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Whole genome sequencing identifies exotoxin and antimicrobial resistance profiles of Staphylococcus aureus from Maine dairy farms

BMC Veterinary Research volume 21, Article number: 154 (2025) Cite this article

Abstract

Background

Staphylococcus aureus is a leading cause of mastitis in dairy livestock and is a pathogen with unknown but potential impact on public and herd health in Maine. The primary objective of this study was to describe retrospective trends in S. aureus detection at the University of Maine Cooperative Extension Veterinary Diagnostic Laboratory (UMVDL) for milk samples submitted between July 2017 and June 2022. The second objective was to assess the genetic profiles focused on antibiotic resistance and exotoxin genes of 29 S. aureus isolates submitted from dairy farms in Maine in 2017 and 2022.

Results

Overall, 7.8% of milk samples submitted to UMVDL between July 2017 and June 2022 were positive for S. aureus. The 29 isolates collected in 2017 (2 isolates) and between May and July of 2022 (27 isolates) were analyzed by whole genome sequencing and belonged to 8 strain types and 5 clonal complexes typically associated with ruminant species. Across the genomes of the 29 isolates, 14 antimicrobial resistance genes were detected, with antibiotic efflux as the primary resistance mechanism. Each isolate contained 2 to 10 staphylococcal enterotoxin genes representing 15 unique genes. lukED, lukMF’, Staphylococcal superantigen-like proteins (SSLs), and hla, hlb, hld, hlgABC genes were also observed. Antimicrobial resistance and staphylococcal enterotoxin gene carriage mostly clustered with clonal complex and host species of origin.

Conclusions

Whole genome sequencing identified ruminant-associated sequence types and antimicrobial susceptibility profiles consistent with other regional reports. Exotoxins with relevance to mastitis and SFP development were also identified. This study provides insight into future opportunities to study S. aureus prevalence and to survey dairy production in animal and public health contexts in Maine.

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Background

Staphylococcus aureus is a leading cause of mastitis in dairy livestock including cattle, sheep, and goats, and these infections decrease milk quality and quantity [1, 2]. S. aureus possesses a range of virulence factors including an array of exotoxins that modulate host immune response and helps the pathogen evade host immune systems. These exotoxins include cytotoxic enzymes like β-hemolysin, cytotoxins such as hemolysins and leukocidins, and staphylococcal enterotoxins (SEs) [3]. The range and variation of these exotoxins provides evidence of adaptation to different host species [4].

β-hemolysin is present and functional in S. aureus strains of bovine origin where it acts as a sphingomyelinase, while it is inactive in strains of human origin due to the insertion of the Immune Evasion Cluster (IEC) into this gene [5]. γ-hemolysins and LukMF’ can cause lysis of bovine neutrophils, contributing to mastitis development [6]. SEs do not seem to contribute to the development of mastitis in dairy livestock with the exception of SEC. [7, 8]. However, SEs and toxic shock syndrome protein (TSST-1) act as superantigens (SAgs) by binding to variable regions of β-chains of T cell receptors and MHCII molecules to induce T cell activation and cytokine release [9]. Human consumption of milk and dairy products contaminated with S. aureus from infected animals can cause staphylococcal food poisoning (SFP) and toxic shock syndrome if the contaminating strain produces SEs and TSST-1. Additionally, SEs are heat and pH resistant, so disease can occur from consumption of pasteurized or unpasteurized dairy products even if S. aureus is no longer viable [10].

Antimicrobial-resistant S. aureus also poses a risk to public and herd health. The World Health Organization ranks antimicrobial resistance (AMR) as one of the top ten public health threats faced by humanity [11]. Methicillin-resistant S. aureus (MRSA) may be the most notable example of antimicrobial resistant S. aureus in the human clinical setting, but a range of antimicrobial resistance genes have been detected in S. aureus from cases of bovine mastitis around the world [12].

WGS enables comprehensive analysis of complete virulence and antimicrobial resistance gene profiles without the labor and expenses that limit such analysis through traditional biochemical or molecular methods [13], and avoids false-negative results possible in targeted PCR-based identification methods [14]. WGS is particularly advantageous for assessment of SEs since traditional methods were typically limited to identification of classical enterotoxins (SEA, SEB, SEC, SED, and SEE). WGS overcomes this potential reporting bias by identifying se gene profiles and subtyping se gene variants, by also detecting nonclassical SEs and staphylococcal like proteins (Sels), which do not induce emetic activity [15]. In addition, WGS data can be used to predict multilocus sequence types and clonal complexes, replacing traditional multilocus sequence typing using PCR and Sanger sequencing methods. Whole genomemultilocus sequencing typing (wgMLST) informs our understanding of S. aureus epidemiology and host specificity [16].

In the state of Maine in 2022, 171 bovine dairy farms produced 554 million pounds of milk [17], and small ruminant dairy operations further expanded that figure. Maine’s dairy farms occupy 700,000 acres of farmland and create thousands of jobs [18]. Antibiotic resistance, herd transmission, and enterotoxigenic potential of S. aureus vary among sequence types (STs) of S. aureus [19,20,21], and STs vary by geographic region [22]. Therefore, understanding the frequency of S. aureus sequence types can inform our understanding of the relative importance of S. aureus as a mastitis pathogen on dairy farms, as well as the potential public health risk. While control of S. aureus in dairy production is currently most relevant to cattle health, the public health concern may be emerging as sale of raw milk is legal in Maine except in eating establishments, and the number of licensed raw milk facilities increased from 15 in 2006 to 54 in 2015 [23, 24]. Although S. aureus has not been identified as a major cause of foodborne illness outbreaks from dairy products in the US over the last 26 years, foodborne illness from unpasteurized milk is 3.2 times more likely to occur in states where sale of unpasteurized milk is allowed, suggesting future surveillance is warranted [25]. Cases of foodborne illnesses by all pathogens including S. aureus are likely underdiagnosed and underreported [26, 27]. It consequently is important to understand the characteristics of any pathogen in dairy production systems, including S. aureus, which has potential to cause foodborne illness. Therefore, studying S. aureus mastitis epidemiology in Maine is necessary to evaluate its impact on the local dairy industry. The primary objective of this study was to describe retrospective trends in S. aureus detection at the University of Maine Cooperative Extension Veterinary Diagnostic Laboratory (UMVDL) for milk samples submitted between July 2017 and June 2022. The second objective was to assess the genetic profiles focused on antibiotic resistance and exotoxin genes of 29 S. aureus isolates from dairy farms in Maine submitted in 2017 and 2022.

