and 77% respectively (Kwok et al., 1999, Yugueros et al., 2000, Drancourt and Raoult,

2002, Shah et al., 2007, Vanderhaeghen et al., 2015). In general, these alternative

housekeeping genes have more sequence variation than rRNA (Ghebrenedhin et al.,

2008), and therefore, are better at discriminating between Staphylococcus species. As reviewed by Zadoks and Watts, (2009), genotypic methods have high accuracy, discriminatory power, tyeability, and reproducibility compared to phenotypic methods.

For sequence based species identification; tuf and rpoB genes have higher discriminatory power and are currently the most common housekeeping genes used for staphylococci sequence based identification (Drancourt and Raoult, 2002, Mellmann et al., 2006, Hwang et al., 2011, Li et al., 2012, Geraghty et al., 2013, Fry et al., 2014,

Condas et al., 2017a). Among epidemiologic studies of CNS on dairy farms, rpoB appears to be commonly used (Table 1-2). Whether tuf and rpoB genes are equally good for identification of staphylococci of dairy origin is not clear. Tuf has been used in identification of CNS of human origin and has been shown to have better discriminatory power than 16S rRNA (Hwang et al., 2011). In the Barlow laboratory, we use both phenotypic and genotypic methods (Figure 1-2) for presumptive and definitive staphylococci identification respectively. For definitive species identification, we used either tuf or rpoB and 16S rRNA where necessary.

Figure 1-2: Scheme for presumptive identification of staphylococci Coagulase test differentiates CNS from the CPS. Definitive identification of staphylococci in the Barlow laboratory is done using tuf gene PCR amplification and sequencing.

Table 1-2: Common CNS identification methods for epidemiologic purposes on dairy farms

Identification method Strain typing method Reference (GTG)5 Fingerprinting None Braem et al., 2011. Vet. Microbiol. 147(1-2):67-74. rpoB gene sequencing None Condas et al., 2017a. J. Dairy Sci. 100(7):5592-5612. rpoB gene sequencing PFGE Fry et al., J. Dairy Sci. 97(8):4876-4885 rpoB gene sequencing AFLP Piessens et al., 2011. J. Dairy Sci. 94(6):2933-2944 rpoB gene sequencing None Condas et al., 2017b. J. Dairy Sci. 100(7):5613-5627 rpoB gene sequencing None Supre et al., 2011. J. Dairy Sci. 94(5):2329-2340 rpoB gene sequencing None De Visscher et et al., 2014. Vet. Microbiol. 172(3-4):466-474 tDNA-PCR None Koop et al., 2012. J. Dairy Sci. 95 :5075–5084 tDNA-PCR None De Visscher et et al., 2014. Vet. Microbiol. 172(3-4):466-474 AFLP AFLP Piessens et al., 2011. J. Dairy Sci. 94(6):2933-2944 Biochemical PFGE Rajala-Schultz et al., 2009. Vet. Microbiol. 134(1-2):55-64 Biochemical None Thorberg et al., J. Dairy Sci. 92(10):4962-4970 Biochemical AFLP Taponen et al., 2007. J. Dairy Sci. 90(7):3301-3307 Biochemical None Schukken et al., 2009. Vet. Microbiol. 134(1-2):9-14 Biochemical PFGE Gillespie et al., 2009. Vet. Microbiol. 134 (2009) 65–72 Biochemical None Sampimon et al., 2009. Vet. Microbiol. 134(1-2):37-44 tDNA-PCR None Supre et al., 2011. J. Dairy Sci. 94(5):2329-2340 Ribotyping None Taponen et al., 2016. Acta Vet. Scand. 58:12 SodA gene sequencing PFGE Mørk et al., 2012. Vet. Microbiol. 159 (2012) 171–180 1.8 Strain typing of staphylococci

Typing microbes to strain level is not only an important tool in taxonomy, but

also in epidemiology. Applications include, but are not limited to, understanding

epidemiologic sources of bacteria in disease outbreak investigations, differentiating

strains causing transient and chronic infections, bacterial evolutionary biology, and

elucidation of bacterial/pathogen transmission dynamics (Zadoks and Schukken, 2006).

Effective control of diseases requires effective detection of transmission events in

outbreaks. Inferences on transmission of bacterial pathogens can be informed by strain

typing of isolates from hosts within populations. Various criteria have been proposed for

evaluating typing methods and these include; typeability, reproducibility, discriminatory

power, ease of performance, and interpretation (Tenover et al., 1994, Struelens, 1996,

Tenover et al., 1997, Zadoks and Schukken, 2006).

Typeability is the ability of a typing technique to assign a result (type) non- ambiguously to an isolate under investigation. A nontypeable isolate is where typing produces a non-interpretable result. Typeability (T) of a typing system can be calculated as follows:

T = Nt/N

Where: Nt is the number of isolates assigned a type, and N the total number of isolates tested. For a good typing system, the value of T should be closer to 1 (Maslow et al.,

1993, Tenover et al., 1994).

Reproducibility (R) refers to the ability of typing method to give the same result if a given strain is typed repeatedly.

R = Nt/N

Where: Nt is the number of isolates assigned a particular type on repeat testing and N is the total number of isolates (Maslow et al., 1993, Tenover et al., 1994)

Discriminatory power (D) refers to the ability of a typing technique to differentiate between two epidemiologically unrelated strains. The discriminatory power

D, can be calculated using a formula

D =1-1/N (N-1) nj (nj − 1)

Where N is the total number of strains in the sample population, n is the total of types described, nj is the number of strains belonging to the jth type (Hunter and Gaston,

1988).

All these criteria have been described in detail elsewhere (Maslow et al., 1993,Tenover et al., 1994, Struelens, 1996, Tenover et al., 1997, Zadoks and Schukken, 2006). A number of strain typing techniques have been developed over the past 50 years for typing staphylococci and they can be broadly divided into phenotypic and genotypic methods.

1.8.1 Phenotypic typing methods

Phenotypic typing methods are based on phenotypic differences between isolates.

Since the methods rely on gene expression, their properties can be affected by growth conditions, growth phase, and spontaneous mutations (Tenover et al., 1997), influencing their reproducibility and discriminatory power. These methods include but not are limited to the following:

1.8.1.1 Biotyping

Biotyping uses a number of biochemical markers that vary within a taxon. The markers used depend on the bacterial species under study (Hebert et al., 1988, Struelens,

1996). The phenotypic identification systems mentioned earlier; API 20 Staph, can create a biochemical profile of a biotype and be used to distinguish isolates within a species

(Vandenesch et al., 1993). A major limitation associated with these methods/systems is that they were not developed for subspecies discrimination and therefore, are ineffective in epidemiologic investigations. Typeability in these systems tends to be good but the discriminatory power can vary and is usually low. However, the discriminatory power can be improved by increasing the number of biochemical markers used (Struelens,

1996). In bovine mastitis, biotyping has been used to type S. aureus (Devriese, 1984,

Aarestrup et al., 1995, Myllys et al., 1997, Reinoso et al., 2004) but data on CNS is scant.

A study done in the 1990s on S. aureus isolates from bovine milk showed that biotyping had a relative good discriminatory power higher than that of phage typing. Combining biotyping with other phenotypic or genotypic methods increased the discriminatory power (Aarestrup et al., 1995, Myllys et al., 1997).

1.8.1.2 Antibiogram typing

Susceptibility testing on a number of drugs or chemicals not necessarily relevant for therapy can be used. Antibiogram typing, with careful selection of markers, can be applied to type many bacterial species. The discriminatory power depends on the number and relative prevalence of the detectable resistance mechanisms in the study isolates. If isolates have multiple resistances, in the case of nosocomial bacteria, it may be difficult to discriminate between strains (Vandenesch et al., 1993). Secondly, due to either loss

(e.g. plasmid curing) or acquisition of mobile genetic elements through horizontal gene transfer, and spontaneous mutations, epidemiologically related isolates may have different antibiotic susceptibility profiles. On the other hand, unrelated isolates may have similar susceptibilities, for example, if isolates acquired a similar plasmid (Tenover et al.,

1994, Tenover et al., 1997). Antibiogram typing is the first line of bacterial typing in clinical laboratories where results are easy to score and interpret. If a standard method is used and the appropriate markers are selected, definitive typing can be achieved. This typing method has been used to type S. aureus from bovine mastitis cases and it was shown to be less suitable than other genotypic methods e.g. biotyping and phage typing as most isolates were susceptible to all antibiotics (Aarestrup et al., 1995). Although

antibiotic susceptibility testing is done on most mastitis pathogens including CNS, it has not been used for epidemiologic purposes in recent studies possibly because of its low discriminatory power.

1.8.1.3 Serotyping

Serotyping uses a series of antibodies to detect various antigenic determinants on bacterial surfaces (Tenover et al., 1997). Microorganisms of the same species often differ in the expression of surface antigenic determinants. The detection of such differences using immunologic techniques has been exploited to differentiate between bacterial strains, for example, examining bacterial agglutination or latex agglutination. The major problem with serotyping is that polyclonal sera and monoclonal antibodies are expensive and difficult to develop and not readily available in most clinical microbiology laboratories. The discriminatory power is often poor because bacteria have fewer number of serotypes, and some isolates are non-typeable (Maslow et al., 1993). Among the staphylococci from bovine mastitis, serotyping has been utilized mainly in typing S. aureus by targeting the capsule antigens. S. aureus capsule serotype 5 (CP5) and 8 (CP8) are the most common (Poutrel et al., 1988), though some variability does exist. A study by Guidry and colleagues on the prevalence of bovine milk S. aureus capsular serotypes in the United States showed that 59% of the isolates were untypeable by CP5 and CP8 antisera (Guidry et al., 1997). Staphylococci other than S. aureus are usually untypeable by CP5 and CP8 antisera (Tollersrud et al., 2000).

1.8.1.4 Phage typing

Bacteriophages (phages) are viruses that infect bacteria, some of which are host specific, and can infect particular strains within a bacterial species. This can be used to understand phage susceptibility (lysis), or resistance patterns and discrimination of bacterial strains by phage specificity. Since the early 1960s and before the development of molecular based typing, phage typing was commonly used to type S. aureus, S. epidermidis, and some coagulase negative staphylococci (Jefferson and Parisi, 1979,

Alvarez et al., 1986, Kloos and Bannerman, 1994). Phage typing generally requires technical expertise, and experimental and biological variability is repeatedly encountered.

Some strains are non-typeable by the available phages, and requires further investigation into new phages to be used (Fox et al., 1991, Dryden et al., 1992, Maslow et al., 1993). A typeability between 10 to 50% has been identified for some CNS species (Jefferson and

Parisi, 1979) and the discriminatory power can also be low (Dryden et al., 1992). For example, phage typing could not discriminate between S. aureus strains from cows’ milk and teat skin suggesting that cow skin can be reservoir for IMI (Fox et al., 1991). Yet subsequent studies using other systems have demonstrated that strains found on skin can be different from those causing IMI in some herds (Zadoks et al., 2002, Smith et al.,

2005b). In addition, a large number of isolates were non-typeable by the panel of phages used in the study by Fox et al.(1991). The choice of a typing system used may have a strong impact on the conclusions made from a given study.

1.8.1.5 Multilocus Enzyme Electrophoresis (MEE)

Multilocus enzyme electrophoresis (MEE) involves characterization of bacterial isolates by the electrophoretic mobility of a set of constitutive enzymes (usually involved in metabolism) under non-denaturing conditions (Eberle and Kiess, 2012). Each enzyme represents a unique and independent characteristic of an isolate. The enzymes differ in size and charge resulting in differential mobility on the gel (Enright and Spratt, 1999).

Enzyme activities can be traced on the gel after adding color-generating substrates. The variation in electrophoretic mobility of the enzymes depends on non-synonymous mutations at the gene locus that results in a change of amino acids, altering the overall charge of the protein. The mobility variants are called electromorphs, and bacterial isolates can have a unique electromorph or electrophoretic type representing a strain

(Enright and Spratt, 1999, Eberle and Kiess, 2012). Compared to other phenotypic methods, MEE has a higher discriminatory power, however, MEE has low reproducibility and it is difficult to compare results between laboratories (Maiden et al., 1998). Among staphylococci from mastitis, the use of MEE method has limited to strain typing S. aureus (Kapur et al., 1995). To the best of my knowledge, MEE has not been applied to strain typing other Staphylococcus species isolated from milk or cattle, although it has been applied to CNS isolated from other species including dogs (Barrs et al., 2000).

Although phenotypic methods have been used for decades, they’re rarely used today and have been replaced by molecular or genotypic methods. It has been replaced by the most favored multi-locus sequence typing.

1.8.2 Genotypic typing methods

Genotypic typing methods are generally preferred to phenotypic typing methods.

They provide a higher level of standardization, typeability, reproducibility, and discriminatory power. These typing methods can be grouped into: restriction enzyme based methods, polymerase chain reaction (PCR) based methods, restriction enzyme and

PCR based methods, and DNA sequencing.

1.8.2.1 Restriction enzyme based methods

1.8.2.1.1 Ribotyping

Ribotyping is a technique that uses southern blot analysis to detect polymorphisms associated with the ribosomal RNA (rRNA) operons (Sung et al., 2008).

The bacterial genomic DNA is cut by restriction enzymes and the fragments are separated by gel electrophoresis. Southern blotting follows, and probes specific to the RNA are hybridized (Maslow et al., 1993). This method is tedious, expensive and time consuming however, automated ribotyping systems have been developed decreasing labor and improving sensitivity. When typing S. aureus from bovine milk the index of discrimination for ribotyping was demonstrated to be high while typing S. aureus from bovine milk compared to phage typing, biotyping, antibiogram typing (Aarestrup et al.,

1995). Another study concluded that the discriminatory power of ribotyping could further be improved by applying more restriction enzymes (Myllys et al., 1997). One prior study used ribotyping to characterize S. aureus strain diversity on small-scale dairy farms producing artisan cheese in Vermont (D’Amico and Donnelly, 2011). Ribotyping has

rarely been used to type CNS of bovine origin (Taponen et al., 2008, Taponen et al.,

2016).

1.8.2.1.2 Pulsed Field Gel Electrophoresis (PFGE)

Pulsed Field Gel Electrophoresis (PFGE) is a modification of the traditional gel electrophoresis. Bacterial cells are embedded in an agarose gel (the plug) and then treated with enzymes and RNAse to cleave unwanted protein and RNA, leaving purified chromosomal DNA (Eberle and Kiess, 2012). The plug is cut into segments and treated with restriction enzymes to digest the DNA. The DNA fragments are separated by gel electrophoresis with an electric field applied across the gel and the current is changed periodically (Li et al., 2009). The changing electric field enhances movement of larger

DNA fragments that are formed. This is not possible with the conventional restriction endonuclease enzyme analysis (REA) of the chromosomal DNA (Li et al., 2009). The end result is a fingerprint unique to a given bacterial isolate, and isolates are distinguished by the variations in their fingerprint patterns. Isolates with similar DNA fingerprint patterns are predicted to be closely related. Although PFGE has great discriminatory power, it requires a lot of expertise, and some bacterial isolates are untypeable. Comparing results between laboratories can also be challenging and interpreting results is highly subjective (Zadoks et al., 2002, Wulf et al., 2012). It has been demonstrated to be good for local but not global epidemiology because it is too discriminatory and detects variations in the genome that occur rapidly (Maiden et al.,

1998). Therefore, PFGE is not good for understanding long term epidemiology for example if epidemics of a given pathogen in one country belong to a similar clone found

in other countries (Enright and Spratt, 1999). Regardless of its limitations, PFGE is a widely used bacterial typing technique (He et al., 2014). Until the development of high- throughput whole genome sequencing methods, it was considered a gold standard by

United States’ Center for Disease Control and Prevention for typing many bacterial species, including S. aureus (cdc.gov) for strain typing bacterial pathogens. For many US state laboratories, PFGE remains the primary typing system for outbreak investigations.

PFGE has been used extensively for typing staphylococci, including CNS, from bovine mastitis (Zadoks et al., 2002, Haveri et al., 2008, Taponen et al., 2008, Hata et al., 2010), and in some studies, it has been shown to agree with MLST for typing S. aureus (Hata et al., 2010; Barlow et al., 2013).

1.8.2.2 Polymerase chain reaction (PCR) based methods

1.8.2.2.1 Random Amplified Polymorphic DNA (RAPD)

RAPD is a PCR-based typing method in which arbitrary primers (typically 10bp) are designed to amplify pure genomic DNA randomly, producing a genetic profile visualized electrophoretically (Power, 1996). The primers are not designed to target any particular genome sequence; rather a low annealing temperature allows the primers to hybridize to random multiple chromosomal sites with mismatches and initiate DNA synthesis via PCR (Power, 1996, Tenover et al., 1997, Tyler et al., 1997). The electrophoretic profile of the DNA fragments is used to distinguish between strains. The differences between the gel profiles of bacterial strains are due to mutations, deletions or insertions at the primer binding sites (Tyler et al., 1997). The RAPD typing method is less discriminatory than PGFE, but very inexpensive, easy to use, and rapid. Its major 36

weakness is the low reproducibility due to the low annealing temperature (Sabat et al.,

2013). It has been shown using S. aureus from bovine milk that the discriminatory power was dependent on the primers used. The discriminatory power was equal to that of ribotyping but it could be improved by apply more primers (Myllys et al., 1997).

1.8.2.3 Typing methods combining Restriction enzyme digests and PCR amplification

1.8.2.3.1 Amplified Fragment Length Polymorphism (AFLP)

In this typing technique, the genomic DNA is digested using two restriction enzymes, and ligation of double stranded adaptors having complementary sequences to the restriction site of the generated fragments. The fragments are PCR amplified, followed by electrophoresis for accurate sizing (Vos et al., 1995). A more detailed description of this typing method can be found elsewhere (Savelkoul et al., 1999, Sabat et al., 2013, Krawczyk et al., 2016). This method’s discriminatory power is comparable to that of PFGE, but is more labor intensive (Sabat et al., 2013). This method has been used successfully for typing S. aureus and CNS from cases of bovine mastitis (Piessens et al.,

2011, Sakwinska et al., 2011b, Piessens et al., 2012). Like, other methods based on banding patterns, it is complicated to compare results between laboratories.

1.8.2.4 Sequencing based typing

1.8.2.4.1 Multilocus Sequence Typing (MLST)

MLST is a modification of MEE. Instead of using the enzymes, MLST utilizes sequence differences in the housekeeping genes that encode those enzymes or proteins

(Enright and Spratt, 1999). Multi-virulence locus sequence typing (MVLST) a close 37

relative of MLST is based on polymorphisms of virulence and virulence-associated genes. The S. aureus MLST scheme was developed more than a decade ago (Enright et al., 2000). A MLST scheme has been developed for four other Staphylococcus species, three of which are CNS: S. epidermidis, S. haemolyticus, S. hominis, and S. pseudintermidius as per MLST database (https://pubmlst.org/; Thomas et al., 2007;

Solyman et al., 2013; Zhang et al., 2013; Kornienko et al., 2016). MLST is a high discriminatory method of characterizing bacterial isolates based on sequence differences in the internal fragments of seven housekeeping genes (loci); each fragment is approximately 450pb. The sizes of the loci may vary depending on the scheme and the bacterial species (pubmlst.org). For each gene fragment, different unique allele sequences are assigned numbers. A set of allele numbers at the seven housekeeping loci determines a strain/sequence type or allelic profile of a particular isolate (Aanensen and Spratt,

2005). A new allele or sequence type can occur when at least a single nucleotide polymorphism (SNP) is detected in the loci. For example, allele 1 for a given gene/locus might be different from allele 2 by a single base pair change or more. This means that two strain/sequence types can be separated by a single base pair change or more as well.

The number of housekeeping loci used may vary between bacterial species, but in most schemes, it is usually 7 (pubmlst.org). Unlike other typing methods, MLST enables comparison of results from other studies via the internet as described by Aanesnsen and

Spratt (2005). Closely related sequence types (STs) are grouped into clonal complexes

(CCs) (Figure 1-3). This grouping is achieved using the eBurst algorithm (Feil et al.,

2004). The algorithm predicts the founder/ancestral ST within a group or clonal complex

as well as the recent evolutionary descent of all other STs. STs from the same CC are believed to have descended from a similar recent common ancestor and share 6-7 identical alleles with each other. The founder is determined by the ST with large number of single locus variants (slvs) and it is color coded blue and the subgroup founders are color coded yellow in the eBurst diagram (Figure 1-3). As diversification continues subgroup founders may form their own clonal complexes. The unambiguous nature, portability, reproducibility, high discriminatory power, and typeability of MLST, make it a great typing technique to understand local and global epidemiology as well as the evolution of pathogens (Maiden et al., 1998, Enright and Spratt, 1999, Smith et al.,

2005a). Staphylococcus aureus MLST has been used to elucidate the lineages that carry antibiotic resistant determinants (Enright et al., 2000), as well as predominant lineages involved in bovine mastitis worldwide (Smith et al., 2005b). Some S. aureus strain types

(STs) or clonal complexes (CC) have been shown to be host specific, for example ST97,

ST151, ST479, and ST705 are commonly isolated from cases of bovine mastitis (Zadoks et al., 2011). S. aureus ST1, ST5, ST8, ST15, ST30, and ST45, commonly infect humans

(Enright et al., 2000, Croes et al., 2009). However, current epidemiologic studies have shown strains infecting multiple hosts (Lowder et al., 2009, Resch et al., 2013), including the zoonotic livestock associated methicillin S. aureus (LA-MRSA) lineage (CC398).

Strain types in CC8, a known human associated lineage, have been isolated in cases of subclinical bovine mastitis suggesting host switching (Sakwinska et al., 2011a,Barlow et al., 2013, Resch et al., 2013). MLST has been extensively used to understand local and global epidemiology of S. aureus from dairy farms (Boss et al., 2016; Budd et al., 2015;

Peton and Le Loir, 2014). Bovine mastitis is caused by STs in limited lineages that have a pandemic spread. Clonal complex (CC) 97 is one of the most common lineages causing bovine mastitis. While some lineages are bovine specific (e.g. CC97 and CC151), others have been shown to have multiple hosts causing bovine mastitis and infections or colonizing other hosts including humans (e.g. CC8, CC130, and CC398). These lineages shared by humans and animals have a public health implication; they pose a health risk to farmers especially those lineages that tend to be multidrug resistant like CC398 methicillin resistant S. aureus (MRSA). Whereas MLST has been widely embraced in S. aureus, it is not widely used in CNS even with those species that have MLST schemes well established and so there is limited knowledge.

CC97 (Cow adapted)

CC15 (Human adapted)

CC5

CC8 (Human & cows) CC239 (Human)

Figure 1-3: eBurst analysis of some S. aureus clonal groups Diagram made using input data from S. aureus MLST database (pubmlst.org). Probable host adaptation of some clonal complexes is also indicated. Note that the diagram only includes a few CCs, the analysis can also be done on the entire S. aureus MLST database

1.8.2.4.2 Multilocus Variable Number of Tandem Repeats Analysis (MLVA)

The MLVA is based on the detection of the differences in the number of tandem repeats in the particular loci of the organism’s genome. The loci with high allelic variations are selected using software tools, and the repeat sequences are multiplex PCR amplified using flanking primers (Sabat et al., 2003). The PCR products can be separated using gel electrophoresis or sequenced to ascertain their size. The size depends on the number of tandem repeats and the number may vary between strains of a given species

(Li et al., 2009). The method is rapid and it has been shown to have reproducibility and discriminatory power comparable to PFGE when used to type S. aureus isolates (Sabat et al., 2003). This method is not standardized and primers need to be designed for each pathogenic species depending on the loci used and it is difficult to compare data between laboratories. The banding pattern generated does not reveal which band belongs to which

PCR target however; variation in the loci can alternatively be measured by sequencing

(Sabat et al., 2013).

1.8.2.4.3 Whole Genome Sequencing (WGS)

Whole genome sequencing (WGS) is now widely used to study pathogen epidemiology (Salipante et al., 2015; Park et al., 2017). Effective control of diseases requires effective detection of transmission events in outbreaks. One approach that has been used historically is strain typing so that inferences on transmission are made based on the genetic relatedness of the pathogens. Whole genome sequencing (WGS) has by far the highest discriminatory power compared to other strain typing methods discussed

(Harris et al., 2013). This method distinguishes closely related bacteria strains, for example, it has been used to infer the evolutionary history of emergence of the pandemic poultry lineage ST5 from a human S. aureus ancestor (Lowder et al., 2009). Sequence reads are aligned to a reference genome to identify single nucleotide polymorphisms

(SNPs) in the core genome (Price et al., 2012, Spoor et al., 2013, Tong et al., 2015b). To make inferences about genetic relatedness of the bacteria using WGS data, a phylogenetic tree can be constructed using the core genome SNP analysis that can assign each genome sequence into clades (Price et al., 2012). It has been shown that phylogenies derived from

concatenated genes of MLST are incongruent with whole genome phylogenies due to fewer bases in the MLST loci (Tsang et al., 2017). Since sequencing is becoming cheaper every year, WGS is likely to replace most of the conventional strain typing techniques.

The typing techniques reviewed in this write up are not exhaustive and readers can refer to other reviews and articles (Kloos and Bannerman, 1994, Tenover et al., 1994,

Fournier et al., 2008, Braem et al., 2011, Mehndiratta and Bhalla, 2012, Adzitey et al.,

2013, Sabat et al., 2013). Species-specific typing methods also exist, for example, spa

(Staphylococcus protein A) and coagulase gene typing of S. aureus. Spa typing is based on the determining the repeat profile and spa type within an isolate’s spa gene. The X region of the spa gene has variable number of repeats (21-27) bp, this region is amplified and sequenced. The sequence profile of the repeat sequences represents a spa type

(Shopsin et al., 2000, Koreen et al., 2004). The coa gene (coagulase) typing is based on the polymorphisms of S. aureus coagulase gene (Shopsin et al., 2000). Advantages and disadvantages of some of the common genotypic typing methods discussed have been reviewed in more depth and summarized in a tabular format (Boccia et al., 2015). Zadoks and colleagues have reviewed the use of genotypic typing methods in molecular epidemiology of bovine mastitis pathogens (Zadoks and Schukken, 2006, Zadoks et al.,

2011).

1.9 Staphylococci virulence factors

Staphylococcus species possess a plethora of virulence factors important in bacterial pathogenesis and disease progression. The virulence determinants, including biofilm formation are well studied in S. aureus compared to other staphylococcus species.

Although the focus in this section of the review is on S. aureus, virulence factors for other species, mainly CNS associated with udder health have been reviewed recently

(Vanderhaeghen et al., 2014). Some virulence factors are universal to all pathogenic staphylococci, though species-specific differences do exist (von Eiff et al., 2002,

Longauerova, 2006, Vanderhaeghen et al., 2014), and are beyond the scope of this review. In general, CNS have fewer virulence factors than S. aureus (Longauerova,

2006). Apart from biofilm formation and antimicrobial resistance, other virulence factors reviewed here were not studied in this dissertation. These other factors are briefly reviewed here, as they may contribute to pathogenesis of Staphylococcus and may represent areas for future study. Some virulence factors especially those involved in the initial bacterial adhesion to host cells or extracellular matrixes, which are also crucial steps during biofilm formation. Some virulence factors have been shown to a play role in cell-to-cell adhesion a hallmark of biofilm formation (Table 1-3).

1.9.1 Adhesion to host cells and extracellular matrix

Staphylococci species possess a number of highly regulated virulence factors. For instance, virulence factors that are important for the bacteria to adhere to host cells or extracellular matrix (ECM) are expressed in the exponential growth phase, whereas, those important for establishment of the disease process are expressed in the stationary phase (Lowy, 1998). The adhesion to host cells or ECM is a crucial step in the pathogenesis and initiation of staphylococcal infections. Adhesion is mediated by a variety of surface molecules called adhesins (Zecconi and Scali, 2013). These can be on the bacterial surface or secreted. The surface adhesins are commonly known as microbial

surface components recognizing adhesive matrix molecules (MSCRAMMs). These secreted proteins play a role in invasion or host immune cell evasion (discussed later), and are termed as secretable expanded repertoire adhesive molecules (SERAMs) (Bien et al., 2011). The major staphylococci MSCRAMMs include: fibronectin-binding proteins

(FnBPs), clumping factors (Clfs), protein A (SpA) and collagen-binding protein (CnA).

S. aureus produces two fibronectin/fibrinogen binding proteins (FnBPA and FnBPB) which are important for host colonization. In particular, the FnBPs bind host fibronectin and elastin, whereas FnBPA can also bind fibrinogen (Gordon and Lowy, 2008, Bien et al., 2011). The attachment of FnBPs to fibronectin creates a bond between S. aureus and host integrins. Clumping factors A and B adhere to fibrinogen and also promotes platelet aggregation. Clumping factors also bind to cytokeratin 8 and 10 allowing S. aureus to colonize the anterior nares. Collagen-binding protein, as the name suggests binds to the host collagen, which help in the invasion of diverse host tissues (Bien et al., 2011).

Staphylococcus aureus mutants in most of the above-described adhesins have been shown to be less virulent as compared to the wild type. Protein A plays a pivotal role in the S. aureus host immune evasion, and will be discussed later.

1.9.2 Host tissue invasion and damage

Staphylococcal species produce exoproteins such as enzymes and exotoxins. The enzymes that play a role in disease progression include: nucleases, lipases, hyaluronidases, esterases, phospholipases, and collagenases (Dinges et al., 2000, von

Eiff et al., 2002). These proteins cause tissue damage and play a major role in the spread of bacteria within host tissues and development of the disease. The enzymes; nucleases,

lipases, hyaluronidases and collagenases, degrade their respective substrates during infection and thus contribute to bacterial invasion, tissue damage and disease development. Hyaluronidases, for instance, degrade hyaluronic acid, an acid polysaccharide present within the matrix of the connective tissue enabling bacterial spread within tissues (Dinges et al., 2000). Hydrolysis of lipids by the lipases is believed to be essential for the staphylococci to survive within the sebaceous area of the skin. It is believed that lipases must be present for staphylococci to invade cutaneous and subcutaneous tissues. Although the role of coagulase in S. aureus pathogenesis is still debatable, the fibrin layer formed around abscesses is thought to localize the infection and protect S. aureus from phagocytosis (Gordon and Lowy, 2008).

