Phenotypic and genotypic characterization of ST103 Serotype Ia Streptococcus agalactiae isolated from bovine mastitis in China

Phenotypic and genotypic characterization of ST103 Serotype Ia Streptococcus agalactiae isolated from bovine mastitis in China | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Phenotypic and genotypic characterization of ST103 Serotype Ia Streptococcus agalactiae isolated from bovine mastitis in China Yue Wang, Siyu Meng, Halihaxi Bahetijiang, Haoxia Li, Tian Wang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6746409/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Oct, 2025 Read the published version in BMC Microbiology → Version 1 posted 14 You are reading this latest preprint version Abstract Streptococcus agalactiae is a contagious pathogen responsible for bovine mastitis, leading to significant economic losses in the global dairy industry. Our objectives were to determine the population structure, to profile the antimicrobial resistance and to investigate the pathogenicity and genes associated with pathogenicity in S. agalactiae isolated from Chinese dairy herds. A total of 266 milk samples were collected on three dairy farms in Ningxia (herd A) and Hebei provinces (herds B & C) with outbreaks of bovine mastitis from September 2020 to April 2021. There were 116 isolates identified as Streptococcus agalactiae by 16S rRNA sequencing. Twenty-seven S. agalactiae isolates were randomly selected using a stratified approach from the three farms for whole genome sequencing analysis and phenotypic analyses, including antimicrobial resistance profiling, identification of adhesion, invasion and virulence factor genes using in vitro bovine mammary epithelial cell models and in vivo Galleria mellonella models. Multilocus sequence typing and serotyping showed that all isolates belonged to sequence type ST103 and serotype Ia. In total, 34 genes were identified as virulence factor genes in Streptococcus species. Isolates from herd C had significantly higher virulence than those from herd B. Genome-wide association analysis revealed 166 virulence-related genes, 221 adhesion-related genes and 218 invasion-related genes. Furthermore, 47 genes were associated with pathogenicity in infecting G. mellonella . Resistance to tetracycline and macrolides was related to the presence of antimicrobial resistance genes tetO, tetM , and ermB . Pan-genome analyses revealed that 1,421 S. agalactiae isolates (27 from our study and 1,394 from the NCBI genome database) had 20,955 genes, including 666 and 20,289 genes in the core and accessory genomes, respectively. This study characterized the phenotypic and genotypic profiles for S. agalactiae , and identified associations between phenotypic traits and genetic determinants of virulence and antimicrobial resistance, providing new insights into controlling S. agalactiae mastitis in Chinese dairy herds. Streptococcus agalactiae bovine mastitis whole-genome sequencing phenotypes virulence genes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Bovine mastitis is one of the most prevalent and problematic diseases that mainly caused by bacterial pathogens in dairy farming worldwide [ 1 ]. Mastitis pathogens are generally classified into two categories, namely contagious and environmental pathogens, although recent studies suggest there is no distinct boundary between those two categories [ 2 ]. Contagious bacterial pathogens include Staphylococcus aureus and Streptococcus agalactiae , and the prevalence of S. aureus and S. agalactiae have been largely under control since the implementation of the “five-point” mastitis plan especially in the developed countries [ 1 ]. However, recent epidemiological studies suggest increased prevalence of S. agalactiae in Nordic countries [ 3 ] and China [ 4 ]. Over the past two decades, China has seen a significant increase in herd size and improvement in dairy farming management, along with the increased prevalence of S. agalactiae . Recent studies showed the isolation rate of S. agalactiae from mastitis cases in dairy herds ranges from 2.0 to 25.0% in China [ 4 ]. However, the population structure and molecular characteristics of S. agalactiae remain elusive in Chinese dairy herds. Population structure and genetic diversity of pathogens determines the control measures for contagious mastitis pathogens. S. agalactiae has been classified into ten serotypes (Ia, Ib, II–IX) based on capsular polysaccharide [ 5 ]. Both the predominant serotypes and genotypes of S. agalactiae vary across regions [ 6 ]. In China, the most prevalent serotype and genotypes of S. agalactiae are serotype II, and genotype ST67, ST103 and ST568, respectively [ 4 ]. Therefore, it is important to determine the population structure of S. agalactiae in order to design tailor-made effectively control programs for S. agalactiae caused mastitis. Bacterial pathogenicity depends on multiple virulence factors including adhesion, immune evasion, and toxin [ 7 , 8 ]. These virulence factors are vital for survival, transmission and infection within and across hosts [ 9 ]. Capsular polysaccharide, an important virulence factor in S. agalactiae , is used to characterize antigenicity and immunogenicity and also used for serotyping [ 10 ]. While the distribution of virulence factors is still lacking for S. agalactiae in Chinese dairy herds. In addition, antimicrobial resistance deteriorates the effect of antimicrobial treatment, therefore, the aims of this study were to (1) determine the population structure; (2) profile the antimicrobial resistance and (3) investigate the pathogenicity as well as genes associated with pathogenicity in S. agalactiae isolated from Chinese dairy herds. Materials and Methods Sample collection and bacterial species identification A total of 266 milk samples (235 clinical mastitis samples and 31 subclinical mastitis samples) were collected from three large dairy farms with outbreaks of bovine mastitis in Ningxia and Hebei provinces of China from September 2020 to April 2021. Clinical mastitis and subclinical mastitis were defined according to National Mastitis Council (NMC) guidelines [ 2 ]. Milk samples were collected aseptically, stored in sterile plastic vials at 4°C, and transported to the Mastitis Reference Laboratory at China Agricultural University in Beijing, China. Bacterial species identification was performed using bacteriological culture, colony morphology, Gram staining, CAMP test, and 16S rRNA sequencing, according to NMC guidelines [ 2 ]. In brief, 10 µL of milk were streaked on tryptone soy agar plate (TSA; Aoboxing Biotechnology, Beijing, China) with 5% defibrinated sheep blood (Solarbio Technology, Beijing, China). These plates were incubated in an inverted position at 37°C for 24 to 48 h. Genomic DNA was extracted using a bacterial genomic DNA extraction kit (Accurate Biotechnology, Hunan, China), according to the Gram-positive bacteria genomic DNA extraction protocol. Concentration and purity of the extracted DNA were assessed (NanoDrop 2000; ThermoFisher Scientific, Waltham, MA, USA) before sequencing. All DNA samples with nucleoside concentration ≥ 50 ng/µL and purity indices A260/280 ≥ 1.8, A260/230 ≥ 2.0 were subjected to 16S rRNA sequencing and whole-genome sequencing. The 16S rRNA gene sequencing was performed using a pair of primers 27F and 1492R that commonly used to identify bacterial species. The PCR product was sequenced with 3730 platform (Thermo Fisher Scientific) [ 11 ]. After 16S rRNA sequencing, bacterial species were identified by blasting the 16S rRNA sequences against the sequences deposited in the National Center for Biotechnology Information (NCBI) database. Serotyping All S. agalactiae isolates were serotyped with multiplex PCR with 19 specific primers to detect capsular polysaccharide (CPS) clusters [ 12 ]. The PCR reactions consisted of 2×Green Taq Mix (Vazyme, Nanjing, China) and 250 nM of each specific primer, except primers cps-Ia-6-7-F and cps-7-9-F, which used 400 nM of each (Shanghai Sangon Biotech Company, Shanghai, China). Serotyping PCR procedure includes: 5 min at 95°C, followed by 15 cycles of 95°C for 60 s, 54°C for 60 s, 72°C for 2 min, and then by additional 25 cycles of 95°C for 60 s, 56°C for 60 s, 72°C for 2 min and a final cycle of 72°C for 10 min. The PCR products were examined on 1.5% agarose gel using a gel documentation system. Multi-locus sequence typing (MLST) MLST was performed on 116 isolates based on seven housekeeping genes: adhP , pheS , atr , glnA , sdhA , glcK , and tkt . All primer sequences that were amplified for sequencing were obtained from the MLST database ( http://sagalactiae.mlst.net ) and synthesized by Shanghai Sangon Biotech Company. The 25-µL PCR reaction system contained 12.5 µL 2 × Green Taq Mix (Vazyme), 50 ng template DNA, and 1 µL forward primer and reverse primer (10 µM). The PCR protocol was set as initial denaturation at 95°C for 3 min; 34 cycles of 95°C for 15 s, 57°C for 15 s and 72°C for 1 min; and final extension at 72°C for 5 min. Thereafter, PCR products were sequenced and blasted against to the MLST database to determine the MLST type of each isolate. The clonal complex of each isolate was determined with an eBURST algorithm using PHYLOViZ online ( https://online.phyloviz.net/index ). Virulence, adherence and invasion assays Stratified random sampling was performed to select isolates that capture the population structure and molecular characteristics using representative isolates in each herd, consequently, 27 isolates were selected (four isolates from herd A, 12 isolates from herd B and 11 isolates from herd C). Bovine mammary epithelial cells (bMECs, Jingma Biotechnology Co., Shanghai, China) were cultured in DMEM medium (Gibco, Brooklyn, NY, USA), supplemented with 5% fetal bovine serum (FBS, Gibco), overnight at 37°C in 5% CO 2 until cell density reached coverage of approximately 80%. These cells were transferred to 96-well plates for quantifying LDH release from cells [ 13 ]. Meanwhile, bMECs were also transferred to 24-well plates and cultured in 2 × 10 5 cells/well to assess adherence and invasion. Briefly, 27 isolates were diluted to 1 × 10 6 CFU/mL with DMEM medium containing 1% FBS before adding to the monolayer of bMECs at multiplicity of infection (MOI) = 5:1 and incubated for 9 h, 2 h or 3 h for quantifying LDH release, adherence and invasion rate, respectively. Cytotoxic effect of S. agalactiae on bMECs were evaluated with an LDH assay kit (Beyotime Biotechnology, Beijing, China). After infection, 200 µL of supernatant from experimental and control groups were collected, transferred to centrifuge tubes, and centrifuged (8,000 × g for 5 min at 4°C). Then, 120 µL of the supernatant was transferred to a new 96-well polystyrene plate and 60 µL of the reaction mixture was added to each well, and incubated on a rotator shaker (150 rpm) at room temperature in dark for 30 min. Absorbance of the incubation mixture was read at 490 nm (680 Multipurpose Microplate Reader; Bio-Rad Laboratories, Berkeley, CA, USA). Adherence and invasion assays were performed according to Bonsaglia et al. (2023) [ 14 ]. Unbound bacteria were removed by washing three times with 1 × PBS, the bMECs were digested with trypsin and the mixture was cultured on TSA plate with 5% defibrinated sheep blood, consequently, the CFU of adhering bacteria was enumerated after incubating for 24 h at 37°C and 5% CO 2 . For the invasion assay, after washing three times with 1 × PBS, bMECs were placed in 500 µL of DMEM medium with 1% FBS containing 100 µg/mL penicillin for 30 min to kill extracellular bacteria. Plates were incubated for 1 h at 37°C in 5% CO 2 . Thereafter, bMECs were washed three times with 1 × PBS, and the bMECs were digested with trypsin, the CFU of invading bacteria was determined by inoculating the digested cell mixture on TSA with 5% defibrinated sheep blood. Attachment and adhesion were calculated according