Results

Objective 1: retrospective trends of S. aureus isolation

At UMVDL, 467 of 6,116 (7.8%) milk samples assessed between July 2017 and June 2022 were positive for S. aureus (Table 1). This included 430 of 5,919 (7.3%) bovine milk samples from 65 farms, 34 of 189 (18.0%) caprine milk samples from 12 farms, and 3 of 8 (37.5%) of ovine milk samples from 3 farms. One farm had a S. aureus-positive result for both a bovine and caprine milk sample. Milk samples submitted to UMVDL were either composite or quarter milk samples. The health status of the animals of origin is unknown.

Table 1 S. aureus isolation events from milk samples submitted to UMVDL by year and species
Full size table

Using a logistic regression model, where the outcome was a positive S. aureus culture among milk sample submissions stratified by sample accession number and month we found the predicted odds of S. aureus isolation from submitted milk samples over time decreased 18.5% each year.

The 467 S. aureus-positive milk samples originated from 350 unique animals on 79 farms from every county in Maine except Sagadahoc. The frequency of S. aureus-positive samples varied among farms. Forty-eight (61%) of the 79 farms had only one S. aureus-positive submission over the five-year period. The remaining 31 farms had S. aureus-positive submissions on 2 to 26 individual occasions during the five-year period. At the extreme, the 26 submissions of 639 total samples from a single farm resulted in 86 S. aureus-positive samples.

At the individual animal level, 83.1% (291/350) of S. aureus-positive animals had S. aureus-positive samples submitted only once, with the remaining 59 animals having two or more positive submissions. The highest number of S. aureus-positive samples from an individual animal was eight, submitted on seven dates over the course of 748 days. The longest interval between two S. aureus-positive samples from an individual animal was 840 days.

Antibiotic susceptibility testing was performed via disk diffusion by UMVDL technicians upon submitter request, and results for oxacillin resistance were recorded in the UMVDL mastitis database. Ninety-one S. aureus isolates from 51 farms and 83 individual animals had undergone phenotypic antibiotic susceptibility testing, and 25 (27%) were identified as resistant to oxacillin. No methicillin resistance (mec) genes were identified among isolates by whiole genome sequencing, and methicillin resistance could not be confirmed as no additional confirmatory tests were performed.

Objective 2: isolate analysis

Isolate sources

Since UMVDL did not routinely store SA isolates in the course of normal diagnostic operations, only S. aureus cultured from submitted milk samples between May and July 2022 were available for analysis. This resulted in 27 S. aureus isolates from recent UMVDL milk sample submissions, and 2 isolates recovered from storage (frozen at -20˚C since isolation in 2017). Twenty-one isolates were from bovine milk samples, 6 from caprine milk, 1 from ovine milk, and 1 from bovine bulk tank milk. The samples originated from 23 animals on 13 farms. On three occasions, milk samples from different udder quarters or halves of a single animal were submitted to the UMVDL on the same day and resulted in two separate isolations of S. aureus. Once, two udder composite samples from a single animal submitted to UMVDL on the same day resulted in two isolations of S. aureus. It is unclear if these samples were collected by the farmer at the same time or on different dates. Lastly, two isolates were obtained from milk samples from the same animal on different submission dates. We analyzed all 29 available isolates to expand our descriptive capacity since these samples are not reflective of a single reference population but rather of a broad range of the Maine dairy industry.

MLST

The 29 S. aureus isolates were classified into 8 sequence types (STs) within 5 clonal complexes (CCs; Table 2). There was no overlap between STs identified from bovine, caprine, and ovine milk samples. Two novel STs were identified, ST8510 in CC151 is a novel ST related to ST151 with single locus variant at the arcC locus (n = 1), and ST8509 in CC133 is a novel ST related to ST133 with a single locus variant at the aroE locus. ST352 was the most prevalent ST accounting for 27.6% of all samples (8 of 29) and 36.4% (8 of 22) of all bovine samples (including the isolate from bovine bulk tank milk).

Table 2 MLST types of S. aureus stratified by species
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Two or more STs were identified from 3 of 13 farms. Two farms from which multiple isolates originated had 1 ST identified. The 8 remaining farms were the source of single isolates, with one ST identified per farm. In the four pairs of isolates which originated from the same animals on the same submission dates but from different teats (for 3 pairs) or from different composite samples (for 1 pair), the isolates belonged to the same STs. The single pair of isolates sourced from the same animal on two different submission dates also belonged to the same ST.

AMR

All 29 isolates were phenotypically susceptible via disk diffusion to amoxicillin, ampicillin, cefoxitin, ceftiofur, cephalothin, erythromycin, gentamicin, oxacillin, penicillin, pirlimycin, streptomycin, and tetracycline. Across the genomes of the 29 isolates, fourteen AMR genes were detected (arIR, arIS, FosB, GlpT, kdpD, LmrS, mepR, mgrA, murA, norA, norC, sdrM, sepA, vanT). Antibiotic efflux was the primary mechanism of resistance as defined by the Comprehensive Antibiotic Resistance Database (CARD); less frequent mechanisms were target alteration and antibiotic inactivation. Eight genes were detected in all isolates (arIR, LmrS, mepR, mgrA, norA, norC, sepA, vanT) with a minimum of 10 genes and a maximum of 13 genes detected in any given individual isolate.

AMR gene carriage clustered based on isolate clonal complex and species of origin (Fig. 1). We detected FosB exclusively in CC133. GlpT and murA were always identified together in the same isolates. Caprine samples had significantly more AMR genes than bovine samples (P = 0.0238). A comparison was not conducted with ovine samples because we only had one isolate of ovine origin.

Fig. 1
figure 1

Heat map of antimicrobial resistant genes identified from whole genome sequencing of 29 S. aureus isolates stratified by species host of origin and clonal complex. Light green = gene present, dark green = gene absent

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Exotoxin genes

The hemolysin genes hla, hlb, hlgA, hlgB, and hlgC were identified in all 29 genomes. hld was in 22 genomes all belonging to CC5 or CC97. Leukocidin components lukDE were identified in all 29 genomes. lukMF’ were identified in 11 genomes (38%), including all 8 ST352 isolates of bovine origin, 1 isolate of bovine origin from ST151, and two isolates belonging to ST133, one of ovine origin and one of caprine origin.

Chromosomal SE genes selw and selx were identified ubiquitously in all isolates. Four bovine isolates contained a total of 10 additional SE genes (Fig. 2). Eight additional genes were observed in the single ST8510 isolate in CC151 (seg, sei, sem, sen, seo, seu, sey, sez) and 7 additional genes were observed in all three isolates in ST350 (sei, sem, sen, seo, seu, sel26, sel27). One caprine isolate and the single ovine isolate, both belonging to CC133, possessed the 3 additional genes sec, sel, and tst. However, these genes were not detected in the genome of the other caprine ST133 isolate (UM23). Aside from sec, the other classical enterotoxins, sea, seb, sed, and see, were not detected in any isolates.