The first group of exotoxins is cytolytic; they form pores within host cell membranes leading to leakage of vital cell contents, cell lysis and death (Gordon and

Lowy, 2008). These toxins include: α-hemolysin, β-hemolysin, δ-hemolysin, leucocidin, and Panton-Valentine Leukocidin (PVL). The α-hemolysin oligomerizes into a β-barrel upon insertion in platelets and monocytes causing osmotic cytolysis. The PVL is bicomponent cytolysin (LukF-PV and LukS-PV) that hetero-oligomerizes to form a pore within host cells. PVL and leukocidin have high affinity for leukocytes whereas; δ- hemolysins are cytotoxic to erythrocytes (Gordon and Lowy, 2008, Graves et al., 2010,

Powers and Bubeck Wardenburg, 2014). The second group of exotoxins do not lyse host cells. These include: toxic shock syndrome toxin-1 (TSST-1), enterotoxins and exfoliative toxins (ETA and ETB). The TSST-1 and enterotoxins are known as pyrogenic superantigens (PTSAgs) (Dinges et al., 2000, Bien et al., 2011). The PTSAgs

non-specifically stimulate T-lymphocyte proliferation and over production of cytokines that can lead to toxic shock syndrome. Enterotoxins are also a common cause of staphylococcal food poisoning and have emetic properties. Although a lot of enterotoxins have been discovered, enterotoxin A, B, C, D and E are well studied.

Exfoliative toxins: ETA and ETB, cause Staphylococcal scaled skin 1syndrome (SSSS)

(Powers and Bubeck Wardenburg, 2014).

1.9.3 Evasion of host defense mechanisms

Staphylococci, including S. aureus, are facultative intracellular pathogens. The bacteria encounter host innate and adaptive immune defenses and they have evolved to counteract host immune defenses. Staphylococcus aureus in particular secretes proteins or virulence factors that are able to compromise both lines of the host immune defenses.

1.9.3.1 Staphylococcal neutrophil evasion

Neutrophils migrate from blood to the infected site and engulf the invading pathogens before the adaptive immunity is stimulated. With infection of S. aureus, neutrophil migration is modulated by the Staphylococcal superantigen-like 5 (SSL5).

SSL5 binds to P-selectin glycoprotein ligand 1 (PSGL-1) abrogating neutrophil binding to P-selectin on the endothelial wall preventing neutrophil rolling, extravasation and migration to an infection site (Bestebroer et al., 2009). SSL5 also negatively regulates leukocytes responses to chemokines CXC, CC, CXC3 and to complement fragments C3a and C5a (Bestebroer et al., 2010, Spaan et al., 2013). Additionally, chemotaxis inhibitory protein of staphylococci (CHIPS) binds and inhibits formyl protein receptor 1 (FPR1) and

C5aR, preventing neutrophil chemotaxis. Staphylococcus aureus extracellular adherence protein (Eap) binds intercellular adhesion molecule 1 (ICAM-1) on endothelial cells, inhibiting the binding of LFA-1 (lymphocyte associated antigen 1) on the surface of neutrophils. This further prevents leukocyte adhesion, diapedesis and extravasation

(Foster, 2005, Spaan et al., 2013).

Phagocytosis of S. aureus by neutrophils is enhanced by opsonins on the surface of bacterial cells. The opsonins include antibodies (IgG) and complement proteins that are recognized by phagocytic cells’ receptors. S. aureus possesses proteins that inhibit phagocytosis. Protein A, for example, binds to the Fc portion of IgG resulting in coating of S. aureus cells with IgG molecules in a reverse orientation that cannot be recognized by the neutrophils (Lowy, 1998, Powers and Bubeck Wardenburg, 2014). Protein A mutant strains are easily phagocytized and have reduced virulence in animal experimental models (Kim et al., 2012). Some bacteria, including S. aureus, possess a capsule that is thought to prevent neutrophil phagocytosis. In vitro assays showed reduced neutrophil uptake of bacteria with a capsule even in the presence of opsonins suggesting that the capsule is an antiphagocytic structure. Probably the capsule hides the cell surface epitopes and so opsonins cannot bind (Thammavongsa et al., 2015).

If neutrophil phagocytosis happens, S. aureus can survive in the phagosome. One of the factors that play critical role in phagosome survival is staphylothanthin, a carotenoid pigment that scavenges free oxygen radicals that are detrimental to the bacteria (Spaan et al., 2013). S. aureus also expresses catalase and two superperoxide dismutase enzymes that also remove free oxygen radicals that are toxic to the bacteria. In

addition, the bacteria can be protected from antimicrobial peptides. This is partly attributable to modification within the wall teichoic acid, lipoteichoic acid and membrane phospholipids. The modifications reduce the relatively affinity of the antimicrobial peptides (Foster, 2005).

1.9.3.2 Inactivation of the complement

Complement activation is mediated by binding of C3 convertases (C4aC2 and

C3bBb) on bacteria cell surface. S. aureus secretes staphylococcus complement inhibitor

(SCIN), which binds the C3 convertases stabilizing them, inhibiting C3b formation.

Extracellular fibrinogen binding protein Efb has also been shown to be an inhibitor of C3 binding to bacterial cell surface (Foster, 2005, Spaan et al., 2013).

1.9.3.3 Lysozyme Evasion

Lysozymes are part of innate immune defenses and are present in many body fluids. They cleave peptidoglycan cell wall linkages causing cell lysis and death.

Resistance of S. aureus to lysozyme is due to O-acetyltranferase that modifies H6 hydroxyl group of muramic acid. Mutants are sensitive to lysozymes and complementation of the wild type gene restores the resistance (Foster, 2005).

Table 1-3: Staphylococci virulence factors associated with biofilm formation identified in isolates obtained from dairy cattle

Protein name Staphylococcus species 1 References ica locus S. aureus Kundalik et al., Trop Anim Health Prod (2012) 44:247–252 S. epidermidis, S. hominis, S. kloosi, S. sciuri Felipe et al., Microbial Pathogenesis 104 (2017) 278e286 S. chromogenes, S. sciuri, S. xylosus Rumi et al., J Infect Dev Ctries 2013; 7(7):556-560 S. haemolyticus, S. epidemidis, S. simulans Tremblay et al., J. Dairy Sci. 96:234–246 S. capitis, S. cohnii, S. saprophyticus, S. warneri Piessens et al., 2012. Journal of Dairy Science Vol. 95 No. 12, 2012 Biofilm associated proten (bap) S. aureus Cucarella et al. .J. Bacteriol. 183, 2888–2896 (2001).

S. chromogenes, S. haemolyticus, Tremblay et al., J. Dairy Sci. 96:234–246

S. epidermidis, S. simulans, S. equorum Xu et al.,Microbial Pathogenesis 88 (2015) 29e38

S. xylosus, S. saprophyticus, S. warneri Felipe et al., Microbial Pathogenesis 104 (2017) 278e286 Accumulation associated protein S. chromogenes, S. haemolyticus, Tremblay et al., J. Dairy Sci. 96:234–246 S. epidermidis, S. simulans

Extracellular matrix binding protein S. chromogenes, S. haemolyticus, Tremblay et al., J. Dairy Sci. 96:234–246 S. epidermidis, S. simulans Clumping factor B S. aureus, S. chromogenes, S. kloosii, S. xylosus, Abraham & Jefferson. Microbiology 158, 1504–1512 (2012). S. warneri, S. haemolyticus, S. epidermidis, S. hominis Xu et al.,Microbial Pathogenesis 88 (2015) 29e38 S. sciuri, S. warneri, S. simulans, S. saprophyticus Felipe et al., Microbial Pathogenesis 104 (2017) 278e286

Fibrinonectin binding protein A S. aureus, S. chromogenes, S. kloosii, S. simulams O’Neill et al. . J. Bacteriol. 190, 3835–3850 (2008).

S. haemolyticus, S. epidermidis, Xu et al.,Microbial Pathogenesis 88 (2015) 29e38 S. warneri, S. xylosus Felipe et al., Microbial Pathogenesis 104 (2017) 278e286 Fibrinonectin binding protein B S. aureus, S. simulans, S. chromogenes, S. warneri O’Neill et al. . J. Bacteriol. 190, 3835–3850 (2008). S. kloosii, S. epidermidis, S. saprophyticus Xu et al.,Microbial Pathogenesis 88 (2015) 29e38 Felipe et al., Microbial Pathogenesis 104 (2017) 278e286 S. aureus protein C Schroeder et al. PLoS ONE 4, e7567 (2009). S. aureus protein G Geoghegan et al.J. Bacteriol. 192, 5663–5673 (2010). Serine aspartate repeat protein C Barbu et al. Mol. Microbiol. 94(1):172-185. S. aureus protein A Merino et al. J. Bacteriol. 191, 832–843 (2009). S. aureus protein X Li et al. Nature Med. 18, 816–819 (2012

Bacterial species in which the respective biofilm associated factors have been identified. Data are restricted to isolates obtained from milk or cases of bovine mastitis studies. Proteins (or their associated genes) in black have been identified among isolates obtained from dairy cattle or bovine milk. There is no significant information or studies for the prevalence (association) of proteins in blue text in biofilm formation of staphylococci from dairy cows, but these proteins have been shown to play role in biofilm for S. aureus from humans.

1.9.4 Biofilm formation

Staphylococci’s ability to form a biofilm is now considered a virulence factor, and in general, biofilm phenotype in prokaryotes, is a survival strategy against environmental stressors (Hall-Stoodley et al., 2004). A biofilm is a community of bacteria enclosed in self-produced polymeric matrix (Fox et al., 2005b, Melchior et al., 2006). It is 50

hypothesized that biofilm formation may facilitate adhesion to the mammary gland epithelium and host immune evasion (Baselga et al., 1993, Cucarella et al., 2004). The community growth phenotype protects bacterial cells from antibiotics, disinfectants, environmental stressors and phagocytosis due to the presence of exopolysaccharide matrix. Evasion of phagocytosis may increase survival of the bacteria within the host and may contribute to persistent IMI (Melchior et al, 2006). The antibiotic resistance is due to the reduced diffusion of the antibiotics into the biofilm mainly attributed by the extracellular matrix (slime or loosely attached glycocalyx). In addition, the inner cells within the biofilm are metabolically inactive, and most antibiotics (especially β-lactams) are sensitive to active dividing and metabolizing cells. The in vitro minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) can be 100-1000 times higher in bacteria within a biofilm compared to their planktonic counterparts

(Vasudevan et al., 2003, Hall-Stoodley et al., 2004, Hoiby et al., 2010).

Staphylococci biofilm formation is a three-stage process i.e. attachment, maturation, and detachment/dispersal. Initial attachment to abiotic surfaces depends on the physicochemical properties of the surface and that of the bacteria. Therefore, attachment of bacteria to abiotic surfaces (e.g. plastics, indwelling medical devices, food processing surfaces) is mainly driven by the hydrophobic or electrostatic interactions

(Hall-Stoodley et al., 2004, Otto, 2013). However, some bacterial surface molecules, protein autolysin or teichoic acids, have been shown to mediate attachment to abiotic surface as well (Gross et al., 2001). On the other hand, staphylococcal attachment to biotic surfaces (e.g. mammalian tissues) depends on different mechanisms mainly

mediated by MSCRAMMs. Staphylococci as earlier mentioned, express surface bound proteins (MSCRAMMs) that facilitate bacterial attachment to host’s cell and extracellular matrix proteins such as fibrinogen, fibronectin, collagen, and others (Otto, 2013).

Maturation involves bacterial cell division, cell-to-cell adhesion, and formation of channels. This forms a mature multilayered “mushroom/mound” shaped biofilm. In staphylococci, cell-to-cell adhesion is mediated by production of polysaccharide intercellular adhesin (PIA), also known as PNAG derived from its chemical structure

(poly-b(1-6)-N-acetylglucosamine). The PIA is encoded by the ica operon, which consists of icaADB and C genes. The icaR, transcribed divergently from icaADBC regulates icaADBC expression (Cramton et al., 1999). The icaA and icaD are the major genes in biofilm formation as they contribute to exopolysaccharide biosynthesis. The activity of icaA product is enhanced when it is co-expressed with icaD gene. The icaA encodes N-acetylglucosaminotranferase enzyme used in the biosynthesis of acetylglucosaminoglycan oligomers from UDP-N-acetylglucosamine. N- acetylglucosaminoglycan oligomers are the building blocks of PIA, (Arciola et al., 2001,

Otto, 2009, Arciola et al., 2015), and are exported to the bacterial surface by icaC gene product. The polymer (Poly-N-acetylglucosamine) is partially deacetylated by the product of icaB (N-deacetylase) in order to be anchored onto the bacterial surface, and gives PIA a positive charge (Arciola et al., 2015). The role of PIA in biofilm formation has been studied in vitro extensively, however, some PIA negative strains have been shown to form biofilms. This suggests that other ica independent biofilm formation mechanisms exist. The quest for novel biofilm formation determinants has led to the

discovery of other proteins and molecules involved in biofilm formation. These proteins/molecules substitute PIA for cell-to-cell adhesion. They include biofilm- associated protein (bap) encoded by the bap gene (Cucarella et al., 2001), accumulation associated protein (Aap) (Hussain et al., 1997), extracellular matrix binding protein

(Embp), S. aureus protein A (Spa) (Merino et al., 2009), fibrinonectin binding proteins

(FnbpA and FnbpB) (O'Neill et al., 2008), S. aureus surface protein G (SasG)

(Geoghegan et al., 2010), and others reviewed recently (Foster et al., 2014). Teichoic acids and DNA released (eDNA) from lysed bacteria have been demonstrated to play a role in biofilm formation as well (Dengler et al., 2015).

Detachment of bacteria from a mature biofilm creates new foci of infections, a hallmark of infection dissemination and recurrent disease or pathogen shedding episodes.

The detachment is self-mediated by the bacteria within the biofilm, they produce enzymes that digest the biofilm matrix and the adhesins that glue bacteria together. These enzymes include proteases, nucleases, and group of small amphiphilic α-helical peptide

(phenol soluble modulins (PSMs)) functioning as surfactants (Periasamy et al., 2012,

Speziale et al., 2014).

In general, ica locus is more prevalent in S. aureus isolates from mastitis cases compared to CNS. Recent bovine mastitis studies have reported a 95-100% ica locus prevalence in S. aureus isolates (Vasudevan et al., 2003, Szweda et al., 2012, Prenafeta et al., 2014, Felipe et al., 2017), but a lower prevalence (numbers) in the CNS (Piessens et al., 2012, Martins et al., 2017). Fox and colleagues found milk S. aureus isolates to be better biofilm formers than isolates from cow skin (Fox et al., 2005b) and 85% of the

isolates in a recent CNS study were classified biofilm formers and were all from IMI cases (Tremblay et al., 2013). This may suggest that staphylococci from IMI cases are indeed better biofilm formers and this phenotype might contribute to chronic infection.

However, another study on CNS showed no association between biofilm phenotype and persistence of IMI, and percentage of biofilm positive isolates was low (Simojoki et al.,

2012). It’s noteworthy that isolates used in these studies were mainly from cow milk.

There is still some knowledge gap on species-specific biofilm forming potential among staphylococci from diverse niches on farms. Piessens and colleagues analyzed 40 isolates for biofilm formation, which included cow milk, and environmental isolates and only

22.5% were considered biofilm formers (Piessens et al., 2012).

1.9.4.1 Micro-titer plate in vitro biofilm assay

The micro-titer plate assay is arguably the most common assay used to quantify bacterial biofilm forming potential; including staphylococci isolated from dairy cattle or dairy farm environments (Table 1-4). It has high sensitivity and reproducibility, and is quantitative, compared to other methods like congo red agar method (Mathur et al.,

2006). In brief, the micro-titer play assay involves growing bacteria in tryptcase soy broth (TSB) supplemented with glucose in a 96 well polystyrene plate. After 24 hours of incubation in a static environment at 370C, planktonic bacteria are washed off, and the adhered bacteria at the bottom of the wells (biofilms) are stained and the extent of stain uptake is quantified using a plate reader (Christensen et al., 1985). Although this assay is good, it lacks universal standardized protocols especially how to set a cut point

(threshold) optical density for a biofilm negative or positive isolate, which complicates

comparing results between studies. Overall, the common method in literature for determining the cut point ODc (Optical density) is mean OD for blank well plus 3 standard deviation (Christensen et al., 1985, Stepanovic et al., 2000, Atshan et al., 2012,

Piessens et al., 2012, Darwish and Asfour, 2013, Lee et al., 2014, Ploneczka-Janeczko et al., 2014, Cirkovic et al., 2015, Khoramian et al., 2015). Some studies have used the negative control strain mean OD plus 3 standard deviation for cut point set up (Fox et al.,

2005b, Piessens et al., 2012, Simojoki et al., 2012), whereas others just use arbitrary cut points without giving a justification or use cut points from other published papers (Mack et al., 2000, Vasudevan et al., 2003, Oliveira et al., 2006, Esteban et al., 2010, Tremblay et al., 2013, Eyoh et al., 2014, Wojtyczka et al., 2014, Cui et al., 2015). Some authors are clear on the plate type used for example, 96-well tissue culture treated plates, and others just say they used 96-well micro-titer plates without any further information about the type or company source (Table 1-4). It’s hard to know in such scenarios whether such plates were tissue culture treated or not, and thig may be problematic because plate surface type might have an effect on staphylococci biofilm formation (Kennedy and

O'Gara, 2004). Other methods have been used to assess biofilm formation in staphylococci for example, use of congo red agar method and tube method, (Table 1-4).

Unlike the micro-plate assay, which is quantitative, these other methods are mainly used for qualitative assessment of biofilm formation. Congo red agar method differentiates slime (extracellular matrix) producing and none producing strains. Briefly bacteria are inoculated on congo red agar and incubated overnight at optimal temperature. Slime producing bacterial colonies are phenotypically black with a dry crystalline consistency,

whereas, the negative strains’ colonies remain pink (Freeman et al., 1989). The tube methods involve growing bacteria in glass or plastic culture tubes overnight. Planktonic bacteria are washed from the tubes, as in the micro-plate assay and the adhered bacteria

(biofilm are stained). A strain is considered biofilm positive if a stained film is visible on the wall and the bottom of the tube (Dhanawade et al., 2010). Other methods that are less commonly used for observing biofilm in mastitis isolates include but are not limited to, fluorescent in situ hybridization (FISH) and confocal laser scanning microscopy (Table

1-4).

Table 1-4: Common methods used for assessment of biofilm formation of staphylococci on dairy farms

Bacterial Species Source Method Cut point Plate type Reference S. aureus quarter milk microplate assay >0.1 96-well plates (Oxvital, 167008) M. Oliveira et al. / Veterinary Microbiology 118 (2006) 133–14 S. aureus quarter milk FISH & Congo red M. Oliveira et al. / Veterinary Microbiology 118 (2006) 133–14

S. epidermidis quarter milk microplate assay 96-well plates (Oxvital, 167008) M. Oliveira et al. / Veterinary Microbiology 118 (2006) 133–14 S. aureus quarter milk microplate assay >0.1 Sterile 96-well ‘‘U’’ bottom polystyrene tissue culture plates P. Vasudevan et al. / Veterinary Microbiology 92 (2003) 179–185 S. aureus quarter milk Congo red P. Vasudevan et al. / Veterinary Microbiology 92 (2003) 179–185 S. aureus milk microplate assay Negative control strain Sterile 96-well ‘‘U’’ bottom polystyrene tissue culture plates L.K. Fox et al. / Veterinary Microbiology 107 (2005) 295–299

S. aureus cow skin microplate assay Negative control strain Sterile 96-well ‘‘U’’ bottom polystyrene tissue culture plates L.K. Fox et al. / Veterinary Microbiology 107 (2005) 295–300

S. aureus liner microplate assay Negative control strain Sterile 96-well ‘‘U’’ bottom polystyrene tissue culture plates L.K. Fox et al. / Veterinary Microbiology 107 (2005) 295–301 S. aureus quarter milk microplate assay >0.1 Szweda P. et al.Polish Journal of Microbiology 2012, Vol. 61, No 1, 65–69 S. aureus cow milk microplate assay Negative control strain Polystyrene microtiter plates Prenafeta et al. J Dairy Sci. 2014 Aug;97(8):4838-41. CNS quarter milk microplate assay Negative control strain 96-well microtiter tissue culture treated plates Simojoki et al., 2012.Veterinary Microbiology 158 (2012) 344–352 CNS quarter milk Cong red Simojoki et al., 2012.Veterinary Microbiology 158 (2012) 344–353 CNS quarter milk FISH Simojoki et al., 2012.Veterinary Microbiology 158 (2012) 344–354

CNS quarter milk microplate assay Negative control strain 96-well microtiter tissue culture treated plates Tremblay et al., 2013. J. Dairy Sci. 96:234–246

Staphylococus spp dog and swine microplate assay Negative control strain 96-well flat-bottomed tissue culture plates Seo et al., 2008. Research in Veterinary Science 85 (2008) 433–438 S. aureus quarter milk microplate assay >0.1 96-well polystyrene tissue culture plates Melo et al., Brazilian Journal of Microbiology 44, 1, 119-124 (2013) S. aureus quarter milk Cong red Melo et al., Brazilian Journal of Microbiology 44, 1, 119-124 (2013) S. aureus quarter milk microplate assay Not mentioned 96-well polystyrene tissue culture plates Dhanawade et al. Vet Res Commun (2010) 34:81–89 S. aureus quarter milk Cong red Dhanawade et al. Vet Res Commun (2010) 34:81–90 S. aureus quarter milk tube method Dhanawade et al. Vet Res Commun (2010) 34:81–91

S. aureus quarter milk microplate assay Blank absorbance 96-well, flat- bottomed plastic microplate Lee et al., 2014. J. Dairy Sci. 97:1812–1816

CNS quarter milk & Env. microplate assay Negative control strain flat-bottomed polystyrene 96-well microtiter plate Piessens et al., 2012. J. Dairy Sci. 95:7027–7038 CNS quarter milk microplate assay Not mentioned 96-well polystyrene tissue culture plates Goetz et al., 2017. J. Dairy Sci. 100:6454–6464

CNS quarter milk confocal microscopy Goetz et al., 2017. J. Dairy Sci. 100:6454–6465

CNS quarter milk Microfluidic system Goetz et al., 2017. J. Dairy Sci. 100:6454–6466

CNS quarter milk microplate assay Negative control strain 96-well polystyrene microtiter plate Isaac et al., Veterinary Microbiology 207 (2017) 259–266 Staphylococus spp Negative control strain 96-well tissue culture treated polystyrene microplates Felipe et L., Microbial Pathogenesis 104 (2017) 278e286 Cut off point- Method used to set the threshold OD for biofilm negative and positive isolates. Studies with (>0.1), means that any isolates with blank adjusted OD above 0.1 were considered biofilm positive with no other categories. Some studies use the blank OD or negative control strain to set threshold and categorize biofilm formation as none, weak, moderate, and strong biofilm formers as described by Stepanovic et al., (2000).

1.10 Staphylococci antimicrobial resistance

Many antimicrobial agents, belonging to different classes, are available for treating staphylococcal infections. Their mode of action, and the mechanisms of how the bacteria become resistant to them have been reviewed recently (Munita and Arias,

2016). In the United States and Canada dairy industry, mastitis is the number one reason for antibiotic use on dairy farms for example, during dry cow therapy or treatment of clinical mastitis cases (Kaneene and Miller, 1992, Saini et al., 2012). It is estimated that

90% of US dairy farms use antibiotics, and β-lactams are the most common drugs used

(Pol and Ruegg, 2007, USDA, 2014). Although, treatment of mastitis is good from animal welfare point of view, antibiotic use on farms is believed to drive antimicrobial resistance in farm animals (van den Bogaard et al., 2001, Rajala-Schultz et al., 2009). Use of antibiotics may select for resistant population of microbes. This is not only an animal health problem but also a public health hazard as some resistant bacteria can be transmitted from animals to human directly or through consumption of dairy products like milk and cheese (Fey et al., 2000). The major concern is the increasing prevalence of multidrug resistant bacteria especially in humans, for instance, methicillin resistant S. aureus (MRSA) and CNS (MRCNS). Methicillin resistant bacteria are usually resistant to all β-lactam antibiotics and other classes of antibiotics (Woodford, 2005, Cuny et al.,

2015). β-lactam antibiotics act by binding to the bacterial penicillin binding proteins

(PBPs), which are important in the cell wall peptidoglycan biosynthesis. The blaZ and mecA genes, whose products confer resistance to penicillin and methicillin resistance respectively, are the most common forms of resistance to β-lactam antibiotics. BlaZ gene

encodes a penicillinase, which is a lactamase that hydrolyzes the β-lactam antibiotics rendering them ineffective (Lowy, 2003). The mecA gene encodes an altered penicillin binding protein (PBP), known as PBP2a that has lower affinity for β-lactam antibiotics, including penicillins, cephalosporins, and carbapenems, except the fifth generation cephalosporins, allowing bacterial cell wall biosynthesis in presence of inhibitory concentrations. Although the mecA (MRSA N315 strain prototype) gene is similar in most staphylococci (95-100% identical), homologues have been discovered, for example, mecC in S. aureus (Garcia-Alvarez et al., 2011), mecB and mecD in Macrococcus caseolyticus (Gomez-Sanz et al., 2015, Schwendener et al., 2017), mecA1 and mecA2 in

S. sciuri and S. vitulinus respectively (Wu et al., 1996, Schnellmann et al., 2006,

Tsubakishita et al., 2010), mecC1 (in S. xylosus) and mecC2 (in S. saprophyticus)

(Harrison et al., 2013, Malyszko et al., 2014). These mecA variants/homologues seem to be limited to a few species or species specific (Table 1-5). For example, apart from mecC, there is no published research on presence of the rest of the other homologues in S. aureus to the best of my knowledge. In addition to S. aureus, mecC has been detected in one CNS species strain (S. stepanovicii) isolated from a wild Eurasian lynx (Loncaric et al., 2013). S. aureus carrying mecC has been reported with relatively low prevalence in

13 European countries (Paterson et al., 2014). The mecC carriage is mainly associated with S. aureus CC130 and CC425. These mecC-associated S. aureus lineages have been identified in at least 14 host species including humans, wildlife, and cows suggesting wide host tropism (Paterson et al., 2014). In the United States, a recent study on 102

MRSA strains isolated from military personnel found zero mecC prevalence (Ganesan et

al., 2013). To the best of my knowledge there are no documented cases of staphylococci with mecC causing bovine mastitis in the U.S. suggesting geographical specificity of the mecC positive S. aureus lineages. The nomenclature of the mec variants is based on the recently published standardized guidelines on naming novel mecA gene homologues (Ito et al., 2012). Although, mecA1 is highly prevalent in S. sciuri isolates, most mecA1 positive strains tend to be susceptible or show heteroresistance to β-lactam antibiotics

(Wu et al., 1996, Wu et al., 1998, Couto et al., 2003, Harrison et al., 2014). Similarly, mecA alleles have been found in some S. vitulinus, S. capitis, and S. kloosii isolates

(Monecke et al., 2012). Surprisingly, one S. sciuri isolate contained both the prototype mecA and mecA1 (Wu et al., 1998), and another with mecA and mecC (Harrison et al.,

2014). Carriage of multiple gene variants might explain heteroresistance in some isolates.

It is noteworthy that most of the mecA gene homologues described were initially identified in bacteria from animals (Table 1-5) supporting the concept that animals might be reservoirs of these novel antibiotic resistance gene variants.

The mecA gene is carried on mobile genetic element called staphylococcal chromosomal cassette mec (SCCmec) (Lowy, 2003). The SCCmec in general consists of two major components, i) the mec complex that contains the mecA gene and ii) the ccr complex, encoding site-specific recombinases required for the movement of the cassette. Upon excision, the cassette integrates within the chromosome at 3’ end of orfX, an open reading frame of no known function, located in close proximity to the origin of replication (oriC) (Katayama et al., 2000, Kuroda et al., 2001, Harrison et al., 2013). The SCCmec cassette is classified based on the combination of types of mec

and ccr complexes. The staphylococci can exchange this cassette allowing the spread of mecA gene to other bacteria; for instance, mecA gene in CNS can be transferred to more pathogenic bacteria like S. aureus (Wielders et al., 2001, Berglund and Soderquist, 2008,

Bloemendaal et al., 2010). In fact, it is speculated that S. fleurettii is the origin of mecA gene. The mecA gene in S. fleurettii was found to be (99-100%) identical to the prototype mecA in S. aureus N315 strain, but it was located on the chromosome instead of the cassette. This prompted Tsubakishita and colleagues to propose that a SCC mecA free cassette might have acquired the mecA gene and its surrounding chromosomal region from S. fleurettii (Tsubakishita et al., 2010). Other CNS species postulated to have had the precursor of the mecA gene include S. sciuri, and S. vitulinus. These species belong to

S. sciuri group, which contains S. sciuri, S. vitulinus, S. fleurettii, S. lentus, and S. stepanovicii (Lamers et al., 2012, Becker et al., 2014). Understanding antibiotic resistance of these bacteria and other staphylococci in general is crucial to monitoring emerging multidrug resistant clones and reservoirs of methicillin resistance genes

(mecA).

Methicillin resistance is well studied in S. aureus and epidemiologically, resistant strains are broadly categorized into hospital acquired (HA-MRSA), community acquired (CA-MRSA), and, most recently, livestock associated (LA-MRSA) (Cuny et al., 2015). These MRSA groups have unique characteristics for example, CA-MRSA tend to have Panton-Valentine Leukocidin (PVL), have smaller cassettes, and are more susceptible to other classes of antibiotics compared to HA-MRSA (Chambers and Deleo,

2009). The LA-MRSA has become more prominent since first emerging in 2005 when

similar MRSA strains colonized pigs and pig farmers in the Netherlands (Voss et al.,

2005). These pig strains were later found to belong to clonal complex (CC) 398 by

MLST in subsequent studies. CC398 strains cause infections in humans suggesting zoonotic transmission, and representing one of the common zoonotic MRSA lineages

(Lewis et al., 2008). CC398 is the most dominant LA-MRSA lineage in most European countries, whereas studies done in the United States indicate that LA-MRSA is a mixture of CC398, CC5 and CC8 lineages as recently reviewed (Smith, 2015).Whereas

MRSA and MRCNS are a threat in humans (Fey et al., 2003), they’re not common among bovine mastitis associated strains or species in the USA at least from recent studies (Virgin et al., 2009, Haran et al., 2012, Cicconi-Hogan et al., 2014, Ruegg et al.,

2015).

