An update on non-aureus staphylococci and mammaliicocci in cow milk: unveiling the presence of Staphylococcus borealis and Staphylococcus rostri by MALDI-TOF MS

An update on non-aureus staphylococci and mammaliicocci in cow milk: unveiling the presence of Staphylococcus borealis and Staphylococcus rostri by MALDI-TOF MS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An update on non-aureus staphylococci and mammaliicocci in cow milk: unveiling the presence of Staphylococcus borealis and Staphylococcus rostri by MALDI-TOF MS Martina Penati, Fernando Ulloa, Clara Locatelli, Valentina Monistero, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4218430/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Jun, 2024 Read the published version in Veterinary Research Communications → Version 1 posted 11 You are reading this latest preprint version Abstract Non-aureus staphylococci and mammaliicocci (NASM) are microorganisms most frequently isolated from milk. Given their numerosity and complexity, MALDI-TOF MS is one of the preferred species identification approaches. Nevertheless, reference mass spectra for the novel species Staphylococcus borealis were included only recently in the Bruker Biotyper System (MBT) library, and other species of veterinary interest such as S. rostri are still absent. This work provides an updated picture of the NASM species found in milk, gained by retrospectively analyzing the data relating to 21,864 milk samples, of which 6,278 from clinical mastitis (CM), 4,039 from subclinical mastitis (SCM), and 11,547 from herd survey (HS), with a spectrum library including both species. As a result, S. borealis was the second most frequently isolated NASM (17.07%) after S. chromogenes (39.38%) in all sample types, with a slightly higher percentage in CM (21.84%), followed by SCM (17.65%), and HS (14.38%). S. rostri was also present in all sample types (3.34%), reaching 8.43% of all NASM in SCM and showing a significant association (p < 0.01) with this condition. Based on our findings, the presence of S. borealis and S. rostri in milk and their potential association with mastitis has been overlooked, possibly due to the difficulties in differentiating these species from other closely related NASM. Our results indicate that S. borealis might be a more frequent contributor to bovine udder infections than previously thought and that S. rostri should also not be underestimated considering its significant association with SCM. NASM S. borealis S. rostri mastitis coagulase-negative staphylococci dairy ruminant milk Figures Figure 1 Introduction The bacteria most frequently isolated from cow milk are non- aureus staphylococci and mammaliicocci (NASM) (Ruiz-Romero and Vargas-Bello-Pérez 2023 ; Reydams et al. 2023 ). However, their specific ability to establish intramammary infection (IMI) and cause mastitis, particularly subclinical mastitis (SCM), is still not entirely clarified. In the last years, the epidemiology of NASM species and their relationships with bovine mammary gland health are getting increasing attention (Lienen et al. 2022 ; Ruiz-Romero and Vargas-Bello-Pérez 2023 ). Studies have shown that different NASM behave differently, which can lead to different outcomes in mastitis cases (De Buck et al. 2021 ; Souza et al. 2023 ). Therefore, obtaining a precise species identification can be relevant; by clarifying the relationships between species and clinical outcomes, we might be able to ultimately improve animal health (Condas et al. 2017 ; Ruiz-Romero and Vargas-Bello-Pérez 2023 ). The Staphylococcus genus encompasses over 88 species. Due to limitations in traditional biochemical tests, their laboratory identification can present some challenges. Genotypic methods, such as sequencing of 16s RNA , rpoB , or hsp60 genes, offer improved accuracy, but are time and labor-demanding, and may fail to differentiate closely related species (Vanderhaeghen et al. 2014 ; Pain et al. 2020 ). Being mainly of veterinary interest, the 5 species belonging to the novel genus Mammaliicoccus are also neglected in biochemical galleries, and optimized, validated molecular tests are less available. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is recognized as a rapid and precise method for the identification of bacteria isolated from milk (Nonnemann et al. 2019 ). Regular updates of the MALDI-TOF MS library and the inclusion of mass spectra from new species and field isolates can further improve the reliability and accuracy of bacterial identification at the species level, including the NASM group (De Buck et al. 2021 ). According to the recent literature, the NASM species most commonly isolated from milk are S. chromogenes , S. haemolyticus , S. xylosus , S. simulans , and S. epidermidis (Vanderhaeghen et al. 2014 ; De Buck et al. 2021 ). In line with this, in two recent surveys from our research group the NASM most frequently isolated from clinical mastitis (CM) and SCM quarters were S. chromogenes and S. haemolyticus . S. haemolyticus was also frequently isolated from composite herd survey (HS) milk (Freu et al. 2023 ; Addis et al. 2024 ). Recently, some S. haemolyticus were reclassified to the newly defined species S. borealis . S. borealis was isolated from the skin and blood of six people in Norway and Denmark. These isolates initially appeared to be S. haemolyticus due to the extremely high similarity (99.86–99.93%) in the 16S rRNA gene. However, whole-genome sequencing highlighted the presence of significant differences, with only ~ 88% average nucleotide identity compared to the S. haemolyticus type strain. This led to their reclassification as S. borealis (Pain et al. 2020 ). S. borealis is both genetically and phenotypically diverse, suggesting that separate bacterial strains live in different host types. Indeed, recent data has indicated that cow strains might be closer to each other than to human strains, suggesting a separate evolution in these hosts (Król et al. 2023 ). Up to now, S. borealis has been isolated from the milk of cows with mastitis in Finland, Canada, Poland, and USA (Taponen et al. 2022 ; Król et al. 2023 ; Freu et al. 2023 ). Thus, understanding the prevalence and distribution of S. borealis and its association with mastitis can be of interest for understanding its relationships with mammary gland health. Although not as frequently as S. chromogenes and S. haemolyticus , S. microti has also been isolated from CM, SCM, and HS milk. Our two surveys indicated percentages around 1% for CM, 4% for SCM and 1.5% for HS milk (Freu et al. 2023 ; Addis et al. 2024 ). A recent work reported that the identification by MALDI-TOF MS of NASM isolated from milk as S. microti might have been subjected to misclassification (Kløve et al. 2023 ). By applying whole genome sequencing, these authors analyzed a total of 81 milk isolates identified as S. microti by MALDI-TOF MS, finding that these belonged to the S. rostri species They revealed a strong genetic intra-herd conservation, implying the bovine adaptation of S. rostri and its ability to specifically spread within this host. Accordingly, the existence of S. rostri and its relevance for bovine mammary gland health might have been overlooked so far. Based on these premises, this work aims to provide an updated picture of the NASM species distribution by retrospectively analyzing the results obtained by MALDI-TOF MS on CM, SCM, and HS milk, throughout one year by MALDI-TOF MS against a library including spectra for S. borealis and S. rostri , to shed light on their presence in dairy cow milk. The study was carried out in northern Italy, an area characterized by a high dairy herd density playing a relevant role in the European dairy production (CLAL, 2022). Materials and methods Milk samples and contributing herds We retrieved the bacteriological results related to the milk samples sent to the Animal Infectious Disease Laboratory (MiLab), University of Milan, between December 2022 and November 2023. The study included 106 dairy farms from Northern Italy housing Holstein-Friesian cows in free-stall barns, which sent CM, SCM and HS milk samples. For CM, trained personnel, guided by established clinical criteria (Adkins et al., 2018), identified affected mammary quarters through visual examination of first milk streams for abnormal characteristics such as flakes, clots, discolouration, or watery consistency, alongside swelling, redness, and pain in the udder. The SCM originated from cows with elevated SCC in the latest DHI recording, which underwent further evaluation with the California Mastitis Test (CMT). Samples from quarters testing positive for CMT without clinical signs were classified SCM according to established criteria (Adkins et al., 2018). Finally, composite HS samples were collected during total herd samplings to assess herd-level prevalence of infectious pathogens. All personnel adhered to National Mastitis Council (NMC) protocols (Adkins et al., 2018) during sample collection, employing pre-dipping disinfectant and alcohol-containing wipes for teat disinfection before taking the samples, and promptly sending them to the laboratory in a refrigerated box. Bacteriological analysis of milk Milk samples were cultured