to Xu et al. [ 15 ]. Galleria mellonella infection The infection experiment was performed following the protocol in Six et al. [ 16 ]. In brief, 10 G. mellonella larvae (2 to 2.5 cm long) were challenged with 3×10 7 CFU of S. agalactiae in each group at 37°C. At the same time, ten larvae in control group were injected with 10 µL 0.9% Sodium chloride solution. Survival and clinical signs of larvae were evaluated at six time points (12, 18, 24, 36, 48, and 60 h post infection). Survival analysis was performed to examined the pathogenicity of S. agalactiae using Kaplan-Meier survival analysis with survfit function in survival package (version 3.5.7, https://cran.r-project.org/web/packages/survival/index.html ) and survival plot was produced with ggsurvplot function in survminer package (version 0.4.9, https://cran.r-project.org/web/packages/survminer/index.html ). Antimicrobial susceptibility testing Minimal inhibitory concentration (MIC) of each isolate against each antimicrobial was determined according to the CLSI VET01 [ 17 ] or CLSI guidelines [ 18 ]. Breakpoints were applied to interpret antimicrobial susceptibility and resistance according to CLSI VET01 or CLSI wherever no veterinary breakpoint available, Staphylococcus aureus ATCC 29213 and S. agalactiae ATCC 13813 were used as quality-control isolates. The tested antimicrobials included amoxicillin, ampicillin, azithromycin, ceftiofur, clindamycin, enrofloxacin, erythromycin, oxytetracycline, penicillin G, tetracycline, tilmicosin, tylosin, and vancomycin. Association between antimicrobial resistance indicate by MIC and presence of antimicrobial resistance genes was tested using Fisher exact test. Whole genome sequencing Representative isolates (n = 27) were randomly selected from clinical and subclinical mastitis cases for shotgun whole-genome sequencing. Genomic DNA samples were sent to Shanghai Personal Biotechnology Co., Ltd (Shanghai, China), and paired-end reads (2 × 150 bp) were sequenced with Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA) sequencing platform. Genome assembly and annotation Quality control of raw reads was performed using FastQC (version 0.11.9, https://github.com/s-andrews/FastQC ). Raw reads were filtered and trimmed using fastp (version 0.20.1, https://github.com/OpenGene/fastp ). The N50 value of the contigs were computed to assess the quality of assembly. Thereafter, the clean reads were assembled and annotated using SPAdes (version 3.13.1, https://github.com/ablab/spades ) and Prokka (version1.14.6, https://github.com/tseemann/prokka ), respectively. The quality controlled reads were aligned to the assemblies using bowtie2 (version 2.5.3, https://github.com/BenLangmead/bowtie2 ) and the average coverage of depth of sequence from each isolate was calculated using samtools (version 1.20, https://github.com/samtools/samtools ). The N50 and L50 statistics were obtained using quast (version 5.2.0, https://github.com/ablab/quast ). Genome sequences were filtered with average coverage of depth > 30 for subsequent analysis. Identification of virulence genes and AMR genes Virulence and AMR genes were detected using ABRicate (version 0.8, https://github.com/tseemann/abricate ) to blast whole genome sequences against gene sequences in the VFDB and CARD databases, with minimum identity of 60% sequence coverage and 75% nucleotide identity. Genome wide association analyses We used the presence/absence of genes as independent variable and continuous phenotype data such as adhesion to, and invasion to bMECs as dependent variable to perform genome wide association analysis using linear mixed model (lme4 version 1.1–34, https://cran.r-project.org/web/packages/lme4/index.html ), respectively, Benjamini and Hochberg method was applied for multiple test correction. The Venn diagram was generated using BioLadder ( https://www.bioladder.cn/web/#/pro/cloud ), a bioinformatics online analysis and visualization cloud platform. Pan-genome analysis The pan-genome of 1,421 S. agalactiae isolates (27 isolates from our study and 1,394 isolates from the NCBI database) was constructed with Roary (version 3.13.0, http://sanger-pathogens.github.io/Roary/ ) using outputs produced by Prokka. Core genes (present in all genomes), accessory genes (present in two or more isolates but not all isolates) and unique genes (not shared by other genomes) were identified and visualized with Roary. Functional categories of genes in COG and KEGG categories were visualized using Roary. Core-genome based phylogenetic tree was constructed using Roary and visualized with iTOL ( https://itol.embl.de/ ). Statistical analyses All data analyses were performed in R (version 4.3.2, https://www.r-project.org/ ) and statistical significance was defined as a p value < 0.05 unless stated otherwise. Results Descriptive statistics of isolates To determine the population structure of S. agalactiae in Chinese dairy herds, 116 isolates were obtained from 266 milk samples collected from three dairy herds with outbreaks of bovine mastitis ( Supplementary Fig. 1 ). Brief descriptions of these isolates are in Table 1. Among culture-positive samples from these three herds, the positive rate of S. agalactiae in milk samples was 29% (Ningxia herd A), 62% (Hebei herd B) and 39% (Hebei herd C), respectively. Table 1 Information of 116 ST 103 S. agalactiae isolates from outbreaks of bovine mastitis in 235 mastitis samples in 3 large (> 2000 cows) Chinese dairy herds. Province Farm Date Mastitis type No. of samples No. of isolates Positive rate (%) 1 Ningxia A 2021.04 SCM 31 14 45.2 CM 4 12.9 Hebei B 2020.09 CM 81 50 61.7 Hebei C 2020.12 CM 123 48 39 1: Positive rate: positive rate for S. agalactiae in milk samples AMR profiles The MIC of the selected 27 S. agalactiae isolates against 13 antimicrobials were shown in Table 2 and Supplementary Table 1 . All isolates were resistant to tilmicosin, with 74.07%, 55.56% and 33.33% resistant to oxytetracycline, tetracycline and vancomycin, respectively. Resistance rates to enrofloxacin, tylosin, azithromycin, erythromycin, and ampicillin were 22.22%, 14.81%, 14.81%, 11.11%, and 3.70%, respectively. Finally, all isolates were sensitive to ceftiofur, penicillin G sodium, amoxicillin, and clindamycin. Table 2 The MIC of the 27 selected S. agalactiae isolates bovine mastitis milk samples collected in 3 dairy farms to 13 antimicrobials. Antimicrobial MIC (µg/mL) Resistance rate (%) MIC 50 (µg/mL) MIC 90 (µg/mL) 64 Erythromycin 14 5 5 1 2 11.11 64 Tylosin 1 1 5 16 4 14.81 1 >64 Tilmicosin 5 17 1 4 100 8 >64 Tetracycline 11 1 4 1 10 55.56 8 32 Oxytetracycline 2 5 5 1 14 74.07 32 32 Ceftiofur 14 2 11 0 <0.03 1 Penicillin G sodium 2 20 5 0 0.06 0.12 Ampicillin 5 21 1 3.7 0.12 0.12 Amoxicillin 1 25 1 0 0.06 0.06 Clindamycin 22 4 1 0 <0.03 0.06 Enrofloxacin 7 14 2 3 1 22.22 1 4 Vancomycin 1 7 10 9 33.33 1 2 Serotyping and MLST Isolate serotypes were determined by multiplex PCR, and the amplicon sizes of 116 isolates were 680 and 272 bp ( Supplementary Fig. 2 ), suggesting that serotypes of these isolates from all three herds were all Ia. Furthermore, MLST analysis classified all S. agalactiae isolates as ST103. Thereafter, 27 isolates were selected for further studies (11 isolates from herd A, four isolates from herd B and 12 isolates from herd C, respectively). Pathogenic effects of S. agalactiae on bMECs and Galleria mellonella Isolates from herd C stimulated a significantly higher LDH release from bMECs than those isolates from herds A and B (Fig. 1a and b ). Streptococcus agalactiae isolates adhered to bMECs at 2 h post infection and invaded bMECs at 3 h post infection (Fig. 1c-f). Adhesion and invasion rates of isolates from herd C were significantly higher than those isolates from herd B. The survival of G. mellonella infected with S. agalactiae isolates from herd C was significantly lower compared to larvae infected with isolates from the other two herds ( Fig. 2 ) . The survival rate of larvae in the control group was 100%. Whole genome analyses The mean average depth of coverage of the genome sequence of the 27 isolates was 421.80 (2.5%-97.5% quantile: 227.37-542.88). The genome size of 27 S. agalactiae varied from 2,186,837 to 2,069,980 bp. The average number of coding sequence in all isolates was 2,118. Furthermore, all S. agalactiae belonging to type II-A CRISPR-Cas system. The assembly statistics, repeat regions, and fragments coding for rRNA, tRNA and tmRNA are shown in Supplementary Table 2 , and only isolates from herd B consist prophage regions. Putative virulence genes of all isolates from the three Chinese dairy herds were classified into six functional categories: adherence, immune evasion, immunoreactive antigen, toxin, protease, and enzyme. A total of 34 putative virulence factors were identified, including four adherence-related genes ( fbs54, fbsB, plr/gapA , tuf ), nine immune evasion related genes ( cpsA, cpsB, cpsC, cpsD, cpsF, cpsG, cpsK, and cpsL ), 13 toxin-related genes ( acpC, cylA, cylB, cylD, cylE, cylF, cylG, cylI, cylJ, cylK, cylX, cylZ, and cfa/cfb ), three enzyme-related genes ( hylB , mf3 and eno ), three protease-related genes ( cppA, htrA/degP, tig/ropA ) and two immunoreactive antigen and manganese related genes ( sip and psaA ). Detailed information on virulence associated genes are provided in Supplementary Dataset 1 . The AMR genes were identified with CARD databases, and all S. agalactiae isolates contained mprF gene. Isolates from herd C harbored tetO gene, whereas four isolates from herd C (C04, C05, C35, C50) also carried the ermB gene. Meanwhile, isolates from herd A contained tetM gene (Supplementary Table 1) . Genome-wide association analyses The GWAS analysis identified 166 genes associated with virulence, 221 genes associated with adhesion and 218 genes associated with invasion. In total, 47 genes were correlated with mortality rates of G. mellonella at 18, 24, and 36 h ( Supplementary Dataset 1 , Fig. 3). Interestingly, these 47 genes also had correlations with cytotoxicity, adhesion, and invasion ( Supplementary Fig. 3 ). Bin3 and soj were mainly related to DNA repair, whereas AdhA2 were involved in signal transduction. Presence of AadK and tetO suggest antimicrobial resistance in S. agalactiae isolates. AadK is an aminoglycoside nucleotidyl transferase that mediates low-level resistance to streptomycin. Positive correlations between the presence of antimicrobial resistance genes and MIC against certain antimicrobials were found. The isolates from herd C and A had both tetO and tetM gene were resistance to tetracycline and oxytetracycline. Four isolates with ermB gene were resistant to azithromycin and tylosin. Pan-genome wide association analyses Genome structures of the 27 sequenced S. agalactiae isolates were further analyzed in combination with 1,394 whole genome sequences of S. agalactiae deposited in NCBI genome database. The MLST-based minimum-spanning tree is displayed in Fig. 4. Among all 1,421 isolates, serotype III was dominant serotype, with a total of 381 isolates (Fig. 4a), followed by type Ia with 280 isolates, and type II with 264 isolates. The ST103 differed by one allele from ST651 (human) and by two alleles from ST930 (human) and ST485 (human). Except SG2 which belongs to Ib, all ST103 isolates belonged to serotypes Ia. The distribution of species origin of those S. agalactiae isolates is presented in Fig. 4b. There were 901 isolates of human origin, 221 isolates from bovine and 36 isolates from fish. Pan-genome analysis revealed that 1,421 S. agalactiae isolates contained 20,955 genes (Fig. 5 ) . The core genome (present in all isolates) consisted of 666 genes. Soft-core genes (present in ≥ 95% but not all isolates), shell genes (present in ≥ 10% while ˂ 95% isolates), and cloud genes (present in ˂ 10% of isolates) consisted of 390, 1 626, and 18 273 genes, respectively, whereas the unique genome had 7 364 genes in cloud genes (Fig. 6a ) . The