Table 1-5: Animals as potential reservoirs of bacteria with mec homologues mec homologues Year1 % Identity 2 Bacterial species 3 Strain origin MLST (Clonal Complex)4 References mecA1 1998 79.1 S. sciuri Cattle NA Wu et al., 1998. J. Bacteriol. 180:236-242 mecA2 2006 91 S. vitulinus Horse NA Schnellmann et al., 2006. J. Clin. Microbiol. 44:4444-4454

mecB 2010 61.6 M. caseolyticus Domestic Chicken NA Baba et al., 2009. J. Bacteriol. 191:1180-1190

mecC 2011 68.7 S. aureus Cattle (Bulk tank milk) ST425 (CC425) Garcia-Alverez et al.,2011. Lancet. Infect. Dis. 11:595-603

ST130 (CC130) Vanderndriessche et., al 2013. Animicrob. Agents Chemother. 68:1510-1516 2508 (CC599) Unnerstad et al., 2013. Acta. Vet. Scand. 55:6 ST2573 (CC130 Gindonis et al. 2013. Acta. Vet. Scand. 55:61

mecC1 2013 69.9 S. xylosus Bovine mastitis NA Harrison et al., 2013. Animicrob. Agents Chemother. 57:1524-1528

mecC2 2014 69.9 S. saprophyticus Common shrew NA Malyszko et al., 2014. Animicrob. Agents Chemother.

mecD 2017 61 M. caseolyticus Bovine mastitis milk NA Schwendener et al., 2017. Sci Rep. 7:43797 and dog otitis

1- Year when a given mec homologue was identified 2- Percentage sequence similarity of the mec homologues to the conventional mecA gene in S. aureus N315 3- Bacterial species in which a particular homologue was first identified. 4- Strain types or clonal complexes of S. aureus with mecC isolated from bovine milk. NA, no available strain type data.

1.11 Summary The overall goal of this thesis is to understand the molecular epidemiology of bacteria in the genus staphylococcus and phenotypes that might contribute to bacterial survival. Studies were done on selected Vermont dairy farms with the major objective to elucidate the potential sources of bacteria that cause bovine mastitis. We used molecular based bacterial species identification using mainly tuf gene sequencing. We elected to do strain typing on S. aureus and S. chromogenes, the leading CPS and CNS species causing bovine mastitis, respectively. These two species were strain typed using unambiguous multilocus sequence typing technique (MLST). We applied a

Staphylococcus chromogenes MLST scheme that was recently developed in our laboratory with collaborators.

The phenotypes we focused on were: antibiotic susceptibility and biofilm formation. We hypothesized that these phenotypes may contribute to the predominance of a given species on a farm or in a particular niche compared to others. Antibiotic susceptibility was done using two in vitro methods; disk diffusion and broth micro- dilution, and we also evaluated the sensitivity and specificity of these methods in detecting β-lactam antibiotic resistance.

CHAPTER 2 : STAPHYLOCOCCUS AUREUS MULTI-LOCUS

SEQUENCE TYPES FROM VERMONT ORGANIC FRARM BULK

TANK MILK ARE ASSOCIATED WITH IN VITRO BIOFILM

CAPACITY AND ANTIMICROBIAL SUSCEPTIBILITY

Robert Mugabi, Samuel Hart, Amanda Ochoa, John Barlow*

University of Vermont, Burlington, Vermont, USA

*Corresponding author: John Barlow, Department of Animal Science, University of

Vermont

570 Main ST Burlington VT, USA 05405

Phone: 802-656-1395

Email: [email protected]

2.1 Abstract

The objective of this pilot study was to estimate the phenotypic and genotypic diversity of Staphylococcus aureus isolates obtained from organic dairy farms in Vermont. Multi- locus sequence types, in vitro biofilm formation ability and antibiotic susceptibility phenotypes and genotypes were determined for 100 isolates obtained from bulk tank milk samples from 44 organic dairy farms in Vermont. Multi-locus sequence typing (MLST) of isolates had a typeability of 100%, a total of 20 strain types were revealed, and of which 10 were novel. The novel strains included ST963 (n=1), ST3020 (n=1), ST3021

(n=3), ST3022 (n=1), ST3023 (n=1), ST3024 (n=1), ST3025 (n=1), ST3026 (n=1),

ST3027 (n=1), and ST3028 (n=13). Apart from ST3023 in clonal complex (CC) 45, the other novel strains were single locus variants of known bovine associated STs in CC97,

CC151/CC705. The novel and known strain types were distributed in 8 clonal complexes,

CC1, CC8, CC30, CC45, CC59, CC97, and CC151/CC705. However, the isolates were dominated by strain types in CC8 (n=11), CC97 (n=59), CC151 (n=19), which are known to cause bovine mastitis. All isolates were bap gene negative but icaA and icaD positive.

In vitro biofilm formation was evaluated by the micro-titer plate assay method on 2 different plate types and biofilm capacity was associated with clonal lineage and plate type. One hundred percent of the isolates in CC8 and 6.78% of isolates in CC97 were resistant to ampicillin and penicillin, while 100% of isolates in CC151 and CC705 were susceptible to all beta-lactam antibiotics. Comparison of the diversity of S. aureus strains among organic dairy farm isolates from Vermont supports prior observations of dominant

CCs associated with dairy cattle globally, but also identifies regional differences in STs

suggesting unique regional epidemiological clusters. Associations between CC and biofilm formation ability or antimicrobial resistance provide support for future research on genetic factors underlying host-adaptation and virulence.

Key words: Dairy cattle, Molecular epidemiology, Antibiotic resistance, Biofilm

2.2 Introduction

Staphylococcus aureus remains a frequent cause of chronic subclinical and clinical mastitis in dairy cattle (Persson et al. 2011; Keane et al. 2013). Mastitis is the leading cause of production losses among the dairy industry in the USA. Using traditional epidemiological classification schemes, S. aureus is a major contagious mastitis pathogen where the dominant source of new infections is other infected cows or quarters within a herd (Barkema et al., 2006; Barlow et al., 2013; Keefe, 2012). A number of studies have demonstrated the prevalence of S. aureus mastitis on organic dairy farms (Smith et al.,

2005a, Bennedsgaard et al., 2006, Roesch et al., 2006, Cicconi-Hogan et al., 2013).

The proportion of organic dairy farms has been increasing in many countries and as of 2014, was reported to range from 2 to 26 % of dairy farms in selected developed countries (Barkema et al., 2015). In 2001 there were 48,677 milk cows on US certified organic farms, which increased to 254,771 milk cows in 2011 (USDA Economic

Research Service, 2013). In 2013, 198 (21%) of dairy farms in Vermont were certified organic, and this number has remained stable with 202 organic farms in 2017, while the total number of dairy farms in Vermont has decreased to <800 (Vermont Agency of

Agriculture, Food and Markets, 2017). Improved understanding of mastitis epidemiology and milk quality on organic dairy farms is needed. Continued increase in consumer

demand for organic milk and dairy products will support continued expansion of the US organic dairy sector (Greene and McBride, 2015). In addition, understanding mastitis epidemiology and control on well-managed organic farms may provide knowledge applicable to enhancing animal health and disease control on conventional farms (Barlow

2001; Barkema et al., 2015). Bulk tank milk (BTM) culture can be used to estimate herd level prevalence of S. aureus in specific geographic regions or farm populations (Olde

Riekerink et al., 2006). The identification of S. aureus infected herds and cattle remains an important mastitis control practice with public health food safety relevance (Kummel et al., 2016).

In the US, it appears the prevalence of S. aureus is greater among organic herds compared to conventional herds. Cicconi-Hogan et al. (2013) identified S. aureus from a single BTM sample in 62% of 191 organic herds in New York, Wisconsin and Oregon.

The presence of S. aureus was assessed using the standard methods from Hogan et al.

(1999), where 0.5 mL of raw milk was plated on a blood agar plate and incubated for 48 hours at 37°C and colonies were determined to be S. aureus by assessing for hemolysis, a positive tube coagulase test, and a positive catalase test. Despite frequent isolation of S. aureus from US organic farms, to the best of our knowledge no prior studies have characterized the strain diversity of S. aureus isolates obtained from US organic farms, and only one prior study has described S. aureus strain diversity within a single UK organic dairy farm (Smith et al., 2005a).

S. aureus genotypes have been previously associated with different epidemiological and biological properties, including differences in virulence and

persistence of intramammary infections (IMIs), within and between farm IMI prevalence, and clustering within farms and geographic regions, and potential for local strain evolution (Barkema et al., 2006; Fournier et al., 2008; Graber et al., 2009; Cosandey et al., 2016). A partial list of examples of S. aureus genotyping methods applied to isolates from dairy cattle or dairy farms includes: amplified fragment length polymorphism

(AFLP), pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), spa typing, ribosomal spacer-PCR (RS-PCR), and variable number of tandem repeats

(VNTR) analysis (Fournier et al., 2008; Zadoks et al., 2011; Sakwinska et al., 2011a).

MLST is a discriminatory, reproducible, repeatable, and portable sequence-based epidemiologic tool that unambiguously facilitates comparison of S. aureus isolates

(Zadoks et al., 2011; Peton and Le Loir, 2014). MLST has been applied to describe local and global epidemiology of S. aureus infections of dairy cattle (Barlow et al., 2013;

Smith et al., 2005a; Smith et al., 2005b; Boss et al., 2016; Budd et al., 2015). S. aureus clonal complexes (CC) determined by MLST have been shown to cluster with phylogenetic groupings based on genes encoding known adhesion factors (Boss et al.,

2016) or with potentially relevant epidemiologically groupings such as carriage of antimicrobial resistance genes or other proposed virulence markers (Sakwinski et al.,

2011b; van den Borne et al., 2010; Budd et al., 2016). Epidemiological and biological phenotypes of S. aureus that have been proposed to promote persistence of bovine intramammary infections and increased dairy farm prevalence include, but are not limited to, antimicrobial susceptibility, biofilm forming capacity, and adhesion to bovine mammary epithelial cells (Boss et al., 2016; Budd et al., 2016). Understanding

antimicrobial susceptibility patterns of mastitis isolates from US organic dairy farms, where there are substantial limits on antimicrobial use, will improve our understanding of factors that may be driving selection, maintenance, and spread of antimicrobial resistance pathogens or antibiotic resistance genes (ARGs) in all farm systems (Pol and Ruegg,

2007). Given these previous findings, we hypothesized that antimicrobial susceptibility and biofilm formation phenotypes will be associated with specific MLST genotypes.

Further, we hypothesized that increased biofilm forming capacity will be associated with the more prevalent genotypes on organic dairy farms in Vermont, and in the absence of antimicrobial selective pressure, antimicrobial resistance phenotypes and genotypes will be relatively infrequent on these farms.

The objectives of this study were to describe S. aureus genotypic and phenotypic diversity among organic dairy farms within Vermont and to test potential associations between MLST STs or CCs and genotypic or phenotypic measures of antimicrobial susceptibility and in vitro static biofilm formation capacity. A secondary objective was to describe the outcomes of applying different culture-based and molecular diagnostic procedures for identifying genotypic and phenotypic variants among S. aureus isolates obtained from bulk tank milk samples

2.3 Materials and Methods

2.3.1 Study design and reporting

This was a pilot study using non-probability convenience samples to collect preliminary data on the prevalence and diversity of S. aureus MLST strain types obtained

from BTM from organic dairy herds in Vermont. Reporting of molecular epidemiology methods and results followed STROME-ID recommendations (Field et al., 2014). Herein, we define isolates as the individual bacterial colonies selected from primary culture plates and passaged in secondary culture, with “pure” isolates displaying homogeneous colony morphology on the secondary culture plates (Zadoks and Schukken, 2006). We define strains as isolates that have a common MLST allelic profile, inferring descent and recognizing the limitation that isolates within the same MLST strain type may differ outside of the MLST loci where their amplicon sequences are indistinguishable (Field et al., 2014; Zadoks and Schukken, 2006).

2.3.2 Farm sampling

Our laboratory performed milk microbiological analysis on 479 bulk tank milk samples collected from 44 organic dairy farms in Vermont between July 2010 and June

2013. The bulk tank milk samples were collected over the course of 3 separate surveys of nutritional and mastitis management practices on organic farms in Vermont. The 3 studies varied in the frequency of milk sample collection [study A, 2 samples per farm

(n=27 farms); study B, monthly samples for approximately 1 year (n=30 farms); study C, weekly samples for 10 months, (n=3 farms)]; some farms participated in more than one study. Common criteria for enrollment of farms in the 3 studies included being certified organic for more than 1 year and willingness of the farmers to participate by allowing study personnel to collect and analyze BTM samples. Trained laboratory personnel collected all milk samples. Following agitation of bulk tanks for 5 minutes, milk samples were collected from the top of the bulk tank using sterile single-use polystyrene sample

collection containers with detachable long handles (SterlinTM DippaTM #192, Thermo

Scientific) and transported to the laboratory on ice, held under refrigeration, and cultured within 24 hours of sampling. Somatic cell counts were measured for each sample using a

DeLaval Cell Counter DCC (DeLaval-USA, Kansas City, Missouri) and the farm level

SCC was calculated as the average of all collected samples.

2.3.3 Bacteriologic Culture

Serial dilutions of BTM samples (undiluted, 10-fold and 100-fold dilutions in sterile distilled deionized water) were spread on Tryptic Soy Agar with 5% sheep blood and 0.1% esculin (“blood agar” BA) plates (100 µL milk per plate, 3 plates per dilution).

A subset of BTM samples (100 µL of undiluted and a 10-fold dilution) were also spread in triplicate on 3 different types of selective media: Mannitol Salt agar (MSA; 180 samples), Vogel-Johnson agar (VJ; 232 samples), and Baird-Parker with egg yolk tellurite agar (BP; 100 samples). All agar plates were prepared and quality controlled from a commercial source (Northeast Laboratory Services, Waterville, Maine) and stored at 4°C until use before the lot expiration date. All plates were incubated at 37°C and examined at 24 and 48 hours. All farms had at least 2 BTM samples plated to all 4 types of media. Culture plates were examined in a consistent order when multiple plates were available for a single BTM sample: BA, MSA, VJ, BP. Two individuals with prior experience in identification of bacteria from milk cultures completed the analysis of the primary culture results and selected isolates for isolation and subsequent identification

2.3.4 Bacterial isolation and identification

Isolate selection and presumptive identification of S. aureus was based on colony morphology (size, color, form/texture, margins) after 48 hours growth at 370C.

Specific presumptive identification criteria included: opaque greyish-white, pale tan, pale-yellow or golden-yellow colonies generally hemolytic on BA; clear to white or yellow colonies that ferment mannitol on MSA; black colonies that ferment mannitol on

VJ; and, grey to black colonies that may or may not demonstrate proteolytic or lecithinase (opaque or clear zones) activity on BP (Graber et al., 2013). Presumptive isolates were sub-cultured on BA, and examined for growth characteristics, Gram staining, and catalase testing. All Gram-positive, catalase positive, hemolytic cocci were tested for coagulase production by the tube coagulase method using rabbit plasma with

EDTA (BD and Company, Sparks, MD). Selected non-hemolytic gram-positive, catalase positive, cocci that displayed morphology on BA as describe above were also tested for coagulase production. Single colonies of Gram-positive, catalase-positive cocci were sub- cultured at least once and stored frozen at -800C in tryptic soy broth with 15% glycerol or on Microbank™ beads (Pro-Lab Diagnostics) until further analysis. Isolates were recovered from frozen stock by streaking 10uL (or 1 bead) to BA, and purity of stored isolates was visually assessed after 24 hours growth. Individual colonies (3-5) of recovered isolates were suspended in molecular grade water and genomic DNA was extracted using Qiagen DNeasy Blood and Tissue Kit (Qiagen) per manufacturer’s instructions. We extended a previously reported multiplex PCR (Virgin et al. 2009) by adding primers for β-lactamase resistance gene sequence (blaZ),

5’AAGAGATTTGCCTATGCTTC3’ and 5’GCTTGACCACTTTTATCAGC 3’

(Vesterholm-Nielsen et al. 1999), to the reaction mix containing S. aureus specific thermostable nuclease gene (nuc) primers 5’GCGATTGATGGTGATACGGTT 3’ and

5’AGCCAAGCCTTGACGAACTAAAGC 3’ (Brakstad et al., 1992), and methicillin resistance gene sequence (mecA) primers

5’AACAGGTGAATTATTAGCACTTGTAAG3’ and

5’ATTGCTGTTAATATTTTTTGAGTTGAA 3’ (Martineau et al., 2000). Each 50 µL reaction mixture contained 2.5 µL of each blaZ primer (10µM), 2.0 µL of each nuc and mecA primer (10uM), 1.0 uL of dNTPs (10 mM, New England Biolabs), 2.5 uL of template DNA, 2 µL 50 mM MgCl2, 5 µL 10x buffer (New England BioLabs), 0.4 uL

Taq DNA polymerase (5,000 units/ml, New England BioLabs), and 25.1 µL DNA free water (Fisher Scientific). Reaction conditions included initial denaturation at 95°C for 3 min, followed by 35 cycles at 95°C for 30 sec., 55°C for 30 sec., and 72°C for 30 sec., and final extension at 72°C for 6 min. S. aureus (nuc positive) DNA template controls,

ATCC 25923 (blaZ and mecA negative), ATCC 29213 (blaZ-positive and mecA negative), and ATCC 33591 (blaZ and mecA positive), and negative template controls

(DNase free PCR water) were included with each amplification reaction. Presence of

PCR products of approximate size (nuc, 270 bp fragment; blaZ, 518 bp fragment, and mecA, 174 bp fragment) was determined by visualization of ethidium bromide stained

1.5% agarose gels following electrophoresis. Any presumptive S. aureus (Gram-positive, catalase-positive, coagulase-positive) isolates that were nuc-PCR-negative were retested using the multiplex PCR and if twice nuc-PCR-negative the species of the isolate was

identified by sequencing a 412 bp amplicon of the tuf gene (Heikens et al. 2005). Species identification was determined by comparison of the amplicon sequence to known sequences in NCBI (http://blast.ncbi.nlm.nih.gov/Blast.cgi) with ≥ 98% sequence identity used to assign an isolate to a species. All gram-positive, catalase-positive, coagulase-negative cocci that were nuc-PCR-negative in a series of 2 multiplex PCR assays were defined as coagulase-negative staphylococci (CNS) and not further analyzed.

2.3.5 Selection of isolates for further genotypic and phenotypic analysis

All nuc-PCR positive isolates were categorized based on a combination of the observed phenotypic hemolysis pattern on BA (coded as either “0” no hemolysis, “1” a single zone of complete hemolysis, “2” a single zone of incomplete hemolysis, or “3” a zone of complete hemolysis surrounded by a zone of partial hemolysis, i.e., double hemolysis) plus the multiplex-PCR blaZ amplicon status (“1” positive or “0” negative), and the mecA amplicon status (“1” positive or “0” negative). Using the combination of these 3 categorical variables the diversity of the different “type-variants” was determined.

For each farm, at least 1 representative isolate of each unique type-variant was selected for MLST, antimicrobial susceptibility testing, and biofilm typing. In addition, all blaZ-

PCR-positive isolates were included for MLST, antimicrobial susceptibility testing, and biofilm typing. A total of 100 isolates were selected for further typing due to logistic and financial constraints

2.3.6 Multi-locus sequence typing

S. aureus MLST was performed according to Enright et al. (2000). Amplified

DNA was purified using ExoSAP-IT PCR clean up (Affymetrix, Cleveland, OH) and sent to the University of Vermont Core facility for Sanger sequencing in both directions. For allele number and ST assignment, consensus sequences generated from alignment of reverse and forward sequences were compared to sequences in the S. aureus MLST database (http://pubmlst.org). Reverse and forward sequences of putative novel alleles and allelic profiles of novel STs were submitted to the MLST database curator for allelic and ST number assignment and publication in the database.

2.3.7 Antimicrobial susceptibility testing

Agar disk diffusion (DD) and broth micro-dilution minimum inhibitory concentration (MIC) methods were completed following Clinical Laboratory Standards

Institute (CLSI, 2013) guidelines. A commercially available 96-well format plate was used for broth micro-dilution assays (Sensititre Mastitis MIC plates, CMV1AMAF, Trek

Diagnostic Systems, Oakwood Village, OH) for ampicillin, cephalocin, cefitofur, erythromycin, oxacillin (w/ 2% NaCl), penicillin, penicillin/novobiocin, pirlimycin, sulfadimethoxine, and tetracycline. Susceptibility by disk diffusion was completed for the same antimicrobials except penicillin/novobiocin and sulphadimethoxine. Additional antimicrobials evaluated by disc diffusion included amoxicillin/clavulanic acid, cefoxitin, clindamycin, enrofloxacin, gentamycin, lincomycin, and vancomycin. Screening for inducible macrolide-lincosamide resistant phenotypes was performed on all

Erythromycin resistant isolates using the D-test as previously described (Wang et al.,

2008).

2.3.8 Biofilm genotyping and in vitro assay

The isolates were also screened for biofilm-associated genes, polysaccharide intercellular adhesion (PIA) encoded by the ica gene operon (e.g. icaA and icaD), and biofilm associated protein (bap) by PCR using established primers, icaA-F 3’-CCT AAC

TAA CGA AAG GTA G-5’, icaA-R 5’-AAG ATA TAG CGA TAA GTGC-3’, icaD-F

3’-AAA CGT AAG AGA GGT GG-5’, icaD-R 5’-GGC AAT ATG ATC AAG ATA C-

3’ (Simojoki et al., 2012), and bap-F: 5’-CCCTATATCGAAGGTGTAGAATTGCAC 3’ bap-R 5’GCTGTTGAAGTTAATACTGTACCTGC3’ (Cucarella et al., 2001). PCR reaction conditions were as previously reported, with one modification, the annealing temperature for the bap PCR reaction was 55°C due to presence of unspecific bands with the published annealing temperature. Presence of PCR products (icaA 315bp; icaD

381bp, and bap 971bp) was determined by visualization of ethidium bromide stained

1.5% agarose gels after electrophoresis. Positive DNA control strains included in each set of PCR reactions were S. xylosus ATCC 29971 for bap and S. aureus ATCC 25923 for ica genes.

Isolates were tested in a micro-titer plate-based biofilm assay (Tremblay et al.,

2013). Isolates were recovered from frozen stock solution by growth overnight on TSA, with plates examined for purity at 24 and 48 hours. A weak biofilm producer control strain, S. epidermidis ATCC 12228, and a strong biofilm producer control strain, S. epidermidis ATCC 35984 were included in the assays. A single colony from the stock

culture TSA plate was transferred to tryptic soy broth (TSB), grown overnight, and 5 µL of this overnight culture was diluted 1:200 in TSB supplemented with 0.25% glucose.

The diluted culture was transferred to a 96 well polystyrene flat-bottomed tissue-culture- treated plate (#3595, Corning, NY, USA) in triplicate (200 µL per well) and the plates incubated for 24hrs at 370C without agitation. After 24hrs, broth was removed from each well; the plates were washed three times with PBS and air-dried at room temperature for at least 2hrs. The dried plate was stained with 0.4% (w/v) safranin solution for 10 minutes, washed three times with double distilled water, and air-dried at room temperature for at least 2hrs. The stained biofilms were de-stained using 95% ethanol for

15 minutes and absorbance at 490nm was measured using a plate reader (Synergy HT,

BioTek Instruments, Inc.). The experiments using each type of plate were repeated three times on different days. Each plate contained 3 blank wells (un-inoculated medium), and the corrected absorbance value for each sample-well was calculated by subtracting the mean absorbance of the blank wells for that plate. The weak and strong biofilm producer control strains were each included in triplicate on every plate. The mean of the nine blank-corrected absorbance values for each isolate for each type of plate was recorded as the final result. Isolates were classified on their ability to form a biofilm on each type of plate using the following categories from (Christiansen et al., 1985, Stepanovic et al.,2000),

- Negative = obsOD < ODc

- Weak = ODc> obsOD<2ODc

- Moderate 2ODc > obsOD < 4ODc

- Strong = obsOD>4ODc >, where ODc = mean OD + 3 x sd of negative control wells, and obsOD = the mean of the nine blank corrected absorbance values.

2.3.9 Data analysis

Statistical analyses were carried out using STATA version 3.1. The normality of the biofilm data was checked and transformed accordingly. Since isolates were selected depending on different phenotypes and 1-2 isolates in most cases were selected per farm, these samples were assumed to be independent. Differences in biofilm biomass

(mean OD reading natural log transformed) among CC categories were evaluated using a linear regression model. A mixed model approach accounting for farm as a random effect was also explored and the addition of the random effect term did not improve the fit of the model. For graphical presentations, the untransformed OD readings were reported.

OD means of CCs within plate types were compared using one-way ANOVA Post Hoc tests with Bonferroni correction were used for multiple comparisons. The association between ST and antimicrobial susceptibility was also assessed. The seven-allele sequences for each strain type were concatenated to produce a 3,198-bp sequence.

Phylogenetic analyses of the concatenated sequences were completed using MEGA

(Molecular Evolutionary Genetics Analysis) version 6.0 (Tamura et al., 2013). STs were assigned to clonal complexes using eBurst software (http://saureus.mlst.net/eburst).

2.4 Results

2.4.1 MLST

Forty-three (98%) of the farms had S. aureus isolated from at least one bulk tank milk sample, and the percentage of S. aureus positive BTM samples within farms ranged from 0 to 100%. The typeability of the 100 isolates by MLST was 100%; 10 known and

10 novel STs were identified. The known STs included ST1, ST8, ST30, ST87, ST97,

ST151, ST350, ST352, ST705, and ST2187. Novel alleles were identified for the loci arcC, yqil, glpF and aroE, and were all single nucleotide polymorphisms (SNPs) of known alleles (Table 2-1). The novel strains included: ST693, a single locus variant (slv) of ST124 and a double locus variant (dlv) of ST97; ST3020 & ST3028, slv’s of ST2187;

ST3021, ST3022, & ST3024, slv’s of ST352; ST3023, a slv of ST45; ST3025, a slv of

ST705; and, ST3026 & ST3027, slv’s of ST151 (Figure 2-2). Five strain types were dominant; they were ST151 (n=17 isolates), ST352 (n=23), ST2187 (n=13), ST3028

(n=14) and ST8 (n=11) isolated from bulk tank milk of 15, 17, 10, 10 and 6 farms respectively (Figure 2-1B). The strain types clustered in 8 clonal complexes (Figure 2-

1B). One strain type, ST350 was a singleton according to eBURST analysis. Ninety-four percent of the isolates belonged to three clonal complexes, CC8 (n= 11), CC97 (n=60) and CC151 (n=23) (Figure 2-1B).

STs were distributed among the 5 type-variants. Seven STs displayed more than one hemolysis phenotype. There were 12 farms where different hemolysis patterns were observed among the same STs, while for 6 farms typing isolates with different hemolysis phenotypes did not result in identifying additional STs. Among the 32 farms with > 1 78

type variant, there were 26 farms where selecting isolates with different phenotypes resulted in identification of different STs. This included 18 farms with STs belonging to more than one CC, and 8 farms where the STs identified clustered in the same CC.

Overall, we identified only a single CC on 25 of the 43 S. aureus positive herds. On 17 of these farms, only one ST was identified, but in 11 (65%) of these cases only 1 isolate was typed due to lack of phenotypic variation of isolates from that farm. All ST8 isolates had a double zone of hemolysis. Isolates with a single zone of complete hemolysis were ST 1,

30, 97, 151, 352, 693, 2187, 3020, 3023, and 3028. Non-hemolytic isolates belonged to

ST 1, 352, 3021, and 3028.

2.4.3 Antibiotic susceptibility

Based on MIC interpretive criteria for the 100 typed isolates, 16% of isolates were resistant to ampicillin and penicillin, 1 isolate was classified as resistant and 4 isolates as intermediate susceptible to erythromycin, and 50% of isolates were classified as resistant to sulphadimethoxine (Table 2-2). All the isolates were sensitive to the remaining antibiotics by either broth micro-dilution (Table 2-2) or disk diffusion (data not shown), with the exception of 1 isolate that was classified as resistant to amoxicillin-clavulanic acid by disk diffusion. This isolate was also resistant to ampicillin and penicillin. There was complete agreement in interpretation of the results for disk and microdilution. Both disk diffusion and MIC data were available for ampicillin, penicillin, cephalothin, ceftiofur, pirlimycin, oxacillin/cefoxitin, and tetracycline, and isolates classified as susceptible based on MIC criteria were also susceptible based on zone diameter criteria

(data not shown). For erythromycin, there were 4 isolates with discordant results, 3

classified as susceptible based on zone diameter but as intermediate based on MIC, and 1 isolate classified as intermediate based on zone diameter and susceptible based on MIC.

All 11 CC8 (ST8) isolates from 6 farms, 4 CC97 (3 ST97 and 1 ST693) isolates from 2 farms, and the 1 CC30 (ST30) isolate were resistant to ampicillin and penicillin and were blaZ-PCR positive. The blaZ-PCR positive isolates also displayed reduced susceptibility (smaller zone diameter) to amoxicillin-clavulanic acid by disk diffusion.

The ST30 isolate was also resistant to erythromycin and had inducible clindamycin resistance on the D-test (data not shown). All 84 remaining isolates were susceptible to β- lactam antibiotics and were blaZ-PCR negative. All 100 isolates were mecA-PCR negative and displayed a methicillin susceptible phenotype by broth microdilution and disk diffusion. Overall, blaZ-PCR positive isolates were obtained from 10 (2%) of 480

BTM samples from 9 farms. On one farm β-lactam resistant isolates (ST97) were found in 2 of 2 BTM samples, while on the remaining 8 farms the blaZ-PCR positive isolates

(ST8, ST30, and ST693) were isolated from a single BTM sample, and not found on subsequent repeated samples (range 2-41, mean 13, and median 11 serial BTM samples).