following the NMC (Middleton et al., 2017 ). Briefly, 10 µL of milk was spread on blood agar (Microbiol, Cagliari, Italy) and incubated aerobically at 37°C for 24–48 hours. Plates were then interpreted and classified as positive, contaminated, or negative according to NMC criteria (Adkins et al., 2017 ). From the positive plates, the isolated colonies were identified using MALDI-TOF MS (Rosa et al. 2022 ) and the spectra were processed with the MALDI Biotper (MBT) Compass® Library Revision H (2021) (Bruker Daltonik GmbH, Bremen, Germany). A custom MALDI-TOF MS library was used for this analysis. It included two strains of S. rostri that were previously identified by sequencing the rpoB gene (Locatelli et al. 2013 ). Data analysis Since November 30, 2022, when the MBT library was updated with the mass spectra for S. borealis and S. rostri , 21,864 milk samples were analyzed, including 6,278 CM, 4,039 SCM, and 11,547 composite HS samples. Information on farm ID, sampling dates, sample types, microbiological results, and identification scores were stored in a Microsoft Access database, together with information on clinical/subclinical status. The data used for this work was extracted using Microsoft Excel (Microsoft Office, version 16.82, 2024). Pivot tables and built-in Excel functions were employed to generate descriptive statistics. Statistical analysis was carried out using SPSS 28.0 (IBM, SPSS, Armonk, USA). A multinomial logistic regression model was used to compare the relative prevalence of NASM species in CM and SCM. The subclinical outcome served as the reference category for estimation of parameters using Wald statistics. Significance for the analyses was determined with p-values < 0.05 and < 0.01.For estimating the within-farm distribution of NASM species, only farms sending at least 10 samples of which one positive for NASM were considered. Results Microbiology results according to the sample type: quarter and composite milk samples The microbiological culture results obtained on the 21,864 milk samples are summarized in Table 1 according to the sample type. Out of 6,278 CM milk samples collected from 96 herds, 63.57% (3,991) were positive, of which 17.66% (705) were positive for NASM. Out of 4,039 SCM milk samples collected from 34 herds, 69.03% (2,788) of samples were positive, of which 31.49% (878) for NASM. Out of 11,547 composite HS milk samples collected from 33 herds, 32.37% (3,738) were positive, of which 38.5% (1,439) for NASM (Table 1 ). Table 1 Bacteriological culture results obtained for all the milk samples considered in this study, according to their respective categories. Results Clinical quarter milk Subclinical quarter milk Composite herd survey milk Total Negative 1,578 (25.14%) 892 (22.08%) 7,113 (61.6%) 9,583 (43.83%) Contaminated 709 (11.29%) 359 (8.89%) 696 (6.03%) 1,764 (8.07%) Positive 3,991 (63.57%) 2,788 (69.03%) 3,738 (32.37%) 10,517 (48.10%) Of which NASM* 705 (17.66%) 878 (31.49%) 1,439 (38.5%) 3,022 (28.73%) Total 6,278 4,039 11,547 21,864 *NASM percentage on the total positive samples in each category. NASM species isolated from mastitis and herd survey milk and identified by MALDI-TOF MS with the MBT System Species information could be retrieved for 3,022 NASM isolates. A total of 19 distinct NASM species were identified and are reported in Table 2 with their respective average MALDI-TOF MS Log score. S. chromogenes was the first species with 39.38%, followed by S. borealis (17.07%) and M. sciuri (9.89%). The average identification Log score was 2.08, with a minimum of 1.77 for S. gallinarum and a maximum of 2.43 for S. rostri . Table 2 Total number of isolates for each NASM species with their respective average MALDI-TOF MS Log score. NASM species Number of isolates (%) Average Log score S. chromogenes 1,190 (39.38%) 2.14 S. borealis 516 (17.07%) 2.13 M. sciuri 299 (9.89%) 1.95 S. xylosus 262 (8.67%) 1.98 S. epidermidis 224 (7.41%) 2.05 S. haemolyticus 197 (6.52%) 1.93 S. rostri 101 (3.34%) 2.43 S. simulans 64 (2.12%) 2.07 S. arlettae 52 (1.72%) 1.82 S. equorum 46 (1.52%) 2.02 S. saprophyticus 19 (0.63%) 2.00 S. agnetis/hyicus 1 16 (0.53%) 2.11 S. gallinarum 14 (0.46%) 1.77 S. capitis 8 (0.26%) 1.93 S. cohnii 6 (0.2%) 1.93 S. hominis 3 (0.1%) 1.97 S. succinus 3 (0.1%) 1.88 S. microti 1 (0.03%) 2.29 S. schleiferi 1 (0.03%) 2.28 Total 3,022 (100.00%) 2.08 1 MALDI-TOF MS does not differentiate these two species. Table 3 reports the NASM species identified according to the sample type. The three most frequent NASM in CM quarters were S. chromogenes (24.82%), S. borealis (21.84%), and M. sciuri (20.57%), with similar prevalence levels. In SCM quarters, S. chromogenes was also the most prevalent species (31.78%) followed by S. borealis , albeit with slightly lower percentages (17.65%). S. xylosus was third (10.59%). In composite milk, S. chromogenes was largely predominant, representing over half (51.15%) of the isolates, once again followed by S. borealis (14.38%). Among other NASM species, M. sciuri , S. equorum , and S. arlettae were significantly more present in CM, while S. xylosus , S. epidermidis , and S. rostri were significantly more present in SCM samples (p < 0.01; Supplementary Table). Table 3 Distribution of NASM species across bovine clinical mastitis, subclinical mastitis, and herd survey milk samples. Clinical quarter Number of isolates (%) Subclinical quarter Number of isolates (%) Composite herd survey Number of isolates (%) S. chromogenes 175 (24.82%) S. chromogenes 279 (31.78%) S. chromogenes 736 (51.15%) S. borealis 154 (21.84%) S. borealis 155 (17.65%) S. borealis 207 (14.38%) M. sciuri 145 (20.57%) S. xylosus 93 (10.59%) S. epidermidis 114 (7.92%) S. xylosus 73 (10.36%) S. epidermidis 83 (9.45%) S. xylosus 96 (6.67%) S. haemolyticus 54 (7.66%) S. haemolyticus 74 (8.43%) M. sciuri 93 (6.46%) S. epidermidis 27 (3.83%) S. rostri 74 (8.43%) S. haemolyticus 69 (4.79%) S. equorum 23 (3.26%) M. sciuri 61 (6.95%) S. simulans 39 (2.71%) S. arlettae 19 (2.7%) S. simulans 16 (1.82%) S. arlettae 24 (1.67%) S. simulans 9 (1.28%) S. equorum 12 (1.37%) S. rostri 21 (1.46%) S. gallinarum 6 (0.85%) S. arlettae 9 (1.03%) S. equorum 11 (0.76%) S. rostri 6 (0.85%) S. saprophyticus 6 (0.68%) S. agnetis/S. hyicus 1 8 (0.56%) S. saprophyticus 6 (0.85%) S. gallinarum 5 (0.57%) S. saprophyticus 7 (0.49%) S. agnetis/S. hyicus 1 5 (0.71%) S. capitis 3 (0.34%) S. cohnii 5 (0.35%) S. succinus 2 (0.28%) S. agnetis/S. hyicus 1 3 (0.34%) S. capitis 4 (0.28%) S. capitis 1 (0.14%) S. cohnii 1 (0.11%) S. gallinarum 3 (0.21%) S. cohnii - S. hominis 1 (0.11%) S. hominis 2 (0.14%) S. hominis - S. microti 1 (0.11%) S. microti - S. microti - S. schleiferi 1 (0.11%) S. schleiferi - S. schleiferi - S. succinus 1 (0.11%) S. succinus - Total 705 Total 878 Total 1,439 1 MALDI-TOF MS does not differentiate these two species. NASM distribution by farm A varied distribution of NASM species was observed in the farms sending composite HS samples (Fig. 1 ). S. chromogenes was isolated in all but one farm (96.43%) and was the main NASM in over half of the farms (57.14%). Notably, S. borealis was the second species, being present in 22 of 28 farms (78.57%) and representing the main NASM in 6 of 28 farms (21.42%). Other frequently identified NASM were M. sciuri (64,29%), S. xylosus (60,71%), S. epidermidis (46,73%), S. haemolyticus (46,43%) and S. simulans (42,86%). S. rostri was isolated in 8 out of 28 farms (28.57%) but it was never the most prevalent NASM species found in the herd. Discussion The relevance of NASM for animal welfare and milk quality is increasingly recognized in light of their association with CM and SCM in modern dairy farms (Schukken et al. 2009 ; De Buck et al. 2021 ; Ruiz-Romero and Vargas-Bello-Pérez 2023 ). This retrospective study investigated the prevalence of various NASM species identified by the MBT System with the aim of gathering novel information on S. borealis and S. rostri . In the course of one year, we identified 19 different NASM species on a total of 21,864 samples including CM, SCM and HS milk. Of these, S. borealis was the second most common species after S. chromogenes across sample types. Therefore, our results indicate that S. borealis might be a more frequent contributor to bovine udder infections than previously thought, confirming the recent findings from our group in the US (Freu et al. 2023 ) and in line with the increasingly reported presence of S. borealis within cattle population as a possible cause of IMI (Król et al. 2023 ). In our previous retrospective studies (Freu et al. 2023 ; Addis et al. 2024 ), S. haemolyticus was the second most prevalent species after S. chromogenes . A recent systematic review by Ruiz-Romero and Vargas-Bello-Pérez ( 2023 ) also reported S. haemolyticus as the second most frequently isolated NASM. However, the identification of S. haemolyticus has created significant challenges in the past due to the elevated genomic variability combined with a high similarity of its marker genes with other species (Wanecka et al. 2018 ; Rosa et al. 2022 ). Recently, whole genome sequencing of S. haemolyticus has uncovered a significant phylogenetic distance among isolates, leading to the first description of S. borealis