pan-genome size increased with number of isolates, but the number of core genes stabilized at approximately 666 (Fig. 6b ) . A phylogenetic tree was constructed based on core genes of 1,421 S. agalactiae isolates including the 27 isolated from our samples ( Fig. 7 ) . Genome sequences of isolates within the same herd were highly homologous, genome sequences of isolates from herd C were more homologous to genomes of isolates from herd A, but more phylogenetically distant from genomes of isolates in herd B. Among the 12 isolates of bovine origin, DK-B-USS-084 was isolated in the 1990s in Denmark, PZD12, M19, PZD30, PZD29, C001, NJ1606, 8B14M, and G9 were isolated in the 2010s; MRI Z1-023, G6-23, and G1-9 were only from cattle. GBS85147 is a human isolate isolated from Brazil in the 1990s. CH24 (Kenya, 2008), VB11227, BSU451 (2015), SG2 (China, 2018), and LZF004 (China) were also isolated from humans. With the exception of SG2 and PZD30, whose serotypes are unknown, all other isolates belonged to type Ia. Functional annotation of genes in these 27 isolates, using the COG (Cluster of Orthologous Groups of Complete Eukaryotic Genomes) and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases, revealed core, accessory and unique gene functions annotation distribution. According to the COG functional category, most core genes were related to information storage, processing and metabolism, whereas most auxiliary genes were related to metabolism, and unique genes were related to metabolism (Fig. 8a ) . Based on KEGG functional categories, most core genes were related to metabolism, most auxiliary genes were related to genetic information processing and metabolism, and unique genes were related to metabolism (Fig. 8b ) . COG and KEGG functional categories of genes belong core, accessory and unique genome are shown in Fig. 8c and Fig. 8d, respectively. Discussion This study provides relatively comprehensive characterization of S. agalactiae isolated from three Chinese dairy herds with outbreaks of S. agalactiae . Isolates in herd C were significantly higher in virulence (indicated by LDH, adherence, invasion and G. mellonella infection). Interestingly, 34 virulence-related genes were obtained for all isolates annotated by VFDB ( Streptococcus spp.). Furthermore, GWAS predicted 166 genes associated with virulence, 221 genes associated with adhesion, 218 genes associated with invasion, and 47 genes associated with pathogenicity in infecting G. mellonella . ST103 is a prevalent sequence type in northern Europe [ 19 ], China [ 4 , 20 ], Colombia [ 21 ] and Brazil [ 22 ]. ST103 isolates are from both human and cattle origin, suggesting potential host adaptation of S. agalactiae . This implies they did not evolve uniquely within a single host, perhaps representing a missing links between human and bovine-adapted clones [ 24 ]. There were 34 virulence factors responsible for adhesion, invasion, colonization, and defense against host immune responses. Among isolates, only C04, C05, C06, C07, C23, and B15 had the mf3 gene. In contrast, the cylX gene was absent in isolates C24, C35, and all samples from herd B. This could explain some variations among isolates in virulence phenotypes. Genes such as fbp54 [ 25 ], fbsB [ 26 ], mf3 [ 27 ], and hylB [ 28 ] are involved in these processes, facilitating attachment to extracellular matrix proteins and host cells, promoting bacterial colonization, and interfering with host immune responses. The protein sip , which is widely distributed and highly conserved, has immunogenic properties and strong adhesion ability, making it a potential target for developing vaccine [ 28 ]. These findings highlighted the importance of these surface proteins in S. agalactiae pathogenesis. S. agalactiae has several immune evasion factors, including capsule synthesis-related genes, and toxin-related genes β -Hemolysin/Cytolysin cfa/cfb [ 29 ]. The β -h/c-dependent hemolysis is produced through a series of reactions orchestrated by translational products of components encoded in the cyl operon ( acpC , cylA , cylB , cylD , cylE , cylF , cylG , cylI , cylJ , cylK , cylX , and cylZ ) and acts as a hemolytic lipid essential for hemolysis. These factors enable S. agalactiae to escape the host immune system through various mechanisms, e.g., inhibiting complement activation, degrading immune proteins, and interfering with immune cell functions. The presence of these immune evasion factors contributes to S. agalactiae pathogenicity and persistence. Furthermore, cppA , tig , psaA , tuf , htrA , gapA , and eno are involved in the turnover of surface proteins, facilitating attaching, invading host cells, and evading host immune system [ 30 – 33 ]. The GWAS analysis identified several genes correlated with virulence, adhesion, invasion, and survival of G. mellonella , indicating their roles in bacterial adhesion, colonization, and invasion and pathogenicity. In short, bin3 is a putative transposon (Tn552 DNA-invertase bin3), AdhA2 is associated with alcohol dehydrogenase activity [ 34 ] and the aadK gene encodes aminoglycoside 6-adenylyltransferase and inactivate the macrolides [ 35 ]. Furthermore, tetracycline resistance genes tetO was also detected [ 36 ]. Moreover, soj also known as parA [ 37 ] functions as a chromosome-partitioning ATPase, facilitating DNA segregation within daughter cells by interacting with the segregation complex [ 38 ]. These findings provide new insights regarding pathogenicity and potential targets for development of new strategies to treat and control S. agalactiae mastitis. In this study, the MICs of S. agalactiae (27 isolates) were measured against 13 antimicrobials. All isolates were resistant to tilmicosin, among which the resistance rates to oxytetracycline and tetracycline were high (74.07% and 55.56%). These might indicate a high resistance rate in S. agalactiae and warrant urgently prudent use of these three antimicrobials in dairy farming. Finally, all isolates were sensitive to ceftiofur, penicillin, amoxicillin and clindamycin, suggesting a strategy for treatment. Subsequently, comparison with the reference CARD revealed the presence of AMR genes, including the presence of the mprF gene in all isolates. This gene encodes a phosphatidylglycerol lysyltransferase and is known to be involved in S. agalactiae virulence and resistance to cationic antimicrobial peptides [ 39 ]. Furthermore, isolates from herd C carried tetO [ 40 ] and isolates from herd A consist of tetM , conferring resistance against tetracyclines antimicrobials [ 40 , 41 ]. Resistance to erythromycin and clindamycin are mediated by erm(B) (16/193, 8.2%) [ 42 ]. Additionally, four isolates had the ermB gene, and those four isolates were resistant to macrolides antimicrobials, meanwhile all isolates were resistant to tilmicosin, but most of isolates were sensitive to other antimicrobials [ 43 ]. The enzyme encoded by the ermB gene can reduce the binding of macrolide and lincosamide antimicrobials in bacteria, thereby reducing their inhibitory effect on bacteria and making bacteria resistant to erythromycin. Our results found that isolates containing ermB gene are highly resistant to macrolide antimicrobials. But those isolates carrying the ermB gene are mostly sensitive to clindamycin, the underlying mechanism warrant further study. Antimicrobial resistance among these groups underscores the importance of surveillance of AMR in S. agalactiae isolated from dairy herds to curb the antimicrobial resistance in dairy farming. We observed differences in the number of predicted prophage regions in the genomes of isolates from different regions, which is consistent with Sváb et al. [ 44 ]. This finding highlighted the genetic diversity of S. agalactiae in various geographical regions. Conclusions This study characterized S. agalactiae isolated from three dairy herds in China, including population structures, virulence phenotypes, and AMR profiles. Our findings highlighted the importance of understanding the genetic basis of virulence and AMR in S. agalactiae which could be used to inform designing effective control and prevention strategies for bovine mastitis caused by S. agalactiae . Additionally, this study also predicted a large number of genes related to virulence, adhesion and invasion that may be important targets for future research on the pathogenesis of S. agalactiae and developing novel therapeutics. Abbreviations bMECs: bovine mammary epithelial cells; MOI: multiplicity of infection; CFU: colony forming unit; DMEM: Dulbecco's modified eagle medium; PBS: phosphate-buffered saline; MLST: multi-locus sequence typing; MIC: Minimum inhibitory concentrations; STs: Sequence types; VFDB: Virulence Factors Database; CARD: Comprehensive Antimicrobial Research Database; WGS: whole genome sequencing; GWAS: genome-wide association studies. Declarations The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be seen as potential conflicts of interest. Statement of Ethics This study all animal experiments were performed in accordance with the animal welfare and animal experiment ethical guidelines and standards of biosafety and institutional safety regulations of China Agricultural University (CAU; Beijing, China). Prior to the beginning of this study, we obtained the approval of the Animal Welfare and Animal Experimental Ethics Review Committee of China Agricultural University (Issue No: AW01605202-2-02). All deceased Galleria mellonella were collected in biohazard bags labeled as "infectious waste" followed by autoclaving (121°C, 15 min) and incineration according to laboratory biosafety protocols. Moribund larvae (e.g., melanized but not fully expired) were rapidly frozen at -20°C prior to identical sterilization and disposal procedures. These measures comply with institutional biosafety regulations. We confirm that informed consent for sample collection and subsequent data release was obtained from all cattle owners prior to sample collection. Data availability statement Datasets presented in this study are in online repositories (names of the repository/repositories and accession number(s) are in the article or Supplementary Material). All whole genome sequence data used in this study are available without restriction from NCBI (BioProject no. PRJNA 933979). Funding This study was supported financially by the National Natural Science Foundation of China (No. 31772813), the High-end Foreign Experts Recruitment Program (No. G2022108009L) and Natural Science Foundation of Beijing, China (No. 6244052). A uthorship contribution statement Yue Wang, Siyu Meng, Halihaxi Bahetijiang, Haoxia Li, Tian Wang, Talgat Assabayev: Writing - original draft, Data curation, analysed data, Investigation. Zhaoju Deng, Herman W Barkema, John P Kastelic, Bo Han: Writing - review & editing. Bo Han: conceived and designed the experiment, Supervision, Investigation. All authors approved the final version of the manuscript. Acknowledgements The authors thank our laboratory members who assisted us with the research and the manuscript, for their skillful technical assistance, invaluable comments, and suggestions. 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Front Microbiol . 2022;13:896296. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.pdf Supplementary Figure 1. Geographical location of the three dairy farms in China. SupplementaryFigure2.pdf Supplementary Figure 2. Multiplex PCR-based molecular serotyping of 116 S. agalactiae . Amplicons for all isolates measured 680 and 272 bp. SupplementaryFigure3.pdf Supplementary Figure 3. Distribution of virulence factors and antimicrobial resistance genes in those 27 S. agalactiae isolates. SupplementaryTable1.xlsx Supplementary Table 1 Distributions of antimicrobial resistance genes in 27 S. agalactiae isolates. SupplementaryTable2.xlsx Supplementary Table 2 Sequencing, assembly statistics and annotations of 27 S. agalactiae isolates. SupplementaryDataset1.xlsx Supplementary Dataset 1 LDH, adhesion, invasion, and mortality-related genes in G. mellonella identified by GWAS analysis. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6746409","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483214229,"identity":"5f7ec185-8b18-4134-9de7-6238d335c1a0","order_by":0,"name":"Yue Wang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Wang","suffix":""},{"id":483214230,"identity":"1cf0ab6a-ac3d-4bfa-8b5d-3cef4a7594e7","order_by":1,"name":"Siyu Meng","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Siyu","middleName":"","lastName":"Meng","suffix":""},{"id":483214231,"identity":"8884b6c5-0362-4ce3-9429-838ade98630c","order_by":2,"name":"Halihaxi Bahetijiang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Halihaxi","middleName":"","lastName":"Bahetijiang","suffix":""},{"id":483214232,"identity":"92d85a8d-ee83-4185-8d89-ae66d51ee8eb","order_by":3,"name":"Haoxia Li","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Haoxia","middleName":"","lastName":"Li","suffix":""},{"id":483214233,"identity":"0a56de6a-80dd-4f1d-b26a-279f42d9d122","order_by":4,"name":"Tian Wang","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Wang","suffix":""},{"id":483214234,"identity":"6fc21392-8e4e-4e27-86dd-258c302b0835","order_by":5,"name":"Talgat Assabayev","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Talgat","middleName":"","lastName":"Assabayev","suffix":""},{"id":483214235,"identity":"2a04cafc-82d6-4332-a9a1-2016b08c7f2c","order_by":6,"name":"Herman W Barkema","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"prefix":"","firstName":"Herman","middleName":"W","lastName":"Barkema","suffix":""},{"id":483214236,"identity":"2848b844-30f7-4023-8eb5-b34bf06e3a8e","order_by":7,"name":"John P Kastelic","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"P","lastName":"Kastelic","suffix":""},{"id":483214237,"identity":"5789ac9a-da10-4559-bafa-f2147dcb6876","order_by":8,"name":"Bo Han","email":"","orcid":"","institution":"China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Han","suffix":""},{"id":483214238,"identity":"af04db47-2772-4057-8e6b-5243cbff569c","order_by":9,"name":"Zhaoju Deng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDACCQhmbADiBxChBOK1MBsQr4UBooVNgigt8rObHz6wbGOQ7Zduv1bxo+YwAz97jgHDzx24tTDOOWZsINnGYDxzzpmymz3HDjNI9rwxYOw9g1sLs0SCmQRQS+KGGzlptxnYDjMY3MgxYGZsw62FTSL9G1jLfqCWYoZ/hxnsCWnhkciB2iKRfgyoEmiLBAEtEhI5xQYS5xiMZ9zIYZbs7UvnkTjzrOBgLx4t8jPSNz6WKAOG2Iz0hx9+fLOW429P3vjgJx4tkCBg+A9yIzgmeUDEAfwagAH9AUyxPyCkcBSMglEwCkYoAAAYf007mAJeBQAAAABJRU5ErkJggg==","orcid":"","institution":"China Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Zhaoju","middleName":"","lastName":"Deng","suffix":""}],"badges":[],"createdAt":"2025-05-26 02:38:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6746409/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6746409/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12866-025-04315-7","type":"published","date":"2025-10-14T15:57:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86418476,"identity":"6be70d41-bc11-4a66-a98f-65cbebd84b9c","added_by":"auto","created_at":"2025-07-10 12:15:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":492773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCytotoxicity, adhesion and invasion ability of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae\u003c/strong\u003e\u003c/em\u003e \u003cstrong\u003eto bMECs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea and b\u003c/strong\u003e. Cytotoxicity measured by LDH release with an MOI of 5 and 9 h incubation. \u003cstrong\u003ec\u003c/strong\u003e \u003cstrong\u003eand d.\u003c/strong\u003e Relative adhesion measured with an MOI of 5 and 2 h incubation. \u003cstrong\u003ee and f.\u003c/strong\u003e Relative invasion measured with an MOI of 5 and 3 h incubation. n = 3 independent samples. Data are expressed as mean ± SD. The significant difference was detected by one-way ANOVA with Tukey’s multiple comparisons test. \u003csup\u003ea-j \u003c/sup\u003eIsolates without a common superscript differed between each other.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/a76086568e3f5510a5ce10c0.png"},{"id":86417633,"identity":"d512eb5c-fd6b-4755-b15f-910898d4cca9","added_by":"auto","created_at":"2025-07-10 11:59:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":544435,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSurvival curve of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eGalleria mellonella\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e infected with 27 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolated from three Chinese dairy herds.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/5089de2a32ad7f50c8305da0.png"},{"id":86418475,"identity":"f566fb11-b19a-425e-9b61-f21b1d99cfbb","added_by":"auto","created_at":"2025-07-10 12:15:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":384067,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSignificant genes identified by GWAS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003eVenn diagrams showing genes associated with survival of \u003cem\u003eG. mellonella\u003c/em\u003e. \u003cstrong\u003eb.\u003c/strong\u003e Venn diagrams illustrating genes related to virulence, adhesion, invasion and survival at 18, 24, and 36 h.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/604ca5f831e3d742b112b963.png"},{"id":86417636,"identity":"c898e3c6-829e-4538-bdea-4b3d03d45b19","added_by":"auto","created_at":"2025-07-10 11:59:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":972349,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMLST analysis of 1,421 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eisolates.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003eMLST allelic map nodes based on serotype distribution, with distinct nodes indicating different ST types, and colors denoting diverse serotypes. \u003cstrong\u003eb.\u003c/strong\u003eMLST allelic map nodes based on origin distribution, showing unique nodes for distinct ST types, and different colors indicating varied origins.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/1bab5b4385c9c7f34f953f21.png"},{"id":86417646,"identity":"e82aee67-6a4e-4f06-8f43-12c292bb52c0","added_by":"auto","created_at":"2025-07-10 11:59:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1833917,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePresence/absence matrix of genes in each \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eisolate in Pan-genome analysis of 1,421 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eisolates.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePresent (blue) or absent (white) of core and accessory genes indicated on the generated tree. The 1,421 isolates included 20,955 genes.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/acc2b6f9e19927fe9eeb1199.png"},{"id":86418478,"identity":"20508a81-ad07-4745-b9b4-ca85bf72c6b6","added_by":"auto","created_at":"2025-07-10 12:15:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":686148,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePan-genome analysis of 1,421 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eisolates.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea. \u003c/strong\u003ePan-genome composition depicted in a pie chart: core genes (666 genes, 99% ≤ isolates ≤ 100%), soft-core genes (390, 95% ≤ isolates \u0026lt; 99%), shell genes (1,626, 95% ≤ isolates \u0026lt; 99%), cloud genes (18273, 95% ≤ isolates \u0026lt; 99%), and unique genes (7,364). \u003cstrong\u003eb.\u003c/strong\u003e Genome size increased with number of isolates, stabilized at 666 core genes.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/d917d626830c2cc8aa720a0e.png"},{"id":86417831,"identity":"44bd6ea8-6fbc-47a1-9eb7-1b8d3316485c","added_by":"auto","created_at":"2025-07-10 12:07:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2092430,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogeny of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates based on core-genes\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003ePhylogenetic tree based on core genes of 1,421 genomes.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/bafc59a6f60a04c698bd2429.png"},{"id":86417835,"identity":"d63e8512-aaa9-4c50-9f0a-1b3778a4278e","added_by":"auto","created_at":"2025-07-10 12:07:47","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1958136,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCOG and KEGG functional categories in core, accessory and unique genes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003eDistribution of four COG functional categories in core, accessory, and unique genes. \u003cstrong\u003eb. \u003c/strong\u003eCOG functional sub-categories within core, accessory, and unique genes. \u003cstrong\u003ec. \u003c/strong\u003eDistribution of six KEGG functional categories among core, accessory, and unique genes. \u003cstrong\u003ed.\u003c/strong\u003e KEGG functional sub-categories within core, accessory and unique genes\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/bf209ba1ec924d1c14c29127.png"},{"id":93955996,"identity":"6029d35a-767a-4a4e-8113-dcbfc8620a4a","added_by":"auto","created_at":"2025-10-20 16:09:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9963397,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/bdb71add-a9d5-4706-800e-27fdd37c7082.pdf"},{"id":86418477,"identity":"db97a881-b37d-4bc8-b382-e23efe271ae5","added_by":"auto","created_at":"2025-07-10 12:15:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":981143,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1. Geographical location of the three dairy farms in China.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/b2246f43a0a20cbb2faa114b.pdf"},{"id":86417826,"identity":"29f7b834-c80a-4228-84d6-858b1b2a2f2b","added_by":"auto","created_at":"2025-07-10 12:07:47","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":36316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 2. Multiplex PCR-based molecular serotyping of 116 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmplicons for all isolates measured 680 and 272 bp.\u003c/p\u003e","description":"","filename":"SupplementaryFigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/99a3fcb89b323bfd5cddd23e.pdf"},{"id":86417641,"identity":"02669dce-eeb4-45b2-afbb-80d19c69c5bc","added_by":"auto","created_at":"2025-07-10 11:59:47","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":151265,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 3. Distribution of virulence factors and antimicrobial resistance genes in those 27 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. agalactiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryFigure3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/1cfcb1439e129e6c4fac679c.pdf"},{"id":86417643,"identity":"634889dc-d1f8-4632-8932-644888271508","added_by":"auto","created_at":"2025-07-10 11:59:47","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":19361,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDistributions of antimicrobial resistance genes in 27 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates.\u003c/p\u003e","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/7f4f2b460d273c43c87c23a0.xlsx"},{"id":86419061,"identity":"49a572d8-f77a-4d2d-94d2-a54a8e9bfd06","added_by":"auto","created_at":"2025-07-10 12:23:47","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":18229,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSequencing, assembly statistics and annotations of 27 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates.\u003c/p\u003e","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/1b93fbdbb486752b5def3cb5.xlsx"},{"id":86417836,"identity":"48a6e2cb-159f-439f-8724-af7eea76db27","added_by":"auto","created_at":"2025-07-10 12:07:47","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":121741,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Dataset 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLDH, adhesion, invasion, and mortality-related genes in \u003cem\u003eG. mellonella\u003c/em\u003eidentified by GWAS analysis.