2.4.4 Biofilm phenotypes and genotypes

All isolates were PCR positive for icaA and icaD genes, but were bap negative.

Isolates were classified on their ability to form a biofilm based on absorbance results,

(A490 ≤0.059), weak (0.059

(A490 > 0.236). According to the cutoff described in the methods, 23% (n=23) of the isolates formed biofilms with 39.1% (n=9) of these being CC8 isolates. Given the fact that some clonal complexes had only one or two isolates, statistical analysis of

association between biofilm biomass and genotypes was done on three dominant clonal complexes (CC8, CC151 and CC97). In a linear regression model, clonal complex was a significant predictor of biofilm OD. After adjusting for multiple comparisons, CC8 isolates formed significant biofilm biomass than CC97 or CC151 (p<0.01) (Figure 2-3).

There was no significant difference in the mean biofilm ODs between CC97 and CC151

(p>0.05).

2.5 Discussion

Because previous research groups have documented a relatively high prevalence of S. aureus in individual cattle or bulk tank milk of U.S. organic dairy herds (Pol and

Ruegg, 2007; Cicconi-Hogan et al., 2013), we elected to screen for S. aureus among

BTM samples collected from organic dairy farms in Vermont. Staphylococcus aureus was common on Vermont organic dairy farms consistent with previous studies (Cicconi-

Hogan et al., 2013). A recent study in New York, Oregon and Wisconsin indicated 62% prevalence in organic bulk tank samples as compared to 42% and 43% in conventional nongrazing and conventional grazing herds respectively (Cicconi-Hogan et al., 2013).

Another study though on conventional dairy farms showed 84% prevalence in bulk milk in Minnesota (Haran et al., 2012). In addition, dry cow therapy a common practice on conventional dairy farms that has been proven to be effective in controlling contagious pathogens is not permitted on organic farms. This may increase the incidence or prevalence and the odds of S. aureus spread within or between organic dairy farms.

Comparison of prevalence estimates with other studies should be done with caution due to differences in methods among the studies. For example, few other studies 81

reported repeated sampling of farms over time, plating bulk tank milk samples in triplicate (thus a total of 300 µL plated per sample) or plating serial dilutions of samples.

The inclusion of other selective media and multiple sampling may have also influenced the high prevalence observed among Vermont farms, although only 4 % of the time was a

S. aureus isolate observed on a selective media and not on a blood agar plate run in parallel. The 10 true nuc-PCR negative isolates were identified as coagulase-positive S. hyicus and S. chromogenes. Coagulase-positive S. hyicus isolates have been previously reported (Phillips and Kloos, 1981), but to the best of our knowledge this is the first report of coagulase positive S. chromogenes. Specificity of this assay approaches 100% in our hands, and we have examined approximately 11 CNS isolates (species confirmed by sequence based typing), which were all nuc-PCR negative (data not shown). The use of targeted selection based on type variants might be effective in identifying diversity though analogous studies to compare are limited. We could have missed some rare variants if we randomly selected 100 out of 585 for strain typing. However, all β-lactam resistant isolates as well as non-hemolytic isolates were selected. So, we do know the true strain diversity of b-lactam resistant and non-hemolytic isolates.

The typeability of the 100 S. aureus isolates using MLST was 100%, which is comparable to a previous study (Smith et al., 2005a). Sixty of the isolates (60%) were in

CC97 with seven different strain types. At least a strain type belonging to CC97 was isolated on 79.07% of the farms (n=34). This suggests that this lineage is heterogeneous and is widely spread in Vermont organic dairy farms. This was also observed as one of the dominant lineages causing bovine mastitis in Brazil and Ireland (Rabello et al, 2007;

Budd et al, 2015). The high level of diversity (20 STs) was not a surprise given the fact that a lot of farms were sampled. We observed greater diversity between farms than within farms. Within farm strain diversity is usually low due to contagious spread and clonal population structure of S. aureus (Smith et al., 2005a). The discovery of 10 novel strain types shows the continued need for monitoring the epidemiology and evolutionary biology of S. aureus and acquisition of antibiotic resistant genotypes. Most of the novel strain types clustered in known bovine associated clonal complexes (CC97, CC151).

Some strains had atypical non-hemolytic pattern as compared to other bovine associated strain types. The genotypic and phenotypic changes have been shown to play a role in host adaptation and host jumping. CC8 human to bovine jump for instance was shown to have occurred by loss of β-hemolysin converting prophage and acquisition of a new

Staphylococcal Cassette Chromosome (Resch et al., 2013). Emergence of livestock associated MRSA with zoonotic potential over the past 10 years is of public health importance (Paterson et al., 2012). The dominant clonal complexes in this study CC8,

CC151, and CC97 are some of the common clonal complexes isolated from cows with clinical or subclinical mastitis (Sung et al., 2008, Barlow et al., 2013, Bergonier et al.,

2014, Budd et al., 2015) though CC8 is human associated with recent jump to cattle

(Sakwinska et al., 2011, Resch et al., 2013). The other minor clonal complexes CC1,

CC30, CC45, and CC59 with one or two isolates each are common human lineages

(Enright et al., 2002, Croes et al., 2009). CC1, CC30 and CC45 have been reported rarely in cases of subclinical bovine mastitis (Kozytska et al., 2010, Bergonier et al., 2014).

Pilla and others (Pilla et al., 2012) reported a chronic case of bovine mastitis ST1

MRSA. The presence of human associated CCs in bulk tank milk could be due to human contamination on the farms or from cows suffering from transient mastitis. Human contamination is not conclusive from this study because human beings were not sampled.

It is therefore likely, that human associated CC ended up in bulk tank from quarter milk of cows suffering from S. aureus transient mastitis. From our recent data (unpublished), strain types from bulk tank milk were the same as those from quarter milk suggesting that most of the S. aureus come from quarter milk of infected cows.

Selection pressures, which create localized variants of S. aureus might explain identification of novel alleles (Carter et al., 2003, Smith et al., 2005a). However, it has been suggested that it could also be due to analysis of a new population, probably analysis of another population could reveal novel alleles. It’s not uncommon to have novel alleles in S. aureus strains of animal origin as compared to their human counterparts (Smith et al., 2005a). In fact, most of the new alleles were in strain types that clustered in bovine associated clonal complexes.

All isolates were methicillin sensitive and mecA negative. This supports previous findings that show very low presence of methicillin resistant S. aureus in bulk tank milk in the United States regardless of whether organic or non-organic (Virgin et al., 2009,

Haran et al., 2012, Cicconi-Hogan et al., 2014). Out of the 100 isolates, 16% were resistant to ampicillin and penicillin and carried a blaZ gene. All ST8 isolates were resistant to the above two antibiotics consistent with a recent study (Barlow et al., 2013).

It is noteworthy that all ST97 isolates within CC97 were resistant to penicillin and ampicillin contrary to a recent paper from Europe that showed β-lactam resistance in 84

other strain types within CC97 (Budd et al., 2015). However, the isolates were from cases of bovine mastitis and the farms were not organic. Half of the isolates were not inhibited at highest concentration of sulfadimethoxine suggesting high level resistance. All isolates were susceptible to the rest of the antibiotics apart from one ST30 isolate that was resistant to penicillin/ampicillin, erythromycin and with inducible clindamycin resistance (data not shown). Despite the high prevalence of S. aureus in bulk tank milk on these organic dairy farms, antibiotic resistance was low and more common in human associated STs e.g ST8, ST30 and a few bovine associated STs (two ST97 isolates and

ST693). More work is needed to understand the composition of β-lactam resistance elements in ST97 and ST8 from dairy cattle.

All isolates were PCR positive for icaA and icaD genes suggesting presence of ica locus but negative for bap gene. These genes have been shown to be crucial for S. aureus to form biofilm (Cramton et al., 1999). The ica locus was reported in 95-100% of

S. aureus isolates in previous studies (Vasudevan et al., 2003,Szweda et al., 2012,

Prenafeta et al., 2014) suggesting that ica locus is highly prevalent in S. aureus of bovine origin. However, the bap gene is not common in S. aureus (Szweda et al., 2012, Budd et al.,2015). Although ica is considered a big player of S. aureus biofilm formation, its presence did not correlate to biofilm formation which has been reported in other studies

(Vasudevan et al., 2003,Szweda et al., 2012, Prenafeta et al., 2014). Other unknown genes might play a role in biofilm formation (Cramton et al., 1999, Cucarella et al.,

2001). In fact, deletion of the ica locus did not have an effect on biofilm formation on some human MRSA isolates (O'Neill et al., 2007). Mack and others (Mack et al., 2000)

identified three genetic loci that had an influence on genes encoding PIA production at transcriptional level. Whole genome sequencing to compare poor and good biofilm forming strain types surface proteins may elucidate these discrepancies. Although no research had showed a relationship between S. aureus lineage and biofilm formation in organic dairy isolates, previous studies on human S. aureus showed lineage specificity of biofilm formation (Croes et al., 2009, Naicker et al., 2015). In this study, CC8 isolates formed stronger biofilm (Figure 2-3) than CC97 or CC151. Budd et al., (2015) and

(2016) showed that some S. aureus strain types from bovine mastitis cases are more biofilm formers than others. In these two studies, CC151 and CC97 were the predominant clones and none of the isolates were in CC8, and untreated plates were used. According to Kennedy and O’Gara (Kennedy and O'Gara, 2004), some S. aureus strains were unable to form biofilms on untreated polystyrene plates. However, this work was done on few isolates and even of unknown strain types. These findings may suggest that plate surface may influence the expected outcome and may depend on the S. aureus lineage. Biofilm formation may play a role in persistence of certain S. aureus STs or lineages in a population and may be driven by available surface type. A recent study showed that CC8 isolates persisted in the cheese making production chain compared to other lineages

(Kummel et al., 2016). This might be to the fact that CC8 is a good biofilm former on hydrophilic surfaces as depicted in our study compared to other cattle associated lineages.

Surface type differences may affect the ability of STs to survive in specific dairy environments. More work understanding the potential relationship between dominant STs

or lineages and biofilm forming capacity is warranted. The clinical significance of the good biofilm forming strains types needs to be elucidated in a feasible animal model.

2.6 Conclusion

Penicillin resistance among S. aureus ST8 and ST97 from bulk tank milk of the organic dairy farms suggests more research is needed to describe the epidemiology of these strain types. The finding that CC97 and CC8 isolates had differential biofilm forming potential on demonstrates the potential heterogeneity of S. aureus cattle biotypes. To the best of our knowledge this is the first research finding a positive association between S. aureus lineages and biofilm forming potential from organic dairy farms. Biofilm formation was variable and not associated with ica or bap status. Studies are needed to identify other genetic markers of biofilm phenotypes among S. aureus CCs from dairy farms as well as the role of different surfaces in biofilm formation.

2.7 Acknowledgements

This work was funded by USDA food systems grant and Hatch grant. We acknowledge

University of Vermont core facility for all the sequencing work

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Figure 2-1: Map of Vermont showing S. aureus geographic distribution of CCs (A) and a dendrogram showing phylogeny and frequency (Freq.) of STs, % penicillin resistance and number of farms a particular ST was isolated (B)

Figure 2-2: eBurst analysis of the S. aureus sequence types Blue and yellow represents the predicted founder and subgroup founder respectively. The size of the dot represents the relative frequency of the respective strain type in the isolates studied

A B

Figure 2-3: Biofilm formation of S. aureus lineages from organic farms 97 on (A) and biofilm categories (B)

Table 2-1: Allelic profile of the 20 strain types identified ST CC arcC aroE glpF gmk pta tpi yqil 1 1 1 1 1 1 1 1 1 8 8 3 3 1 1 4 4 3 30 30 2 2 2 2 6 3 2 87 59 19 23 15 2 41 20 15 97 97 3 1 1 1 1 5 3 151 151 6 72 12 43 49 67 59 350 NA 6 79 51 47 7 70 61 352 97 3 78 1 1 1 5 3 693 97 3 126 1 37 1 5 3 705 705 6 72 50 43 49 67 59 2187 97 3 317 1 1 1 5 3 3020 97 3 317 385* 1 1 5 3 3021 97 3 78 386* 1 1 5 3 3022 97 337* 78 1 1 1 5 3 3023 45 10 437* 8 6 10 3 2 3024 97 3 437* 1 1 1 5 3 3025 705 6 72 50 43 49 67 369* 3026 151 6 72 12 43 49 67 370* 3027 151 6 72 12 43 49 152 59 3028 97 3 317 1 184 1 5 3 ST; strain type, CC; clonal complex; * novel alleles, **; allelic substitutions. ST3020- 3028 and ST693 are novel strain types.

Table 2-2: Broth micro-dilution in vitro susceptibility testing of S. aureus

1Bp = breakpoint, MIC at which an isolate is considered resistant, according CLSI 2013 guidelines 2 Percentage classified as resistant based on CLSI breakpoints 3 MIC50 value underlined; MIC90 value in bold; dash indicates concentration not tested; bold vertical line MIC cutpoint for resistance; grey vertical line MIC cutpoint for intermediate susceptibility

4 NI= Not inhibited at the highest concentration tested 5 MIC breakpoints based on human derived interpretive criteria for S. aureus per CLSI 2013 guidelines 6 MIC breakpoints based on bovine mastitis recommended CLSI (2013) guideline

CHAPTER 3 : TUF GENE SPECIES IDENTIFICATION REVEALS

UNIQUE STAPHYLOCOCCUS DIVERSITY ON SELECTED DAIRY

FARMS PRODUCING FARMSTEAD CHEESE IN VERMONT

Robert Mugabi, Samantha D’Amico, Amanda Ochoa, John Barlow*

University of Vermont, Burlington, Vermont, USA

*Corresponding author: John Barlow, Department of Animal Science, University of

Vermont

570 Main St Burlington VT, USA 05405

Phone: 802-656-1395

Email: [email protected]

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3.1 Abstract

Staphylococci are a common cause of intrammamary infections (IMI) and mastitis in dairy cattle. Milk from infected cows is the entry point of most bacteria that end up in the cheese production chain. The objective of this non-random cross-sectional study was to use sequence-based species identification methods to understand the epidemiology and potential reservoirs of staphylococci causing IMI on dairy farms that produce milk for artisan or farmstead cheese production. A combination of the tuf and rpoB, genes were used to speciate presumptive staphylococci from various niches, including humans, on five farmstead cheese-producing dairy farms in Vermont. Staphylococcus aureus isolates were further strain typed using multilocus sequence typing (MLST). The predominant species observed overall was S. haemolyticus, but variation in the frequency of other species was noted between the farms. A total of twenty-seven different species were identified from different niches. Sixteen species were isolated from infected cow quarters, with S. chromogenes (n=62), S. haemolyticus (n=20), S. aureus (n=20), S. simulans (n=9), and S. xylosus (n=9) making up the five species observed most frequently. S. haemolyticus and S. xylosus were isolated from various niches suggesting multiple reservoirs. Alternatively, S. chromogenes and S. simulans were mainly isolated from cow sources, which are likely their main reservoir with milking equipment acting as fomites. S. equorum, and S. xylosus were the predominant species isolated from environmental niches, whereas S. epidermidis and S. aureus were the predominant species isolated from humans. S. aureus MLST revealed distinct strain types (STs) between humans and those in cow quarters with IMI, suggesting host specificity. Among

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the top four common coagulase negative staphylococci (CNS) causing IMI in this study, the average somatic cell count (SCC) of S. simulans and S. xylosus IMI was similar to that of S. aureus. Among the top five species causing IMI in this study, S. xylosus, and S. haemolyticus seemed to have multiple reservoirs. The other three species (S. aureus, S. chromogenes and S. simulans) were rare in non-cow sources, so they are more likely to be host adapted and we speculate that, they spread from cow to cow.

Key Words; Dairy cattle, Staphylococci, Epidemiology, Mastitis, artisan cheese

3.2 Introduction

Some Staphylococcus species, commonly found on the teat and extra-mammary skin of cattle, are opportunistic mastitis pathogens, while others may be normal commensal organisms that have no effect on the host, and still others may be beneficial to dairy cows by contributing to a healthy skin environment protecting the host from other pathogenic organisms (Cogen et al., 2008, Christensen and Bruggemann, 2014,

Vanderhaeghen et al., 2015). In addition, some CNS species found in raw milk may be part of the consortium of ripening bacteria that contribute to flavor or other attributes of finished cheeses (Bockelmann W., 2001, Bockelmann, 2002, Place et al., 2003). In particular, S. equorum is one of the most common none pathogenic Staphylococcus species isolated in cheese (Kastman et al., 2016), and it has been proposed as a potential starter culture, and may have anti-listerial effect (Carnio et al., 2000, Place et al., 2003).

Farms that harvest milk for farmstead or artisan cheese production, including raw milk cheeses, may have simultaneous goals of encouraging or maintaining beneficial bacterial communities on the teat skin and in raw milk, while limiting the risk for intramammary

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infections (IMI) and of raw milk contamination with potential human pathogens such as

S. aureus (Tsegmed et al., 2007, D'Amico and Donnelly, 2010). Raw milk is the common route for introducing human pathogens like S. aureus in the cheese production chain, most of which are from cows with mastitis (D'Amico D and Donnelly, 2011, Kummel et al., 2016). Previous work on artisan cheese farms in Vermont focused on S. aureus undermining the CNS epidemiology (D'Amico and Donnelly, 2010, D'Amico D and

Donnelly, 2011). Understanding the CNS epidemiology on artisan cheese farms is crucial given their relative high abundance in cheese (Wolfe et al., 2014).

Members of the genus Staphylococcus are the most common cause of subclinical mastitis on dairy farms (Pyorala and Taponen, 2009). Mastitis is found in two forms: clinical and subclinical. Clinical mastitis is characterized by visible signs displayed by the cow and long term decreased milk production, while subclinical mastitis, is characterized by a high somatic cell count (SCC) and suboptimal milk production, but without any clinical signs (Taponen et al., 2006, Taponen et al., 2008, Vanderhaeghen et al., 2014). Milk production does not necessarily improve after complete recovery from subclinical mastitis (Halasa et al., 2007). Mastitis is considered to be one of the most prevalent and costly diseases in the dairy industry due to its effects on milk production and quality (Halasa et al., 2007, Vanderhaeghen et al., 2015). Management practices, such as treatment, prevention of transmission of infection, and improvement of the immune system, are considered to be the most effective ways to control mastitis (Halasa et al., 2007).

Staphylococci are divided into two groups depending on their ability to clot blood 103

plasma: coagulase negative staphylococci (CNS), which are unable to clot blood plasma, and coagulase positive staphylococci, which are able to clot blood plasma (Pyorala and

Taponen, 2009). Staphylococcus aureus is the most common coagulase positive staphylococcal species, though other coagulase positive and coagulase variable species do exist, including S. intermedius, S. pseudintermedius, S. delphini, S. hyicus, S. lutrae, and S. agnetis, the remaining species are considered coagulase negative (van Duijkeren et al., 2011, Becker et al., 2014). In recent Brazilian study of S. chromogenes, isolates obtained from buffalo milk samples have been shown to clot blood plasma (Dos Santos et al., 2016).

In the Staphylococcus genus, S. aureus is considered a major pathogen due to its induction of a severe inflammation, and it has been studied extensively. Molecular epidemiologic studies suggest that most S. aureus STs are host specific (Smyth et al.,

2009, Sakwinska et al., 2011), but a few STs can infect multiple hosts including humans, which may present a public health threat. For instance, S. aureus ST1, ST8, ST79, ST130 and ST398 have been associated with human infections or colonization as well as bovine mastitis (Zadoks et al., 2011). S. aureus presence in raw milk for cheese making is of public health importance as it can cause staphylococcal food poisoning (De Buyser et al.,

2001)

On the other hand, CNS are considered minor pathogens because they seem to induce moderate inflammation compared to S. aureus and infections are usually subclinical (Ruegg, 2009, Schukken et al., 2009). However, in one study, cows infected with S. chromogenes, S. simulans and S. xylosus had a somatic cell count comparable to 104

that of S. aureus suggesting that some CNS species or strains might behave like major pathogens (Supre et al., 2011). Although the relative role of some of some CNS species in mastitis is uncertain, recent studies indicate an increased prevalence of CNS IMI on dairy farms, especially those that have contained contagious pathogens like S. aureus and

Streptococcus agalactiae (Pyorala and Taponen, 2009). At least nine CNS species have been isolated from cow milk with IMI or mastitis. Most recent studies in Europe show S. chromogenes, S. simulans, S. haemolyticus, S. epidermidis, S. hyicus and S. xylosus as the predominant CNS species isolated in bovine quarter milk (Pyorala and Taponen, 2009,

Thorberg et al., 2009, Zadoks and Watts, 2009). CNS species that mainly had an environmental origin were S. equorum, S. sciuri, S. cohnii, and S. xylosus (Piessens et al.,

2011, De Visscher et al., 2014). The reservoirs of CNS causing IMI are not entirely clear, and some species may have multiple reservoirs, including humans or pets on dairy farms.

Older studies identified CNS using biochemical methods, which are less accurate

(Capurro et al., 2009, Zadoks and Watts, 2009, Zadoks et al., 2011). This partly contributed to the controversies about whether CNS are true pathogens. In this project, sequence-based methods were used, which are the proposed gold standard for the definitive identification of Staphylococcus species (Zadoks and Watts, 2009). The major objective of this project was to understand the epidemiology of staphylococci and to identify the reservoirs of bacteria that cause mastitis or contaminate milk meant for cheese making. The second objective was to ascertain the association of common staphylococcus species causing IMI and somatic cell count induction. To the best of our knowledge, this is the first study to investigate distribution of staphylococci in humans,

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cattle, and the dairy farm environment of small herds where the milk is used to make artisanal cheese.

3.3 Materials and Methods

3.3.1 Herd and sample collection

A total of five dairy farms were enrolled in this non-random cross-sectional pilot study to explore staphylococcal diversity. Criteria for inclusion in the study were that the farmers either produced farmstead cheese on the same premises they milked the cows or they supplied milk to a small-scale artisan cheese producer, and that they had previously established S. aureus control programs under the guidance of a veterinary practitioner.

We solicited recommendations for participating herds from private veterinary practitioners or from artisan cheese producers to identify herds. All farms had to be willing to provide access to cow and environmental sampling. For each farm, all samples were collected during 2 visits within a two-week period. Four of the farms were seasonally grazed pasture-based herds housed in tie-stalls or free-stall housing sampled in a month, when cows were maintained under winter confinement housing, while the 5th herd was housed year-round in free-stall housing.

On the first visit per farm, duplicate individual quarter milk samples were collected from all lactating cows using established sampling procedures (Hogan et al.,

1999). Samples were collected from cow and milking system associated sources. Cow sources included: individual quarter milk collected in duplicate, cannulated milk, clean and dirty teat canal swabs (swabs taken before and after disinfection with 70% ethanol), and swabs taken from teat end, teat barrel, teat laceration, udder cleft, perineum, hock,

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vagina, and external nares. Apart from quarter milk samples, which were taken from all the cows, the other cow source samples were taken from 6-10 cows per farm on the second visit a week later, based on their quarter milk bacteriologic culture. Milking system associated sources included: bulk tank milk, inner surface of the milk line and milking inflations before and after milking the herd, external teat cup before and after milking the herd, and teat cup rims. The milk line filter samples were also collected at the end of milking the whole herd. In addition, swabs were taken from human nares and hands as well as other animal species, if present on the farm, including dog and pig nares.

For the skin and mucosal swabs, flocked swabs (Copan diagnostics) were moistened in the transport medium containing 0.9% NaCl, 0.1% Tween 80, 0.5% whole milk powder, and 0.2% sodium thiosulfate. Minitip floqswabs (Copan diagnostics) were used for collection of teat streak canal samples. This study was conducted with approval of the

University of Vermont Institutional Animal Care and Use Committee (IACUC) protocol

#3-033. Collection of human samples was completed under protocol CHRMS 14-512 approved by University of Vermont Committee on Human Subjects Research. Human swabs were collected from all individuals on the farm that volunteered to participate and had direct contact with cows. The individuals who agreed to provide nasal samples were trained to collect a self-swab following previously described procedures (Gamblin et al.,

2013). All samples were placed in individual vials containing 5 mL of transport medium and held on ice for transport back to the laboratory. Samples were also obtained from the barn environment. Environmental samples included fresh and used saw dust bedding, grain, forage/hay, stall neck rails, stall partition rails, and water trough rims. Finally, air

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particulate samples were collected using a settle plate method. All environmental swab samples were obtained using 3-M sponge sticks (3M Corp, St. Paul, MN) hydrated with

15 mL transport medium. Samples were transported on ice back to the laboratory and stored under refrigeration for no more than 48 hours prior to culture.

3.3.2 Sample processing and isolation of staphylococci

The samples were plated on tryptic soy agar with 5% sheep blood (TSB) and mannitol salt agar (MSA) and incubated aerobically for up to 48 hours at 370C.

Individual quarter milk samples (10 �l) were cultured using established methods and interpretation of the culture results was performed according to established guidelines

(Hogan et al., 1999). Vials containing skin and environmental flocked swabs in transport medium were votexed vigorously for 5 minutes at 2,500 rpm. Sample bags containing the sponge swabs were homogenized in a sterile stomacher bag for 3 minutes. Bedding and feed samples were also placed in a sterile stomacher bag and homogenized for 3 minutes.

Aliquots (100�l) of media from skin and environmental samples were plated on TSB and

MSA before incubation. Colonies of presumptive staphylococci were selected from each plate based on distinct morphology. A total of 2-6 colonies were selected per environmental sample or animal/human swab depending on the colony phenotype diversity per medium. The individual selected colonies were streaked for isolation on

TSB and incubated for 24 to 48 hours. Presumptive identification of staphylococci was done using gram staining, catalase testing, and examining colony morphology. A coagulase test was done on all isolates to presumptively differentiate S. aureus from

CNS. All presumptively identified staphylococci were stored frozen at -800C in TSB with

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15% glycerol until further analysis. Throughout the process, including after the frozen isolates were recovered from storage, culture purity was confirmed by plating on blood agar and visual assessment of plates after 48 hours of incubation. Final selection of isolates for DNA extraction was based on distinct colony phenotype on blood agar if a lot of isolates were saved from the same source.

3.3.3 DNA extraction

The DNeasy Blood and Tissue Kit (Quiagen) was used to extract DNA from each isolate by following the manufacturer’s instructions with some slight modifications.

Briefly, the cells were incubated for 1 hour at 370C with enzymatic lysis buffer.

Proteinase K was then added and the mixture incubated at 560C for 30 minutes. Ethanol was added before the total mixture was placed in a DNeasy spin column (Jaffe et al.,

2000). The column was washed to remove any remaining contaminants and the DNA was eluted. Extracted DNA was stored at -200C until further analysis.

3.3.4 Polymerase Chain Reaction (PCR)

The coagulase positive staphylococci (S. aureus) were confirmed by PCR amplification of the S. aureus thermostable nuclease gene (nuc) as previously described

(Brakstad et al., 1992). The species confirmation of the presumptive CNS isolates was done by PCR amplification and sequencing of the tuf or rpoB gene. These housekeeping genes encode elongation factor Tu and the � subunit of RNA polymerase respectively.

The 16S rRNA gene was used to identify isolates that gave negative PCR for tuf or rpoB gene. Previously published primers were used for amplification of the tuf gene. The

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primers were TufF 5’-GCC AGT TGA GGA CGT ATT CT-3’ and TufR 5’-CCA TTT

CAG TAC CTT CTG GTA A-3’ (Heikens et al., 2005, Hwang et al., 2011). The amplicon produced for these primers was 412bp long (Heikens et al., 2005). The PCR reaction contained 5�l of 10x Taq buffer (New England BioLabs), 2�l of 50mM MgCl2,

2�l of 10�M of each primer, 1�l of 10mM deoxynucleotide triphosphates (dNTPS), 0.5�l of 5,000-units/mL Taq polymerase (5,000 units/ml, New England BioLabs), and 2.5�l of each template. The thermocycler conditions used included an initial denaturation at 950C for 5 minutes, followed by 34 cycles of 60 seconds at 950C, 30 seconds at 550C, 60 seconds at 720C, and final extension for 10 minutes at 720C. Primers used for rpoB gene amplification were 1418F 5’-CAA TTC ATG GAC CAA GC-3’ and 3554R 5’-CCG

TCC CAA GTC ATG AAA C-3’ (Drancourt and Raoult, 2002, Mellmann et al., 2006).

The amplicon produced by these primers was 899 base pairs long. The PCR mixture for the rpoB gene contained 5µl of 10x Taq buffer (New England BioLabs), 1µl of 10mM

DNTPs, 1µl of 10µM of each primer, 0.25µl of 5,000 units/mL of Taq polymerase (5,000 units/ml, New England BioLabs), and 1.8µl of 50mM MgCl2. Thermocycler conditions consisted of 5 minutes of initial denaturation at 940C, then 35 cycles of 35 seconds at

940C, 60 seconds at 520C, 90 seconds at 720C, and 1 final cycle for 10 minutes at 720C.

Primers used for 16S rRNA gene amplification were 27F 5’-AGA GTT TGA TCC TGG

CTC AG-3’ and 1492R 5’–TAC CTT GTT ACG ACT T-3’ (Li et al., 2012). The PCR reaction contained 5µl of 10x Taq buffer (New England BioLabs, 2µl of 50mM MgCl2,

2µl of 10µM of each primer, 1µl of 10mM DNTPs, 0.5µl of 5,000 units/mL Taq polymerase (New England BioLabs), and 2.5µl of each template. The thermocycler

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conditions used were 5 minutes at 950C, then 35 cycles of 950C for 30 seconds, 550C for

60 seconds, 720C for 60 seconds, and a final single cycle elongation at 720C for 5 minutes. Six American Type Culture Collection (ATCC) quality control strains were used to confirm that the protocol and primers for the tuf and rpoB genes were working correctly. The strains used were ATCC 12228 (S. epidermidis), ATCC 27626 (S. haemolyticus), ATCC 29971 (S. xylosus), ATCC 33591 (S. aureus), ATCC 35984 (S. epidermidis), and ATCC 43958 (S. equorum). They were correctly identified using both tuf and rpoB genes with 100% identity.