Fig. 2
figure 2

Heat map of exotoxin genes identified from whole genome sequencing of 29 S. aureus isolates stratified by species host of origin and clonal complex. Light green = gene present, dark green = gene absent

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Staphylococcal superantigen-like protein genes ssl5, ssl7, ssl9, ssl10, and sll11 were present in all isolate genomes. ssl1 was ubiquitous except in the ST8510 isolate, ssl2 was ubiquitous except in one ST3028 isolate, and ssl3 was ubiquitous except in the two ST8509 and 8510 isolates.

Discussion

Objective 1: retrospective trends of S. aureus isolation

Here we report a retrospective study describing the frequency and strain diversity of S. aureus isolated from milk samples submitted to UMVDL by Maine dairy farms. To the best of our knowledge, there are no previous studies examining prevalence or diversity of S. aureus from dairy sources in Maine. Also, in a search of PubMed, we identified no previous publications describing S. aureus MLST diversity in Maine. Our primary objective was to report the frequency of S. aureus isolation from milk samples submitted to the UMVDL using laboratory records. Recognizing the limited ability to make inferences from these data we elected to augment these data with genomic sequencing results for isolates collected from recent laboratory submissions. There are several limitations with reporting pathogen and disease frequencies from laboratory databases. Key among the limitations is the issue of sampling or ascertainment bias, where we can not determine what the samples submitted to the diagnostic laboratory may represent. For example, the frequencies of S. aureus isolation observed by the laboratory should not be used to infer S. aureus prevalence among Maine dairy farms. The issue of sampling bias is particularly evident from the observation that there is variation in the number of samples submitted per farm per year. Further, the laboratory records contained limited sample metadata, and in particular lacked key information such as clinical disease state or the reason for sample submission, so we can not infer disease frequency associated with the isolation events. Finally, while the laboratory records allowed us to link the S. aureus positive samples to an accession number and associated farm and individual cow identification, the records lacked these data for submissions where S. aureus was not isolated, so we could only model S. aureus frequencies from positive sample submissions.

Therefore, while we observed a decrease in odds of S. aureus isolation from milk samples submitted each year this does not infer a change in prevalence of S. aureus in Maine’s dairy herds. The observed decrease may be due to changes in farmer motivation to submit samples, or access to other resources for milk culture. Submissions from the same farm might be expected to show correlations in their outcomes and when modeling pathogen prevalence in regions the hierarchical nature of the data, such as clustering within farms and regions should be considered. Accession numbers are assigned by UMVDL to each sample or set of samples submitted by a individual. Unfortunately, farm information was only available for accession numbers with positive test results, so we were not able to account for clustering within farms in a model of isolation frequency. When modeling the change in isolation frequency over time, we explored an analysis with accession number as a random predictor, but this model did not converge. Repeated submissions of samples from individual animals was also evident, further supporting the value of a modeling approach accounting for clustering of animals within farms, although the majority of submissions were from individual animals. Whether the observed single occurrence of S. aureus-positive samples from most individual animals was due to subsequent infection clearance, farmer interventions such as culling S. aureus positive cows, or a lack of continued monitoring through follow-up sample submissions is unclear.

At the farm level, since this study was conducted using opportunistic, client-provided samples from a diagnostic laboratory, the motivations behind sample submission may bias the characteristics of S. aureus isolated from samples. S. aureus CCs differ in virulence properties and ability to cause mastitis [28], and S. aureus strains have differing abilities to cause persistent intramammary infections [29]. Previous studies have demonstrated the presence of dominant STs within individual farms [29]. Since the isolates in this study were sourced from milk samples at a mastitis diagnostic laboratory, our results were likely biased to more frequently include those STs that contribute to signs that warrant diagnostic testing. Less virulent strains of S. aureus may be present on farms but consequently might not be included in our samples. This potential bias may have been mitigated if some samples were sent to UMVDL regardless of mastitis status as part of routine practices, potentially enabling detection of less pathogenic strains of S. aureus. Farmer motivations for sample submissions are not currently known and should be evaluated in future surveys.

Farms with S. aureus-positive samples from several animals on multiple dates may have had contagious genotypes of S. aureus which are more difficult to eliminate from a herd. In contrast, farms which only had S. aureus-positive samples on a single date may have experienced infections with S. aureus genotypes that cause sporadic mastitis [21]. Strain typing of S. aureus isolates collected from dairy herds in other geographic regions has demonstrated the epidemiology of S. aureus was associated with the genotype [19]. Alternatively, farms with several S. aureus-positive submission dates may have been more diligent in continuing to monitor their herds for S. aureus compared to farms that reportedly had S. aureus-positive samples once and failed to submit more samples for follow up. Rather than representing inter-farm differences of S. aureus strains, this would reflect farm management practices. A randomized, longitudinal sampling scheme could assess within-farm S. aureus ST diversity and state-wide S. aureus prevalence to better understand these issues.

.

Objective 2: isolate analysis

MLST

The majority (81.8% or 18 of 22) of bovine-sourced isolates belonged to CC97 (ST352, ST2187, ST3028), which is a major CC reported in Pennsylvania, Vermont, and Canada [30,31,32] and was the most prevalent CC reported in a global analysis of bovine S. aureus [22]. However, only one isolate belonged to CC151 which has also been frequently detected in these locations and globally [22, 30,31,32]; this may be attributed to our limited sample size.

Our observed association of ST with milk sample source species is consistent with a study of S. aureus from a variety of animal species in four New England states including Maine where ST151, ST2187, and ST352 were found exclusively in samples from cows [33]. ST6, ST133, and the related novel ST8509 were only from small ruminant origin in our study which is consistent with reports that ST133 is rarely identified in bovine sources in New England and Canada [31, 33], and with findings in Victoria, Australia where ovine and caprine samples exclusively belonged to ST133 or a related single locus variant [34].

AMR

The antimicrobial susceptibility profiles of S. aureus from Maine dairy farms were consistent with other studies in the Northeast US. The phenotypic susceptibility of our isolates is similar to the susceptibility profiles observed by Thomas et al. in isolates in Pennsylvania, although that study lacked genotypic AMR assessment for comparison with our genotypic results [30]. The AMR genes we detected are similar to those detected in the study of S. aureus in diverse animal hosts in New England where antibiotic efflux genes norA and lmrS were in all genomes and mgrA was in all but two [33]. Similarly, we detected FosB infrequently; this gene was found exclusively in ST133 in our study, and not in ST6 or other STs as previously reported [33]. Our results are also consistent with a Canadian study which found antibiotic efflux genes in all isolates [31].