\u003c/p\u003e","description":"","filename":"SupplementaryDataset1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6746409/v1/ded4a11b9bfb5ed8851162ba.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePhenotypic and genotypic characterization of ST103 Serotype Ia \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e isolated from bovine mastitis in China\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBovine mastitis is one of the most prevalent and problematic diseases that mainly caused by bacterial pathogens in dairy farming worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Mastitis pathogens are generally classified into two categories, namely contagious and environmental pathogens, although recent studies suggest there is no distinct boundary between those two categories [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Contagious bacterial pathogens include \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e, and the prevalence of \u003cem\u003eS. aureus\u003c/em\u003e and \u003cem\u003eS. agalactiae\u003c/em\u003e have been largely under control since the implementation of the \u0026ldquo;five-point\u0026rdquo; mastitis plan especially in the developed countries [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, recent epidemiological studies suggest increased prevalence of \u003cem\u003eS. agalactiae\u003c/em\u003e in Nordic countries [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and China [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Over the past two decades, China has seen a significant increase in herd size and improvement in dairy farming management, along with the increased prevalence of \u003cem\u003eS. agalactiae\u003c/em\u003e. Recent studies showed the isolation rate of \u003cem\u003eS. agalactiae\u003c/em\u003e from mastitis cases in dairy herds ranges from 2.0 to 25.0% in China [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, the population structure and molecular characteristics of \u003cem\u003eS. agalactiae\u003c/em\u003e remain elusive in Chinese dairy herds.\u003c/p\u003e\u003cp\u003ePopulation structure and genetic diversity of pathogens determines the control measures for contagious mastitis pathogens. \u003cem\u003eS. agalactiae\u003c/em\u003e has been classified into ten serotypes (Ia, Ib, II\u0026ndash;IX) based on capsular polysaccharide [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Both the predominant serotypes and genotypes of \u003cem\u003eS. agalactiae\u003c/em\u003e vary across regions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In China, the most prevalent serotype and genotypes of \u003cem\u003eS. agalactiae\u003c/em\u003e are serotype II, and genotype ST67, ST103 and ST568, respectively [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, it is important to determine the population structure of \u003cem\u003eS. agalactiae\u003c/em\u003e in order to design tailor-made effectively control programs for \u003cem\u003eS. agalactiae\u003c/em\u003e caused mastitis.\u003c/p\u003e\u003cp\u003eBacterial pathogenicity depends on multiple virulence factors including adhesion, immune evasion, and toxin [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These virulence factors are vital for survival, transmission and infection within and across hosts [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Capsular polysaccharide, an important virulence factor in \u003cem\u003eS. agalactiae\u003c/em\u003e, is used to characterize antigenicity and immunogenicity and also used for serotyping [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While the distribution of virulence factors is still lacking for \u003cem\u003eS. agalactiae\u003c/em\u003e in Chinese dairy herds. In addition, antimicrobial resistance deteriorates the effect of antimicrobial treatment, therefore, the aims of this study were to (1) determine the population structure; (2) profile the antimicrobial resistance and (3) investigate the pathogenicity as well as genes associated with pathogenicity in \u003cem\u003eS. agalactiae\u003c/em\u003e isolated from Chinese dairy herds.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSample collection and bacterial species identification\u003c/h2\u003e\u003cp\u003eA total of 266 milk samples (235 clinical mastitis samples and 31 subclinical mastitis samples) were collected from three large dairy farms with outbreaks of bovine mastitis in Ningxia and Hebei provinces of China from September 2020 to April 2021. Clinical mastitis and subclinical mastitis were defined according to National Mastitis Council (NMC) guidelines [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMilk samples were collected aseptically, stored in sterile plastic vials at 4\u0026deg;C, and transported to the Mastitis Reference Laboratory at China Agricultural University in Beijing, China. Bacterial species identification was performed using bacteriological culture, colony morphology, Gram staining, CAMP test, and 16S rRNA sequencing, according to NMC guidelines [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In brief, 10 \u0026micro;L of milk were streaked on tryptone soy agar plate (TSA; Aoboxing Biotechnology, Beijing, China) with 5% defibrinated sheep blood (Solarbio Technology, Beijing, China). These plates were incubated in an inverted position at 37\u0026deg;C for 24 to 48 h. Genomic DNA was extracted using a bacterial genomic DNA extraction kit (Accurate Biotechnology, Hunan, China), according to the Gram-positive bacteria genomic DNA extraction protocol. Concentration and purity of the extracted DNA were assessed (NanoDrop 2000; ThermoFisher Scientific, Waltham, MA, USA) before sequencing. All DNA samples with nucleoside concentration\u0026thinsp;\u0026ge;\u0026thinsp;50 ng/\u0026micro;L and purity indices A260/280\u0026thinsp;\u0026ge;\u0026thinsp;1.8, A260/230\u0026thinsp;\u0026ge;\u0026thinsp;2.0 were subjected to 16S rRNA sequencing and whole-genome sequencing.\u003c/p\u003e\u003cp\u003eThe 16S rRNA gene sequencing was performed using a pair of primers 27F and 1492R that commonly used to identify bacterial species. The PCR product was sequenced with 3730 platform (Thermo Fisher Scientific) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. After 16S rRNA sequencing, bacterial species were identified by blasting the 16S rRNA sequences against the sequences deposited in the National Center for Biotechnology Information (NCBI) database.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSerotyping\u003c/h3\u003e\n\u003cp\u003eAll \u003cem\u003eS. agalactiae\u003c/em\u003e isolates were serotyped with multiplex PCR with 19 specific primers to detect capsular polysaccharide (CPS) clusters [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The PCR reactions consisted of 2\u0026times;Green Taq Mix (Vazyme, Nanjing, China) and 250 nM of each specific primer, except primers cps-Ia-6-7-F and cps-7-9-F, which used 400 nM of each (Shanghai Sangon Biotech Company, Shanghai, China). Serotyping PCR procedure includes: 5 min at 95\u0026deg;C, followed by 15 cycles of 95\u0026deg;C for 60 s, 54\u0026deg;C for 60 s, 72\u0026deg;C for 2 min, and then by additional 25 cycles of 95\u0026deg;C for 60 s, 56\u0026deg;C for 60 s, 72\u0026deg;C for 2 min and a final cycle of 72\u0026deg;C for 10 min. The PCR products were examined on 1.5% agarose gel using a gel documentation system.\u003c/p\u003e\n\u003ch3\u003eMulti-locus sequence typing (MLST)\u003c/h3\u003e\n\u003cp\u003eMLST was performed on 116 isolates based on seven housekeeping genes: \u003cem\u003eadhP\u003c/em\u003e, \u003cem\u003epheS\u003c/em\u003e, \u003cem\u003eatr\u003c/em\u003e, \u003cem\u003eglnA\u003c/em\u003e, \u003cem\u003esdhA\u003c/em\u003e, \u003cem\u003eglcK\u003c/em\u003e, and \u003cem\u003etkt\u003c/em\u003e. All primer sequences that were amplified for sequencing were obtained from the MLST database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sagalactiae.mlst.net\u003c/span\u003e\u003cspan address=\"http://sagalactiae.mlst.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and synthesized by Shanghai Sangon Biotech Company. The 25-\u0026micro;L PCR reaction system contained 12.5 \u0026micro;L 2 \u0026times; Green Taq Mix (Vazyme), 50 ng template DNA, and 1 \u0026micro;L forward primer and reverse primer (10 \u0026micro;M). The PCR protocol was set as initial denaturation at 95\u0026deg;C for 3 min; 34 cycles of 95\u0026deg;C for 15 s, 57\u0026deg;C for 15 s and 72\u0026deg;C for 1 min; and final extension at 72\u0026deg;C for 5 min. Thereafter, PCR products were sequenced and blasted against to the MLST database to determine the MLST type of each isolate. The clonal complex of each isolate was determined with an eBURST algorithm using PHYLOViZ online (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://online.phyloviz.net/index\u003c/span\u003e\u003cspan address=\"https://online.phyloviz.net/index\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eVirulence, adherence and invasion assays\u003c/h3\u003e\n\u003cp\u003eStratified random sampling was performed to select isolates that capture the population structure and molecular characteristics using representative isolates in each herd, consequently, 27 isolates were selected (four isolates from herd A, 12 isolates from herd B and 11 isolates from herd C). Bovine mammary epithelial cells (bMECs, Jingma Biotechnology Co., Shanghai, China) were cultured in DMEM medium (Gibco, Brooklyn, NY, USA), supplemented with 5% fetal bovine serum (FBS, Gibco), overnight at 37\u0026deg;C in 5% CO\u003csub\u003e2\u003c/sub\u003e until cell density reached coverage of approximately 80%. These cells were transferred to 96-well plates for quantifying LDH release from cells [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Meanwhile, bMECs were also transferred to 24-well plates and cultured in 2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/well to assess adherence and invasion. Briefly, 27 isolates were diluted to 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e CFU/mL with DMEM medium containing 1% FBS before adding to the monolayer of bMECs at multiplicity of infection (MOI)\u0026thinsp;=\u0026thinsp;5:1 and incubated for 9 h, 2 h or 3 h for quantifying LDH release, adherence and invasion rate, respectively.\u003c/p\u003e\u003cp\u003eCytotoxic effect of \u003cem\u003eS. agalactiae\u003c/em\u003e on bMECs were evaluated with an LDH assay kit (Beyotime Biotechnology, Beijing, China). After infection, 200 \u0026micro;L of supernatant from experimental and control groups were collected, transferred to centrifuge tubes, and centrifuged (8,000 \u0026times; g for 5 min at 4\u0026deg;C). Then, 120 \u0026micro;L of the supernatant was transferred to a new 96-well polystyrene plate and 60 \u0026micro;L of the reaction mixture was added to each well, and incubated on a rotator shaker (150 rpm) at room temperature in dark for 30 min. Absorbance of the incubation mixture was read at 490 nm (680 Multipurpose Microplate Reader; Bio-Rad Laboratories, Berkeley, CA, USA).\u003c/p\u003e\u003cp\u003eAdherence and invasion assays were performed according to Bonsaglia \u003cem\u003eet al.