as a distinct species (Pain et al. 2020 ). Accordingly, isolates initially identified as S. haemolyticus were later confirmed to be S. borealis (Król et al. 2023 ). Therefore, the high similarity of its marker genes to S. haemolyticus and the absence of reference spectra in the MBT database for S. borealis have likely led to its previous misclassification as S. haemolyticus , underestimating the presence of S. borealis and overestimating S. haemolyticus (Freu et al. 2023 ). The present work confirmed that S. borealis is indeed a common cause of bovine mastitis, confirming our findings in the US for CM (Freu et al. 2023 ) and underscoring the importance of distinguishing it from S. haemolyticus for an accurate understanding of its role in CM and SCM. Its monitoring and characterization can also be important for the potential ability to spread antimicrobial resistance genes, as multidrug-resistant S. borealis strains have been already detected in pigs (Abdullahi et al. 2023 ). Another interesting finding was the emergence of S. rostri , and of its significant association with SCM, after updating our library with in-house spectra for his species. Different studies suggested that creating an internal mass spectrum library of accurately identified reference strains can significantly improve the reliability of isolate identification by MALDI-TOF MS, especially when commercially available databases include a limited number of reference spectra or when some species are absent (Cassagne et al. 2011 ; Posteraro et al. 2012 ; Kolecka et al. 2014 ). In the past, S. rostri has been identified in various hosts, including pigs (Vanderhaeghen et al. 2012 ) and water buffaloes (Locatelli et al. 2013 ). In cows, previous evidence suggested that S. rostri may serve as a pathogen contributing to mastitis and that it can persist on farms through cow-to-cow transmission or within environmental reservoirs (Jenkins et al. 2019 ; Kløve et al. 2023 ). As in the case of S. borealis , differentiating S. rostri from S. microti and S. muscae is hampered by genetic similarity as well as by limitations in existing databases (Rosa et al. 2022 ; Kløve et al. 2023 ). In our previous retrospective studies, S. microti was the sixth most prevalent NASM in SCM and the ninth and tenth, respectively, in CM cases from US and Italy (Freu et al. 2023 ; Addis et al. 2024 ). In the present study, S. rostri accounted for 8.43% of all NASM identified in SCM, while S. microti was isolated only once, suggesting that previously reported S. microti might have actually been S. rostri and that the reported prevalence data for S. microti might have been overestimated. Previous studies identified antibiotic resistance in S. rostri (Wuytack et al. 2019 ), and monitoring resistance patterns in isolates from bovine mastitis could also be an area for future research. Regarding the potential association of NASM with mastitis cases, S. borealis was detected more frequently in CM, but it was not preferentially associated with SCM or CM. On the other hand, S. rostri was significantly associated with SCM. Concerning NASM species isolated in HS, S. borealis emerged as the second most prevalent species after S. chromogenes , with a widespread presence on most farms; S. rostri had a lower prevalence compared to the previous two NASM, being isolated from a smaller number of farms. In conclusion, the prevalence of S. borealis and S. rostri has likely been strongly underestimated due to a lack of capacity to differentiate them from closely related bacteria. The MBT database, initially focused on human pathogens (Tomazi et al. 2014 ), is gradually expanding its coverage of veterinary isolates. Continued development of this resource will be crucial for accurate identification of NASM species. By further exploring the specific impacts of different NASM species on udder health, future research can inform more targeted farm management strategies to enhance animal health and milk quality. Declarations Acknowledgements We sincerely thank the farmers and veterinarians for their collaboration and trust. Author contributions MP and MFA designed the study. CL, VM, and LFP carried out milk bacteriology and MALDI-TOF MS identification. MP, FU, CL and VB carried out data analysis. MP, FU and MFA drafted the manuscript. RP, PM, and VB contributed to data interpretation and manuscript drafting. All authors critically revised, read and approved the final manuscript. Funding This research was supported by internal funds from the Laboratory of Animal Infectious Diseases (MiLab) at the University of Milan. Competing interests The authors declare no competing interests. Ethics approval Not Applicable. Consent to participate Not applicable. Consent for publication Not applicable. 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J Dairy Sci 97:5275–5293. https://doi.org/10.3168/jds.2013-7775 Wanecka A, Król J, Twardoń J, et al (2018) Characterization of a genetically distinct subpopulation of Staphylococcus haemolyticus isolated from milk of cows with intramammary infections. Vet Microbiol 214:28–35. https://doi.org/10.1016/j.vetmic.2017.12.004 Wuytack A, De Visscher A, Piepers S, et al (2019) Non- aureus staphylococci in fecal samples of dairy cows: First report and phenotypic and genotypic characterization. J Dairy Sci 102:9345–9359. https://doi.org/10.3168/jds.2019-16662 Additional Declarations No competing interests reported. Supplementary Files Penatietalsupplementarytable.docx Cite Share Download PDF Status: Published Journal Publication published 18 Jun, 2024 Read the published version in Veterinary Research Communications → Version 1 posted Editorial decision: Revision requested 05 May, 2024 Reviews received at journal 21 Apr, 2024 Reviews received at journal 15 Apr, 2024 Reviewers agreed at journal 12 Apr, 2024 Reviewers agreed at journal 09 Apr, 2024 Reviewers agreed at journal 09 Apr, 2024 Reviewers agreed at journal 09 Apr, 2024 Reviewers invited by journal 09 Apr, 2024 Editor assigned by journal 08 Apr, 2024 Submission checks completed at journal 08 Apr, 2024 First submitted to journal 04 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Only positive farms sending at least 10 milk samples are reported.\u003c/p\u003e","description":"","filename":"Onlinedrawingimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4218430/v1/384acb135bd7523684a0222d.png"},{"id":58823536,"identity":"95190418-7a4e-4a6b-b89e-719c9ba0c0ce","added_by":"auto","created_at":"2024-06-21 17:02:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":730669,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4218430/v1/fd4d5dd8-7299-4e06-9f7a-f61a54aa7275.pdf"},{"id":54488025,"identity":"2437a277-45b7-43ec-af64-54e9a111ff6e","added_by":"auto","created_at":"2024-04-11 09:37:09","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":29202,"visible":true,"origin":"","legend":"","description":"","filename":"Penatietalsupplementarytable.docx","url":"https://assets-eu.researchsquare.com/files/rs-4218430/v1/edc348e41a6f8857b791aa8a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"An update on non-aureus staphylococci and mammaliicocci in cow milk: unveiling the presence of Staphylococcus borealis and Staphylococcus rostri by MALDI-TOF MS","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe bacteria most frequently isolated from cow milk are non-\u003cem\u003eaureus\u003c/em\u003e staphylococci and mammaliicocci (NASM) (Ruiz-Romero and Vargas-Bello-P\u0026eacute;rez \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Reydams et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, their specific ability to establish intramammary infection (IMI) and cause mastitis, particularly subclinical mastitis (SCM), is still not entirely clarified. In the last years, the epidemiology of NASM species and their relationships with bovine mammary gland health are getting increasing attention (Lienen et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ruiz-Romero and Vargas-Bello-P\u0026eacute;rez \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Studies have shown that different NASM behave differently, which can lead to different outcomes in mastitis cases (De Buck et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Souza et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, obtaining a precise species identification can be relevant; by clarifying the relationships between species and clinical outcomes, we might be able to ultimately improve animal health (Condas et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ruiz-Romero and Vargas-Bello-P\u0026eacute;rez \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eStaphylococcus\u003c/em\u003e genus encompasses over 88 species. Due to limitations in traditional biochemical tests, their laboratory identification can present some challenges. Genotypic methods, such as sequencing of \u003cem\u003e16s RNA\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, or \u003cem\u003ehsp60\u003c/em\u003e genes, offer improved accuracy, but are time and labor-demanding, and may fail to differentiate closely related species (Vanderhaeghen et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pain et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Being mainly of veterinary interest, the 5 species belonging to the novel genus \u003cem\u003eMammaliicoccus\u003c/em\u003e are also neglected in biochemical galleries, and optimized, validated molecular tests are less available. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is recognized as a rapid and precise method for the identification of bacteria isolated from milk (Nonnemann et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Regular updates of the MALDI-TOF MS library and the inclusion of mass spectra from new species and field isolates can further improve the reliability and accuracy of bacterial identification at the species level, including the NASM group (De Buck et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). According to the recent literature, the NASM species most commonly isolated from milk are \u003cem\u003eS. chromogenes\u003c/em\u003e, \u003cem\u003eS. haemolyticus\u003c/em\u003e, \u003cem\u003eS. xylosus\u003c/em\u003e, \u003cem\u003eS. simulans\u003c/em\u003e, and \u003cem\u003eS. epidermidis\u003c/em\u003e (Vanderhaeghen et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; De Buck et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In line with this, in two recent surveys from our research group the NASM most frequently isolated from clinical mastitis (CM) and SCM quarters were \u003cem\u003eS. chromogenes\u003c/em\u003e and \u003cem\u003eS. haemolyticus\u003c/em\u003e. \u003cem\u003eS. haemolyticus\u003c/em\u003e was also frequently isolated from composite herd survey (HS) milk (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Addis et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecently, some \u003cem\u003eS. haemolyticus\u003c/em\u003e were reclassified to the newly defined species \u003cem\u003eS. borealis\u003c/em\u003e. \u003cem\u003eS. borealis\u003c/em\u003e was isolated from the skin and blood of six people in Norway and Denmark. These isolates initially appeared to be \u003cem\u003eS. haemolyticus\u003c/em\u003e due to the extremely high similarity (99.86\u0026ndash;99.93%) in the 16S rRNA gene. However, whole-genome sequencing highlighted the presence of significant differences, with only\u0026thinsp;~\u0026thinsp;88% average nucleotide identity compared to the \u003cem\u003eS. haemolyticus\u003c/em\u003e type strain. This led to their reclassification as \u003cem\u003eS. borealis\u003c/em\u003e (Pain et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). \u003cem\u003eS. borealis\u003c/em\u003e is both genetically and phenotypically diverse, suggesting that separate bacterial strains live in different host types. Indeed, recent data has indicated that cow strains might be closer to each other than to human strains, suggesting a separate evolution in these hosts (Kr\u0026oacute;l et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Up to now, \u003cem\u003eS. borealis\u003c/em\u003e has been isolated from the milk of cows with mastitis in Finland, Canada, Poland, and USA (Taponen et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kr\u0026oacute;l et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Thus, understanding the prevalence and distribution of \u003cem\u003eS. borealis\u003c/em\u003e and its association with mastitis can be of interest for understanding its relationships with mammary gland health.\u003c/p\u003e \u003cp\u003eAlthough not as frequently as \u003cem\u003eS. chromogenes\u003c/em\u003e and S. \u003cem\u003ehaemolyticus\u003c/em\u003e, \u003cem\u003eS. microti\u003c/em\u003e has also been isolated from CM, SCM, and HS milk. Our two surveys indicated percentages around 1% for CM, 4% for SCM and 1.5% for HS milk (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Addis et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A recent work reported that the identification by MALDI-TOF MS of NASM isolated from milk as \u003cem\u003eS. microti\u003c/em\u003e might have been subjected to misclassification (Kl\u0026oslash;ve et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). By applying whole genome sequencing, these authors analyzed a total of 81 milk isolates identified as \u003cem\u003eS. microti\u003c/em\u003e by MALDI-TOF MS, finding that these belonged to the \u003cem\u003eS. rostri\u003c/em\u003e species They revealed a strong genetic intra-herd conservation, implying the bovine adaptation of \u003cem\u003eS. rostri\u003c/em\u003e and its ability to specifically spread within this host. Accordingly, the existence of \u003cem\u003eS. rostri\u003c/em\u003e and its relevance for bovine mammary gland health might have been overlooked so far.\u003c/p\u003e \u003cp\u003eBased on these premises, this work aims to provide an updated picture of the NASM species distribution by retrospectively analyzing the results obtained by MALDI-TOF MS on CM, SCM, and HS milk, throughout one year by MALDI-TOF MS against a library including spectra for \u003cem\u003eS. borealis\u003c/em\u003e and \u003cem\u003eS. rostri\u003c/em\u003e, to shed light on their presence in dairy cow milk. The study was carried out in northern Italy, an area characterized by a high dairy herd density playing a relevant role in the European dairy production (CLAL, 2022).\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMilk samples and contributing herds\u003c/h2\u003e \u003cp\u003eWe retrieved the bacteriological results related to the milk samples sent to the Animal Infectious Disease Laboratory (MiLab), University of Milan, between December 2022 and November 2023. The study included 106 dairy farms from Northern Italy housing Holstein-Friesian cows in free-stall barns, which sent CM, SCM and HS milk samples. For CM, trained personnel, guided by established clinical criteria (Adkins et al., 2018), identified affected mammary quarters through visual examination of first milk streams for abnormal characteristics such as flakes, clots, discolouration, or watery consistency, alongside swelling, redness, and pain in the udder. The SCM originated from cows with elevated SCC in the latest DHI recording, which underwent further evaluation with the California Mastitis Test (CMT). Samples from quarters testing positive for CMT without clinical signs were classified SCM according to established criteria (Adkins et al., 2018). Finally, composite HS samples were collected during total herd samplings to assess herd-level prevalence of infectious pathogens. All personnel adhered to National Mastitis Council (NMC) protocols (Adkins et al., 2018) during sample collection, employing pre-dipping disinfectant and alcohol-containing wipes for teat disinfection before taking the samples, and promptly sending them to the laboratory in a refrigerated box.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBacteriological analysis of milk\u003c/h2\u003e \u003cp\u003eMilk samples were cultured following the NMC (Middleton et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Briefly, 10 \u0026micro;L of milk was spread on blood agar (Microbiol, Cagliari, Italy) and incubated aerobically at 37\u0026deg;C for 24\u0026ndash;48 hours. Plates were then interpreted and classified as positive, contaminated, or negative according to NMC criteria (Adkins et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). From the positive plates, the isolated colonies were identified using MALDI-TOF MS (Rosa et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and the spectra were processed with the MALDI Biotper (MBT) Compass\u0026reg; Library Revision H (2021) (Bruker Daltonik GmbH, Bremen, Germany). A custom MALDI-TOF MS library was used for this analysis. It included two strains of \u003cem\u003eS. rostri\u003c/em\u003e that were previously identified by sequencing the \u003cem\u003erpoB\u003c/em\u003e gene (Locatelli et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eSince November 30, 2022, when the MBT library was updated with the mass spectra for \u003cem\u003eS. borealis\u003c/em\u003e and \u003cem\u003eS. rostri\u003c/em\u003e, 21,864 milk samples were analyzed, including 6,278 CM, 4,039 SCM, and 11,547 composite HS samples. Information on farm ID, sampling dates, sample types, microbiological results, and identification scores were stored in a Microsoft Access database, together with information on clinical/subclinical status. The data used for this work was extracted using Microsoft Excel (Microsoft Office, version 16.82, 2024). Pivot tables and built-in Excel functions were employed to generate descriptive statistics. Statistical analysis was carried out using SPSS 28.0 (IBM, SPSS, Armonk, USA). A multinomial logistic regression model was used to compare the relative prevalence of NASM species in CM and SCM. The subclinical outcome served as the reference category for estimation of parameters using Wald statistics. Significance for the analyses was determined with p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u0026lt;\u0026thinsp;0.01.For estimating the within-farm distribution of NASM species, only farms sending at least 10 samples of which one positive for NASM were considered.