Notably, none of our isolates contained the mecA or blaZ genes which confer resistance to methicillin and penicillin respectively. This differs from the studies in Vermont, Pennsylvania, New England, and Canada where blaZ was detected, albeit at a low prevalence [30,31,32,33, 35] but is similar to finding no mecA positive isolates in Vermont [32, 35]. However, most of these studies are non-probability studies and the true prevalence of methicillin-resistant S. aureus in dairy-associated samples is unknown. Our observed lack of mecA and blaZ genes and no phenotypic resistance to oxacillin for the 29 isolates from 2022 studied in Objective 2 is surprising given that the UMVDL reportedly identified oxacillin phenotypic resistance in 27% of samples evaluated over the prior five-year period. From this historical value, assuming a 95% confidence interval that the true prevalence in this discrete population lies between 17 and 37%, we would have expected 4 or more of our 29 isolates to display phenotypic oxacillin resistance. However, there is controversy over the use of disk diffusion methods for oxacillin resistance to identify MRSA and cefoxitin discs are preferred [35]. In addition, among the antimicrobials tested in this study veterinary-specific breakpoints are only available for ceftiofur and pirlimycin, and breakpoints used for other antimicrobials are adapted from human data [36]. For the 2022 isolates, we conducted disk diffusion susceptibility testing to remain consistent with UMVDL procedures, and we were unable to confirm beta-lactam or methicillin resistance. Future prevalence studies should use minimum inhibitory concentration of oxacillin or disk diffusion with cefoxitin to describe the occurrence of oxacillin and methicillin resistance more reliably [35].

There is an apparent discordance between the phenotypic susceptibility of isolates and the genotypic presence of AMR genes which, if expressed, should confer resistance to some of the antibiotics tested. For example, mep and mgrA encode antibiotic efflux mechanisms which confer multi-drug resistance [37]; however, no phenotypic resistance was observed despite detection of these genes in all 29 isolates. In contrast, other studies have observed the opposite issue where phenotypic resistance was observed but whole genome sequencing failed to find associated genetic markers [30]. Identification of resistance determinants, such as single nucleotide polymorphisms (SNPs), from whole-genome sequence (WGS) data could provide explanations for the observed discrepancies [38].

Exotoxin genes

γ-hemolysins, lukED, and lukMF’ are frequently identified in S. aureus from bovine mastitis and cause lysis of bovine neutrophils, thereby contributing to mastitis development [6, 39]. Our ubiquitous identification of lukED genes is consistent with previous reports [30, 31]. ST352 in CC97 has also been observed to have a high prevalence of lukMF’ [30, 40], as have CC133 ovine and caprine isolates [41]. Expression of these genes may vary according to host factors to manifest in clinical or subclinical mastitis [41].

In a study of 57 S. aureus STs isolated from bovine mastitis, Wilson et al. reported most bovine S. aureus contained a range of 2 to 13 superantigen genes (SAgs) in all genomes [20], which is similar to our detected range of 2 to 10 genes. Our detection of non-chromosomal SEs in 18.2% (4 of 22) of bovine isolates is much lower than the 64.41% prevalence of enterotoxin genes detected in Thomas et al.’s Pennsylvania study and contrasts with a report suggesting that all bovine S. aureus typically contain 5 or more superantigen genes [20, 30]. Our less frequent identification of SEs is likely due to a difference in predominant STs. Whereas Wilson et al. included a variety of STs, and the majority of SEs in the Pennsylvanian study were detected in CC151, our isolates mostly belonged to CC97 and lacked enterotoxin genes [20, 30]. Wilson et al. reported CC97 genomes contained the fewest SAgs [20], and CC97 isolates from Naushad et al.’s Canadian study similarly lacked any enterotoxin genes [31], so our results are consistent with these prior reports.

Previously, SEC has been the most frequently detected SE from S. aureus animal mastitis isolates [42] and was most frequently identified in bovine, ovine, and caprine raw milk samples from small-scale artisan cheese production in Vermont [43]. In contrast, sec was only identified in two isolates in our study which belonged to ST133; sec detection in only some ST133 isolates is not without precedent [34]. Perhaps the difference in sec detection frequency can be attributed to limitations of traditional phenotypic methods which primarily detected classical SEs, as in D’Amico and Donnelly’s assessment in Vermont [43]. Regardless, any presence of sec is concerning. SEC may act as a virulence factor in mastitis development [8] and has been associated with clinical mastitis in small ruminants [44], so the presence of SEC-producing S. aureus strains within a herd could pose a risk to herd health and milk production. SEC has also been associated with SFP outbreaks [45] and could have implications for public health. In our study, co-detection of sec with sel and tst in two isolates suggests that these isolates contain the SaPIbov pathogenicity island [46]. The toxic shock syndrome protein (TSST-1) encoded by the tst gene is concerning due to its superantigen activity and ability to cause toxic shock [47].

Presence of SE genes does not necessarily correlate with in vivo toxin production [10], although CC has been directly linked to the vSAβ genomic island which contains the enterotoxin gene cluster (egc) and can be predictive of SEG and SEI production [48].The egc can be composed of a variety of combinations of the genes seg, sei, sem, sen, seo, and seu [9, 48]. Egc has been frequently detected in CC151 [20, 30], and our single isolate in CC151 likewise possessed egc genes. ST350 isolates were the only others in our study to contain egc genes, but this ST was not included in the study by Wilson et al., and the single isolate in Thomas et al.’s study in Pennsylvania belonging to ST350 only possessed sei and sem [20, 30]. seg has been associated with a decreased chance of S. aureus establishing persistent intramammary infections [50], so the presence of seg in only one of our four isolates containing egc genes supports our speculation that our samples are biased towards more pathogenic STs. The role of egc enterotoxins in staphylococcal food poisoning is evidenced by SFP outbreaks which lacked detection of classical enterotoxins but did detect egc [26], so the presence of these genes could pose a risk to consumers.

Our identification of selx, selw, sey, selz, sel26 and sel27 adds to the understanding of the diversity of enterotoxins associated with S. aureus from dairy sources. There is a discrepancy between the nomenclature and associated sequences of selw and sel26 used in some studies; we referred to selw as the chromosomal gene found in studies by Wilson, Nouws, and Aung [15, 20, 51] and sel26 and sel27 as the genes identified by Zhang and used in analysis by Aung [51, 52].

A variety of ssl genes was similarly observed by Naushad et al., although we observed only 8 rather than 39 of the 40 ssl genes [31]. This was likely due to our much smaller sample size (29 vs. 119) and diversity between observed clonal complexes.