For the first 111 isolates and the quality control ATCC strains, both the tuf and rpoB genes were amplified and sequenced in parallel to identify the species. Because no discrepancies in identity between the two genes were seen for the first 111 isolates, subsequently, the tuf gene was primarily used to amplify and sequence the remainder of the isolates. In a single instance where the tuf gene reported ≥99% identity for two separate species on the same isolate, the rpoB gene was used to discriminate between the two species. The 16S rRNA gene was only used if the tuf or rpoB genes did not amplify after two attempts and there was question as to whether the isolate was part of the

Staphylococcus genus.

Amplified DNA fragments of the tuf, rpoB, and 16S rRNA were purified using

ExoSAP-IT PCR clean up (Affemetrix, Cleveland, OH) and sent to the University of

Vermont Core facility for Sanger sequencing. Amplicon sequences were analyzed using

Geneious software (Biomatters Ltd.). A consensus pairwise alignment of the reverse and forward sequences of each gene was generated. The consensus sequence was queried

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with the NCBI basic local alignment search tool (BLAST), https://blast.ncbi.nlm.nih.gov/Blast.cgi, to determine species identity. All isolates were required to have ≥97% identity to a known sequence in the database in order for the species to be identified (Heikens et al., 2005).

3.3.5 Multi-locus Sequence Typing (MLST)

All S. aureus isolates were strain typed by MLST as previously described

(Enright et al., 2000). Amplified DNA for each allele was prepared in the same manner as described for tuf, rpoB or 16S rRNA amplicons before sequencing. Reverse and forward sequence alignment consensus sequences were compared to allelic sequences in the S. aureus MLST database (http://pubmlst.org/saureus) for allele number and strain type

(ST) assignment. Strain types were assigned cloned clonal complexes (CC) or lineages using eBurst algorithm as previously described (Feil et al., 2004).

3.3.6 Definition of staphylococci IMI

Staphylococci IMI was defined as retrieval from the milk sample of greater than or equal to 100 CFU/mL in pure or mixed culture (Reyher et al., 2013). While Reyher used 200 CFU/ml, a minimum of 100 CFU/ml for CNS was used for this study in order to maximize sensitivity (Dohoo et al., 2011). A sample was considered contaminated if there were at least three dissimilar colony types on a plate.

3.3.7 Statistical Analysis

Descriptive statistics were done to ascertain the distribution of staphylococci species on different farms and within different niches (Table 3-1 & 3-2). For quarter milk 112

isolates, an association between SCC and species was done using a linear mixed model in

STATA version 13.1. The somatic cell count was natural log transformed before the analysis (lnSCC) to normalize the data. The different staphylococci species were treated as fixed effects and farm as a random effect (independent variables), lnSCC (dependent variable) as continuous. Uninfected quarter SCC was made the reference where all the other species were compared to. We also used One-way ANOVA Tukey’s test to compare mean differences (lnSCC) induced by the top seven species causing IMI (Table

3-3). Species with ≤3 counts (Table 3-3) were excluded in the statistical analysis.

3.4 Results

3.4.1 Bacterial identification

A total of 1,241 isolates were selected from various niches and presumptively identified as staphylococci based on phenotypic characteristics (Gram-positive, catalase- positive cocci). Among the first 111 isolates obtained from farm A that were typed by both tuf and rpoB amplicon sequencing, we identified 15 Staphylococcus species, including S. aureus (n=1), S. auricularis (n=21), S. capitis (n=2), S. caprae (n=3), S. chromogenes (n=9), S. cohnii (n=7), S. epidermidis (n=5), S. equorum (n=9), S. haemolyticus (n=14), S. homnis (n=1), S. pasteuri (n=2), S. saprophyticus (n=1), S. simulans (13), and S. warneri (n=3). Nineteen isolates were either tuf/rpoB PCR negative or the identity percentage was lower than the cutoff value. We definitively identified the remaining isolates (n=92) using both genes as staphylococci with ≥97% identity.

Following these results, the remaining 1130 isolates were typed by tuf amplicon sequencing. A total of 190 isolates (15.3%) could not be amplified by tuf PCR primers or 113

had a low percentage identity. These tuf amplicon-negative isolates were further analyzed by 16S rRNA gene PCR amplification and sequencing. Alignment to 16S RNA sequences in the BLAST database revealed that these isolates were in different genera, mainly Macrococcus and Kocuria (data not shown). Of the remaining isolates, three were

≥98% identical to Macrococcus caseolyticus using tuf gene and 1,048 were definitively identified as Staphylococcus species with 68 S. aureus isolates confirmed with nuc gene

PCR. Other non-S. aureus coagulase positive species included, S. pseudintermedius

(n=1), and S. agnetis (n=3). Although, most of the CNS were identified by tuf gene, four isolates that were amplified and sequenced using the tuf gene resulted in ≥99% identity to two different species when queried in the BLAST database. When these ambiguous results occurred, the species that resulted with similar percentages were S. caprae/S. capitis (n=1) and S. pasteuri/S. warneri (n=3). The rpoB gene was able to resolve the discrepancy and identified the species.

3.4.2 Bacteriologic Findings in Various Niches

Of the 1,048 total staphylococci isolates that were speciated, twenty-four CNS and three coagulase positive staphylococci (S. aureus, S. agnetis and, S. pseudintermedius) species were identified among the five farms. The prevalence of CNS species varied between farms and within niches. For instance, apart from farms C and D, which were dominated by S. haemolyticus (44.48% and 42.77% of isolates respectively), the other farms were dominated by unique species; including S. auricularis (25.54%) on farm A, S. chromogenes (40%) on farm B, and S. succinus (20.52%) on farm E (Table 3-

1). When considering all five farms, S. haemolyticus was the dominant CNS species,

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driven by its high prevalence on farm C, which had the greatest number of isolates overall (Table 3-1). A notable finding was that there was a high prevalence of S. fleurettii on farm E, while this species was not detected on the other four farms. S. chromogenes was the predominant species isolated from quarter milk samples and S. equorum was the predominant species isolated from environmental niches, with the exception of farm D on which S. xylosus was the most commonly isolated species from environmental niches.

Overall, the dominant species isolated from quarter milk samples (from cows with IMI) were S. chromogenes, S. haemolyticus, S. simulans, S. aureus and S. xylosus (Table 3-3).

S. aureus was isolated in 1.2% (20/1688) quarter milk samples and CNS in 7.9%

(134/1688). On farm A and farm C, S. auricularis and S. haemolyticus were the dominant species on teat skin and extramamary skin sources. Staphylococcus haemolyticus was also common on skin sources on farm D, S. succinus and S. equorum on farm E. S. haemolyticus was the only species that was more prevalent on cow skin as well as quarter milk from cows with IMI (Table 3-2). There were several species that were found in both human and dog or pig samples, including, S. epidermidis, S. warneri,

S. succinus, and S. fleurettii.

3.4.3 S. aureus MLST

All 68 S. aureus isolates were strain typed. Eight different STs were identified including, ST5 (n=5), ST8 (n=2), ST30 (n=4), ST45 (n=2), ST151 (n=24), ST352 (n=4),

ST3021 (n=2), and ST3028 (n= 25). These STs were within six clonal complexes (CC) according to eBurst, including CC97 (ST352, ST3021, and ST3028), CC151 (ST151),

CC5 (ST5), CC30 (ST30), and CC45 (ST45). Strain types were host/niche specific, for

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instance ST8, ST151, ST352, ST3021 and ST3028 were only identified from cow quarter milk samples, teat end swabs, bulk tank milk, or milking equipment swabs, whereas ST5,

ST30, and ST45 were isolated only from humans or dogs on these farms. Strain types were exactly the same in cows where S. aureus was isolated from teat end or streak canal as well as quarter milk. S. aureus was more often isolated from quarter milk and streak canal than teat end, and no S. aureus was detected from cow extrammammary sources

(hock, perineum, nose, and vagina) and the environment. At farm level, ST3028 and

ST151 were the widest spread STs, isolated from at least one cow on 4/5 farms in the study. ST3021 and ST8 were found only on farm C and ST352 only on farm B. One S. aureus isolate from farm A was isolated from a dog-nasal swab and was classified as

ST45. Although ST45 was isolated from both human and dog samples, they were not from the same farm.

3.4.4 Association of Staphylococcus Species and Somatic Cell Count (SCC)

A total of 1,688-quarter milk samples were collected from 427 cows across the five farms. At least one staphylococci colony was isolated from 127 samples in pure culture, 17 samples were contaminated. Samples from the second visit for collection of skin isolates were not included in the SCC association analysis. As expected the SCC of uninfected quarters was significantly lower than that of infected quarters (p<0.05). At the species level, among the top seven causes of IMI (Figure 3-1), there was significant increase in SCC for the infected compared to uninfected quarters except for quarters infected with S. auricularis and S. epidermidis. Somatic cell count from infected quarters

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with, S. simulans, and S. xylosus were not significantly different from that of S. aureus

(p>0.05).

3.5 Discussion

Some Staphylococcus species (CNS) are thought to protect cows from being infected by pathogenic contagious pathogens (Lam et al., 1997, De Vliegher et al., 2004).

This concept is not conclusive as other studies showed the opposite (Hogan et al., 1988) or no protective effect (Zadoks et al., 2001). Resolving these controversies require accurate identification of CNS and staphylococci as a whole. This is crucial on farmstead cheese farms as some Staphylococcus species may play role in cheese ripening

(Bockelmann W., 2001). Sequence based species identification is now accepted as the gold standard. A number of genes have been used for sequence-based species identification of staphylococci including, the tuf gene (Heikens et al., 2005), the rpoB gene (Drancourt and Raoult, 2002), the sodA gene (Poyart et al., 2001), the hsp60 gene

(Kwok et al., 1999), the dnaJ gene, (Shah et al., 2007), the gap gene (Yugueros et al.,

2000), the femA gene (Vannuffel et al., 1999), and the 16S rRNA gene (Becker et al.,

2004). We conducted a preliminary experiment comparing tuf and rpoB sequence-based typing for the first 111 isolates collected in this study, in order to select a suitable gene to use for species typing. After initial comparison of the two genes, tuf PCR was used as the primary typing method. Tuf gene failed to discriminate two pairs of species for some isolates in this study e.g, S. caprae/S. capitis and S. pasteuri/S. warneri. The inability of this tuf gene amplicon to discriminate between S. pasteuri/S. warneri has been reported

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previously in human clinical isolates (Hwang et al., 2011). It was also found that 16S rRNA sequencing could not discriminate between S. caprae and S. capitis (Shin et al.,

2011). This suggests that these bacterial species pairs are closely related and a combination of genes may be required to discriminate them. For instance, the rpoB gene has been shown to discriminate these two species (Mellmann et al., 2006, Park et al.,

2011). Tuf gene identification of Macrococcus caseolyticus was not surprising as it was formerly in the genus Staphylococcus (Staphylococcus caseolyticus), and the two genera are closely related to each other (Baba et al., 2009)

Fifteen percent of isolates that were presumptively identified as staphylococci by phenotypic identification were tuf PCR negative or amplified with a low identity percentage identity. Sequencing of 16S rRNA gene fragments, revealed that these isolates were mainly in the genera Macrococcus and Kocuria, which are gram positive, catalase positive cocci and can be easily misidentified to be staphylococci based on growth on either selective or non-selective media (Faller and Schleifer, 1981). This flaw in the initial identification demonstrates the need to use more accurate methods of identification, such as molecular based methods described in this paper, to replace phenotypic based methods (Ben-Ami et al., 2005). Data on misidentification of staphylococci is not available in recent sequence based species identification studies, and we speculate researchers do not report these incorrectly identified isolates.

A total of 1,048 staphylococci were analyzed, representing 27 different species.

Dominant species varied per farm (Figure 3-1) except on farm C and D. This differential predominance of staphylococci species is not uncommon; a similar pattern was seen in a

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longitudinal study focusing on the epidemiology of CNS on six Flemish dairy farms in

Belgium (Piessens et al, 2011). The differential prevalence of staphylococci species on these farms may be driven by farm-level management practices. For instance, a recent study showed that bulk tank milk samples from farms with a tie-stall housing system were more likely to be culture positive for some CNS species than farms with freestall barn (De Visscher et al., 2017). Further research is needed to identify farm practices that may prevent the spread of CNS causing IMI but allow the flourishing of commensal bacteria that may be beneficial to the cows. On the other hand, this difference might be driven by pathogen characteristics, for instance, varying virulence determinants between strains of similar species.

Distribution of species also varied within different niches between farms, but overall, the dominant species isolated from quarter milk (from cows with IMI) was S. chromogenes (Table 3-3) with little prevalence in the environment (Table 3-2). This suggests that S. chromogenes is a cow-adapted species, which is consistent with previous findings (Fry et al., 2014), and milking equipment acting as fomites. Other species that were common in quarter milk samples with IMI include S. haemolyticus, S. simulans S. aureus, and S. xylosus. S. chromogenes, S. haemolyticus and S. simulans were among the top five CNS species causing IMI in previous studies conducted in Europe and Canada

(Piessens et al., 2011, Piessens et al., 2012, Fry et al., 2014, Vanderhaeghen et al., 2015).

S. haemolyticus and S. aureus were the second co-dominant species causing of IMI among all the staphylococci isolated from infected cow quarters (Table 3-3). Despite improved control of contagious pathogens on these farmstead cheese farms, S. aureus is

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still a problem though its overall prevalence is low compared to CNS. The overall CNS quarter level prevalence (7.9%) in this study is slightly high, but S. aureus prevalence

(1.2%) is very low compared to a recent study on 18 farms that supplied milk to an alpine dairy for cheese making in Australia (Kummel et al., 2016). However, compared to some non-cheese producing farm studies (Thorberg et al., 2009, Fry et al., 2014), the CNS prevalence in this study is lower. The high prevalence of CNS IMI in this study, and others (Thorberg et al., 2009) compared to S. aureus supports increasing role of CNS on farms that have contained contagious pathogens. Among the top three common causes of

IMI (Table 3-3), only S. haemolyticus, was isolated from all niches in the study suggesting multiple reservoirs. This is consistent with the previous study (De Visscher et al., 2014), strain typing these S. haemolyticus isolates would add more knowledge on potential reservoir IMI strains and transmission.

S. auricularis and S. succinus were the dominant species on teat skin with relatively low prevalence in quarter milk samples (Table 3-2) especially on farm A and E respectively. These two species have been isolated on teat skin, extrammamary sources, and environment, but are rarely isolated in bovine milk (Piessens et al., 2011, Piessens et al., 2012, De Visscher et al., 2014). The dominant environmental species included S. equorum and S. xylosus, though they were also present in other niches (e.g cow skin and humans and cow quarter milk with low prevalence). S. equorum is a common environmental species (Piessens et al., 2011) and it is thought to be beneficial in cheese making (Bockelmann W., 2001, Place et al., 2003). S. equorum, S. xylosus, S. succinus, and S. saprophyticus are the four common Staphylococcus species isolated in naturally

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aged cheese (Coton et al., 2010, Wolfe et al., 2014, Kastman et al., 2016). Interestingly, apart from S. xylosus, the remaining species don’t seem to be important mastitis pathogens from this study (Table 3-3). Allowing these species to flourish might be of great importance on cheese producing farms. However, S. saprophyticus is a known human pathogen (Raz et al., 2005) and its presence in cheese might be a public health threat. Although, it is debatable on whether S. saprophyticus cheese strains can cause disease in humans, keeping it out of cheese products is advisable (Kastman et al., 2016).

S. equorum, S. succinus, S. auricularis, and S. fleurettii were predominant on cow skin on some farms but rarely caused IMI. This may suggest that they are normal commensal organisms. Some species like S. fleurettii, S. haemolyticus or S. epidermidis, were distributed in almost all niches including quarter milk and humans. Strain typing of these species will provide knowledge on strain diversity and insights on transmission and potential reservoirs. For example, S. fleurettii was detected on only farm E, isolates were distributed throughout the five different niches, including humans.

The two most common species isolated from humans were S. aureus and S. epidermidis. These two species are among the most commonly isolated Staphylococcus species in humans (Becker et al., 2014, Kumar et al., 2015). Some farms, where S. epidermidis was isolated in humans, had at least one S. epidermidis IMI positive cow, suggesting that humans could be a potential source of S. epidermidis causing IMI. S. epidermidis is considered a human adapted species with strains causing IMI coming from humans (Thorberg et al., 2006, Vanderhaeghen et al., 2015). S. aureus MLST revealed

ST-host specificity. Humans sampled in this study were colonized by the known human

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adapted S. aureus strain types; ST5, ST30 and ST45. Cows were infected with ST8,

ST151, ST3021, and ST3028. This host specificity suggests that there is no evidence of cross transmission of S. aureus between cows and humans or dogs at least from this data set. This could be attributed to good hygiene on the farms, which prevents cross transmission between hosts or these strains have unique host specific virulence determinants as has earlier been determined for some S. aureus (Sung et al., 2008).

Quarter milk STs were similar to STs from bulk tank milk suggesting that S. aureus in bulk tank milk is primarily from infected cow quarter milk especially on farms with good hygiene.

S. aureus ST3021 and ST3028 are recently identified novel STs in our laboratory in a study that focused on understanding S. aureus genotypes in bulk tank milk samples from 44 organic dairy farms in Vermont (Chapter 2). ST3028 was among the most prevalent STs. The prevalence of ST3028 in this study is comparable to that of ST151 suggesting that ST3028 is an important novel ST causing IMI in this region. ST352,

ST3021, ST3028 belong to CC97 which is a known bovine adapted clonal complex globally (Smith et al., 2005). ST3021 and ST2187 are single locus variants (slvs) of

ST352 and ST3028 is a slv of ST2187. Although, we did not find ST2187 in this study, a previous study identified it in cases of bovine mastitis in this region (Barlow et al., 2013).

It is noteworthy that ST2187, ST3021, and ST3028 have been isolated only in the New

England region according to MLST database and literature suggesting a geographic effect on ST distribution. ST151 belongs to CC151, another bovine adapted lineage, commonly isolated in milk (Sung et al., 2008, Bergonier et al., 2014). CC8 is a human adapted

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lineage with recent jump into cattle (Sakwinska et al., 2011, Resch et al., 2013). The prevalence of CC8 mastitis is generally low in the USA but relatively high in some

European countries (van den Borne et al., 2010). CC8 could be still adapting to cow udder environment, as in this study, it was isolated in one cow quarter. Its epidemiology should be monitored because in our previous work, ST8 isolates were 100% resistant to

Penicillin and Ampicillin antibiotics and the majority were good biofilm formers on hydrophilic surfaces (Chapter 2).

The association between quarter milk SCC and Staphylococcus species was analyzed, with the goal to identify other CNS species that induce SCC that are comparable to that of S. aureus. S. aureus is known to induce severe inflammation in cow mammary tissue compared to CNS (Schukken et al., 1999). As expected uninfected quarters had a significantly lower SCC than infected quarters consistent with other studies (Fry et al., 2014). At the species level, SCC induced by S. auricularis and S. epidermidis was not statistically different from uninfected quarters. This could be due to fewer numbers of infected quarters or they truly don’t induce inflammation. The average

SCC of S. simulans, and S. xylosus were comparable to that of S. aureus. This is consistent with one study in Europe that showed S. simulans, and S. xylosus induced SCC similar to that of S. aureus (Supre et al., 2011). Although S. chromogenes was the most prevalent CNS species isolated from infected quarters, the average SCC was significantly lower than that of S. aureus (p<0.01). This is not consistent with the findings of Supre et al., 2011 where S. chromogenes was shown to induce SCC comparable to S. aureus. This discrepancy could suggest that S. chromogenes is heterogeneous, with some strains

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inducing more severe inflammation than others. Elucidation of this phenomenon will require use of unambiguous strain typing techniques, like MLST, to compare global distribution of S. chromogenes strains causing IMI. This will also allow studying strain specific factors that drive differences in the pathogenicity of different strains. It’s clear at least from induction of inflammation that some strains are more severe than others

(Breyne et al., 2015). Additionally, other studies did not see any significant difference in

SCC between CNS species (Taponen et al., 2006, Thorberg et al., 2009). However, this could also be driven by mere difference in the virulence determinants between or within strains. Coagulase negative staphylococci can possess similar virulence determinants present in S. aureus (Kuroishi et al., 2003).

3.6 Conclusion

Staphylococci remain important mastitis pathogens and molecular based species identification has given more insight on the true epidemiology of these bacteria. The predominance of species was farm specific. Although over sixteen species were isolated from infected quarters, only five species are most prevalent cause of IMI, including S. chromogenes, S. haemolyticus, S. aureus, S. simulans and, S. xylosus. S. succinus, S. auricularis, S. fleurettii and S. equorum were common on the cow skin and rarely cause

IMI. These are likely to be normal commensal bacteria and any infections caused may just be opportunistic. Some species like S. haemolyticus, S. xylosus, S. epidermidis, and

S. fleurettii were isolated in multiple niches, suggesting the presence of multiple reservoirs. There was no evidence of S. aureus transmission from humans to cows or vice versa. Based on quarter level prevalence, S. simulans, S. xylosus, S. chromogenes, S.

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haemolyticus are four top important CNS species causing IMI, with S. simulans and S. xylosus inducing inflammation comparable to that of S. aureus. Among the top five species causing IMI in this study only S. xylosus and S. haemolyticus seem to have multiple reservoirs. The other three species (S. aureus, S. chromogenes and S. simulans) seem to be cow adapted. Future CNS studies in this region should mainly focus on these top five bacterial species causing IMI especially their molecular epidemiology and transmission dynamics within and across farms.

3.7 Acknowledgments

This study was supported by USDA food systems grant, Hatch grant and North East

SARE grant no. GNE14-087. We thank Sam Hart, Amanda Carmellini, and Laura Budd for their help during field sample collection. We gratefully acknowledge the participating farmers as well as University of Vermont core facility for the sequencing work.

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Becker, K., D. Harmsen, A. Mellmann, C. Meier, P. Schumann, G. Peters, and C. von Eiff. 2004. Development and evaluation of a quality-controlled ribosomal sequence database for 16S ribosomal DNA-based identification of Staphylococcus species. J. Clin. Microbiol. 42(11):4988-4995.

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Bergonier, D., D. Sobral, A. T. Fessler, E. Jacquet, F. B. Gilbert, S. Schwarz, M. Treilles, P. Bouloc, C. Pourcel, and G. Vergnaud. 2014. Staphylococcus aureus from 152 cases of bovine, ovine and caprine mastitis investigated by Multiple-locus variable number of tandem repeat analysis (MLVA). Vet. Res. 45(1):97.

Berry, D. P. and W. J. Meaney. 2006. Interdependence and distribution of subclinical mastitis and intramammary infection among udder quarters in dairy cattle. Prev. Vet. Med. 75(1-2):81-91.

Bockelmann, W. 2002. Development of defined surface starter cultures for the ripening of smear cheeses. . International Dairy Journal 12:123-131.

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Table 3-1: Distribution of staphylococci species by farm No. of isolates per farm

Staphylococci A B C D E Total (%) S. arlettae - 1 - - - 1 (0.1) S. agnetis - - - - 3 3 (0.3) S. aureus 14 10 31 5 8 68 (6.5) S. auricularis 47 3 29 2 - 81 (7.8) S. capitis 3 1 3 - - 7 (0.7) S. caprae 6 - - - - 6 (0.6) S. chromogenes 14 36 51 6 34 141 (13.4) S. cohnii 12 5 - - 2 19 (1.8) S. gallinarum - 2 5 1 - 8 (0.8) S. epidermidis 9 4 6 2 6 27 (2.7) S. equorum 14 4 25 9 52 104 (10) S. fleurettii - - - - 36 36 (3.4) S. haemolyticus 19 9 152 71 27 278 (26.5) S. hominis 3 3 8 - 4 18 (1.7) S. kloosii - - 1 - - 1 (0.1) S. lugdunensis - 1 - - 1 2 (0.2) S. saprophyticus 1 - - 1 2 4 (0.4) S. pasteuri 3 1 1 1 1 7(0.8) S. pseudintermedius - - - - 1 1 (0.1) S. simulans 21 5 - - 1 27 (2.6) S. sciuri 5 - 6 - - 11 (1) S. succinus 1 - - 7 56 64 (6) S. vitulinus - - - 7 8 15 (1.4) S. warneri 7 1 2 7 1 18 (1.8) S. xylosus 2 3 15 43 21 84 (8) S. sp. C035 1 - - - - 1 (0.1) S.sp. 020902-022-273 - 1 6 4 5 16 (1.5) Total 182 90 341 166 269 1048 (100)

Bold indicates the dominant species per farm

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Table 3-2: Overall distribution of Staphylococcus species by source of sample collection No. (%) of isolates per niche Milking Extra Human System and Environm Dogs and Quarter Milk1 Teat Skin3 Mammary hand and Total (%) Bulk Tank ent5 pigs Cow Skin4 nose Staphylococci Milk2 S. arlettae - - 1 (100) - - - - 1 (0.1) S. agnetis 2 (66.7) - 1 (33.3) - - - - 3 (0.3) S. aureus 35 (51.5) 10 (14.7) 12 (17.6) - - 10 (14.7) 1 68 (6.5) S. auricularis 6 (7.3) 3 43 (53.7) 27 (32.9) 2 (2.4) - - 81 (7.8) S. capitis 2 (28.6) - 4 (57.1) - 1 (14.3) - - 7 (0.7) S. caprae 1 (16.7) - 1 (16.7) 4 (66.7) - - - 6 (0.6) S. chromogenes 82 (58.2) 22 (15.6) 18 (12.8) 15 (10.6) 2 (1.4) - 2 (1.4) 141 (13.4) S. cohnii - 3 (15.8) 10 (52.6) 2 (10.5) 4 (21.1) - - 19 (1.8) S. gallinarum 4 (50) 3 (37.5) - 1 (12.5) - - - 8 (0.8) S. epidermidis 7 (25) - 3 (14.3) 1 (3.8) - 16 (57.1) - 27 (2.7) S. equorum 11 (10.6) 5 (4.8) 21 (20.2) 28 (26.9) 29 (27.9) 7 (6.7) 3 (2.9) 104 (10) S. fleurettii 9 (25) 6 (16.7) 12 (33.3) 6 (16.7) 1 (2.8) 2 (5.6) - 36 (3.4) S. haemolyticus 37 (13.26) 10 (3.6) 109 (39.4) 109 7 (2.5) 5 (1.8) 1 (0.4) 278 (26.5) S. hominis 5 (27.8) 3 (16.7) 4 (22.2) 2 (11.1) - 4 (22.2) - 18 (1.7) S. kloosi - - 1 (100) - - - - 1 (0.1) S. lugdunensis - - - - - 2 (100) - 2 (0.2) S. saprophyticus 1 (25) - - 1 (25) - 2 (50) - 4 (0.4) S. pasteuri 1 (12.5) 1 (12.5) - 1 (12.5) - 4(62.5) - 7 (0.8) S. pseudintermedius ------1 (100) 1 (0.1) S. simulans 13 (48) 2 (7.4) 9 (33.3) 3 - - - 27 (2.6) S. sciuri - - - 1 (9.1) 7 (63.6) - 3 (27.3) 11 (1) S. succinus 3 (4.8) 7 (11.1) 27 (42.9) 15 (23.8) 6 (9.5) 5 (6.3) 1 (1.6) 65 (6) S. vitulinus 2 (13.3) 1 (6.7) 3 (20) 6 (40) 2 (13.3) 1 (6.7) - 15 (1.4) S. warneri 4 (21.1) 4 (21.1) 1 (5.3) 2 (10.5) - 6 (36.8) 1 (5.3) 18 (1.8) S. xylosus 9 (10.7) 4 (4.8) 21 (25) 21 (25) 25 (29.8) 2 (2.4) 2 (2.4) 84 (8) S. sp. C035 ------1 (100) 1 (0.1) S.sp. 020902-022-273 5 (31.3) 1 (6.3)) 5 (31.3) 5 (31.3) - - - 16 (1.5) Total 239 (22.8) 85 (8.1) 306 (29.2) 250 (23.9) 86 (8.2) 66 (6.3) 16 (1.5) 1048 (100)

1: Includes quarter and cannulated milk samples 2: Includes bulk tank milk, milk filter, inflation pre-milking, and teat cup post-milking samples. 3: Includes streak canal, teat end, teat barrel, and teat laceration samples. 4: Includes perineum, hock, vagina, cow nose, and udder cleft samples. 5: Includes stall partition rail, grain, water bowl rim, used sawdust bedding, feed trough and water trough samples. Bold indicates some of the dominant staphylococci species per niche.

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Table 3-3: Number of cow quarters infected with the respective Staphylococcus species per farm

1- Number of quarters with two Staphylococcus species isolated and identified

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Figure 3-1: Box plot for association between Staphylococcus species and somatic cell count (*) Outlier data points.

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CHAPTER 4 : A MULTILOCUS SEQUENCE TYPING SCHEME

PROVIDES INSIGHTS INTO THE DIVERSITY OF

STAPHYLOCOCCUS CHROMOGENES ISOLATED FROM DAIRY

FARMS FROM THE UNITED STATES AND BELGIUM

1Robert Mugabi, 1Samantha D’Amico, 2George Sensabaugh, 3Larry Fox, 4Sarne De Vliegher,

4Anneleen De Visscher 1John Barlow*

1. Department of Animal and Veterinary Sciences, University of Vermont, Burlington,

Vermont, USA

2. School of Public Health, University of California, Berkeley, USA

3. Department of Animal Science, Washington State University, USA

4. Department of Reproduction, Obstetrics and Herd Health, Gent University, Belgium

*Corresponding author: John Barlow, Department of Animal Science, University of Vermont

570 Main St, Burlington VT, USA 05405

Phone: 802-656-1395

Email: [email protected]

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4.1 Abstract

Staphylococcus chromogenes is the leading cause of intrammamary bovine infections (IMI) among the coagulase negative staphylococci. Staphylococcus chromogenes’ local and global epidemiology, evolution, and transmission dynamics are not entirely clear. In this study, 241

S. chromogenes isolates were analyzed using a recent novel multilocus sequence-typing

(MLST) scheme. Isolates were from the USA (n=169) and Belgium (n=48) from various sources including, cow milk, cow skin, milking equipment, cheese, pigs, and the environment.