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiology results according to the sample type: quarter and composite milk samples\u003c/h2\u003e \u003cp\u003eThe microbiological culture results obtained on the 21,864 milk samples are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e according to the sample type. Out of 6,278 CM milk samples collected from 96 herds, 63.57% (3,991) were positive, of which 17.66% (705) were positive for NASM. Out of 4,039 SCM milk samples collected from 34 herds, 69.03% (2,788) of samples were positive, of which 31.49% (878) for NASM. Out of 11,547 composite HS milk samples collected from 33 herds, 32.37% (3,738) were positive, of which 38.5% (1,439) for NASM (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBacteriological culture results obtained for all the milk samples considered in this study, according to their respective categories.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical quarter milk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubclinical quarter milk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eComposite herd survey milk\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,578 (25.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e892 (22.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,113 (61.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,583 (43.83%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContaminated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e709 (11.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e359 (8.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e696 (6.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,764 (8.07%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,991 (63.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,788 (69.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,738 (32.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10,517 (48.10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOf which NASM*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e705 (17.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e878 (31.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,439 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,022 (28.73%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21,864\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*NASM percentage on the total positive samples in each category.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNASM species isolated from mastitis and herd survey milk and identified by MALDI-TOF MS with the MBT System\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSpecies information could be retrieved for 3,022 NASM isolates. A total of 19 distinct NASM species were identified and are reported in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e with their respective average MALDI-TOF MS Log score. \u003cem\u003eS. chromogenes\u003c/em\u003e was the first species with 39.38%, followed by \u003cem\u003eS. borealis\u003c/em\u003e (17.07%) and \u003cem\u003eM. sciuri\u003c/em\u003e (9.89%). The average identification Log score was 2.08, with a minimum of 1.77 for \u003cem\u003eS. gallinarum\u003c/em\u003e and a maximum of 2.43 for \u003cem\u003eS. rostri\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal number of isolates for each NASM species with their respective average MALDI-TOF MS Log score.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNASM species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of isolates (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage Log score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. chromogenes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,190 (39.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. borealis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e516 (17.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM. sciuri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e299 (9.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e262 (8.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. epidermidis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224 (7.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. haemolyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197 (6.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. rostri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101 (3.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. simulans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (2.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. arlettae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52 (1.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. equorum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46 (1.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. saprophyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (0.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. agnetis/hyicus\u003c/em\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (0.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. gallinarum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (0.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. capitis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (0.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. cohnii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. hominis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. succinus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. microti\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. schleiferi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3,022 (100.00%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e1\u003c/sup\u003e MALDI-TOF MS does not differentiate these two species.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reports the NASM species identified according to the sample type. The three most frequent NASM in CM quarters were \u003cem\u003eS. chromogenes\u003c/em\u003e (24.82%), \u003cem\u003eS. borealis\u003c/em\u003e (21.84%), and \u003cem\u003eM. sciuri\u003c/em\u003e (20.57%), with similar prevalence levels. In SCM quarters, \u003cem\u003eS. chromogenes\u003c/em\u003e was also the most prevalent species (31.78%) followed by \u003cem\u003eS. borealis\u003c/em\u003e, albeit with slightly lower percentages (17.65%). \u003cem\u003eS. xylosus\u003c/em\u003e was third (10.59%). In composite milk, \u003cem\u003eS. chromogenes\u003c/em\u003e was largely predominant, representing over half (51.15%) of the isolates, once again followed by \u003cem\u003eS. borealis\u003c/em\u003e (14.38%). Among other NASM species, \u003cem\u003eM. sciuri\u003c/em\u003e, \u003cem\u003eS. equorum\u003c/em\u003e, and \u003cem\u003eS. arlettae\u003c/em\u003e were significantly more present in CM, while \u003cem\u003eS. xylosus\u003c/em\u003e, \u003cem\u003eS. epidermidis\u003c/em\u003e, and \u003cem\u003eS. rostri\u003c/em\u003e were significantly more present in SCM samples (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Supplementary Table).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of NASM species across bovine clinical mastitis, subclinical mastitis, and herd survey milk samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical quarter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of isolates (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubclinical quarter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of isolates (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eComposite herd survey\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNumber of isolates (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. chromogenes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175 (24.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. chromogenes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e279 (31.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. chromogenes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e736 (51.15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. borealis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (21.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. borealis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e155 (17.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. borealis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e207 (14.38%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM. sciuri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145 (20.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (10.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. epidermidis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e114 (7.92%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (10.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. epidermidis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 (9.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. xylosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96 (6.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. haemolyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (7.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. haemolyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74 (8.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eM. sciuri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93 (6.46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. epidermidis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (3.