Conclusion

This study quantifies S. aureus isolation from milk samples submitted to UMVDL by dairy farms in Maine over a five-year period. Whole genome sequencing identified ruminant-associated sequence types and antimicrobial susceptibility profiles consistent with other regional reports. Exotoxins with relevance to mastitis and SFP development were also identified. We provided insight into future opportunities to study S. aureus epidemiology and to survey dairy production in animal and public health contexts in Maine.

Methods

Objective 1: retrospective trends of S. aureus isolation

In order to summarize the frequency of S. aureus isolation events from milk samples submitted to the UMVDL, we conducted a non-probability retrospective observational study of S. aureus isolation events reported in the UMVDL custom Mastitis database on Access platform. Milk samples submitted to UMVDL Mastitis Lab were initially cultured (10µL aliquots) on Tryptic Soy Agar with 5% sheep blood following National Mastitis Council mastitis diagnostic procedures [53]. Presumptive S. aureus colonies were identified based on colony morphology and were sub-cultured for isolation. S. aureus isolates were confirmed by observation of Gram-positive cocci in grape-like clusters, catalase and coagulase positivity, and production of black colonies surrounded by yellow zones on Vogel-Johnson agar. Each milk sample positive for S. aureus was considered a unique event. Data about S. aureus isolated between July 2017 and June 2022 were extracted from the Mastitis database, then analyzed in Microsoft Excel. Farm names were coded for anonymity in the dataset, and the location of each farm (county only) was noted. Additionally, for each isolation event, the dairy animal species, type of sample (udder composite vs. individual udder quarter or half), and oxacillin antibiotic susceptibility (if tested per submitter request) were compiled. Bulk tank samples were not included in the retrospective analysis.

Objective 2: isolate analysis

Isolate identification

To augment the retrospective analysis by describing the genetic diversity of a recent subset of isolates collected by the UMVDL, 27 S. aureus isolates were collected from milk samples submitted to UMVDL between May and July of 2022, and 2 samples had been collected in 2017 and were available from frozen storage. The S. aureus positive milk samples originated from dairy cattle, goats, and sheep, and were submitted by organic and conventional farms in Maine. Phenotypic identification of S. aureus was conducted at the Mastitis Lab in UMVDL as described above in Objective 1.

Phenotypic antibiotic susceptibility testing

Kirby-Bauer disk diffusion assays were performed for each isolate at UMVDL Mastitis Lab following the American Society for Microbiology’s protocol [54]. Susceptibility to the following BD BBL Sensi-Disc Antimicrobial Susceptibility Test Disks was assessed: Amoxicillin/Clavulanic Acid (30 µg), Ampicillin (10 µg), Cefoxitin (30 µg), Ceftiofur (30 µg), Cephalothin (30 µg), Erythromycin (15 µg), Gentamicin (10 µg), Oxacillin (1 µg), Penicillin (10 µg), Streptomycin (10 µg), and Tetracycline (30 µg). Pirlimycin (2 µg) was also tested but sourced from Oxoid. Isolates were designated as Sensitive, Intermediate, or Resistant to each antibiotic by comparison of measured zone sizes to values from CLSI guidelines [36] or from genus-specific cut points on pamphlets provided with antibiotic disks by manufacturers when specific values were not provided by CLSI. Zone diameter breakpoints in CLSI guidelines are adapted from human data for antimicrobial agents tested except for Ceftiofur and Pirlimycin where veterinary-specific breakpoints were available for bovine mastitis associated S. aureus isolates [36]. S. aureus ATCC strain 25923 was used as a positive control.

Whole genome sequencing

S. aureus isolates were transported to University of Vermont Quality Milk Research Lab on Nutrient Agar Slants (Northeast Laboratory, ME). Isolates were transferred to tryptic soy broth with 15% glycerol for storage at -80˚C then recovered for subsequent analysis. Isolates were plated on Tryptic Soy Agar with 5% sheep blood (Northeast Laboratory, ME) for 24–48 h at 37˚C, transferred to Tryptic Soy Broth (TSB) and incubated at 37˚C to produce overnight broth culture. DNA extraction was completed from a 100uL aliquot of the overnight culture using MasterPure Gram Positive DNA Purification Kit from Biosearch Technologies. DNA was sent for quality control using Qubit quantification at UVM VIGR CORE facility. Library preparation and sequencing for Oxford Nanopore (ONT) and Illumina sequencing was conducted by the CORE facility. ONT was performed with GridION platform with SQK-LSK109 + EXP-NBD196 kit for library prep, and Illumina was performed with HiSeq platform using150bp paired-end technique with PerkinElmer Nextflex DNASeqKit for library prep.

Genome analysis

ONT long reads and Illumina short reads were assembled using the Unicycler tool to create hybrid genomes [55]. Assembled genomes were submitted to CARD to detect AMR genes, and to VirulenceFinder to detect leukocidin, hemolysin, and enterotoxin genes using default parameters [13, 37, 56,57,58]. NCBI blastn tool was used to search isolate genomes for ses, set, selv, selw, selx, sey, sez, sel26, and sel27 since these were lacking from VirulenceFinder [15]. Exotoxins genes as categorized by Virulence Factor Database (VFDB) [57], including SSLs, α, β, δ, and γ-hemolysins, and leukocidin genes were identified using Rapid Annotation using Subsystem Technology (RAST) [58,59,60] with the exception of lukMF’ which were identified using NCBI blastn tool. Sequence Type was determined using MLST tool [56, 59,60,61,62,63,64,65]. The 29 whole genomes are archived at the National Center for Biotechnology Information (NCBI) repository, under BioProject PRJNA993145.

Novel MLST confirmation

For two suspected novel STs, MLST PCR and amplicon sequencing was completed to define the variant alleles for the aroE gene from isolate UM1 and arcC gene from isolate UM9. Amplified DNA was submitted to UVM VIGR facility for Sanger sequencing. Sequences were then submitted to PubMLST for novel sequence type assignments.

Data management, statistical analysis and data visualization

Data was exported from the UMVDL custom Mastitis database into Microsoft Excel files and descriptive statistics were completed using Microsoft Excel. To test for potential changes in S. aureus isolation frequency over time the probability of a S. aureus positive culture was modeled using logistic regression with a logit transformation and date of sample submission (month and year) as the predictor, using R 4.2.2 (R Core Team, 2022). Because the UMVDL database did not record farm or cow numbers for S. aureus culture negative submissions, we were not able to include other predictors in the model. The R package “pheatmap” was used to generate presence-absence heatmaps for AMR genes and exotoxin genes in Figs. 1 and 2 [66].