Isolates were also screened for carriage of the mecA and blaZ genes. MLST revealed sixty- two strain types (STs) with a 0.939 Simpson’s diversity of index. Only five STs (ST1, ST6,

ST18, ST29, and ST30) were shared between the two countries. ST1 (n=26) and ST6 (n=31) were the predominant STs causing IMI in the USA and ST28 (n=7) in Belgium. Most STs clustered in four clonal complexes (CCs) including, CC1 (n=12), CC6 (n=9), C15 (n=5), and

CC62 (n=7). ST10 (n=13), ST26 (n=1), ST54 (n=1), ST55 (n=5), and ST61 (n=2) were exclusively isolated on teat skin or extrammamary cow skin only and, therefore, were not associated with IMI. Strain types from the environment and pigs were unique compared to other niches. Number of STs causing IMI ranged from 2-7 within farms. All isolates were mecA negative. The blaZ gene was present in 21.6% (n=54) of isolates and was more associated with STs from cow skin than those causing IMI (p<0.05). This data shows strain type specificity of S. chromogenes geographically as well as source of isolation, and carriage of the blaZ gene. The variability of strain type diversity within farms suggests both an environmental and contagious mode of transmission. This work lays a foundation to further

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study transmission dynamics, virulence, and evolution of S. chromogenes at a strain type level.

Key words; Dairy cattle, Staphylococcus chromogenes, Epidemiology, MLST, Mastitis

4.2 Introduction

Staphylococcus chromogenes is a Gram-positive bacterium in the genus

Staphylococcus. It is among the predominant coagulase negative staphylococcus (CNS) species isolated from cow quarter milk with intrammamary infections (IMI) and subclinical mastitis (Thorberg et al., 2009, Zadoks and Watts, 2009). Mastitis, the inflammation of the mammary gland, is the leading cause of production losses in the dairy industry, especially in developed countries that have contained most animal infectious diseases.

There is increased prevalence of CNS mastitis on farms that have controlled IMI due to major pathogens like S. aureus, streptococci and coliforms. Most CNS IMI studies show a high prevalence of S. chromogenes IMI with the ability to cause persistent infections (Gillespie et al., 2009, Thorberg et al., 2009). Although CNS are considered minor pathogens and tend to induce mild inflammation (Ruegg, 2009, Schukken et al., 2009), one study showed that S. chromogenes infected cow quarters had somatic cell count comparable to that of S. aureus infected quarters (Supre et al., 2011). A recent study in Brazil, has documented some strains that can clot blood plasma (Dos Santos et al., 2016). This phenotype may contribute to the S. chromogenes pathogenesis, and virulence.

Some studies have concluded that S. chromogenes is an animal-adapted species

(Piessens et al., 2012), because it’s rarely isolated in humans (Couto et al., 2001). This species is also rarely isolated in the cow barn environment (Piessens et al., 2011, De Visscher et al.,

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2014). If there is no environmental or human reservoir, then it is plausible that S. chromogenes is being spread contagiously from cow to cow, like S. aureus (Piessens et al.,

2012, De Visscher et al., 2014) or the environmental source has not been identified yet. This is not entirely clear, as some studies showed high heterogeneity of S. chromogenes on farms using Pulsed Field Gel Electrophoresis (PFGE) (Gillespie et al., 2009, Rajala-Schultz et al.,

2009).

In some studies, S. chromogenes has been isolated from cow teat skin and extrammamary cow skin (De Vliegher et al., 2003, De Visscher et al., 2014). The notion that cow skin is the potential reservoir of strains that cause IMI is still being debated. Studies that compared strains on teat skin and those causing IMI have used ambiguous strain typing techniques [PFGE and AFLP (amplified fragment length polymorphism)] that have inter- laboratory variability. (Gillespie et al., 2009, Piessens et al., 2011). In addition, these typing methods are not optimal for studying global epidemiology and the long-term evolution of pathogens (Maiden et al., 1998). Staphylococcus chromogenes is an internationally recognized species that causes bovine IMI. Understanding strains or lineages that commonly cause mastitis globally is also crucial to establishing management practices to prevent their transmission, such as designing vaccines or understanding virulence determinants of those lineages. Delineation of strains that cause persistent and non-persistent infections as well as identifying non-pathogenic strains is crucial as some strains may just be commensals.

To better understand the epidemiology of this bacterium, a novel multilocus sequence-typing (MLST) scheme was recently developed (Sensabaugh et al, in preparation).

Multilocus sequence typing is a strain-typing technique based on sequence variation of seven

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housekeeping genes (Enright and Spratt, 1999, Enright et al., 2000). The unambiguous nature, reproducibility, high discriminatory power, and typeability of MLST make it a great typing technique to understand local and global epidemiology as well as the evolution of pathogens

(Maiden et al., 1998, Enright and Spratt, 1999, Smith et al., 2005a). In S. aureus, it has been used to elucidate lineages that carry antibiotic resistant determinants (Enright et al., 2000) as well as predominant clonal complexes involved in bovine mastitis (Smith et al., 2005b). In this study, the use of MLST to explore the common S. chromogenes strain types (STs) that cause IMI and how these relate to strains isolated from cow skin and the environment is elucidated. Strain types from two countries (Belgium and USA) were also compared with the goal of determining whether there are common strains causing IMI, which would suggest global spread. The isolates were also screened for carriage of blaZ and mecA genes, which encode methicillin and penicillin resistance in staphylococci, respectively (Lowy, 2003). The major objective of this project was to a novel MLST scheme to ascertain strain diversity of S. chromogenes from various niches and geographical areas. The second object was determined potential association S. chromogenes strain types and carriage of blaZ or mecA genes. We hypothesized that carriage of these genes might be associated with specific strain types.

4.3 Materials and Methods

4.3.1 Bacterial isolates

A total of 241 Staphylococcus chromogenes isolates where used in this study. The isolates originated from three distinct geographical regions: Vermont (n=169) and

Washington states (n=24) in the USA and Belgium (n=48). The Vermont isolates were taken from samples in various niches on 10 dairy farms, four of which were conventional farms and 141

the rest were organic. The niches were quarter milk, which included cow quarter and cannulated milk samples (n=106), milking equipment and bulk tank milk (n=25), teat skin, which included teat end, teat barrel, and streak canal (n=17), extrammamary sources, which included perineum, hock skin, cow vagina and cow nose (n=15), the environment (n=2), pig nose (n=2), and cheese (n=2). The Washington isolates were from cow quarter milk samples, apart from one isolate from cow teat skin. Belgium isolates were taken from cow teat skin

(n=19) and cow quarter milk (n=29). Information about the farm source for Washington and

Belgium isolates was unknown; they’re treated as if they were from a single farm. For

Vermont, 83.4% (n=141) of the isolates were from five farms (A, B, C, D, and E) where whole herd cow quarter milk, selected cow skin and environmental sampling were done. This was part of a bigger study to understand the epidemiology of staphylococci on five-selected farmstead cheese-producing farms in Vermont (Chapter 3). The rest of the Vermont isolates included in the study were picked from other unrelated epidemiologic studies done in our lab.

Three of these isolates from bulk tank milk from two farms had a positive coagulase test and were confirmed to be S. chromogenes using tuf gene sequencing (Heikens et al., 2005).

4.3.2 Bacterial identification

The species confirmation of all isolates, including isolates from Washington and

Belgium, was done by PCR amplification and sequencing of the tuf gene. This housekeeping gene encodes elongation factor Tu. Previously published primers were used for amplification of the tuf gene including, TufF 5’-GCC AGT TGA GGA CGT ATT CT-3’ and TufR 5’-CCA

TTT CAG TAC CTT CTG GTA A-3’ (Heikens et al., 2005, Hwang et al., 2011) which produced a 412bp fragment. The PCR reaction contained 5�l of 10x taq buffer (New England

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BioLabs), 2�l of 50mM Mgcl2, 2�l of 10�M of each primer, 1�l of 10mM deoxynucleotide triphosphates (dNTPS), 0.5�l of 5,000-units/mL taq polymerase (New England BioLabs), and

2.5�l of each template. The thermocycler conditions used included an initial denaturation at

950C for 5 minutes, followed by 34 cycles of 60 seconds at 950C, 30 seconds at 550C, 60 seconds at 720C, and final extension for 10 minutes at 720C.

Amplified partial DNA segments of the tuf gene were purified using ExoSAP-IT

PCR clean up (Affemetrix, Cleveland, OH) and sent to the University of Vermont Core facility for Sanger sequencing. Amplicon sequences were analyzed using Geneious software

(Biomatters Ltd.). A consensus pairwise alignment of the reverse and forward sequences of each gene was generated. The consensus sequence was queried with the NCBI basic local alignment search tool (BLAST), https://blast.ncbi.nlm.nih.gov/Blast.cgi, to determine species identity. All isolates were required to have ≥97% identity to a known sequence in the database in order for the species to be identified (Heikens et al., 2005).

4.3.3 PCR Screening for the blaZ and mecA genes

PCR-based amplification of the blaZ and mecA gene fragments, which are common markers for penicillin and methicillin resistance, respectively, was used to screen for carriage of these antimicrobial resistance elements. We developed a multiplex PCR for screening staphylococci isolates by inclusion of the tuf gene primers to act as an internal control for blaZ and mecA amplification. Staphylococcus aureus ATCC strains 33591 and

29213 were used as positive controls for the mecA and blaZ genes respectively. The primers used were; TufF 5’-GCC AGT TGA GGA CGT ATT CT-3’ and TufR 5’-CCA TTT CAG

TAC CTT CTG GTA A-3’ (Chapter 3), BlaZF 5’-AAG AGA TTT GCC TAT GCT TC-3’,

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BlaZR 5’-GCT TGACCA CTT TTA TCA GC-3’, mecAF 5’-AAC AGG TGA ATT ATT

AGC ACT TGT AAG-3’, and mecAR 5’-ATT GCT GTT AAT ATT TTT TGA GTT GAA-

3’ (Vesterholm-Nielsen et al., 1999, Martineau et al., 2000). Each PCR reaction contained 5µl of 10x Taq buffer (New England BioLabs), 3µl of 50mM MgCl2, 2µl of 10µM of each tuf and mecA primer, 2.5µl of 10µM of each blaZ primer, 1µl of 10mM DNTPs, 0.4µl of 5,000 units/mL Taq polymerase (New England BioLabs), and 2.5µl of each template. Thermocycler conditions included an initial elongation for 15 minutes at 950C, then 34 cycles of 30 seconds at 940C, 30 seconds at 550C, 30 seconds at 720C, and a final elongation for 10 minutes at

720C.

4.3.4 MLST

Multilocus sequence typing was done as previous explained (Sensabaugh et al, in preparation). Each of the seven PCR amplified genes, the amplicon was prepared and sequenced using the methods described for the tuf gene. Each consensus sequence was trimmed to the required standard size (Sensabaugh et al, in preparation). Allele numbers were assigned to each unique gene sequence in order of their discovery due to having no existing database to compare with. Each allele for newer isolates was compared to the already existing alleles and it was determined whether it was novel or pre-existing. These manipulations were done using Geneious software (Biomatters Ltd.). Each of the unique set of seven gene allele numbers represented a distinct strain type (Table 4-3).

4.3.5 Data analysis

A chi-squared test was used to determine whether there was an association

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between strain types and isolate source. To determine whether some strain types from a particular were more likely to carry blaZ gene, a mixed logistic model was done in STATA version 13.1, with blaZ as an outcome of interest and source as the independent variable. This was done for only strain types that had at least an isolate that carried the blaZ gene. Isolates where grouped into clonal complexes or lineages using eBurst as previously described (Feil et al., 2004). The seven loci sequences for each isolate were concatenated in the order arcC,

HutU, FumC, dnaJ, glpF, menF, and pta to produce a 4563bp fragment. Phylogenetic analysis of the strain types was done using MEGA software version 6.0 (Tamura et al., 2013). The discrimination index of MLST (Simpson’s index of diversity) for all isolates was calculated as previously described (Hunter and Gaston, 1988).

4.4 Results

4.4.1 Strain Types

All 241 S. chromogenes isolates were typeable by multilocus sequence typing. The

MLST discriminatory power (Simpson’s index of diversity [D]) for all isolates was 0.939

(Hunter and Gaston, 1988). A total of 62 distinct strain types were identified, with 40 STs in the United States, and 22 STs in the Belgium isolates. There was strong evidence of strain specificity between these two countries, with only 5/62 STs shared between these two countries: ST1, ST6, ST18, ST29, and ST30 (Figure 4-1). Although ST1 (n=36) and ST6

(n=36) were the predominant STs among the USA isolates, there were very few ST1 (n=1) and ST6 (n=2) isolates among the Belgium isolates. ST28 was found most frequently detected

ST, among the Belgium isolates (n=11). In the United States, the 24 isolates from Washington

State made up 13 STs, with ST6 (n=6) and ST17 (n=6) being the most frequent. While

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Vermont isolates had 37 STs, ST1 (n=30) and ST6 (n=36) were the predominant STs. Five

STs were shared between the Vermont and Washington isolates: ST1, ST15, ST17, ST25, and, ST26. Whole herd sampled farms in Vermont showed a wide range of number of strain types for isolates from cow quarter milk. The number of STs in quarter milk isolates from these whole herd sampled farms ranged from 2-7 STs with ST1 and ST6 being the predominant STs causing IMI (Figure 4-3). Farm A and farm D had only 5 and 3 cow quarter with S. chromogenes IMI respectively, only two STs were detected. Farm B had the highest number S. chromogenes infected cow quarters (n=26) and 7 STs were identified.

Interestingly, 64.7% (n=11) of the cow quarters with S. chromogenes IMI on farm E, ST6 was the identified ST. On farm C however, seven different STs were detected in ten S. chromogenes infected cow quarters (Figure 4-3B).

The strain types isolated from quarter milk were similar to strain types isolated from bulk tank milk and milking equipment. In other niches, STs were more often different from those in quarter milk samples with ST10 (n=13), ST26 (n=1), ST54 (n=1), ST55 (n=5),

ST61 (n=2) only being isolated on teat skin and extrammamary cow skin only, ST29 (n=1),

ST30 (n=2) only from the farm environment only, and ST22 and ST23 only from pig nares in

Vermont isolates. However, ST29 isolated from the environment in the US, was isolated from a cow with IMI in Belgium. Whereas, ST1 and ST6 were the predominant STs causing IMI in the USA isolates, ST28 predominated among the Belgium isolates. Strain types that were on cow teat or extrammamary cow skin and quarter milk isolates included ST1, ST2, ST6, ST17, and ST25. One cow from a Vermont dairy farm was colonized with five distinct S. chromogenes STs, including ST1, ST10, ST26, ST54, and ST55. Most of the isolates on this

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cow were from teat skin and extrammamary cow skin and it was S. chromogenes IMI negative. It was however, infected with S. aureus ST151 (S. aureus MLST) in one quarter and

S. haemolyticus in another quarter. ST1, ST6, and ST17 were more associated with IMI

(p<0.05). In a chi square test, the difference in the distribution of the ST28 from IMI and Skin was not different (p=0.37) within the Belgium isolates.

Three isolates from bulk tank milk on two different farms were coagulase positive

S. chromogenes and as expected had unique STs (ST58 and ST59). They were single locus variants (slvs) of each other and were very divergent from other STs as shown by phylogenetic analysis (Figure 4-2). Out of 22 STs identified in the isolates from Belgium, 9 different STs had at least an isolate from both teat skin and a cow quarter milk sample. It is unknown whether these were from independent cows or the same cows.

4.4.2 Identification of clonal complexes (CCs)

The strain types were grouped into clonal complexes using the eBurst software as previously described (Feil et al., 2004). Most STs clustered in four major clonal complexes including, CC1 (n=12, number of STs), CC6 (n=9), CC15 (n=5), and CC62 (n=7) with the predicted founder or ancestral STs being ST1, ST6, ST15, and, ST62 respectively (Figure 4-

1). The number of single locus variants (slv) differed, with CC1 having the highest number

(n=9), followed by CC6 (n=5), while CC15 and CC62 each had three slvs. Three ST pairs were single locus variants to each other: ST58/ST59, ST46/57, and ST17/ST37. The remaining STs were singletons (n=23). Two environmental isolates from Vermont, ST29 and

ST30, a double locus variant (dlv) and slv of ST6 respectively, belonged to CC6. Among the

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STs exclusively isolated from cow skin associated sources in Vermont, ST10 and ST54 belonged to CC6, the remaining STs were singletons, ST26, ST61, and ST55. ST1, ST2 in

CC1, ST6 in CC6, ST25 (singleton) and ST17 were isolated on teat or cow skin as well as infected cow quarters but not necessarily from the same cow.

4.4.3 Prevalence of the blaZ and mecA genes

All isolates were PCR screened for presence of blaZ and mecA genes. Only 33.9%

(n=21) of the strain types had at least one isolate that was blaZ PCR positive. All isolates were mecA negative. Overall 21.6% (n=54) of the isolates were blaZ positive (Table 4-1). In a mixed logistic regression model, source and strain type were significant predictors of blaZ gene carriage. For instance, ST10 and STI3 more often carried the blaZ gene compared to

ST1, one of the most prevalent STs (p<0.05). In addition, all five isolates of ST51 and ST55 were blaZ positive. Other minor STs, that had a blaZ positive isolate included ST4, ST9,

ST14, ST19, ST27, ST37, ST45, ST46, ST53, ST54, and ST61. Source was found to be a significant predictor for the blaZ gene and isolates from teat skin and extramammary cow skin were more likely to be blaZ positive than isolates from cow quarter milk samples (p <0.05).

4.5 Discussion

4.5.1 MLST strain types geographical distribution

Staphylococcus chromogenes is an important bacterium in the dairy sector. Its epidemiology and evolutionary biology is not entirely clear. This has been mainly due to the absence of unambiguous strain typing technique like MLST. In this study, a novel MLST scheme was used to understand the local and global epidemiology of S. chromogenes. All

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isolates were typeable, which was consistent with other MLST schemes for other pathogens, for instance S. aureus (Smith et al., 2005a). The discriminatory power (Simpson’s index of diversity), the ability of a typing method to distinguish between two unrelated strains, was comparable to other studies where MLST was used (Johnson et al., 2007) and to PFGE

(Rajala-Schultz et al., 2009).

Geographical strain type specificity was evident, as only five strain types were shared between the isolates from the two countries (United States and Belgium). Interestingly, among the shared STs, ST1 and ST6 were predominantly isolated from cases of IMI in USA, but not in Belgium. Most S. chromogenes IMI in Belgium was caused by ST28, which is in the same clonal group as ST6 (slv). However, an unequal number of isolates analyzed between the two countries might have biased the data. This geographic effect has been noticed previously in a S. aureus intercontinental study and it was hypothesized that geographic strain specificity is due to differences is selection pressures exposed to the bacteria that tend to drive evolution (Smith et al., 2005b). This could be a wide spread phenomenon in various pathogens including S. chromogenes. We identified four lineages or CCs including CC1, CC6,

CC15, and CC62 and most Belgium STs only clustered into CC1 and CC6 (Table 4-2). This may suggest that ST1 and ST6, the predicted ancestral strains of those lineages, are wide spread globally and their diversification gave rise to new strains in other geographic areas. As more studies start using this MLST scheme, more data will corroborate this speculation.

4.5.2 Strain types niche specificity

MLST revealed ST specificity in various niches. Strain types from pigs and environment were unique from those in cow milk. Strain types from teat skin or cow skin 149

were infrequently isolated from cows with IMI on the same farm. However, skin isolates were not necessarily from the same cows with S. chromogenes IMI, future studies can be target specific, with skin sampling of S. chromogenes infected cows. It is hard to draw conclusions on whether the teat or cow skin is the source of strains causing IMI. Surprisingly, the three cows on one Vermont farm, which were colonized by S. chromogenes on the teat skin, hock or perineum, were infected by S. aureus in at least one quarter, but did not have evidence of S. chromogenes IMI. On one of the three cows, five different STs were isolated, including ST1, one of the predominant causes of IMI. This suggests that cow skin can harbor multiple S. chromogenes strains, some of which might be pathogenic and others just mere commensals. It is unclear whether this observation is driven by the presence of S. aureus. Recent work in our lab demonstrated in vitro growth inhibition of S. chromogenes by S. aureus but not the opposite (Bachmann et al, unpublished). This is contrary to previous work that showed some

S. chromogenes isolates from teat skin having an in vitro growth inhibitory effect against S. aureus and other major pathogens (De Vliegher et al., 2004). In addition, cow quarters with teat apex S. chromogenes colonization were significantly less likely to have SCC >200, 000 cells/mL after calving (De Vliegher et al., 2003). This discrepancy is likely due to S. chromogenes genetic heterogeneity, with some strains having unique behavior. In fact, although, there were a few predominant strains from cow quarter milk, a lot of other minor strain types were isolated from cow quarter milk. Inclusion of unambiguous strain typing techniques like the one described in this chapter in future studies will help improve the understanding of the strain dependent aspects of these bacterial interactions.

The numbers of distinct strain types causing IMI on five Vermont farms that were

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sampled in a cross-sectional study was variable with two farms having 7 STs and other farms with 2-4 distinct STs causing IMI. This differential heterogeneity within farms may suggest two modes of S. chromogenes transmission; a contagious and an environmental mode. Within farm heterogeneity has been noticed in studies where isolates were typed with PFGE

(Gillespie et al., 2009, Rajala-Schultz et al., 2009). This could be due to varying farm management practices that may prevent contagious transmission and drive environmental transmission, even though S. chromogenes is extremely rare in the environment. This was similarly hypothesized with S. aureus IMI infections (Larsen et al., 2000, Smith et al., 2005a).

4.5.3 Phylogenetic analysis

Phylogenetic analysis revealed that most STs clustered together (Figure 4-2), with the dominant STs from cow skin (ST10 and ST55) clustering with milk associated STs. ST58 and

ST59 were a clear out-group and were very divergent from the rest of STs. These divergent

STs were isolated in bulk tank milk and clotted blood plasma. This is the first report of S. chromogenes strains that can clot blood plasma in USA. Recently, a paper was published in

Brazil elucidating identification of S. chromogenes strains that clotted blood plasma. These strains were isolated from Buffalo milk with cases of subclinical mastitis (Dos Santos et al.,

2016). This may not be surprising since S. chromogenes is closely related to some coagulase positive or coagulase variable Staphylococcus species e.g S. hyicus (Becker et al., 2014).

Whether this phenotype in S. chromogenes is relevant for S. chromogenes pathogenesis and virulence need to be elucidated in future studies. The three-coagulase positive isolates were from the bulk tank milk samples not part of the five farms, which were whole herd sampled, and unfortunately, their true source is unknown. The identification of coagulase positive

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strains in CNS may lead to misidentification of species (Taponen et al., 2012), especially in laboratories that rely on coagulase test for S. aureus identification. This emphasizes the need to have clear definitive species identification.

4.5.4 BlaZ and mecA genes

All isolates were mecA gene negative, which is consistent with many studies that show low or no carriage of the gene in S. chromogenes (Sampimon et al., 2011, Frey et al.,

2013, Xu et al., 2015). MecA, however, is more prevalent in CNS species that are not normally causative agents of IMI and are commonly isolated from the environment. These

CNS species include; S. sciuri, S. fleurettii, S. vitulinus (Vanderhaeghen et al., 2013, Xu et al.,

2015), but other CNS species may rarely carry the gene. It has been hypothesized that S. fleurettii is the likely origin of mecA gene (Tsubakishita et al., 2010).

In this study, the blaZ gene was detected in 21.6% (n=54) of the isolates.

Surprisingly, the blaZ gene was more often associated with STs from teat skin (ST10, ST55) compared to STs that were common cause of IMI (ST1 and ST6). This may suggest that the strains’ unique genetic characteristics rather than source of isolates as the major predictor of the gene carriage. Strain specificity for carriage of the blaZ gene was also observed in S. aureus with ST8 and ST25 more often carrying the blaZ gene (Barlow et al., 2013). This demonstrates the heterogeneous nature of pathogens and emphasizes the need for molecular strain typing. Surprisingly, STs that commonly caused IMI were least likely to carry the blaZ gene given the antibiotic selection pressure they’re likely to get exposed to compared to strains colonizing the skin. Carriage of the blaZ gene seems to be driven by the pathogen’s inherent genetic characteristics rather than exposure to antibiotics. 152

4.6 Conclusions

The novel MLST scheme can be used to differentiate between S. chromogenes strains from diverse niches or geographic areas. This work revealed geographic and niche strain type specificity with ST1 and ST6 the predominant cause of IMI in USA, and ST28 in

Belgium. The variability of strain type diversity within farms suggests both an environmental and contagious mode of transmission but this need more exploration in future studies.

Although, some STs causing IMI were found on teat or cow skin, it’s hard to draw conclusion on whether teat or cow skin is the source of IMI strains because, teat or cow skin samples were not necessarily from S. chromogenes infected cows. Skin sampling infected cows in future studies will shed light to the source of strains causing IMI. Carriage of the blaZ gene was associated with strains from cow or teat skin compared to milk strains. This work laid a foundation to further study transmission dynamics, virulence, antimicrobial resistance gene carriage, and evolution of S. chromogenes at strain type level using MLST.

4.7 Acknowledgments

This study was supported by UVM food systems grant, USDA Hatch grant and North East

SARE grant no. GNE14-087. We gratefully acknowledge University of Vermont, and YALE core facilities for all the sequencing work.

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Vesterholm-Nielsen, M., M. Olhom Larsen, J. Elmerdahl Olsen, and F. Moller Aarestrup. 1999. Occurrence of the blaZ gene in penicillin resistant Staphylococcus aureus isolated from bovine mastitis in Denmark. Acta Vet. Scand. 40(3):279-286.

Xu, J., X. Tan, X. Zhang, X. Xia, and H. Sun. 2015. The diversities of staphylococcal species, virulence and antibiotic resistance genes in the subclinical mastitis milk from a single Chinese cow herd. Microb. Pathog. 88:29-38.

Zadoks, R. N. and J. L. Watts. 2009. Species identification of coagulase-negative staphylococci: genotyping is superior to phenotyping. Vet. Microbiol. 134(1-2):20-28.

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Table 4-1: Prevalence of blaZ gene presence within different strain types ST n BlaZ Source Country 1 37 2 Milk USA,-Belgium 4 1 1 Milk USA 5 7 2 Milk USA 6 38 5 Milk/TS USA,-Belgium 9 1 1 Milk USA 10 13 8 Cow-skin USA 13 5 4 Milk USA 14 1 1 Milk USA 17 13 3 Milk/SC USA 19 2 2 Milk USA 27 1 1 Milk USA 28 11 3 Milk/TS Belgium 37 2 2 Milk/TS Belgium 45 1 1 Milk Belgium 46 2 2 Milk Belgium 48 4 2 Milk USA 51 5 5 Milk USA 53 1 1 Milk USA 54 1 1 TS USA 55 5 5 TS/CS USA 61 2 2 TS/SC USA

No isolate was positive for blaZ gene in strain types not shown in the table. n; total number of isolates, blaZ; number of isolates that were blaZ PCR positive. Source and country; origin of the blaZ positive isolates; Milk included quarter milk, cheese, bulk tank milk and milking equipment, TS; teat skin, SC; streak canal, CS; extrammamary cow skin (hock skin and perineum)

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Figure 4-1: eBurst analysis of S. chromogenes strain types Yellow dots represent different strain types, blue represents predicted founder or ancestral ST of a group or clonal complex. Strain types shared between USA and Belgium isolates are colored cyan; STs unique to USA and Belgium isolates are colored black and green respectively. The size of the dots is commensurate to number of isolates of the representative strain type.

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Figure 4-2: Dendrogram of the S. chromogenes STs

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A B

Figure 4-3: Distribution of top four predominant strain types in different niches on five farms where whole herdd quarter milk sampling was done in Vermont (A) and number of strain types causing IMI (B) per farm

ST1 (CC1) and ST6 (CC6) were more associated with quarter milk isolates. n= number of S. chromogenes IMI cases per farm.

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Table 4-2: Clonal complexes, strain types, and number of isolates in each country and niche of isolation

!!!!!!!!!!!!!!!!!!!!!!!!!!!No.!of!isolates ST n CC Farms !!!!UNITED!STATES !!!!!!!!!!!!Belgium Milk TS BT CS ENV Pigs Milk TS 1 37 1 7 26 3 6 1 2 5 1 2 4 1 3 1 1 1 1 4 1 1 1 1 5 7 1 1 7 6 38 6 5 31 1 4 1 1 7 1 1 1 1 8 1 1 1 1 9 1 1 1 1 10 13 6 1 5 8 11 4 1 1 4 12 1 1 1 1 13 5 S 1 3 2 14 1 15 1 1 15 9 15 3 7 2 16 1 15 1 1 17 13 Minor!clone 3 10 2 1 18 2 Singleton 2 1 1 19 2 Singleton 1 2 20 3 Singleton 1 1 2 21 2 62 1 1 2 22 1 Singleton 1 1 23 1 Singleton 1 1 24 1 Singleton 1 1 25 4 Singleton 2 3 1 26 5 Singleton 2 3 2 27 1 1 1 1 28 11 6 1 7 4 29 2 6 2 1 1 30 5 6 2 1 2 2 31 1 6 1 1 32 2 62 1 1 1 33 1 62 1 1 34 1 1 1 1 35 1 Singleton 1 1 36 1 Minor!clone 1 1 37 2 Singleton 1 1 1 38 4 62 1 3 1 39 3 Singleton 1 2 1 40 1 Singleton 1 1 41 1 Singleton 1 1 42 2 Singleton 1 1 1 43 3 Singleton 1 2 1 44 2 Singleton 1 2 45 1 6 1 1 46 2 Minor!clone 1 2 47 1 62 1 1 48 4 62 3 4 49 1 Singleton 1 1 50 1 15 1 1 51 5 6 1 2 3 52 4 Singleton 1 1 53 1 Singleton 1 1 54 1 6 1 1 55 5 Singleton 1 2 3 56 3 15 1 2 1 57 1 Minor!clone 1 58 1 Minor!clone 1 1 59 2 Minor!clone 1 2 60 1 Singleton 1 1 61 2 Singleton 1 2 62 1 62 1 1

Abbreviations. CC; clonal complex, TS; teat skin, BT; bulk tank milk and milking equipment, CS; extrammamary cow skin (hock, perineum), Env; environment. Milk source included; cow quarter milk and cannulated milk.