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. rostri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74 (8.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. haemolyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 (4.79%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. equorum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (3.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM. sciuri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (6.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. simulans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39 (2.71%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. arlettae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. simulans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (1.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. arlettae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24 (1.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. simulans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (1.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. equorum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (1.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. rostri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (1.46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. gallinarum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. arlettae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (1.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. equorum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. rostri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. saprophyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (0.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. agnetis/S. hyicus\u003c/em\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (0.56%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. saprophyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. gallinarum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. saprophyticus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (0.49%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. agnetis/S. hyicus\u003c/em\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (0.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. capitis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. cohnii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (0.35%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. succinus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. agnetis/S. hyicus\u003c/em\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. capitis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (0.28%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. capitis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. cohnii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. gallinarum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (0.21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. cohnii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. hominis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. hominis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (0.14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. hominis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. microti\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. microti\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. microti\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. schleiferi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. schleiferi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eS. schleiferi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. succinus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS. succinus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e705\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e878\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,439\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e1\u003c/sup\u003e MALDI-TOF MS does not differentiate these two species.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eNASM distribution by farm\u003c/h2\u003e \u003cp\u003eA varied distribution of NASM species was observed in the farms sending composite HS samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). \u003cem\u003eS. chromogenes\u003c/em\u003e was isolated in all but one farm (96.43%) and was the main NASM in over half of the farms (57.14%). Notably, \u003cem\u003eS. borealis\u003c/em\u003e was the second species, being present in 22 of 28 farms (78.57%) and representing the main NASM in 6 of 28 farms (21.42%). Other frequently identified NASM were \u003cem\u003eM. sciuri\u003c/em\u003e (64,29%), \u003cem\u003eS. xylosus\u003c/em\u003e (60,71%), \u003cem\u003eS. epidermidis\u003c/em\u003e (46,73%), \u003cem\u003eS. haemolyticus\u003c/em\u003e (46,43%) and \u003cem\u003eS. simulans\u003c/em\u003e (42,86%). \u003cem\u003eS. rostri\u003c/em\u003e was isolated in 8 out of 28 farms (28.57%) but it was never the most prevalent NASM species found in the herd.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe relevance of NASM for animal welfare and milk quality is increasingly recognized in light of their association with CM and SCM in modern dairy farms (Schukken et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; De Buck et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ruiz-Romero and Vargas-Bello-P\u0026eacute;rez \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This retrospective study investigated the prevalence of various NASM species identified by the MBT System with the aim of gathering novel information on \u003cem\u003eS. borealis\u003c/em\u003e and \u003cem\u003eS. rostri\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn the course of one year, we identified 19 different NASM species on a total of 21,864 samples including CM, SCM and HS milk. Of these, \u003cem\u003eS. borealis\u003c/em\u003e was the second most common species after \u003cem\u003eS. chromogenes\u003c/em\u003e across sample types. Therefore, our results indicate that \u003cem\u003eS. borealis\u003c/em\u003e might be a more frequent contributor to bovine udder infections than previously thought, confirming the recent findings from our group in the US (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and in line with the increasingly reported presence of \u003cem\u003eS. borealis\u003c/em\u003e within cattle population as a possible cause of IMI (Kr\u0026oacute;l et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our previous retrospective studies (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Addis et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), S. \u003cem\u003ehaemolyticus\u003c/em\u003e was the second most prevalent species after \u003cem\u003eS. chromogenes\u003c/em\u003e. A recent systematic review by Ruiz-Romero and Vargas-Bello-P\u0026eacute;rez (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) also reported \u003cem\u003eS. haemolyticus\u003c/em\u003e as the second most frequently isolated NASM. However, the identification of \u003cem\u003eS. haemolyticus\u003c/em\u003e has created significant challenges in the past due to the elevated genomic variability combined with a high similarity of its marker genes with other species (Wanecka et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rosa et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recently, whole genome sequencing of \u003cem\u003eS. haemolyticus\u003c/em\u003e has uncovered a significant phylogenetic distance among isolates, leading to the first description of \u003cem\u003eS. borealis\u003c/em\u003e as a distinct species (Pain et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Accordingly, isolates initially identified as \u003cem\u003eS. haemolyticus\u003c/em\u003e were later confirmed to be \u003cem\u003eS. borealis\u003c/em\u003e (Kr\u0026oacute;l et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the high similarity of its marker genes to \u003cem\u003eS. haemolyticus\u003c/em\u003e and the absence of reference spectra in the MBT database for \u003cem\u003eS. borealis\u003c/em\u003e have likely led to its previous misclassification as \u003cem\u003eS. haemolyticus\u003c/em\u003e, underestimating the presence of \u003cem\u003eS. borealis\u003c/em\u003e and overestimating \u003cem\u003eS. haemolyticus\u003c/em\u003e (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The present work confirmed that \u003cem\u003eS. borealis\u003c/em\u003e is indeed a common cause of bovine mastitis, confirming our findings in the US for CM (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and underscoring the importance of distinguishing it from \u003cem\u003eS. haemolyticus\u003c/em\u003e for an accurate understanding of its role in CM and SCM. Its monitoring and characterization can also be important for the potential ability to spread antimicrobial resistance genes, as multidrug-resistant \u003cem\u003eS. borealis\u003c/em\u003e strains have been already detected in pigs (Abdullahi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother interesting finding was the emergence of \u003cem\u003eS. rostri\u003c/em\u003e, and of its significant association with