Data availability

The datasets (whole genome sequence files) supporting the conclusions of this article are available in the National Center for Biotechnology Information (NCBI) repository, Bioproject PRJNA993145, https://www.ncbi.nlm.nih.gov/bioproject/PRJNA993145

Abbreviations

AMR:

Antimicrobial Resistance

CARD:

Comprehensive Antibiotic Resistance Database

CC:

Clonal Complex

MLST:

Multi Locus Sequence Type

MRSA:

Methicillin-resistant S. aureus

ONT:

Oxford Nanopore

SFP:

Staphylococcal Food Poisoning

SNP:

Single Nucleotide Polymorphism

ST:

Sequence Type

SAg:

Superantigen

UMVDL:

University of Maine Cooperative Extension Veterinary Diagnostic Laboratory

UVM:

University of Vermont

VFDB:

Virulence Factor Database

VIGR:

Vermont Integrative Genomics Resource

WGS:

Whole Genome Sequencing

References

  1. Gelasakis AI, Mavrogianni VS, Petridis IG, Vasileiou NGC, Fthenakis GC. Mastitis in sheep– The last 10 years and the future of research. Vet Microbiol. 2015;181(1–2):136–46.

    Article  CAS  PubMed  Google Scholar 

  2. Seegers H, Fourichon C, Beaudeau F. Production effects related to mastitis and mastitis economics in dairy cattle herds. Vet Res. 2003;34(5):475–91.

    Article  PubMed  Google Scholar 

  3. Tam K, Torres VJ. Staphylococcus aureus secreted toxins and extracellular enzymes. Microbiol Spectr. 2019;7(2).

  4. Matuszewska M, Murray GGR, Harrison EM, Holmes MA, Weinert LA. The evolutionary genomics of host specificity in Staphylococcus aureus. Trends Microbiol. 2020;28(6):465–77.

    Article  CAS  PubMed  Google Scholar 

  5. Rohmer C, Wolz C. The role of hlb-Converting bacteriophages in Staphylococcus aureus host adaption. Microb Physiol. 2021;31(2):109–22.

    Article  CAS  PubMed  Google Scholar 

  6. Vrieling M, Boerhout EM, Van Wigcheren GF, Koymans KJ, Mols-Vorstermans TG, De Haas CJC, et al. LukMF′ is the major secreted leukocidin of bovine Staphylococcus aureus and is produced in vivo during bovine mastitis. Sci Rep. 2016;6(1):37759.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Magro G, Biffani S, Minozzi G, Ehricht R, Monecke S, Luini M, et al. Virulence genes of S. aureus from dairy cow mastitis and contagiousness risk. Toxins. 2017;9(6):195.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Fang R, Cui J, Cui T, Guo H, Ono H, Park CH, et al. Staphylococcal enterotoxin C is an important virulence factor for mastitis. Toxins. 2019;11(3):141.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Argudín MÁ, Mendoza MC, Rodicio MR. Food poisoning and Staphylococcus aureus enterotoxins. Toxins. 2010;2(7):1751–73.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Benkerroum N. Staphylococcal enterotoxins and enterotoxin-like toxins with special reference to dairy products: an overview. Crit Rev Food Sci Nutr. 2018;58(12):1943–70.

    Article  CAS  PubMed  Google Scholar 

  11. World Health Organization [Internet]. 2021. Antimicrobial Resistance. Available from: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance

  12. Monistero V, Barberio A, Biscarini F, Cremonesi P, Castiglioni B, Graber HU, et al. Different distribution of antimicrobial resistance genes and virulence profiles of Staphylococcus aureus strains isolated from clinical mastitis in six countries. J Dairy Sci. 2020;103(4):3431–46.

    Article  CAS  PubMed  Google Scholar 

  13. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S, Cattoir V, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020;75(12):3491–500.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Parco A, Macaluso G, Foti M, Vitale M, Fisichella V, Tolone M et al. Phenotypic and genotypic study on antibiotic resistance and pathogenic factors of Staphylococcus aureus isolates from small ruminant mastitis milk in South of Italy (Sicily). Ital J Food Saf [Internet]. 2021 Oct 4 [cited 2022 Jun 24];10(3). Available from: https://www.pagepressjournals.org/index.php/ijfs/article/view/9722

  15. Nouws S, Bogaerts B, Verhaegen B, Denayer S, Laeremans L, Marchal K, et al. Whole genome sequencing provides an added value to the investigation of Staphylococcal food poisoning outbreaks. Front Microbiol. 2021;12:750278.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Chakrawarti Ac, Eckstrom K, Laaguiby P, Barlow JWa. Hybrid Illumina-Nanopore assembly improves identification of multilocus sequence types and antimicrobial resistance genes of Staphylococcus aureus isolated from Vermont dairy farms: comparison to Illumina-only and R9.4.1 nanopore-only assemblies. Access Microbiol. 2024;6:000766v3. https://doiorg.publicaciones.saludcastillayleon.es/10.1099/acmi.0.000766.v3.

    Article  CAS  Google Scholar 

  17. National Agricultural Statistics Service. 2021 State Agricultural Overview: Maine [Internet]. USDA; 2021. Available from: https://www.nass.usda.gov/Quick_Stats/Ag_Overview/stateOverview.php?state=MAINE

  18. Governor Mills J. State of Maine Proclamation: Dairy Month [Internet]. 2022. Available from: https://www.maine.gov/governor/mills/official_documents/proclamations/2022-06-dairy-month-june

  19. Patel K, Godden SM, Royster EE, Crooker BA, Johnson TJ, Smith EA, et al. Prevalence, antibiotic resistance, virulence and genetic diversity of Staphylococcus aureus isolated from bulk tank milk samples of U.S. Dairy herds. BMC Genomics. 2021;22(1):367.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wilson GJ, Tuffs SW, Wee BA, Seo KS, Park N, Connelley T et al. Bovine Staphylococcus aureus Superantigens Stimulate the Entire T Cell Repertoire of Cattle. Freitag NE, editor. Infect Immun. 2018;86(11):e00505-18.

  21. Leuenberger A, Sartori C, Boss R, Resch G, Oechslin F, Steiner A, et al. Genotypes of Staphylococcus aureus: On-farm epidemiology and the consequences for prevention of intramammary infections. J Dairy Sci. 2019;102(4):3295–309.