\u003c/em\u003e (2023) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Unbound bacteria were removed by washing three times with 1 \u0026times; PBS, the bMECs were digested with trypsin and the mixture was cultured on TSA plate with 5% defibrinated sheep blood, consequently, the CFU of adhering bacteria was enumerated after incubating for 24 h at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. For the invasion assay, after washing three times with 1 \u0026times; PBS, bMECs were placed in 500 \u0026micro;L of DMEM medium with 1% FBS containing 100 \u0026micro;g/mL penicillin for 30 min to kill extracellular bacteria. Plates were incubated for 1 h at 37\u0026deg;C in 5% CO\u003csub\u003e2\u003c/sub\u003e. Thereafter, bMECs were washed three times with 1 \u0026times; PBS, and the bMECs were digested with trypsin, the CFU of invading bacteria was determined by inoculating the digested cell mixture on TSA with 5% defibrinated sheep blood. Attachment and adhesion were calculated according to Xu \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eGalleria mellonella\u003c/b\u003e \u003cb\u003einfection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe infection experiment was performed following the protocol in Six \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In brief, 10 \u003cem\u003eG. mellonella\u003c/em\u003e larvae (2 to 2.5 cm long) were challenged with 3\u0026times;10\u003csup\u003e7\u003c/sup\u003e CFU of \u003cem\u003eS. agalactiae\u003c/em\u003e in each group at 37\u0026deg;C. At the same time, ten larvae in control group were injected with 10 \u0026micro;L 0.9% Sodium chloride solution. Survival and clinical signs of larvae were evaluated at six time points (12, 18, 24, 36, 48, and 60 h post infection). Survival analysis was performed to examined the pathogenicity of \u003cem\u003eS. agalactiae\u003c/em\u003e using Kaplan-Meier survival analysis with survfit function in survival package (version 3.5.7, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/survival/index.html\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/survival/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and survival plot was produced with ggsurvplot function in survminer package (version 0.4.9, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/survminer/index.html\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/survminer/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eAntimicrobial susceptibility testing\u003c/h3\u003e\n\u003cp\u003eMinimal inhibitory concentration (MIC) of each isolate against each antimicrobial was determined according to the CLSI VET01 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] or CLSI guidelines [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Breakpoints were applied to interpret antimicrobial susceptibility and resistance according to CLSI VET01 or CLSI wherever no veterinary breakpoint available, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e ATCC 29213 and \u003cem\u003eS. agalactiae\u003c/em\u003e ATCC 13813 were used as quality-control isolates. The tested antimicrobials included amoxicillin, ampicillin, azithromycin, ceftiofur, clindamycin, enrofloxacin, erythromycin, oxytetracycline, penicillin G, tetracycline, tilmicosin, tylosin, and vancomycin. Association between antimicrobial resistance indicate by MIC and presence of antimicrobial resistance genes was tested using Fisher exact test.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eWhole genome sequencing\u003c/h2\u003e\u003cp\u003eRepresentative isolates (n\u0026thinsp;=\u0026thinsp;27) were randomly selected from clinical and subclinical mastitis cases for shotgun whole-genome sequencing. Genomic DNA samples were sent to Shanghai Personal Biotechnology Co., Ltd (Shanghai, China), and paired-end reads (2 \u0026times; 150 bp) were sequenced with Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA) sequencing platform.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGenome assembly and annotation\u003c/h3\u003e\n\u003cp\u003eQuality control of raw reads was performed using FastQC (version 0.11.9, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/s-andrews/FastQC\u003c/span\u003e\u003cspan address=\"https://github.com/s-andrews/FastQC\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Raw reads were filtered and trimmed using fastp (version 0.20.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/OpenGene/fastp\u003c/span\u003e\u003cspan address=\"https://github.com/OpenGene/fastp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The N50 value of the contigs were computed to assess the quality of assembly. Thereafter, the clean reads were assembled and annotated using SPAdes (version 3.13.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/ablab/spades\u003c/span\u003e\u003cspan address=\"https://github.com/ablab/spades\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Prokka (version1.14.6, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/tseemann/prokka\u003c/span\u003e\u003cspan address=\"https://github.com/tseemann/prokka\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), respectively. The quality controlled reads were aligned to the assemblies using bowtie2 (version 2.5.3, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/BenLangmead/bowtie2\u003c/span\u003e\u003cspan address=\"https://github.com/BenLangmead/bowtie2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the average coverage of depth of sequence from each isolate was calculated using samtools (version 1.20, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/samtools/samtools\u003c/span\u003e\u003cspan address=\"https://github.com/samtools/samtools\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The N50 and L50 statistics were obtained using quast (version 5.2.0, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/ablab/quast\u003c/span\u003e\u003cspan address=\"https://github.com/ablab/quast\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Genome sequences were filtered with average coverage of depth\u0026thinsp;\u0026gt;\u0026thinsp;30 for subsequent analysis.\u003c/p\u003e\n\u003ch3\u003eIdentification of virulence genes and AMR genes\u003c/h3\u003e\n\u003cp\u003eVirulence and AMR genes were detected using ABRicate (version 0.8, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/tseemann/abricate\u003c/span\u003e\u003cspan address=\"https://github.com/tseemann/abricate\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to blast whole genome sequences against gene sequences in the VFDB and CARD databases, with minimum identity of 60% sequence coverage and 75% nucleotide identity.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eGenome wide association analyses\u003c/h2\u003e\u003cp\u003eWe used the presence/absence of genes as independent variable and continuous phenotype data such as adhesion to, and invasion to bMECs as dependent variable to perform genome wide association analysis using linear mixed model (lme4 version 1.1\u0026ndash;34, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/lme4/index.html\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/lme4/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), respectively, Benjamini and Hochberg method was applied for multiple test correction. The Venn diagram was generated using BioLadder (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioladder.cn/web/#/pro/cloud\u003c/span\u003e\u003cspan address=\"https://www.bioladder.cn/web/#/pro/cloud\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a bioinformatics online analysis and visualization cloud platform.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePan-genome analysis\u003c/h2\u003e\u003cp\u003eThe pan-genome of 1,421 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates (27 isolates from our study and 1,394 isolates from the NCBI database) was constructed with Roary (version 3.13.0, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sanger-pathogens.github.io/Roary/\u003c/span\u003e\u003cspan address=\"http://sanger-pathogens.github.io/Roary/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using outputs produced by Prokka. Core genes (present in all genomes), accessory genes (present in two or more isolates but not all isolates) and unique genes (not shared by other genomes) were identified and visualized with Roary. Functional categories of genes in COG and KEGG categories were visualized using Roary. Core-genome based phylogenetic tree was constructed using Roary and visualized with iTOL (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://itol.embl.de/\u003c/span\u003e\u003cspan address=\"https://itol.embl.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analyses\u003c/h2\u003e\u003cp\u003eAll data analyses were performed in R (version 4.3.2, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and statistical significance was defined as a p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 unless stated otherwise.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDescriptive statistics of isolates\u003c/p\u003e\n\u003cp\u003eTo determine the population structure of \u003cem\u003eS. agalactiae\u003c/em\u003e in Chinese dairy herds, 116 isolates were obtained from 266 milk samples collected from three dairy herds with outbreaks of bovine mastitis (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1\u003c/strong\u003e). Brief descriptions of these isolates are in Table\u0026nbsp;1. Among culture-positive samples from these three herds, the positive rate of \u003cem\u003eS. agalactiae\u003c/em\u003e in milk samples was 29% (Ningxia herd A), 62% (Hebei herd B) and 39% (Hebei herd C), respectively.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eInformation of 116 ST 103 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates from outbreaks of bovine mastitis in 235 mastitis samples in 3 large (\u0026gt; 2000 cows) Chinese dairy herds.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eProvince\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eFarm\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eDate\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eMastitis type\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eNo. of samples\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eNo. of isolates\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ePositive rate (%)\u003csup\u003e1\u003c/sup\u003e\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eNingxia\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003eA\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e2021.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eSCM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e31\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e45.2\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e12.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHebei\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eB\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2020.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eCM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e81\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e50\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e61.7\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHebei\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2020.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eCM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e123\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e48\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e39\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e1: Positive rate: positive rate for\u0026nbsp;\u003cem\u003eS. agalactiae\u003c/em\u003e in milk samples\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eAMR profiles\u003c/h2\u003e\n \u003cp\u003eThe MIC of the selected 27 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates against 13 antimicrobials were shown in Table 2 \u003cstrong\u003eand Supplementary Table\u0026nbsp;1\u003c/strong\u003e. All isolates were resistant to tilmicosin, with 74.07%, 55.56% and 33.33% resistant to oxytetracycline, tetracycline and vancomycin, respectively. Resistance rates to enrofloxacin, tylosin, azithromycin, erythromycin, and ampicillin were 22.22%, 14.81%, 14.81%, 11.11%, and 3.70%, respectively. Finally, all isolates were sensitive to ceftiofur, penicillin G sodium, amoxicillin, and clindamycin.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe MIC of the 27 selected \u003cem\u003eS. agalactiae\u003c/em\u003e isolates bovine mastitis milk samples collected in 3 dairy farms to 13 antimicrobials.