SCM, after updating our library with in-house spectra for his species. Different studies suggested that creating an internal mass spectrum library of accurately identified reference strains can significantly improve the reliability of isolate identification by MALDI-TOF MS, especially when commercially available databases include a limited number of reference spectra or when some species are absent (Cassagne et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Posteraro et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Kolecka et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In the past, \u003cem\u003eS. rostri\u003c/em\u003e has been identified in various hosts, including pigs (Vanderhaeghen et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and water buffaloes (Locatelli et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In cows, previous evidence suggested that \u003cem\u003eS. rostri\u003c/em\u003e may serve as a pathogen contributing to mastitis and that it can persist on farms through cow-to-cow transmission or within environmental reservoirs (Jenkins et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kl\u0026oslash;ve et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As in the case of \u003cem\u003eS. borealis\u003c/em\u003e, differentiating \u003cem\u003eS. rostri\u003c/em\u003e from \u003cem\u003eS. microti\u003c/em\u003e and \u003cem\u003eS. muscae\u003c/em\u003e is hampered by genetic similarity as well as by limitations in existing databases (Rosa et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kl\u0026oslash;ve et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In our previous retrospective studies, \u003cem\u003eS. microti\u003c/em\u003e was the sixth most prevalent NASM in SCM and the ninth and tenth, respectively, in CM cases from US and Italy (Freu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Addis et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the present study, \u003cem\u003eS. rostri\u003c/em\u003e accounted for 8.43% of all NASM identified in SCM, while \u003cem\u003eS. microti\u003c/em\u003e was isolated only once, suggesting that previously reported \u003cem\u003eS. microti\u003c/em\u003e might have actually been \u003cem\u003eS. rostri\u003c/em\u003e and that the reported prevalence data for \u003cem\u003eS. microti\u003c/em\u003e might have been overestimated. Previous studies identified antibiotic resistance in \u003cem\u003eS. rostri\u003c/em\u003e (Wuytack et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and monitoring resistance patterns in isolates from bovine mastitis could also be an area for future research.\u003c/p\u003e \u003cp\u003eRegarding the potential association of NASM with mastitis cases, \u003cem\u003eS. borealis\u003c/em\u003e was detected more frequently in CM, but it was not preferentially associated with SCM or CM. On the other hand, \u003cem\u003eS. rostri\u003c/em\u003e was significantly associated with SCM. Concerning NASM species isolated in HS, \u003cem\u003eS. borealis\u003c/em\u003e emerged as the second most prevalent species after \u003cem\u003eS. chromogenes\u003c/em\u003e, with a widespread presence on most farms; \u003cem\u003eS. rostri\u003c/em\u003e had a lower prevalence compared to the previous two NASM, being isolated from a smaller number of farms.\u003c/p\u003e \u003cp\u003eIn conclusion, the prevalence of \u003cem\u003eS. borealis\u003c/em\u003e and \u003cem\u003eS. rostri\u003c/em\u003e has likely been strongly underestimated due to a lack of capacity to differentiate them from closely related bacteria. The MBT database, initially focused on human pathogens (Tomazi et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), is gradually expanding its coverage of veterinary isolates. Continued development of this resource will be crucial for accurate identification of NASM species. By further exploring the specific impacts of different NASM species on udder health, future research can inform more targeted farm management strategies to enhance animal health and milk quality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank the farmers and veterinarians for their collaboration and trust.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMP and MFA designed the study. CL, VM, and LFP carried out milk bacteriology and MALDI-TOF MS identification. MP, FU, CL and VB carried out data analysis. MP, FU and MFA drafted the manuscript. RP, PM, and VB contributed to data interpretation and manuscript drafting. All authors critically revised, read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by internal funds from the Laboratory of Animal Infectious Diseases (MiLab) at the University of Milan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdullahi IN, Lozano C, Sim\u0026oacute;n C, et al (2023) Within-Host Diversity of Coagulase-Negative Staphylococci Resistome from Healthy Pigs and Pig Farmers, with the Detection of cfr-Carrying Strains and MDR-\u003cem\u003eS. borealis\u003c/em\u003e. Antibiotics (Basel) 12:1505. https://doi.org/10.3390/antibiotics12101505\u003c/li\u003e\n\u003cli\u003eAddis MF, Locatelli C, Penati M, et al (2024) Non-\u003cem\u003eaureus\u003c/em\u003e staphylococci and mammaliicocci isolated from bovine milk in Italian dairy farms: a retrospective investigation. Vet Res Commun 48:547\u0026ndash;554. https://doi.org/10.1007/s11259-023-10187-x\u003c/li\u003e\n\u003cli\u003eAdkins PRF, Middleton JR, Fox LK et al (2017) Laboratory handbook on bovine mastitis. National Mastitis Council, New Prague\u003c/li\u003e\n\u003cli\u003eCassagne C, Ranque S, Normand A-C, et al (2011) Mould routine identification in the clinical laboratory by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. PLoS One 6:e28425. https://doi.org/10.1371/journal.pone.0028425\u003c/li\u003e\n\u003cli\u003eCLAL. https://www.clal.it/index.php. Accessed 3 Apr 2024\u003c/li\u003e\n\u003cli\u003eCondas LAZ, De Buck J, Nobrega DB, et al (2017) Prevalence of non-\u003cem\u003eaureus\u003c/em\u003e staphylococci species causing intramammary infections in Canadian dairy herds. J Dairy Sci 100:5592\u0026ndash;5612. https://doi.org/10.3168/jds.2016-12478\u003c/li\u003e\n\u003cli\u003eDe Buck J, Ha V, Naushad S, et al (2021) Non-\u003cem\u003eaureus\u003c/em\u003e Staphylococci and Bovine Udder Health: Current Understanding and Knowledge Gaps. Front Vet Sci 8:658031. https://doi.org/10.3389/fvets.2021.658031\u003c/li\u003e\n\u003cli\u003eFreu G, Gioia G, Gross B, et al (2023) Frequency of non-\u003cem\u003eaureus\u003c/em\u003e staphylococci and mammaliicocci species isolated from quarter clinical mastitis: a six-year retrospective study. J Dairy Sci https://doi.org/10.3168/jds.2023-24086\u003c/li\u003e\n\u003cli\u003eJenkins SN, Okello E, Rossitto PV, et al (2019) Molecular epidemiology of coagulase-negative \u003cem\u003eStaphylococcus\u003c/em\u003e species isolated at different lactation stages from dairy cattle in the United States. PeerJ 7:e6749. https://doi.org/10.7717/peerj.6749\u003c/li\u003e\n\u003cli\u003eKl\u0026oslash;ve DC, Farre M, Strube ML, Astrup LB (2023) Comparative Genomics of \u003cem\u003eStaphylococcus rostri\u003c/em\u003e, an Undescribed Bacterium Isolated from Dairy Mastitis. Vet Sci 10:530. https://doi.org/10.3390/vetsci10090530\u003c/li\u003e\n\u003cli\u003eKolecka A, Khayhan K, Arabatzis M, et al (2014) Efficient identification of \u003cem\u003eMalassezia\u003c/em\u003e yeasts by matrix‐assisted laser desorption ionization‐time of flight mass spectrometry (MALDI‐TOF MS). Br J Dermatol 170:332\u0026ndash;341. https://doi.org/10.1111/bjd.12680\u003c/li\u003e\n\u003cli\u003eKr\u0026oacute;l J, Wanecka A, Twardoń J, et al (2023) \u003cem\u003eStaphylococcus borealis\u003c/em\u003e \u0026ndash; A newly identified pathogen of bovine mammary glands. Vet Microbiol 286:109876. https://doi.org/10.1016/j.vetmic.2023.109876\u003c/li\u003e\n\u003cli\u003eLienen T, Schnitt A, Hammerl JA, et al (2022) \u003cem\u003eMammaliicoccus\u003c/em\u003e spp. from German Dairy Farms Exhibit a Wide Range of Antimicrobial Resistance Genes and Non-Wildtype Phenotypes to Several Antibiotic Classes. Biology-Basel. 