    Article  CAS  PubMed  Google Scholar 

  22. Yebra G, Harling-Lee JD, Lycett S, Aarestrup FM, Larsen G, Cavaco LM, et al. Multiclonal human origin and global expansion of an endemic bacterial pathogen of livestock. Proc Natl Acad Sci. 2022;119(50):e2211217119.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Bott J. Maine agricultural officials report record interest in obtaining licenses to sell dairy products [Internet]. Maine Department of Agriculture, Conservation, and Forestry; 2015 Mar. Available from: https://www.maine.gov/dacf/about/news/news.shtml?id=639130

  24. Me Stat. tit. 7, § 2902-B [Internet]. Available from: https://legislature.maine.gov/statutes/7/title7sec2902-B.html

  25. Koski L, Kisselburgh H, Landsman L, Hulkower R, Howard-Williams M, Salah Z, et al. Foodborne illness outbreaks linked to unpasteurised milk and relationship to changes in state laws– United States, 1998–2018. Epidemiol Infect. 2022;150:e183.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Johler S, Giannini P, Jermini M, Hummerjohann J, Baumgartner A, Stephan R. Further evidence for Staphylococcal food poisoning outbreaks caused by egc-Encoded enterotoxins. Toxins. 2015;7(3):997–1004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Scallan E, Hoekstra RM, Angulo FJ, Tauxe RV, Widdowson MA, Roy SL, Jones JL, Griffin PM. Foodborne illness acquired in the united States–major pathogens. Emerg Infect Dis. 2011;17(1):7–15. https://doiorg.publicaciones.saludcastillayleon.es/10.3201/eid1701.p11101.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hoekstra J, Zomer AL, Rutten VPMG, Benedictus L, Stegeman A, Spaninks MP, et al. Genomic analysis of European bovine Staphylococcus aureus from clinical versus subclinical mastitis. Sci Rep. 2020;10(1):18172.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Woudstra S, Wente N, Zhang Y, Leimbach S, Gussmann MK, Kirkeby C, et al. Strain diversity And infection durations of Staphylococcus spp. And Streptococcus spp. Causing intramammary infections in dairy cows. J Dairy Sci. 2023;106(6):4214–31.

    Article  CAS  PubMed  Google Scholar 

  30. Thomas A, Chothe S, Byukusenge M, Mathews T, Pierre T, Kariyawasam S, et al. Prevalence and distribution of multilocus sequence types of Staphylococcus aureus isolated from bulk tank milk and cows with mastitis in Pennsylvania. PLoS ONE. 2021;16(3):e0248528.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Naushad S, Nobrega DB, Naqvi SA, Barkema HW, De Buck J. Genomic analysis of bovine Staphylococcus aureus isolates from milk to elucidate diversity and determine the distributions of antimicrobial and virulence genes and their association with mastitis. mSystems. 2020;5(4):e00063–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Chakrawarti A, Casey CL, Burk A, Mugabi R, Ochoa A, Barlow JW. An observational study demonstrates human-adapted Staphylococcus aureus strains have a higher frequency of antibiotic resistance compared to cattle-adapted strains isolated from dairy farms making farmstead cheese. BMC Vet Res. 2024;20(1):75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Bruce SA, Smith JT, Mydosh JL, Ball J, Needle DB, Gibson R, et al. Shared antibiotic resistance and virulence genes in Staphylococcus aureus from diverse animal hosts. Sci Rep. 2022;12(1):4413.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. McMillan K, Moore SC, McAuley CM, Fegan N, Fox EM. Characterization of Staphylococcus aureus isolates from Raw milk sources in Victoria, Australia. BMC Microbiol. 2016;16(1):169.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Mugabi R, Genotypes. and phenotypes of Staphylococci on selected dairy farms in Vermont [Internet] [PhD Diss]. [Graduate College Dissertations and Theses]: University of Vermont; 2018. Available from: https://scholarworks.uvm.edu/graddis/844?utm_source=scholarworks.uvm.edu%2Fgraddis%2F844%26utm_medium=PDF%26utm_campaign=PDFCoverPages

  36. CLSI. Performance standards for antimicrobial disk and Dilution susceptibility tests for Bacteria isolated from animals. 6th ed. Clinical and Laboratory Standards Institute; 2023.

  37. Alcock BP, Huynh W, Chalil R, Smith KW, Raphenya AR, Wlodarski MA, et al. CARD 2023: expanded curation, support for machine learning, and resistome prediction at the comprehensive antibiotic resistance database. Nucleic Acids Res. 2023;51(D1):D690–9.

    Article  CAS  PubMed  Google Scholar 

  38. Shi J, Yan Y, Links MG, Li L, Dillon JAR, Horsch M, et al. Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection. BMC Bioinformatics. 2019;20(Suppl 15):535.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Campos B, Pickering AC, Rocha LS, Aguilar AP, Fabres-Klein MH, de Oliveira Mendes TA, et al. Diversity and pathogenesis of Staphylococcus aureus from bovine mastitis: current Understanding and future perspectives. BMC Vet Res. 2022;18(1):115.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Schmidt T, Kock MM, Ehlers MM. Molecular characterization of Staphylococcus aureus isolated from bovine mastitis and close human contacts in South African dairy herds: genetic diversity and Inter-Species host transmission. Front Microbiol. 2017;8:511.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Hoekstra J, Rutten VPMG, Van Den Hout M, Spaninks MP, Benedictus L, Koop G. Differences between Staphylococcus aureus lineages isolated from ovine and caprine mastitis but not between isolates from clinical or subclinical mastitis. J Dairy Sci. 2019;102(6):5430–7.

    Article  CAS  PubMed  Google Scholar 

  42. Etter D, Schelin J, Schuppler M, Johler S. Staphylococcal enterotoxin C-An update on SEC variants, their structure and properties, and their role in foodborne intoxications. Toxins. 2020;12(9):584.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. D’amico DJ, Donnelly CW. Characterization of Staphylococcus aureus strains isolated from Raw milk utilized in small-scale artisan cheese production. J Food Prot. 2011;74(8):1353–8.

    Article  PubMed  Google Scholar 

  44. Kotzamanidis C, Vafeas G, Giantzi V, Anastasiadou S, Mygdalias S, Malousi A, et al. Staphylococcus aureus isolated from ruminants with mastitis in Northern Greece dairy herds: genetic relatedness and phenotypic and genotypic characterization. Toxins. 2021;13(3):176.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Veras JF, Do Carmo LS, Tong LC, Shupp JW, Cummings C, Dos Santos DA, et al. A study of the enterotoxigenicity of coagulase-negative and coagulase-positive Staphylococcal isolates from food poisoning outbreaks in Minas Gerais, Brazil. Int J Infect Dis. 2008;12(4):410–5.

    Article  CAS  PubMed  Google Scholar 

  46. Fitzgerald JR, Monday SR, Foster TJ, Bohach GA, Hartigan PJ, Meaney WJ, et al. Characterization of a putative pathogenicity Island from bovine Staphylococcus aureus encoding multiple superantigens. J Bacteriol. 2001;183(1):63–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Abril AG, Villa TG, Barros-Velázquez J, Cañas B, Sánchez-Pérez A, Calo-Mata P, et al. Staphylococcus aureus exotoxins and their detection in the dairy industry and mastitis. Toxins. 2020;12(9):E537.