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Table 4-3: Allelic profile of 62 S. chromogenes STs

Allelic profile (allele number)

ST arcC HutU FumC dnaj glp menF pta 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 3 3 1 1 1 1 1 1 6 4 1 1 1 1 1 1 8 5 1 1 1 1 4 1 1 6 1 1 1 3 2 1 2 7 1 1 1 5 4 1 1 8 1 1 1 8 1 1 1 9 1 1 1 11 1 1 1 10 1 1 5 3 2 1 2 11 1 2 1 1 1 1 1 12 1 6 1 1 1 1 3 13 2 3 3 2 1 1 2 14 3 1 1 1 3 3 2 15 3 1 1 1 3 5 2 16 3 1 1 1 3 6 2 17 3 1 1 1 10 1 2 18 4 4 4 4 5 4 4 19 5 1 1 1 6 5 2 20 6 1 6 2 7 1 2 21 7 1 6 1 3 1 5 22 8 5 14 6 3 8 2 23 9 1 8 7 8 7 7 24 10 1 6 1 9 1 5 25 11 7 2 9 11 2 4 26 12 8 7 10 12 1 2 27 13 1 1 1 1 1 1 29 1 1 1 1 2 9 2 30 1 1 1 3 15 1 2 47 1 1 1 1 3 1 5 48 1 1 6 1 3 1 5 49 1 14 1 22 1 1 14 50 3 13 1 1 3 5 2 51 6 1 1 1 2 1 2 52 6 1 12 1 19 11 12 53 8 1 7 14 3 1 5 54 18 1 5 3 2 1 2 55 18 12 7 21 20 1 13 56 22 1 1 1 3 6 2 57 23 1 6 3 16 1 1 58 24 10 15 19 18 10 11 59 25 10 15 19 18 10 11 60 26 11 16 20 11 12 4 61 12 8 7 23 3 1 15 62 1 1 6 1 3 1 2 ST; strain/sequence type, pta; phosphate actytransferase, glpF; glycerol kinase, dnaJ; chaperone protein; hutU; urocanate kinase; arcC; carbamate kinase; FumC; fumarate hydratase, menF; isochorismate synthase

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CHAPTER 5 : ANTIBIOTIC RESISTANCE AND BIOFILM

FORMATION OF STAPHYLOCOCCI ISOLATED FROM SELECTED

DAIRY FARMS IN VERMONT

Robert Mugabi, Samantha D’Amico, Helen Keen, Caity Walsh, Jimmy Aruzamen, John

Barlow*

Department of Animal and Veterinary Sciences, University of Vermont, Burlington,

Vermont

Email: [email protected]

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5.1 Abstract

Staphylococci are among the leading cause of mastitis in dairy cattle. Antibiotic resistance and biofilm formation are believed to be important phenotypes that contribute to mastitis treatment failures. The objective of this project was to elucidate antibiotic susceptibility and biofilm formation of staphylococci isolated from five dairy farms producing farmstead cheese in Vermont. A total of 61 S. aureus and 780 non-aureus staphylococci or coagulase negative staphylococci (CNS) isolates from various sources were tested for biofilm formation and antibiotic susceptibility. All isolated were screened for the presence of the blaZ and mecA genes, and antibiotic susceptibility was done using both disk diffusion and micro-dilution methods. In addition, biofilm formation was evaluated using two-plate surface types and S. aureus isolates were screened for biofilm- associated genes, including the icaA, icaD, and bap genes. In S. aureus, resistance was mainly detected with suphadimethoxine (39.3%) and penicillin (19.4%). Within the non- aureus staphylococci, resistance to suphadimethoxine (29.5%), penicillin (8.8%), tetracycline (8.7%), and pirlimycin (7.5%), and erythromycin (6.3%) were the top common resistances. The mecA gene was detected in five non-aureus species; S. epidermidis, S. hominis, S. fleurettii, S. vitulinus, and S. sciuri, whereas the blaZ gene was detected in fourteen different species. The mecA gene was significantly associated with the environment and cow skin isolates while the blaZ gene was more significantly associated with human isolates than isolates from cow milk (p<0.05). blaZ or mecA gene presence did not correlate with phenotypic resistance for most CNS isolates. S. xylosus and S. sp. 020902 had high biofilm biomass compared to S. aureus, whereas, S.

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chromogenes, and S. haemolyticus showed heterogeneity in the biofilm phenotype.

Predominance of a species did not seem to correlate with biofilm phenotype for most species.

Key words; Dairy cattle, Staphylococci, Antibiotics, Mastitis, Biofilm

5.2 Introduction

Staphylococci are the common cause of bovine intrammamary infections (IMI) and mastitis, an inflammation of the mammary gland. Among this group of bacteria, S. aureus is considered a major mastitis pathogen as it induces severe inflammation compared to coagulase-negative staphylococci (CNS) (Schukken et al., 1999). However, some CNS species have been shown to induce inflammation comparable to that of S. aureus (Supre et al., 2011) and have been given much attention as emerging mastitis pathogens (Pyorala and Taponen, 2009).

Mastitis is the number one reason for antibiotic use on dairy farms during dry cow therapy or treatment of clinical mastitis cases (Kaneene and Miller, 1992, Saini et al.,

2012). Although, this is, excessive antibiotic use in animals is believed to drive antimicrobial resistance in farm animals (van den Bogaard et al., 2001; Rajala-Schultz et al., 2009). This is not only an animal health problem but also a public health hazard as some resistant bacteria can be transmitted from animals to humans directly or through consumption of dairy by-products like milk and cheese (Fey et al., 2000). The major concern is the presence of multidrug resistant bacteria, for instance, methicillin-resistant

S. aureus (MRSA) and CNS (MRCNS). Methicillin-resistant bacteria are usually resistant to all β-lactam antibiotics and tend to be resistant to other classes of antibiotics like

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aminoglycosides and macrolides (Woodford, 2005). β-lactam antibiotics act by binding to

Penicillin Binding Proteins (PBPs), which are important in the bacterial cell wall peptidoglycan biosynthesis. The blaZ and mecA genes play a significant role in β-lactam resistance among the staphylococci. The blaZ gene encodes a penicillinase, which is a lactamase that hydrolyzes the β-lactam antibiotics rendering them ineffective (Lowy,

2003). The mecA gene encodes an altered penicillin binding protein (PBP2a) that has lower affinity for β-lactam antibiotics, allowing continued cell wall biosynthesis in the presence of otherwise inhibitory concentrations of antimicrobials. Other mecA homologues have been discovered recently, for example, mecC in S. aureus (Garcia-

Alvarez et al., 2011), mecB and mecD in Macrococcus caseolyticus (Gomez-Sanz et al.,

2015; Schwendener et al., 2017).

The mecA gene is carried on a mobile genetic element called staphylococcal cassette chromosome mec (SCCmec) (Lowy, 2003). Staphylococci can exchange this cassette allowing the spread of the mecA gene to other bacteria. For instance; the mecA gene in CNS can be transferred to more pathogenic bacteria like S. aureus (Wielders et al., 2001, Berglund and Soderquist, 2008; Bloemendaal et al., 2010). It is believed that S. fleuretti is the origin of mecA gene (Tsubakishita et al., 2010b). Knowing antibiotic susceptibilities of staphylococci is important in order to monitor the emerging resistant bacterial strains or clones. Although in vitro data does not guarantee treatment success, antibiotic susceptibility testing can guide clinicians on treatment options as treatment failures are partly due to antibiotic resistant bacteria (Barkema et al., 2006). While most studies use either disk diffusion or micro-dilution for antibiotic resistance testing, in this

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study, we evaluated both methods whenever possible. Their specificities and sensitivities on diverse Staphylococcus species was evaluated with a major focus on β-lactam antibiotics

In addition to developing antibiotic resistance, the survival of staphylococci is also enhanced by their ability to form a biofilm. A biofilm is a community of bacteria enclosed in self-produced polymeric matrix (Fox et al., 2005, Melchior et al., 2006).

Biofilm facilitates the adhesion of bacteria to the mammary gland epithelium and host immune evasion, which may promote development of chronic infections (Baselga et al.,

1993; Cucarella et al., 2004). The community growth phenotype (biofilm) protects the bacterial cells from antibiotics, disinfectants, environmental stressors and phagocytosis.

The exopolysaccharide matrix acts as a barrier for antibiotic penetration or phagocytosis, which contributes to the survival of the bacteria within the host (Melchior et al, 2006).

Antibiotic resistance is further enhanced by the reduced metabolism of the innermost cells within the biofilm. Most antibiotics are effective on actively-dividing and metabolizing cells (Vasudevan et al., 2003).

Staphylococci biofilm formation is a three-stage process, which begins with the bacterial cells adhering to a surface mediated by the capsular polysaccharides and other cell surface proteins (Otto, 2009). Division and multiplication follow, forming a multilayered mushroom shaped biofilm characterized by production of polysaccharide intercellular adhesin (PIA), and eventually dispersal. The intercellular adhesin (ica) operon consists of icaADB and C genes which encode proteins/enzymes for PIA biosynthesis, icaR is transcribed divergently from icaADBC, and is a negative regulator

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of icaADBC expression (Cramton et al., 1999). The icaA and icaD genes are the major genes associated with biofilm formation within the locus. The activity of icaA gene product is enhanced when icaA and icaD genes are co-expressed. The icaA gene encodes

N-acetylglucosaminotranferase, an enzyme used in the biosynthesis of acetylglucosaminoglycan oligomers from UDP-N-acetylglucosamine. N- acetylglucosaminoglycan oligomers are the building blocks of PIA, which mediates cell- to-cell adhesion (Arciola et al., 2001, Otto, 2009). However, other ica independent biofilm formation mechanisms in staphylococci do exist and have been reviewed recently

(Foster et al., 2014). Quantification of biofilm formation in staphylococci has been done more often using an in vitro micro-titer assay. Most studies have used tissue culture treated plates as it is believed that bacteria adhere better on treated hydrophilic plates compared to untreated hydrophobic plates (Kennedy and O'Gara, 2004). However, several papers do not mention even the plate type used (Ploneczka-Janeczko et al., 2014;

Szczuka et al., 2015). It is not entirely clear to what extent surface type impacts biofilm formation for staphylococci from dairy farms. In this study, biofilm forming potential of the staphylococci from various niches was analyzed on tissue culture treated plates. The objective of this study was to quantify biofilm in staphylococci with a major goal to understand whether biofilm phenotype may contribute to the predominance of a given species on farms. The second objective was to ascertain antibiotic susceptibility of these bacteria as well species that might be potential reservoirs of mecA gene.

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5.3 Materials and Methods

5.3.1 Source of Isolates

A total of 841 staphylococci were used in this study and were isolated from various sources/niches on five different dairy farms making farmstead cheese in Vermont

(Figure 5-1). This fraction of isolates was part of a larger study to understand the epidemiology of staphylococci on the five farms (Chapter 3). The isolates were stratified by species, farm, and source. All very low prevalent species isolates and S. aureus were selected. Representative isolates were selected by farm and source for high prevalent species e.g. S. haemolyticus (Chapter 3). All non-aureus staphylococci (CNS) isolates were definitively speciated using tuf gene sequencing as described previously (Heikens et al., 2005) and S. aureus, using thermonuclease gene PCR amplification (Brakstad et al.,

1992).

5.3.2 Antibiotic Susceptibility Testing

Antibiotic susceptibility testing was performed using both the agar disk diffusion and broth micro-dilution minimum inhibitory concentration (MIC; Sensititre, Trek

Diagnostic Systems, Oakwood Village, OH) methods following Clinical Laboratory

Standards Institute (CLSI, 2008, 2013) protocols as previously described (Barlow et al.,

2013). Two ATCC control strains were used as quality controls, ATCC 25923 (S. aureus) was used as a control for the agar disk diffusion test and ATCC 29213 (S. aureus) was used as a control for the broth micro-dilution MIC test. Susceptibility testing for the antimicrobials ampicillin, cephalothin, ceftiofur, erythromycin, oxacillin, pirlimycin,

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penicillin, and tetracycline were conducted using both the broth micro-dilution minimum inhibitory concentration and disk diffusion methods. For penicillin/novobiocin and sulphadimethoxine, only MIC was done, as there were no commercially available disks.

Antibiotic susceptibility to amoxicillin/clavulanic acid, cefoxitin, clindamycin, enrofloxacin, gentamycin, lincomycin, and vancomycin, only used the disk diffusion method because these drugs were not present on the MIC plates used. The antibiotics in this panel were selected because they are commonly used in dairy production systems, with the exception of oxacillin and cefoxitin, which are used to screen for methicillin resistance. Where available, Clinical and Laboratory Standards Institute (CLSI) break points were used to define isolates as resistant, intermediate or susceptible. We recognized that clinical antimicrobial susceptibility breakpoints are unknown for some antimicrobials that are used to treat cases of mastitis caused by most CNS species.

Therefore, the raw in vitro susceptibility data of some antimicrobials were analyzed with no inference to clinical response.

If isolates were determined to be erythromycin resistant using the disk diffusion method, they were also tested for inducible lincosamide resistance. For this assay, an erythromycin disk was placed in the center of the plate with the lincosamide disks placed

15mm away. The lincosamides used were clindamycin, lincomycin, and pirlimycin.

Inducible resistance was determined to be present if flattening of the zone diameter occurred adjacent to the erythromycin disk, called a D-zone due to the shape produced

(Prabhu et al., 2011).

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5.3.3 Genetic screening for antibiotic resistance markers

Polymerase chain reaction-based amplification of the blaZ and mecA gene fragments was used to screen for carriage of these antimicrobial resistance determinants

(Barlow et al., 2013) with slight modification. The multiplex PCR was modified for screening of CNS isolates by inclusion of the tuf gene primers to act as a sample amplification control for blaZ, and mecA amplification. Staphylococcus aureus ATCC strains 33591 (for mecA), 25983 (S. aureus nuc or tuf gene), and 29213 (blaZ) were used as positive controls to develop the amplification methods. The primers used were; 5’-

GCC AGT TGA GGA CGT ATT CT-3’ and TufR 5’-CCA TTT CAG TAC CTT CTG

GTA A-3’ (Chapter 3), BlaZF 5’-AAG AGA TTT GCC TAT GCT TC-3’, BlaZR 5’-

GCT TGACCA CTT TTA TCA GC-3’, mecAF 5’-AAC AGG TGA ATT ATT AGC

ACT TGT AAG-3’, mecAR 5’-ATT GCT GTT AAT ATT TTT TGA GTT GAA-3’, and the tuf gene primers previously listed (Vesterholm-Nielsen et al., 1999; Martineau et al., 2000). Each PCR reaction contained 5µl of 10x Taq buffer (New England BioLabs),

3µl of 50mM MgCl2, 2µl of 10µM of each tuf and mecA primer, 2.5µl of 10µM of each blaZ primer, 1µl of 10mM DNTPs, 0.4µl of 5,000 units/mL Taq polymerase (New

England BioLabs), and 2.5µl of each template. Thermocycler conditions included an initial elongation for 15 minutes at 950C, then 34 cycles of 30 seconds at 940C, 30 seconds at 550C, 30 seconds at 720C, and a final 1cycle elongation for 10 minutes at

720C.

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5.3.4 Biofilm genotyping and in vitro assay

Staphylococcus aureus isolates were screened for biofilm-associated genes, polysaccharide intercellular adhesin (PIA) encoded by the ica gene operon (e.g. icaA and icaD), and biofilm associated protein (bap) by PCR using previously published primers, icaA-F 3’-CCT AAC TAA CGA AAG GTA G-5’, icaA-R 5’-AAG ATA TAG CGA

TAA GTGC-3’, icaD-F 3’-AAA CGT AAG AGA GGT GG-5’, icaD-R 5’-GGC AAT

ATG ATC AAG ATA C-3’ (Simojoki et al., 2012), and bap-F: 5’-

CCCTATATCGAAGGTGTAGAATTGCAC 3’ bap-R

5’GCTGTTGAAGTTAATACTGTACCTGC3’ (Cucarella et al., 2001). PCR reaction conditions were as previously reported, with one modification, the annealing temperature for the bap PCR reaction was 55°C. Presence of PCR products (icaA 315bp; icaD 381bp, and bap 971bp) was determined by visualization of ethidium bromide stained 1.5% agarose gels 1 hour after electrophoresis. Positive DNA control strains S. xylosus ATCC

29971 (bap) and S. aureus ATCC 25923 (ica genes) were included in each set of PCR reactions.

All isolates were tested in a micro-titer plate-based biofilm assay (Tremblay et al.,

2013) with minor modifications and including a comparison of biofilm formation on two distinct (tissue culture treated and untreated) micro-titer polystyrene plates. Isolates were recovered from frozen stock solution by growth overnight on trypticase soy agar (TSA), with plates examined for purity at 48 hours. A none biofilm producer control strain, S. epidermidis ATCC 12228, and a strong biofilm producer control strain, S. epidermidis

ATCC 35984 were included in the assays. A single colony from the stock culture TSA

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plate was transferred to tryptic soy broth (TSB), grown overnight. The overnight culture was diluted 1:200 in TSB supplemented with 0.25% glucose and was transferred a 96 well polystyrene flat-bottomed tissue-culture-treated plate (#3595, Corning, NY, USA) in triplicate (200 µL per well). The plates were incubated for 24hrs at 370C without agitation. After incubation, the broth was removed from each well, the plates were washed three times with phosphate buffered saline (PBS) and air-dried at room temperature for at least 2 hours. The dried plate was stained with 0.4% (w/v) safranin solution for 10 minutes, washed three times with double distilled water, and air-dried at room temperature for at least 2hrs. The stained biofilms were de-stained using 95% ethanol for 15 minutes. Absorbance at 490nm was measured using a plate reader

(Synergy HT, BioTek Instruments, Inc.). The experiments using each type of plate were repeated three times on different days. Each plate contained three blank wells (un- inoculated medium), and the corrected absorbance value for each sample-well was calculated by subtracting the mean absorbance of the blank wells. The weak and strong biofilm producer control strains were each included in triplicate on every plate. The mean of the nine blank-corrected absorbance values for each isolate for each type of plate was recorded as the final result. Isolates were classified on their ability to form a biofilm using the following categories from (Christensen et al., 1985, Stepanovic et al., 2000),

- Negative = obsOD < ODc

- Weak = ODc> obsOD<2ODc

- Moderate 2ODc > obsOD < 4ODc

- Strong = obsOD>4ODc >,

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where OD = Optical density, ODc = mean OD + 3 x SD of negative control strain wells, and obsOD = the mean of all blank corrected absorbance values. The ability to form biofilm was classified as Negative (obsOD < 0.15), Weak (0.15> obsOD<0.3), Moderate

(0.3 > obsOD < 0.6), Strong (obsOD>0.6) on treated plates

5.3.5 Statistical analysis

To determine the how each staphylococcus species forms biofilm, we used in a linear mixed model using STATA version 13.1. for statistical analysis. The biofilm ODs were natural log transformed before the analysis (lnOD) because they were not normally distributed. The different staphylococci species, (independent variables) were treated as categorical variables while lnOD (dependent variable) was treated as continuous variable.

Species with ≤10 counts (Table 5-1) were excluded in the statistical analysis and the graphical presentation of the data for biofilm leaving a total of 789 isolates. One-way

Anova with a Tukey’s adjustment for multiple comparisons was used to compare differences in mean ODs of three common species (S. aureus, S. chromogenes, and S. haemolyticus) isolated from cow quarter milk. A mixed logistic model was used to determine the association between mecA or blaZ carriage and source of isolates.

5.4 Results

5.4.1 Detection of β-lactam antibiotic resistance genes

All staphylococci in the study were PCR screened for the presence of two important genes that encode β-lactam antibiotic resistance (mecA and blaZ). Of the 61 S. aureus isolates 11 isolates (18.03%) were blaZ positive (Figure 5-1) with 8 of these

(72.73%) from human sources. The mecA gene was not detected in any S. aureus isolates 175

regardless of the source. For the non-aureus staphylococci (n=780), 138 isolates (17.2%) were blaZ gene positive representing 14 different non-aureus staphylococci species

(Figure 5-1). Consistent with S. aureus, blaZ gene presence was associated with isolates from humans rather than isolates from cow quarter milk (p=0.004). Forty-two non-aureus staphylococci isolates (5.4%) were mecA positive. The mecA gene was detected in five species including, S. epidermidis, S. sciuri, S. hominis, S. fleurettii, and S. vitulinus. The mecA gene was detected in combination with blaZ gene in 6 (14.3%) of the mecA positive isolates. The six isolates were S. epidermidis (n=2), S. hominis (n=2), and S. sciuri (n=2).

It is noteworthy that all S. fleurettii isolates were mecA positive, and were isolated from a single farm in various niches (Table 5-1). The mecA gene was significantly associated with isolates from the environment and extramammary cow skin (p<0.05) compared to cow quarter milk isolates.

5.4.2 Antimicrobial Susceptibility Testing

All S. aureus isolates were susceptible to oxacillin, enrofloxacin, gentamicin, penicillin/novobiocin, enrofloxacin, amoxicillin/clavulanic acid, tetracycline, cephalothin, cefoxitin and ceftiofur (Table 5-2 & 5-3) using either disk or micro-dilution

MIC tests. S. aureus isolates showed detectable resistance to five antimicrobials; erythromycin (9.8%), penicillin (19.4%), ampicillin (14.8%), pirlimycin (1.6%) and sulfadimethoxine (39.3%) (Table 5-2). No lincomycin and vancomycin disk diffusion

CLSI breakpoints, so data for these two drugs is not reported. Close to 40% of S. aureus were not inhibited at the highest concentration of sulfadimethoxine (Table 5-2). Six

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(9.8%) S. aureus isolates were resistant to two different classes of antibiotics (Penicillin and Erythromycin), and were all isolated from humans.

At least 99% of the non-aureus staphylococci were susceptible to penicillin/novobiocin, amoxicillin/clavulanic acid, cephalothin, ceftiofur, gentamicin, and enrofloxacin, which was relatively consistent with the findings for S. aureus. Non-aureus isolates were mainly resistant to ampicillin (3.8%), penicillin (8.8%), erythromycin

(6.3%), tetracycline (8.7%), pirlimycin (7.5%), and sulfadimethoxine (29.5%) based on

MIC data. Most isolates (34.2%) had a zone of ≤10mm for lincomycin, suggesting high resistance but no breakpoint available (CLSI 2013) to make definitive conclusions. For some drugs, CLSI, 2008 breakpoints were used, as was done recently by Ruegg and colleagues (Ruegg et al., 2015).

Some CNS isolates showed discordance for antimicrobials tested on both MIC and Disk diffusion. Data shown for these antimicrobials are based on MIC. The discordance was commonly seen with penicillin and ampicillin, for instance, with disk diffusion; the resistance to ampicillin was 14%, penicillin 9.6%, Pirlimycin 7.6%, erythromycin 6.7%, and tetracycline 8.7%. While for MIC, the resistances were; ampicillin (3.8%), penicillin (8.8%), pirlimycin (7.5%), erythromycin (6.3%), tetracycline (8.7%). One S. pseudintermedius isolate from a dog was the only bacterium resistant to 7 antimicrobials; ampicillin, gentamicin, pirlimycin, clindamycin, penicillin, tetracycline and erythromycin. Among the erythromycin resistant isolates, none showed inducible clindamycin resistance as per D-zone test.

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4.4.3 Comparison of phenotypic resistance and presence of β- lactam antibiotic resistance genes

Unlike S. aureus, a number of blaZ or mecA positive non-aureus staphylococci did not correlate with phenotypic resistance (Table 5-4). For instance, 92 (13%) of the penicillin susceptible isolates (n=711) were blaZ positive based on MIC, whereas among the 69 phenotypically resistant isolates, only 47 (68%) were blaZ gene positive. Of the 22 remaining blaZ negative isolates that were phenotypically resistant to penicillin, only 13

(59.1%) isolates were mecA positive. The discordance was also detected with cefoxitin disk and presence of mecA gene (Table 5-4). Thirty-eight (5%) of the phenotypically cefoxitin susceptible isolates (n=768) were mecA positive and only 4 (33%) of the phenotypically resistant isolates (n=12) were mecA positive. Cefoxitin disk is used as a surrogate for methicillin/oxacillin resistance.

5.4.4 Biofilm formation of the staphylococci

Biofilm genotyping was done for only S. aureus as the amplification using the same primers was not successful with the coagulase negative staphylococci. All the S. aureus isolates were icaA and icaD positive but bap negative. S. xylosu, S. epidermidis, and S. sp. 020902 (un-named species), formed a significantly high biofilm biomass compared to S. aureus. However, the biofilm biomass was significantly low in S. auricularis, S. equorum. In the univariate analysis, quarter milk isolates formed significantly high biofilm biomass (p<0.05) compared to isolates from other sources except human and bulk tank associated isolates. When quarter milk isolates were

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analyzed alone, three CNS species S. simulans, S. sp. 020902 and S. chromogenes formed significant biofilm compared to S. aureus (p<0.05).

At the categorical level, 11 (18%) S. aureus isolates were classified as biofilm formers. For the non- aureus staphylococci, 277 (38%) were classified as biofilm formers. More than half of the biofilm forming isolates were either S. chromogenes or S. haemolyticus. It is noteworthy that at least 80% of S. sp. 020902 isolates were classified strong biofilm formers. Staphylococcus aureus did not have any isolates in the strong category, while S. chromogenes and S. haemolyticus (common CNS species in milk) both had isolates classified as strong biofilm formers. We also used One-way ANOVA

Tukey’s test to compare mean differences (biofilm OD) of top three staphylococci isolated from quarter milk i.e, S. aureus, S. chromogenes and S. haemolyticus (Table 5-1).

Staphylococcus chromogenes isolates formed significant biofilms compared to S. aureus and S. haemolyticus (p<0.05), but the mean difference between S. aureus and S. haemolyticus was not statistically significant.

5.5 Discussion

β-lactam antibiotics are the most common antimicrobials used in both humans and animals. In this this study, we focused on β-lactam antibiotic resistance genotyping.

Methicillin resistant staphylococci tend to be resistant to all β-lactam antibiotics as well as other classes of antimicrobials (Archer and Climo, 1994, Woodford, 2005). The mecA gene was detected in 5 species; S. hominis, S. epidermidis, S. sciuri, S. fleuretti, and S. vitulinus suggesting that the gene might be species specific among the coagulase negative staphylococci. Carriage of the mecA gene was associated with isolates from the

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environmental sources and extramammary cow skin. The 5.4% prevalence of mecA gene carriage within non-aureus staphylococci was lower than the prevalence found in Belgian study where both quarter milk and environmental samples were analyzed, but the sample size in that study was small (Piessens et al., 2012). Consistent with this Belgian study, mecA gene was common in S. sciuri, S. fleurettii, and S. epidermidis and was also common in environmental isolates. These results further support the role of the environment as a potential reservoir of bacteria carrying the mecA gene. Recent studies showed these species as common carriers of mecA the gene, but other species may test positive for the gene with relatively low prevalence (Sampimon et al., 2011; Frey et al.,

2013; Xu et al., 2015). Apart from S. epidermidis, none of these species are important mastitis pathogens. However, these species may act as mecA gene reservoirs on farms and transfer the gene to important mastitis and human pathogens like S. aureus through horizontal gene transfer. It has been postulated that S. fleurettii is the origin of mecA gene

(Tsubakishita et al., 2010b). None of S. aureus isolates were mecA positive, which is consistent with the findings of many studies in the United States that show low to zero prevalence of the mecA in S. aureus on dairy farms (Virgin et al., 2009, Haran et al.,

2012, Barlow et al., 2013, Cicconi-Hogan et al., 2014).

Unlike the mecA gene, the blaZ was detected in fourteen different species (Figure

5-1). The blaZ gene carriage was significantly associated with isolates from humans. For instance, 8/11 blaZ positive S. aureus isolates were from humans. From our previous epidemiologic work (Chapter 3), all these eight isolates were known human adapted strain types (ST5, ST30), which was strain typed using multilocus sequence typing

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(MLST). The remaining two isolates were ST8 isolated from a single cow.

Staphylococcus chromogenes and S. haemolyticus were among the top three species isolated from cow quarter milk and had relative number of blaZ positive isolates (Figure

5-1). The blaZ gene does not seem to be associated with specific species as it was detected in 14 different Staphylococcus species unlike mecA gene that was detected only in five species.

Penicillin and ampicillin (β-lactam antibiotics) are among the most used antimicrobials in animals. Discordance between disk diffusion and MIC tests was seen mainly in these drugs, suggesting that the method chosen for detecting bacterial resistance to these drugs is significant. There was discordance between presence of blaZ gene and resistance to penicillin for the CNS compared to S. aureus. This was also consistent with cefoxitin disk phenotypic resistance and presence of mecA gene. No conclusions were drawn from oxacillin MIC data because the MIC plates used did not have the breakpoints for susceptible and resistance phenotypes, ≤0.25 and ≥0.5, for CNS respectively. However, 20 (47.6%) of the mecA positive isolates had an oxacillin MIC of

≥4µg/ml suggesting phenotypic resistance. For oxacillin disk diffusion, 15 (35.7%) of the mecA positive isolates had a zone diameter of ≤10mm, which may suggest resistance but no breakpoint as per CLSI 2013. Even though, this is an under estimation of resistance, it’s clear that oxacillin MIC and disk diffusion methods are better than cefoxitin disk in detecting resistance, where only four (9.5%) of mecA positive isolates were classified as phenotypically resistant based on the CLSI 2013 cefoxitin disk breakpoint for CNS. A sensitivity of 25% using the cefoxitin disk has been previously reported for 150 isolates

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of S. intermedius and S. schleiferi compared to a 97% sensitivity using oxacillin disk

(Bemis et al., 2006). A study using clinical human isolates also demonstrated a lower sensitivitive cefoxitin disk than oxacillin (Perazzi et al., 2006). Staphylococcus sciuri and

Staphylococcus fleurettii isolates that were both mecA gene positive and susceptible to oxacillin have been reported before (Wu et al., 1996; Sampimon et al., 2011). This emphasizes the need to screen isolates for mecA gene in addition to performing in vitro susceptibility assays. The mecA positive but susceptible isolates may revert to a resistance phenotype in vivo jeopardizing treatment and patient recovery.