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eAntimicrobial\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"14\"\u003eMIC (µg/mL)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eResistance rate (%)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eMIC\u003csub\u003e50\u003c/sub\u003e (µg/mL)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eMIC\u003csub\u003e90\u003c/sub\u003e (µg/mL)\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026lt; 0.03\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.03\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.06\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.12\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.25\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e0.5\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e1\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e2\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e4\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e8\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e16\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e32\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e64\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026gt; 64\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eErythromycin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11.11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026lt;0.03\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e32\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAzithromycin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e6\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e14.81\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026gt;64\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTylosin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e16\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e14.81\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026gt;64\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTilmicosin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e17\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e100\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026gt;64\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTetracycline\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e55.56\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e32\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eOxytetracycline\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e74.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e32\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e32\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCeftiofur\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e11\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026lt;0.03\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePenicillin G sodium\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e20\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.12\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAmpicillin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.12\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAmoxicillin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e25\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eClindamycin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026lt;0.03\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.06\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eEnrofloxacin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e14\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e22.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eVancomycin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e10\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e9\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e33.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003eSerotyping and MLST\u003cp\u003eIsolate serotypes were determined by multiplex PCR, and the amplicon sizes of 116 isolates were 680 and 272 bp (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2\u003c/strong\u003e), suggesting that serotypes of these isolates from all three herds were all Ia. Furthermore, MLST analysis classified all \u003cem\u003eS. agalactiae\u003c/em\u003e isolates as ST103. Thereafter, 27 isolates were selected for further studies (11 isolates from herd A, four isolates from herd B and 12 isolates from herd C, respectively).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePathogenic effects of\u003c/strong\u003e \u003cstrong\u003eS. agalactiae\u003c/strong\u003e \u003cstrong\u003eon bMECs and\u003c/strong\u003e \u003cstrong\u003eGalleria mellonella\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIsolates from herd C stimulated a significantly higher LDH release from bMECs than those isolates from herds A and B (Fig. 1a \u003cstrong\u003eand b\u003c/strong\u003e). \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e isolates adhered to bMECs at 2 h post infection and invaded bMECs at 3 h post infection (Fig. 1c-f). Adhesion and invasion rates of isolates from herd C were significantly higher than those isolates from herd B. The survival of \u003cem\u003eG. mellonella\u003c/em\u003e infected with \u003cem\u003eS. agalactiae\u003c/em\u003e isolates from herd C was significantly lower compared to larvae infected with isolates from the other two herds \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;2\u003cstrong\u003e)\u003c/strong\u003e. The survival rate of larvae in the control group was 100%.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eWhole genome analyses\u003c/h2\u003e\n \u003cp\u003eThe mean average depth of coverage of the genome sequence of the 27 isolates was 421.80 (2.5%-97.5% quantile: 227.37-542.88). The genome size of 27 \u003cem\u003eS. agalactiae\u003c/em\u003e varied from 2,186,837 to 2,069,980 bp. The average number of coding sequence in all isolates was 2,118. Furthermore, all \u003cem\u003eS. agalactiae\u003c/em\u003e belonging to type II-A CRISPR-Cas system. The assembly statistics, repeat regions, and fragments coding for rRNA, tRNA and tmRNA are shown in \u003cstrong\u003eSupplementary Table\u0026nbsp;2\u003c/strong\u003e, and only isolates from herd B consist prophage regions.\u003c/p\u003e\n \u003cp\u003ePutative virulence genes of all isolates from the three Chinese dairy herds were classified into six functional categories: adherence, immune evasion, immunoreactive antigen, toxin, protease, and enzyme. A total of 34 putative virulence factors were identified, including four adherence-related genes (\u003cem\u003efbs54, fbsB, plr/gapA\u003c/em\u003e, \u003cem\u003etuf\u003c/em\u003e), nine immune evasion related genes (\u003cem\u003ecpsA, cpsB, cpsC, cpsD, cpsF, cpsG, cpsK, and cpsL\u003c/em\u003e), 13 toxin-related genes (\u003cem\u003eacpC, cylA, cylB, cylD, cylE, cylF, cylG, cylI, cylJ, cylK, cylX, cylZ, and cfa/cfb\u003c/em\u003e), three enzyme-related genes (\u003cem\u003ehylB\u003c/em\u003e, \u003cem\u003emf3\u003c/em\u003e and \u003cem\u003eeno\u003c/em\u003e), three protease-related genes (\u003cem\u003ecppA, htrA/degP, tig/ropA\u003c/em\u003e) and two immunoreactive antigen and manganese related genes (\u003cem\u003esip\u003c/em\u003e and \u003cem\u003epsaA\u003c/em\u003e). Detailed information on virulence associated genes are provided in \u003cstrong\u003eSupplementary Dataset 1\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eThe AMR genes were identified with CARD databases, and all \u003cem\u003eS. agalactiae\u003c/em\u003e isolates contained \u003cem\u003emprF\u003c/em\u003e gene. Isolates from herd C harbored \u003cem\u003etetO\u003c/em\u003e gene, whereas four isolates from herd C (C04, C05, C35, C50) also carried the \u003cem\u003eermB\u003c/em\u003e gene. Meanwhile, isolates from herd A contained \u003cem\u003etetM\u003c/em\u003e gene \u003cstrong\u003e(Supplementary Table\u0026nbsp;1)\u003c/strong\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \u003ch2\u003eGenome-wide association analyses\u003c/h2\u003e\n \u003cp\u003eThe GWAS analysis identified 166 genes associated with virulence, 221 genes associated with adhesion and 218 genes associated with invasion. In total, 47 genes were correlated with mortality rates of \u003cem\u003eG. mellonella\u003c/em\u003e at 18, 24, and 36 h (\u003cstrong\u003eSupplementary Dataset 1\u003c/strong\u003e, Fig.\u0026nbsp;3). Interestingly, these 47 genes also had correlations with cytotoxicity, adhesion, and invasion (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;3\u003c/strong\u003e). \u003cem\u003eBin3\u003c/em\u003e and \u003cem\u003esoj\u003c/em\u003e were mainly related to DNA repair, whereas \u003cem\u003eAdhA2\u003c/em\u003e were involved in signal transduction. Presence of \u003cem\u003eAadK\u003c/em\u003e and \u003cem\u003etetO\u003c/em\u003e suggest antimicrobial resistance in \u003cem\u003eS. agalactiae\u003c/em\u003e isolates. \u003cem\u003eAadK\u003c/em\u003e is an aminoglycoside nucleotidyl transferase that mediates low-level resistance to streptomycin. Positive correlations between the presence of antimicrobial resistance genes and MIC against certain antimicrobials were found. The isolates from herd C and A had both \u003cem\u003etetO\u003c/em\u003e and \u003cem\u003etetM\u003c/em\u003e gene were resistance to tetracycline and oxytetracycline. Four isolates with \u003cem\u003eermB\u003c/em\u003e gene were resistant to azithromycin and tylosin.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\"\u003e\n \u003ch2\u003ePan-genome wide association analyses\u003c/h2\u003e\n \u003cp\u003eGenome structures of the 27 sequenced \u003cem\u003eS. agalactiae\u003c/em\u003e isolates were further analyzed in combination with 1,394 whole genome sequences of \u003cem\u003eS. agalactiae\u003c/em\u003e deposited in NCBI genome database. The MLST-based minimum-spanning tree is displayed in Fig. 4. Among all 1,421 isolates, serotype III was dominant serotype, with a total of 381 isolates (Fig. 4a), followed by type Ia with 280 isolates, and type II with 264 isolates. The ST103 differed by one allele from ST651 (human) and by two alleles from ST930 (human) and ST485 (human). Except SG2 which belongs to Ib, all ST103 isolates belonged to serotypes Ia. The distribution of species origin of those \u003cem\u003eS. agalactiae\u003c/em\u003e isolates is presented in Fig. 4b. There were 901 isolates of human origin, 221 isolates from bovine and 36 isolates from fish.\u003c/p\u003e\n \u003cp\u003ePan-genome analysis revealed that 1,421 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates contained 20,955 genes (Fig. 5\u003cstrong\u003e)\u003c/strong\u003e. The core genome (present in all isolates) consisted of 666 genes. Soft-core genes (present in ≥ 95% but not all isolates), shell genes (present in ≥ 10% while ˂ 95% isolates), and cloud genes (present in ˂ 10% of isolates) consisted of 390, 1 626, and 18 273 genes, respectively, whereas the unique genome had 7 364 genes in cloud genes (Fig.\u0026nbsp;6a\u003cstrong\u003e)\u003c/strong\u003e. The pan-genome size increased with number of isolates, but the number of core genes stabilized at approximately 666 (Fig.\u0026nbsp;6b\u003cstrong\u003e)\u003c/strong\u003e. A phylogenetic tree was constructed based on core genes of 1,421 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates including the 27 isolated from our samples \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;7\u003cstrong\u003e)\u003c/strong\u003e. Genome sequences of isolates within the same herd were highly homologous, genome sequences of isolates from herd C were more homologous to genomes of isolates from herd A, but more phylogenetically distant from genomes of isolates in herd B. Among the 12 isolates of bovine origin, DK-B-USS-084 was isolated in the 1990s in Denmark, PZD12, M19, PZD30, PZD29, C001, NJ1606, 8B14M, and G9 were isolated in the 2010s; MRI Z1-023, G6-23, and G1-9 were only from cattle. GBS85147 is a human isolate isolated from Brazil in the 1990s. CH24 (Kenya, 2008), VB11227, BSU451 (2015), SG2 (China, 2018), and LZF004 (China) were also isolated from humans. With the exception of SG2 and PZD30, whose serotypes are unknown, all other isolates belonged to type Ia.