11:152. https://doi.org/10.3390/biology11020152\u003c/li\u003e\n\u003cli\u003eLocatelli C, Piepers S, De Vliegher S, et al (2013) Effect on quarter milk somatic cell count and antimicrobial susceptibility of \u003cem\u003eStaphylococcus rostri\u003c/em\u003e causing intramammary infection in dairy water buffaloes. J Dairy Sci 96:3799\u0026ndash;3805. https://doi.org/10.3168/jds.2012-6275\u003c/li\u003e\n\u003cli\u003eMiddleton JR, Fox LK, Pighetti G (2017) Laboratory handbook on bovine Mastitis. National Mastitis Council, Madison, WI, New Prague, MN\u003c/li\u003e\n\u003cli\u003eNonnemann B, Lyhs U, Svennesen L, et al (2019) Bovine mastitis bacteria resolved by MALDI-TOF mass spectrometry. J Dairy Sci 102:2515\u0026ndash;2524. https://doi.org/10.3168/jds.2018-15424\u003c/li\u003e\n\u003cli\u003ePain M, Wolden R, Ja\u0026eacute;n-Luchoro D, et al (2020) \u003cem\u003eStaphylococcus borealis\u003c/em\u003e sp. nov., isolated from human skin and blood. Int J Syst Evol Microbiol 70:6067\u0026ndash;6078. https://doi.org/10.1099/ijsem.0.004499\u003c/li\u003e\n\u003cli\u003ePosteraro B, Vella A, Cogliati M, et al (2012) Matrix-Assisted Laser Desorption Ionization\u0026ndash;Time of Flight Mass Spectrometry-Based Method for Discrimination between Molecular Types of \u003cem\u003eCryptococcus neoformans\u003c/em\u003e and \u003cem\u003eCryptococcus gattii\u003c/em\u003e. J Clin Microbiol 50:2472\u0026ndash;2476. https://doi.org/10.1128/JCM.00737-12\u003c/li\u003e\n\u003cli\u003eReydams H, Toledo-Silva B, Mertens K, et al (2023) Comparison of non-\u003cem\u003eaureus\u003c/em\u003e staphylococcal and mammaliicoccal species found in both composite milk and bulk-tank milk samples of dairy cows collected in tandem. J Dairy Sci 106:7974\u0026ndash;7990. https://doi.org/10.3168/jds.2022-23092\u003c/li\u003e\n\u003cli\u003eRosa NM, Penati M, Fusar-Poli S, et al (2022) Species identification by MALDI-TOF MS and gap PCR\u0026ndash;RFLP of non-\u003cem\u003eaureus\u003c/em\u003e \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eMammaliicoccus\u003c/em\u003e, and \u003cem\u003eStreptococcus\u003c/em\u003e spp. associated with sheep and goat mastitis. Vet Res 53:84. https://doi.org/10.1186/s13567-022-01102-4\u003c/li\u003e\n\u003cli\u003eRuiz-Romero RA, Vargas-Bello-P\u0026eacute;rez E (2023) Non-\u003cem\u003eaureus\u003c/em\u003e staphylococci and mammaliicocci as a cause of mastitis in domestic ruminants: current knowledge, advances, biomedical applications, and future perspectives \u0026ndash; a systematic review. Vet Res Commun 47:1067. https://doi.org/10.1007/s11259-023-10090-5\u003c/li\u003e\n\u003cli\u003eSchukken Y, Gonzalez R, Tikofsky L, et al (2009) CNS mastitis: Nothing to worry about? Vet Microbiol 134:9\u0026ndash;14. https://doi.org/10.1016/j.vetmic.2008.09.014\u003c/li\u003e\n\u003cli\u003eSouza FN, Santos KR, Ferronatto JA, et al (2023) Bovine-associated staphylococci and mammaliicocci trigger T-lymphocyte proliferative response and cytokine production differently. J Dairy Sci 106:2772\u0026ndash;2783. https://doi.org/10.3168/jds.2022-22529\u003c/li\u003e\n\u003cli\u003eTaponen S, Myllys V, Py\u0026ouml;r\u0026auml;l\u0026auml; S (2022) Somatic cell count in bovine quarter milk samples culture positive for various \u003cem\u003eStaphylococcus\u003c/em\u003e species. Acta Vet Scand 64:32. https://doi.org/10.1186/s13028-022-00649-8\u003c/li\u003e\n\u003cli\u003eThe List of Prokaryotic names with Standing in Nomenclature (LPSN). https://lpsn.dsmz.de/search?word=staphylococcus. Accessed 3 Apr 2024\u003c/li\u003e\n\u003cli\u003eTomazi T, Gon\u0026ccedil;alves JL, Barreiro JR, et al (2014) Identification of Coagulase-Negative Staphylococci from Bovine Intramammary Infection by Matrix-Assisted Laser Desorption Ionization\u0026ndash;Time of Flight Mass Spectrometry. J Clin Microbiol 52:1658\u0026ndash;1663. https://doi.org/10.1128/jcm.03032-13\u003c/li\u003e\n\u003cli\u003eVanderhaeghen W, Vandendriessche S, Cromb\u0026eacute; F, et al (2012) Species and staphylococcal cassette chromosome mec (SCCmec) diversity among methicillin-resistant non-\u003cem\u003eStaphylococcus\u003c/em\u003e \u003cem\u003eaureus\u003c/em\u003e staphylococci isolated from pigs. Vet Microbiol 158:123\u0026ndash;128. https://doi.org/10.1016/j.vetmic.2012.01.020\u003c/li\u003e\n\u003cli\u003eVanderhaeghen W, Piepers S, Leroy F, et al (2014) \u003cem\u003eInvited review:\u003c/em\u003e Effect, persistence, and virulence of coagulase-negative \u003cem\u003eStaphylococcus\u003c/em\u003e species associated with ruminant udder health. J Dairy Sci 97:5275\u0026ndash;5293. https://doi.org/10.3168/jds.2013-7775\u003c/li\u003e\n\u003cli\u003eWanecka A, Kr\u0026oacute;l J, Twardoń J, et al (2018) Characterization of a genetically distinct subpopulation of \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e isolated from milk of cows with intramammary infections. Vet Microbiol 214:28\u0026ndash;35. https://doi.org/10.1016/j.vetmic.2017.12.004\u003c/li\u003e\n\u003cli\u003eWuytack A, De Visscher A, Piepers S, et al (2019) Non-\u003cem\u003eaureus\u003c/em\u003e staphylococci in fecal samples of dairy cows: First report and phenotypic and genotypic characterization. J Dairy Sci 102:9345\u0026ndash;9359. https://doi.org/10.3168/jds.2019-16662\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"veterinary-research-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"verc","sideBox":"Learn more about [Veterinary Research Communications](https://www.springer.com/journal/11259)","snPcode":"11259","submissionUrl":"https://submission.nature.com/new-submission/11259/3","title":"Veterinary Research Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"NASM, S. borealis, S. rostri, mastitis, coagulase-negative staphylococci, dairy ruminant milk","lastPublishedDoi":"10.21203/rs.3.rs-4218430/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4218430/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNon-aureus staphylococci and mammaliicocci (NASM) are microorganisms most frequently isolated from milk. Given their numerosity and complexity, MALDI-TOF MS is one of the preferred species identification approaches. Nevertheless, reference mass spectra for the novel species \u003cem\u003eStaphylococcus borealis\u003c/em\u003e were included only recently in the Bruker Biotyper System (MBT) library, and other species of veterinary interest such as \u003cem\u003eS. rostri\u003c/em\u003e are still absent. This work provides an updated picture of the NASM species found in milk, gained by retrospectively analyzing the data relating to 21,864 milk samples, of which 6,278 from clinical mastitis (CM), 4,039 from subclinical mastitis (SCM), and 11,547 from herd survey (HS), with a spectrum library including both species. As a result, \u003cem\u003eS. borealis\u003c/em\u003e was the second most frequently isolated NASM (17.07%) after \u003cem\u003eS. chromogenes\u003c/em\u003e (39.38%) in all sample types, with a slightly higher percentage in CM (21.84%), followed by SCM (17.65%), and HS (14.38%). \u003cem\u003eS. rostri\u003c/em\u003e was also present in all sample types (3.34%), reaching 8.43% of all NASM in SCM and showing a significant association (p \u0026lt; 0.01) with this condition. Based on our findings, the presence of \u003cem\u003eS. borealis\u003c/em\u003e and \u003cem\u003eS. rostri \u003c/em\u003ein milk and their potential association with mastitis has been overlooked, possibly due to the difficulties in differentiating these species from other closely related NASM. Our results indicate that \u003cem\u003eS. borealis\u003c/em\u003e might be a more frequent contributor to bovine udder infections than previously thought and that \u003cem\u003eS. rostri\u003c/em\u003e should also not be underestimated considering its significant association with SCM.\u003c/p\u003e","manuscriptTitle":"An update on non-aureus staphylococci and mammaliicocci in cow milk: unveiling the presence of Staphylococcus borealis and Staphylococcus rostri by MALDI-TOF MS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-11 09:37:04","doi":"10.21203/rs.3.rs-4218430/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-05T09:17:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-21T10:59:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-15T10:48:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152550f1-2fa9-4158-8f76-b407ebd85507","date":"2024-04-12T09:51:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0e104dc6-3221-48bc-bbf0-9f67bebc6e12","date":"2024-04-09T15:00:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e9a62e90-7ef1-45b7-a669-bea2784f0ebf","date":"2024-04-09T08:16:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2fd06497-414d-4db9-b2a6-87d593e84803","date":"2024-04-09T07:16:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-09T04:37:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-08T13:02:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-08T13:02:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Veterinary Research Communications","date":"2024-04-04T14:06:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"veterinary-research-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"verc","sideBox":"Learn more about [Veterinary Research Communications](https://www.springer.com/journal/11259)","snPcode":"11259","submissionUrl":"https://submission.nature.com/new-submission/11259/3","title":"Veterinary Research Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"334952fb-41f8-472e-aa8b-377c3e836ac6","owner":[],"postedDate":"April 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-21T15:21:43+00:00","versionOfRecord":{"articleIdentity":"rs-4218430","link":"https://doi.org/10.1007/s11259-024-10440-x","journal":{"identity":"veterinary-research-communications","isVorOnly":false,"title":"Veterinary Research Communications"},"publishedOn":"2024-06-18 15:21:43","publishedOnDateReadable":"June 18th, 2024"},"versionCreatedAt":"2024-04-11 09:37:04","video":"","vorDoi":"10.1007/s11259-024-10440-x","vorDoiUrl":"https://doi.org/10.1007/s11259-024-10440-x","workflowStages":[]},"version":"v1","identity":"rs-4218430","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4218430","identity":"rs-4218430","version":["v1"]},"buildId":"veTbxFhMMB0_faC6-Wkog","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}