Using this large data set in this study, we have demonstrated that in vitro methods are not good at detecting β-lactam resistance for staphylococci isolates (especially CNS) with known antimicrobial resistance markers from dairy farm settings. Screening for resistance genes is advisable, isolates with the genes but phenotypically susceptible are considered resistant (Haveri et al., 2005). The discordance might be partly due to poor breakpoints for resistance for CNS, given that they currently have one breakpoint despite their diverse nature and some breakpoints are human derived. Ascribing the same breakpoint for all CNS species is probably inaccurate for this heterogeneous group that contains at least 42 species.

Presence of the β-lactam resistance genes without phenotypic resistance can also be explained by the inability of the genes to be expressed due to mutations within the gene and therefore, no enzyme production (b-lactamases). Using whole genome sequencing, a S. xylosus isolate was found to have a new mecC allotype with a frameshift mutation resulting into a truncated gene product. This isolate was phenotypically

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susceptible to oxacillin and cefoxitin (Harrison et al., 2013). In S. sciuri, the mecA gene homologue (mecA1) is not part of mec gene complex (Couto et al., 2003; Tsubakishita et al., 2010b) and most S. sciuri mecA positive isolates are susceptible to β-lactam antibiotics. Consistent with the above studies, all eleven-mecA positive S. sciuri were susceptible to cefoxitin and had an oxacillin MIC of ≤2. However, in other species, presence of two mecA/ blaZ positive populations (susceptible and resistant), may imply unique genetic makeup of the genes and the staphylococcal cassette chromosome mec

(SCCmec), which houses the mecA gene that affects the expression of these genes. Future work should focus on whole genome sequencing to further elucidate the genetic mechanisms of these discordances.

Some isolates were mecA negative but resistant to cefoxitin (n=8) and four mecA negative isolates had an oxacillin MIC of ≥4µg/ml. These might be false mecA negative isolates if there more mutations in the primer binding sites and the gene cannot be amplified as previously speculated (Haveri et al., 2005; Fowoyo and Ogunbanwo, 2017).

However other genes that may confer methicillin resistance do exist, for instance, we did not screen these isolates for mecC gene, which can also encode methicillin resistance

(Garcia-Alvarez et al., 2011). We did not screen for mecC presence because it has not been detected in bacteria from studies done in the United States (Ganesan et al., 2013).

Some isolates on the other hand, may overproduce beta-lactamases and show oxacillin resistance in absence of the mecA gene (Frey et al., 2013). In our study, however, only one mecA negative but blaZ positive isolate was resistant to cefoxitin. According to Frey and colleagues, 157 phenotypically oxacillin resistant CNS isolates were negative for

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mecA, mecC, and blaZ genes (Frey et al., 2013), suggesting presence of unknown resistance mechanisms yet to be discovered. A better understanding of the genetic basis of antimicrobial resistance may help development of novel drugs. Two mecA homologues mecB (Tsubakishita et al., 2010a; Ito et al., 2012) and mecD (Schwendener et al., 2017) have been discovered in Macrococcus caseolyticus and authors described mecD to have the potential to disseminate in other bacterial genera. In future, with use of whole genome sequencing, more mecA homologues are likely to be discovered. Dissemination of the two M. caseolyticus mec genes to staphylococci is plausible since the genus Macrococcus and Staphylococcus are closely related (Tsubakishita et al., 2010a).

In this study, the phenotypic resistance observed in non-aureus isolates regardless of the method used was lower compared to other studies (Frey et al., 2013). Coagulase negative staphylococci in general were resistant to more classes of antibiotics than S. aureus. S. aureus isolates were resistant to mainly to sufadimethoxine, ampicillin, and penicillin. None of the S. aureus isolates was resistant to cefoxitin, which was expected because they were all mecA negative and is consistent with the known low prevalence of methicillin resistant S. aureus in cattle in the United States (Virgin et al., 2009; Haran et al., 2012; Cicconi-Hogan et al., 2014; Ruegg et al., 2015). At least 99% of all isolates (S. aureus and CNS) were susceptible to penicillin/novobiocin, amoxicillin/clavulanic acid, cephalothin, ceftiofur, gentamicin and enrofloxacin consistent with a recent study done in

Wisconsin (Ruegg et al., 2015). One notable resistance was seen with sufadimethoxine, where (29.5%) of CNS and (39.3%) of S. aureus isolates showed resistance. The CNS and S. aureus sufadimethoxine resistance was high compared to the recent study done in

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Wisconsin but a comparable resistance was noticed in streptococcus species in that study

(Ruegg et al., 2015). Eight years earlier, a similar study done in the same state showed high S. aureus sulfadimethoxine resistance on organic (37.6%) and conventional dairy farms (42.3%) (Pol and Ruegg, 2007), comparable to our findings. In another study done over a decade ago, 49% S. aureus isolates from bulk tank milk were sulfadimethoxine resistant (Sato et al., 2004). In this Sato et al., (2004) study, isolates from Denmark showed extremely low resistance to the same drug suggesting geographical differences.

The high sulfadimethoxine resistance in our study is similar to our previous work on antibiotic resistance of S. aureus isolates from bulk tank milk of 43 organic farms in

Vermont, were 50% resistance was noticed (Chapter 2). Generally most S. aureus and other staphylococci in our study were susceptible to a lot of antibiotics consistent with previous studies that showed relatively low resistance among mastitis pathogens (Ruegg et al., 2015). S. aureus from raw milk from 15 artisan cheese farms in Vermont showed high susceptibility to most antimicrobials (D'Amico D and Donnelly, 2011)

Biofilm formation in Staphylococcus is now considered a virulence determinant

(Vasudevan et al., 2003; Fox et al., 2005). In bovine mastitis, the biofilm phenotype is believed to cause chronic infections as bacteria within a biofilm are more resistant to antimicrobials and can evade the host immune system. Biofilm formation in staphylococci is believed to be mediated mainly by the polysaccharide intercellular adhesin (PIA) encoded by the ica locus, and biofilm associated protein (bap). We screened only S. aureus isolates for icaA, icaD, and bap genes. The primers used were not good for amplifying these genes in CNS as we often got unspecific bands

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(unpublished data). Simojoki and colleagues also encountered a similar problem on CNS with the icaA and icaD primers (Simojoki et al., 2012). For the S. aureus, all isolates were icaA and icaD positive but bap negative. This is consistent with our previous work that showed similar findings (Chapter 2). Other studies also have reported a 95-100% ica locus prevalence in S. aureus (Vasudevan et al., 2003; Szweda et al., 2012; Prenafeta et al., 2014) but lower in coagulase negative staphylococcus (Piessens et al., 2012; Martins et al., 2017). Most of S. aureus isolates were non-biofilm formers suggesting that ica and bap are not good predictors of biofilm formation. Other ica or bap independent mechanisms have been reported and reviewed (Foster et al., 2014).

Micro-titer plate assay is one of the widely used in vitro assays to quantify biofilm forming potential of bacteria in general. However, there is limited literature on the optimal plate surface type to use though most studies use tissue culture treated plates and other do not specify the plate type used. Kennedy and colleague demonstrated that treated plates are better but this work was done on a single strain of S. aureus (Kennedy and

O'Gara, 2004). Previous work on S. aureus (Chapter 2) revealed clonal specificity of S. aureus biofilm formation from bulk tank milk from 43 Vermont organic dairy farms on tissue culture treated (hydrophilic) polystyrene plates. This led us to hypothesize that biofilm formation among staphylococcus species might differ and we elected to used tissue culture treated polystyrene plates as the model of choice. A recent study that showed S. aureus isolates from food samples formed more biofilm biomass on hydrophilic surfaces (Lee et al., 2015) than hydrophobic surfaces.

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In comparison to S. aureus, S. sp. 020902 and S. xylosus formed high biofilm biomass whereas S. equorumi and S. auricularis formed very low biofilm biomass. S. xylosus has been reported before to be good biofilm former (Tremblay et al., 2013). At least 80% of S. sp. 020902 isolates were strong biofilm formers. This un-named species may become an extremely virulent pathogen given its biofilm phenotype but only 5/16 isolates in this study were from cow quarter milk. Isolates from cow quarter milk were significant biofilm formers in a univariate model. Fox and colleagues found milk S. aureus isolates to be better biofilm formers than isolates from cow skin (Fox et al., 2005) and 85% of the isolates in a recent CNS study were classified biofilm formers and all were from IMI cases (Tremblay et al., 2013). This may contribute to chronic infections, however, another study on CNS showed no association between biofilm phenotype and persistence of IMI (Simojoki et al., 2012).

At least 46% of the strong biofilm formers were either S. haemolyticus or S. chromogenes and these were among the top three species most frequently isolated from cow quarter milk and were the most prevalent. Their strong biofilm forming phenotype may partly explain their high prevalence but also the majority was non-biofilm formers showing heterogeneity in their biofilm phenotype. In this study, regardless of the plate type, biofilm formation was low e.g at least 80% of the S. aureus and 60% CNS were non-biofilm formers. The percentage of isolates classified as biofilm formers was low compared to some recent studies (Tremblay et al., 2013; da Costa Krewer et al., 2015).

However, other studies have reported comparable CNS findings (Piessens et al., 2012;

Simojoki et al., 2012). It is noteworthy that isolates used in previous studies were mainly

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from cow milk compared to this study where isolates were obtained from seven different niches (Figure 5-1). Differences in the diversity in terms of species and source may explain the discrepancies between studies. Piessens and colleagues analyzed 40 isolates for biofilm formation, which included cow milk, and environmental isolates and only

22.5% were considered biofilm formers (Piessens et al., 2012). The variation in establishing cutpoint for biofilm and non-biofilm optical density as well as different plate types also brings complexity in comparing studies (Stepanovic et al., 2000; Simojoki et al., 2012; Tremblay et al., 2013).

5.6 Conclusion

This work has demonstrated that most isolates are susceptible to many antibiotics and carriage of blaZ and mecA gene was niche specific. Isolates from humans were significantly associated with carriage of the blaZ gene, while environment/cow skin isolates were significantly associated with carriage of the mecA genes compared to cow milk isolates. Among the staphylococci, only five species (S. fleurettii, S. hominis, S. vitulinus, S. epidermidis and S. sciuri) were found to be mecA positive and thus are potential reservoirs of the gene. In general, antibiotic resistance was low apart from resistance to sulfadimethoxine. In vitro antibiotic susceptibility assays were not optimal for detecting resistant CNS compared to S. aureus among the β-lactam antibiotics. There was discordance between presence of blaZ and mecA genes and phenotypic resistance among the CNS and the discordance was more when using microdilution compared to disk diffusion method.

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The ica operon is much prevalent in S. aureus and bap is rare. None of these genes seem to predict biofilm biomass, suggesting the presence of other mechanisms.

Staphylococcus xylosus and S. sp. 020902 significantly formed more biofilm biomass compared to S. aureus. None of these CNS was predominant, however S. haemolyticus and S. chromogenes the top two most frequent species were heterogeneous with regard to biofilm formation, with significant number of isolates within each biofilm category.

Apart from S. haemolyticus and S. chromogenes which seem to be good biofilm formers, other mechanisms are responsible for the high prevalence of other Staphylococcus species.

5.7 Acknowledgments

This study was supported by UVM food systems, USDA Hatch grand and North East

SARE grant no. GNE14-087. We gratefully acknowledge University of Vermont, and

YALE core facilities for all the sequencing work.

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Tsubakishita, S., K. Kuwahara-Arai, T. Sasaki, and K. Hiramatsu. 2010b. Origin and molecular evolution of the determinant of methicillin resistance in staphylococci. Antimicrob. Agents Chemother. 54(10):4352-4359.

van den Bogaard, A. E., N. London, C. Driessen, and E. E. Stobberingh. 2001. Antibiotic resistance of faecal Escherichia coli in poultry, poultry farmers and poultry slaughterers. J. Antimicrob. Chemother. 47(6):763-771.

Vasudevan, P., M. K. Nair, T. Annamalai, and K. S. Venkitanarayanan. 2003. Phenotypic and genotypic characterization of bovine mastitis isolates of Staphylococcus aureus for biofilm formation. Vet. Microbiol. 92(1-2):179-185.

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Wielders, C. L., M. R. Vriens, S. Brisse, L. A. de Graaf-Miltenburg, A. Troelstra, A. Fleer, F. J. Schmitz, J. Verhoef, and A. C. Fluit. 2001. In-vivo transfer of mecA DNA to Staphylococcus aureus [corrected]. Lancet 357(9269):1674-1675.

Woodford, N. 2005. Biological counterstrike: antibiotic resistance mechanisms of Gram-positive cocci. Clin. Microbiol. Infect. 11 Suppl 3:2-21.

Wu, S., C. Piscitelli, H. de Lencastre, and A. Tomasz. 1996. Tracking the evolutionary origin of the methicillin resistance gene: cloning and sequencing of a homologue of mecA from a methicillin susceptible strain of Staphylococcus sciuri. Microbial drug resistance (Larchmont, N.Y.) 2(4):435-441.

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Table 5-1: Source of isolates

Milking Extra Human System and Dogs and Quarter Milk1 Teat Skin3 Mammary Environment5 hand and Total Bulk Tank pigs Cow Skin4 nose Staphylococci Milk2 S. agnetis 2 - 1 - - - - 3 S. aureus 33 6 11 - - 10 1 61 S. auricularis 6 3 39 25 2 - - 75 S. capitis 2 - 3 - 1 - - 6 S. caprae 1 - 1 4 - - - 6 S. chromogenes 73 16 15 15 - - 3 122 S. cohnii - 3 10 2 4 - - 19 S. gallinarum 4 3 - 1 - - - 8 S. epidermidis 7 - 3 1 - 16 - 27 S. equorum 11 5 9 20 24 7 3 79 S. fleurettii 5 4 6 6 1 2 - 24 S. haemolyticus 31 7 92 99 5 5 1 240 S. hominis 5 3 3 1 - 4 - 16 S. lugdunensis - - - - - 2 - 2 S. pseudintermedius ------1 1 S. saprophyticus 1 - - 1 - 2 - 4 S. pasteuri 1 - - 1 - 3 - 5 S. simulans 10 3 8 3 - - - 25 S. sciuri - - - 1 7 - 3 11 S. succinus 3 2 8 5 4 2 1 24 S. vitulinus 2 - 1 3 - 1 - 7 S. warneri 2 - 1 2 - 3 1 9 S. xylosus 8 2 13 15 8 2 2 50 S. sp. C035 ------1 1 S. sp. 020902-022-273 5 1 5 5 - - - 16 Total 212 58 229 210 56 59 17 841

1 Includes quarter and cannulated milk samples, 2Includes bulk tank milk, milk filter, inflation pre-milking, teat cup post-milking samples. 3Includes streak canal, teat end, teat barrel, and teat laceration samples. 4 Includes perineum, hock, vagina, cow nose, udder cleft samples. 5Includes stall partition rail, grain, water bowl rim, used sawdust bedding, feed trough and water trough samples

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Table 5-2: Distribution of MIC for S. aureus and CNS

Percentage of isolates inhibited at each concentration (µg/mL) Resistant1 BP2 Antimicrobial Bacterial spp (%) (µg/mL) ≤0.12 ≤1/2 2/4 0.25 0.5 1 2 4 8 16 32 64 128 256 NI3 Ampicillin CNS 3.8 ≤0.25 89.7 - - 6.4 2.7 0.6 0.3 0 0 - - - - - 0.3 S. aureus 14.8 ≤0.25 68.9 - - 16.4 3.3 6.6 0 3.3 1.6 ------Penicillin CNS 8.9 ≤0.12 91.1 - - 5 1.9 0.8 0.3 0.1 0.4 - - - - - 0.4 S. aureus 19.7 ≤0.12 80.3 - - 3.3 8.2 3.3 0 1.6 0 - - - - - 3.3 Cephalothin CNS 0.1 ≤8 ------99.2 0.5 0.1 - - - - - 0.1 S. aureus 0 ≤8 ------86.9 8.2 4.9 0 - - - - - Ceftiofur CNS 0.3 ≤2 - - - - 79.7 15.5 4 0.5 ------0.3 S. aureus 0 ≤2 - - - - 42.1 47.4 10.5 0 ------Oxacillin CNS NA ≤0.25 ------96.9 1 ------2.1 S. aureus 0 ≤2 ------100 0 ------Erythromycin CNS 6.3 ≤0.5 - - - 68.5 17.4 1.5 2.8 3.3 ------6.3 S. aureus 9.8 ≤0.5 - - - 65.6 14.8 6.6 1.6 1.6 ------9.8 Pirlimycin CNS 7.5 ≤2 - - - - 77.3 7.4 7.8 4 ------3.5 S. aureus 1.6 ≤2 - - - - 78.7 14.8 4.9 ------1.6 Tetracycline CNS 8.7 ≤4 - - - - - 87.7 2.6 0.4 0.3 - - - - - 8.7 S. aureus 0 ≤4 - - - - - 77 13.1 9.8 0 ------Penicillin/Novobiocin CNS 0 ≤1/2 - 99.5 0.5 ------S. aureus 0 ≤1/2 - 90.2 9.8 ------Sulfadimethoxine CNS 29.5 ≤256 ------61 3.1 4.4 1.9 29.5 S. aureus 39.3 ≤256 ------33 15 11.5 3.3 39.3 1 Resistant = percentage of isolates classified resistant based on 2008 and 2013 CLSI break points 2 BP = Breakpoint, MIC at which an isolate is considered susceptible according to 2008 and 2013 CLSI guidelines 3 Isolates that were not inhibited at the concentration of the antibiotic used 4 Coagulase negative Staphylococci, for simplicity three S. agnetis isolates, and one S. pseudintermedius isolate were grouped together with the CNS. Dash indicates concentrations not tested for a given antibiotic; MIC50 is underlined, MIC90 is bold

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Figure 5-1: Distribution of blaZ and mecA gene presence among the staphylococcus species n= Frequency of a particular species. Species where no blaZ or mecA positive isolate was detected are not shown. At least an isolate was mecA positive in S. epidermidis, S. fleurettii, S. hominis, S. sciuri and, S. vitulinus

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Table 5-3: Antibiotic susceptibility categories of S. aureus and coagulase negative staphylococci CNS S. aureus Antibiotic S I R S I R Ampicillin 96.2 - 3.8 85.2 - 14.8 Penicillin 91.2 - 8.8 80.3 - 19.7 Erythromycin 86.7 7.1 6.3 86.9 3.3 9.8 Cefoxitin 98.5 - 1.5 100 - - Pirllimycin 92.6 - 7.5 98.4 - 1.6 Tetracycline 91 0.3 8.7 100 - - Cephalothin 99.9 - 0.1 100 - - Ceftiofur 99.4 0.3 0.3 100 - - Clindamycin 91.6 4.7 3.7 95.1 4.9 - Sulfadimexathone 70.7 - 29.5 60.7 - 39.3 Oxacillin NA - NA 100 - - Gentamycin 99.9 - 0.1 100 - - P/N 99.9 0.1 - 90.2 9.8 - Enrofloxacin 100 - - 100 - - Amoxicillin/Clavulanic acid 99.9 0.1 - 100 - -

S, I, and R; Percentage of isolates that susceptible, Intermediate, and resistance respectively. (-) Means no isolate detected at that category or no CLSI break point for a given category. NA = No break point concentration on the MIC plates and no break points for Disk Diffusion. Data for Gentamicin, Vancomycin, Enrofloxacin, Amoxicillin/Clavulanic acid and Cefoxitin was based on Disk Diffusion and the remaining antibiotics, MIC data was used

Table 5-4: Comparison of phenotypic and genotypic β-lactam resistance among the staphylococci

Penicillin Oxacillin Cefoxitin

Susceptibility No. (%) of No. (%) of No. (%) of Staphylococci test category n blaZ detected n mecA detected n mecA detected S. aureus (61) Susceptible 50 0 (0) 61 0 (0) 61 0 (0) Resistant 11 11 (100) 0 0 (0) 0 0 (0) CNS (n=780) Susceptible 711 92 (13) NA - 768 38 (5) Resistant 69 47 (68) NA - 12 4 (33)

Penicillin and Oxacillin susceptibility category is based on MIC data; Cefoxitin category was based on disk diffusion data. NA, Commercial MIC plates used did have lower concentrations where breakpoint for CNS resistance lies.

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A B

Figure 5-2: Overall biofilm formation of staphylococci (A) and top 3 species causing IMI. Figure 5-2B, only isolates from IMI cases were considered

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Figure 5-3: Biofilm categories by species

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CHAPTER 6 : CONCLUSIONS AND FUTURE DIRECTIONS

Staphylococci are the leading cause of mastitis in the dairy industry. Whereas S. aureus has been studied extensively, there is still a knowledge gap in the epidemiology of the coagulase negative staphylococci (CNS). The major goal of this dissertation was to get an insight of the epidemiology of staphylococci and phenotypes that might contribute to the survival of the bacteria in various niches especially the mammary gland. We hypothesized that the high prevalent strains or species might be better biofilm formers or antibiotic resistant than the low prevalent ones.

The first project (Chapter 2) focused on the molecular epidemiology of selected

S. aureus isolates from bulk tank on organic dairy farms. This work revealed that the dominant clones were CC97 and CC151 (bovine adapted), supporting previous findings.

However, some low prevalent strain types also clustered under human adapted lineages like CC1, CC8, and CC59. Since these isolates were from bulk tank milk, we could not ascertain whether the human adapted strains were from infected cow milk or mere human contaminants. This limited us to understand the true epidemiology of these human adapted lineages. Human adapted strains may cause transient infections in cows and some strains for example ST8 (CC8) are believed to have jumped from humans to cows recently. Further studies at the cow level should be done to ascertain the possibility of other humans adapted STs or lineages switching to cows on theses farms. This work also identified ten novel S. aureus STs, most of which clustered in the dominant CCs associated with dairy cattle globally. Most of these novel STs have not been detected in other areas since their submission to the MLST database three years ago. This suggests

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unique regional epidemiological clusters which might be driven by unknown environmental pressures these bacteria are exposed to or due to random mutations.

Although, antibiotic resistance was extremely low, penicillin resistance was clonally specific, mainly associated with CC8 consistent with what we hypothesized. In fact, 100% of CC8 isolates were resistant to penicillin compared to other lineages. This lineage is of great importance in the dairy industry given its antimicrobial resistance and recent jump into cattle. More studies are needed on this lineage especially the virulence and why it’s more susceptible to carriage of b-lactam antimicrobial resistance gene markers.

In addition, CC8 significantly formed biofilm compared to other cattle adapted lineages. Data presented in this dissertation on biofilm is based on a tissue culture treated polystyrene model. Preliminary work comparing tissue culture treated and non-tissue culture treated polystyrene plate models showed differential biofilm biomass within S. aureus lineages (Figure 6-1A). Bovine adapted lineage CC97, overall formed high biofilm biomass on non-tissue culture treated plates (hydrophobic), however there was some heterogeneity within CC97, with most ST2187 and ST352 being biofilm formers

(Figure 6-1B). These STs were the top predominant strains within CC97 suggesting biofilm formation on hydrophobic surfaces may drive their predominance. The human adapted CC8 isolates were good on treated plates in terms of biofilm formation. Whereas it is arguably believed that bacteria stick better on tissue culture treated plates

(hydrophilic surfaces), findings from this dissertation refutes that notion. Some lineages at least for S. aureus seem to attach and form biofilm on hydrophilic or hydrophobic

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surfaces differentially. More research is required to identify the factors that underlie these differences. Specifically, comparative genomics using whole genome sequence data might be applied to identify genetic differences among isolates that differ in their biofilm forming capacity.

Recent evidence suggests some S. aureus lineages may be at an advantage to persist in milk collected for processing and be more likely to enter the human food chain, while other lineages may be more likely to persist among cattle hosts (Kummel et al.,

2016). It is unclear if biofilm forming capacity contributes to persistence in one niche or the other (i.e. host or milk processing environment). It is also unclear which polystyrene plate model is best to characterize biofilm capacity related to persistence in particular niches. Identification of genetic basis that underlie the ability of S. aureus strains to adhere to specific plate type surfaces, and selection of the appropriate model system is paramount. A better understanding of which surface type most prevalent strains attach and form biofilms may help in designing farm dairy equipment. We hypothesize that differential biofilm formation on different surface types is due to some unique nucleotide differences in the bacterial surface proteins involved in adhesion between strains. This can be explored in future studies using whole genome sequencing.

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Figure 6-1: Biofilm formation of S. aureus lineages from organic farms on untreated (white box plots) and treated (red box plots) surfaces (A) and STs within CC97 (B) In the subsequent projects (chapter 3 & 4), we described the epidemiology of staphylococci, mainly CNS. Tuf gene sequencing proved to be discriminatory enough in the identification of Staphylococcus species. This is the first mastitis study where tuf gene has been used extensively to identify Staphylococcus species from various sources/niches described in this dissertation. Tuf gene has been used widely for identifying staphylococci from humans, and from this work, we have demonstrated that it is equally good for identifying bovine associated staphylococci as well. Although 27 staphylococci species were identified, only five were important mastitis pathogens; S. aureus, S. chromogenes,

S. haemolyticus, S. simulans and S. xylosus depending on the number of infected cow udder quarters. One future study would be to understand the epidemiology of some important staphylococci at strain level in order to better understand the direction of transmission which was not done for most species. Our laboratory uses multilocus sequence typing (MLST; http://pubmlst.org), which is a highly acceptable typing technique to understand local and global epidemiology of bacteria. We have worked on S.

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aureus and S. chromogenes. S. aureus MLST results showed that strain types from humans and animals were unique suggesting no cross transmission. For S. chromogenes, using the novel MLST scheme we developed, there was evidence of niche specificity of strain types. Although some S. chromogenes strain types from cow milk and cow skin were similar, we did not skin sample enough cows to draw conclusions and some skin sampled cows did not have S. chromogenes IMI. This was one of the major limitation of

S. chromogenes MLST project. Future work can do targeted skin sampling of S. chromogenes IMI positive cows. Staphylococcus chromogenes is believed to be an udder-adapted species at least from this study and other studies, it’s rare in the environment and does not seem to colonize humans. It was postulated that the skin might be the source of strains causing IMI or that it could spread from cow to cow in a contagious manner. Taken together, this work has laid a foundation in the mastitis research field for studying the epidemiology, antimicrobial resistance, and virulence of S. chromogenes at strain level using this novel MLST scheme.

Some CNS species though dominant on cow skin or the environment did not seem to be important mastitis pathogens. More studies on these “non-pathogenic” CNS is also needed as they may have beneficial characteristics. Some CNS on teat skin may protect cows from pathogenic microbes like S. aureus. Some of non-pathogenic CNS species

(e.g. S. equorum) might be beneficial in cheese making and therefore farming practices that encourage these microbes should be ascertained in futures studies.

I would propose to expand this work in future to understand the molecular epidemiology of S. haemolyticus and S. epidermidis. S. heamolyticus was common

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almost in all niches whereas S. epidermidis was common in humans and less prevalent in other niches, I would want to know whether humans might be the source of isolates we find in cow milk. MLST has already been developed for these species

(http://pubmlst.org). Staphylococcus fleurettii was also interesting because it was the only species where all the isolates where mecA positive, much prevalent only on one farm.

This species was isolated in all niches sampled including humans. There is no MLST for this species yet but whole genome sequencing can be done on the isolates of this species on this single farm. Whole genome sequencing is more favored than strain typing because of its high discriminatory power and its high resolution to infer phylogeny between strains.

In chapter 5, we evaluated the antibiotic susceptibility and biofilm formation of a fraction of isolates described in chapter 3. In general, antibiotic resistance was low, but some questions remained unanswered. The in vitro antibiotic susceptibility testing methods showed poor association between phenotypic resistance and presence β-lactam resistance genes amongst the CNS compared to S. aureus. However, comparing the two methods, in general, disk diffusion method had a better correlation than MIC on CNS isolates suggesting that indeed the method used maters. This may have clinical relevance in mastitis especially if treatment decisions are based on phenotypic susceptibility.

Susceptible bacteria with presence of β-lactam antimicrobial resistance genes may revert resistance in vivo jeopardizing therapy. Antibiotic resistance genotyping was done for only two genes encoding β-lactam antimicrobial resistance. We don’t know the phenotypic-genotypic discordance that exists in this bacterial population studied for other

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classes of antibiotics. Screening for other antibiotic resistance genes can help to draw conclusions on the suitability of in vitro susceptibility methods in detecting resistance especially in CNS from dairy farms.

Most mecA positive CNS were phenotypically susceptible to cefoxitin an antibiotic that is now acceptable for detection of methicillin resistance. We hypothesize that this has to do with genetic make-up of the staphylococcal chromosomal cassette mec, which could be interfering with the expression of mecA gene. We propose in future to characterize the cassette of all mecA positive resistant CNS isolates and compare it with mecA positive isolates that are phenotypically susceptible. This concept can also be extended to blaZ positive isolates that are susceptible to penicillin or ampicillin. Unlike

CNS, we did not see this genotypic-phenotypic discordance in S. aureus suggesting species specificity. All S. aureus blaZ positive isolates described in this dissertation, were phenotypically resistant to penicillin regardless of the method used. Sequence analysis of the blaZ gene in different Staphylococcus species might give more insight about the discordance within CNS species. The major emphasis being understanding sequence variation of blaZ gene in penicillin susceptible and resistant isolates within the genus Staphylococcus.

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