    Article  Google Scholar 

  48. Schwendimann L, Merda D, Berger T, Denayer S, Feraudet-Tarisse C, Kläui AJ et al. D Ercolini editor 2021 Staphylococcal enterotoxin gene cluster: prediction of enterotoxin (SEG and SEI) production and of the source of food poisoning on the basis of V Saβ typing. Appl Environ Microbiol 87 5 e02662–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Jarraud S, Peyrat MA, Lim A, Tristan A, Bes M, Mougel C et al. egc, A Highly Prevalent Operon of Enterotoxin Gene, Forms a Putative Nursery of Superantigens in Staphylococcus aureus. J Immunol. 2001;166(1):669–77.

  50. Veh KA, Klein RC, Ster C, Keefe G, Lacasse P, Scholl D, et al. Genotypic and phenotypic characterization of Staphylococcus aureus causing persistent and nonpersistent subclinical bovine intramammary infections during lactation or the dry period. J Dairy Sci. 2015;98(1):155–68.

    Article  CAS  PubMed  Google Scholar 

  51. Aung MS, Urushibara N, Kawaguchiya M, Ito M, Habadera S, Kobayashi N. Prevalence and genetic diversity of Staphylococcal enterotoxin (-Like) genes Sey, Selw, Selx, Selz, sel26 and sel27 in Community-Acquired Methicillin-Resistant Staphylococcus aureus. Toxins. 2020;12(5):347.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Zhang DF, Yang XY, Zhang J, Qin X, Huang X, Cui Y, et al. Identification and characterization of two novel superantigens among Staphylococcus aureus complex. Int J Med Microbiol IJMM. 2018;308(4):438–46.

    Article  CAS  PubMed  Google Scholar 

  53. Adkins PR, Middleton JR. Laboratory handbook on bovine mastitis. National Mastitis Council, Incorporated; 2017.

  54. Hudzicki J. Kirby-Bauer Disk Diffusion Suceptibility Testing Protocol [Internet]. American Society for Microbiology; 2009. Available from: https://asm.org/getattachment/2594ce26-bd44-47f6-8287-0657aa9185ad/Kirby-Bauer-Disk-Diffusion-Susceptibility-Test-Protocol-pdf.pdf

  55. Wick RR, Judd LM, Gorrie CL, Holt KE, Unicycler. Resolving bacterial genome assemblies from short and long sequencing reads. Phillippy AM, editor. PLOS Comput Biol. 2017;13(6):e1005595.

  56. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10(1):421.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Malberg Tetzschner AM, Johnson JR, Johnston BD, Lund O, Scheutz F. In Silico Genotyping of Escherichia coli Isolates for Extraintestinal Virulence Genes by Use of Whole-Genome Sequencing Data. Dekker JP, editor. J Clin Microbiol. 2020;58(10):e01269-20.

  58. Joensen KG, Scheutz F, Lund O, Hasman H, Kaas RS, Nielsen EM, et al. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J Clin Microbiol. 2014;52(5):1501–10.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Bartual SG, Seifert H, Hippler C, Luzon MAD, Wisplinghoff H, Rodríguez-Valera F. Development of a multilocus sequence typing scheme for characterization of clinical isolates of Acinetobacter baumannii. J Clin Microbiol. 2005;43(9):4382–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Griffiths D, Fawley W, Kachrimanidou M, Bowden R, Crook DW, Fung R, et al. Multilocus sequence typing of Clostridium difficile. J Clin Microbiol. 2010;48(3):770–8.

    Article  CAS  PubMed  Google Scholar 

  61. Jaureguy F, Landraud L, Passet V, Diancourt L, Frapy E, Guigon G, et al. Phylogenetic and genomic diversity of human bacteremic Escherichia coli strains. BMC Genomics. 2008;9:560.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Larsen MV, Cosentino S, Rasmussen S, Friis C, Hasman H, Marvig RL, et al. Multilocus sequence typing of total-genome-sequenced bacteria. J Clin Microbiol. 2012;50(4):1355–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Lemee L, Dhalluin A, Pestel-Caron M, Lemeland JF, Pons JL. Multilocus sequence typing analysis of human and animal Clostridium difficile isolates of various toxigenic types. J Clin Microbiol. 2004;42(6):2609–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Wirth T, Falush D, Lan R, Colles F, Mensa P, Wieler LH, et al. Sex and virulence in Escherichia coli: an evolutionary perspective. Mol Microbiol. 2006;60(5):1136–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Jolley KA, Bray JE, Maiden MCJ. Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications. Wellcome Open Res. 2018;3:124.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Kolde R. _pheatmap: Pretty Heatmaps_ R package. 2019.

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Acknowledgements

Sequencing services were provided by the Vermont Integrative Genomics Resource DNA Facility and supported by the University of Vermont Cancer Center, Lake Champlain Cancer Research Organization, and the UVM Larner College of Medicine. Statistical support was provided by Dr. Maria Sckolnick from Statistical Software Support & Consulting Services, University of Vermont, Burlington, VT.

Funding

This project was funded by the USDA Vermont Experiment Station Multi-State NE1048 “Mastitis Resistance to Enhance Dairy Food Safety” Hatch project (VT-H02909MS), National Science Foundation Research Experience for Undergraduates Accelerating New Environmental Workskills (NSF Award #1849802), and the University of Maine Cooperative Extension Veterinary Diagnostic Laboratory.

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Authors and Affiliations

  1. Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT, USA

    E. Roadcap

  2. Veterinary Diagnostic Laboratory, Cooperative Extension, University of Maine, Orono, ME, USA

    A. Lichtenwalner, B. Kennedy-Wade & G. Adjapong

  3. School of Food and Agriculture, University of Maine, Orono, ME, USA

    A. Lichtenwalner

  4. Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT, USA

    A. Chakrawarti, F. Machado De Sant’Anna & John W. Barlow

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Contributions

E.R. contributed to conceptualization and design of study, laboratory investigations, data curation, formal analysis, data visualization, and manuscript writing. B.K.W. contributed to microbiological diagnostics, data collection and management. A.L. and J.W.B. contributed to conceptualization and design of study, methodology, data curation, resources, supervision, funding acquisition, project administration, and manuscript writing. A.C. and F.M.S.A. contributed to whole genome sequencing and bioinformatics analysis, data visualization, and manuscript review. G.A. contributed to data analysis and manuscript review. All authors reviewed the manuscript.

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Correspondence to John W. Barlow.

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Roadcap, E., Lichtenwalner, A., Kennedy-Wade, B. et al. Whole genome sequencing identifies exotoxin and antimicrobial resistance profiles of Staphylococcus aureus from Maine dairy farms. BMC Vet Res 21, 154 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12917-025-04630-1

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