\u003c/p\u003e\n \u003cp\u003eFunctional annotation of genes in these 27 isolates, using the COG (Cluster of Orthologous Groups of Complete Eukaryotic Genomes) and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases, revealed core, accessory and unique gene functions annotation distribution. According to the COG functional category, most core genes were related to information storage, processing and metabolism, whereas most auxiliary genes were related to metabolism, and unique genes were related to metabolism (Fig.\u0026nbsp;8a\u003cstrong\u003e)\u003c/strong\u003e. Based on KEGG functional categories, most core genes were related to metabolism, most auxiliary genes were related to genetic information processing and metabolism, and unique genes were related to metabolism (Fig.\u0026nbsp;8b\u003cstrong\u003e)\u003c/strong\u003e. COG and KEGG functional categories of genes belong core, accessory and unique genome are shown in Fig. 8c and Fig. 8d, respectively.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides relatively comprehensive characterization of \u003cem\u003eS. agalactiae\u003c/em\u003e isolated from three Chinese dairy herds with outbreaks of \u003cem\u003eS. agalactiae\u003c/em\u003e. Isolates in herd C were significantly higher in virulence (indicated by LDH, adherence, invasion and \u003cem\u003eG. mellonella\u003c/em\u003e infection). Interestingly, 34 virulence-related genes were obtained for all isolates annotated by VFDB (\u003cem\u003eStreptococcus\u003c/em\u003e spp.). Furthermore, GWAS predicted 166 genes associated with virulence, 221 genes associated with adhesion, 218 genes associated with invasion, and 47 genes associated with pathogenicity in infecting \u003cem\u003eG. mellonella\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eST103 is a prevalent sequence type in northern Europe [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], China [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Colombia [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and Brazil [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. ST103 isolates are from both human and cattle origin, suggesting potential host adaptation of \u003cem\u003eS. agalactiae\u003c/em\u003e. This implies they did not evolve uniquely within a single host, perhaps representing a missing links between human and bovine-adapted clones [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThere were 34 virulence factors responsible for adhesion, invasion, colonization, and defense against host immune responses. Among isolates, only C04, C05, C06, C07, C23, and B15 had the \u003cem\u003emf3\u003c/em\u003e gene. In contrast, the \u003cem\u003ecylX\u003c/em\u003e gene was absent in isolates C24, C35, and all samples from herd B. This could explain some variations among isolates in virulence phenotypes. Genes such as \u003cem\u003efbp54\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], \u003cem\u003efbsB\u003c/em\u003e [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], \u003cem\u003emf3\u003c/em\u003e [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and \u003cem\u003ehylB\u003c/em\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] are involved in these processes, facilitating attachment to extracellular matrix proteins and host cells, promoting bacterial colonization, and interfering with host immune responses. The protein \u003cem\u003esip\u003c/em\u003e, which is widely distributed and highly conserved, has immunogenic properties and strong adhesion ability, making it a potential target for developing vaccine [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These findings highlighted the importance of these surface proteins in \u003cem\u003eS. agalactiae\u003c/em\u003e pathogenesis. \u003cem\u003eS. agalactiae\u003c/em\u003e has several immune evasion factors, including capsule synthesis-related genes, and toxin-related genes \u003cem\u003eβ\u003c/em\u003e-Hemolysin/Cytolysin \u003cem\u003ecfa/cfb\u003c/em\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The \u003cem\u003eβ\u003c/em\u003e-h/c-dependent hemolysis is produced through a series of reactions orchestrated by translational products of components encoded in the \u003cem\u003ecyl\u003c/em\u003e operon (\u003cem\u003eacpC\u003c/em\u003e, \u003cem\u003ecylA\u003c/em\u003e, \u003cem\u003ecylB\u003c/em\u003e, \u003cem\u003ecylD\u003c/em\u003e, \u003cem\u003ecylE\u003c/em\u003e, \u003cem\u003ecylF\u003c/em\u003e, \u003cem\u003ecylG\u003c/em\u003e, \u003cem\u003ecylI\u003c/em\u003e, \u003cem\u003ecylJ\u003c/em\u003e, \u003cem\u003ecylK\u003c/em\u003e, \u003cem\u003ecylX\u003c/em\u003e, and \u003cem\u003ecylZ\u003c/em\u003e) and acts as a hemolytic lipid essential for hemolysis. These factors enable \u003cem\u003eS. agalactiae\u003c/em\u003e to escape the host immune system through various mechanisms, e.g., inhibiting complement activation, degrading immune proteins, and interfering with immune cell functions. The presence of these immune evasion factors contributes to \u003cem\u003eS. agalactiae\u003c/em\u003e pathogenicity and persistence. Furthermore, \u003cem\u003ecppA\u003c/em\u003e, \u003cem\u003etig\u003c/em\u003e, \u003cem\u003epsaA\u003c/em\u003e, \u003cem\u003etuf\u003c/em\u003e, \u003cem\u003ehtrA\u003c/em\u003e, \u003cem\u003egapA\u003c/em\u003e, and \u003cem\u003eeno\u003c/em\u003e are involved in the turnover of surface proteins, facilitating attaching, invading host cells, and evading host immune system [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe GWAS analysis identified several genes correlated with virulence, adhesion, invasion, and survival of \u003cem\u003eG. mellonella\u003c/em\u003e, indicating their roles in bacterial adhesion, colonization, and invasion and pathogenicity. In short, \u003cem\u003ebin3\u003c/em\u003e is a putative transposon (Tn552 DNA-invertase bin3), \u003cem\u003eAdhA2\u003c/em\u003e is associated with alcohol dehydrogenase activity [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and the \u003cem\u003eaadK\u003c/em\u003e gene encodes aminoglycoside 6-adenylyltransferase and inactivate the macrolides [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Furthermore, tetracycline resistance genes \u003cem\u003etetO\u003c/em\u003e was also detected [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Moreover, \u003cem\u003esoj\u003c/em\u003e also known as \u003cem\u003eparA\u003c/em\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] functions as a chromosome-partitioning ATPase, facilitating DNA segregation within daughter cells by interacting with the segregation complex [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These findings provide new insights regarding pathogenicity and potential targets for development of new strategies to treat and control \u003cem\u003eS. agalactiae\u003c/em\u003e mastitis.\u003c/p\u003e\u003cp\u003eIn this study, the MICs of \u003cem\u003eS. agalactiae\u003c/em\u003e (27 isolates) were measured against 13 antimicrobials. All isolates were resistant to tilmicosin, among which the resistance rates to oxytetracycline and tetracycline were high (74.07% and 55.56%). These might indicate a high resistance rate in \u003cem\u003eS. agalactiae\u003c/em\u003e and warrant urgently prudent use of these three antimicrobials in dairy farming. Finally, all isolates were sensitive to ceftiofur, penicillin, amoxicillin and clindamycin, suggesting a strategy for treatment. Subsequently, comparison with the reference CARD revealed the presence of AMR genes, including the presence of the \u003cem\u003emprF\u003c/em\u003e gene in all isolates. This gene encodes a phosphatidylglycerol lysyltransferase and is known to be involved in \u003cem\u003eS. agalactiae\u003c/em\u003e virulence and resistance to cationic antimicrobial peptides [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Furthermore, isolates from herd C carried \u003cem\u003etetO\u003c/em\u003e [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and isolates from herd A consist of \u003cem\u003etetM\u003c/em\u003e, conferring resistance against tetracyclines antimicrobials [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Resistance to erythromycin and clindamycin are mediated by \u003cem\u003eerm(B)\u003c/em\u003e (16/193, 8.2%) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Additionally, four isolates had the \u003cem\u003eermB\u003c/em\u003e gene, and those four isolates were resistant to macrolides antimicrobials, meanwhile all isolates were resistant to tilmicosin, but most of isolates were sensitive to other antimicrobials [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The enzyme encoded by the \u003cem\u003eermB\u003c/em\u003e gene can reduce the binding of macrolide and lincosamide antimicrobials in bacteria, thereby reducing their inhibitory effect on bacteria and making bacteria resistant to erythromycin. Our results found that isolates containing \u003cem\u003eermB\u003c/em\u003e gene are highly resistant to macrolide antimicrobials. But those isolates carrying the \u003cem\u003eermB\u003c/em\u003e gene are mostly sensitive to clindamycin, the underlying mechanism warrant further study. Antimicrobial resistance among these groups underscores the importance of surveillance of AMR in \u003cem\u003eS. agalactiae\u003c/em\u003e isolated from dairy herds to curb the antimicrobial resistance in dairy farming.\u003c/p\u003e\u003cp\u003eWe observed differences in the number of predicted prophage regions in the genomes of isolates from different regions, which is consistent with Sv\u0026aacute;b \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This finding highlighted the genetic diversity of \u003cem\u003eS. agalactiae\u003c/em\u003e in various geographical regions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study characterized \u003cem\u003eS. agalactiae\u003c/em\u003e isolated from three dairy herds in China, including population structures, virulence phenotypes, and AMR profiles. Our findings highlighted the importance of understanding the genetic basis of virulence and AMR in \u003cem\u003eS. agalactiae\u003c/em\u003e which could be used to inform designing effective control and prevention strategies for bovine mastitis caused by \u003cem\u003eS. agalactiae\u003c/em\u003e. Additionally, this study also predicted a large number of genes related to virulence, adhesion and invasion that may be important targets for future research on the pathogenesis of \u003cem\u003eS. agalactiae\u003c/em\u003e and developing novel therapeutics.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ebMECs: bovine mammary epithelial cells; MOI: multiplicity of infection; CFU: colony forming unit; DMEM: Dulbecco\u0026apos;s modified eagle medium; PBS: phosphate-buffered saline; MLST: multi-locus sequence typing; MIC: Minimum inhibitory concentrations; STs: Sequence types; VFDB: Virulence Factors Database; CARD: Comprehensive Antimicrobial Research Database; WGS: whole genome sequencing; GWAS: genome-wide association studies.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be seen as potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study all animal experiments were performed in accordance with the animal welfare and animal experiment ethical guidelines and standards of biosafety and institutional safety regulations of China Agricultural University (CAU; Beijing, China). Prior to the beginning of this study, we obtained the approval of the Animal Welfare and Animal Experimental Ethics Review Committee of China Agricultural University (Issue No: AW01605202-2-02). All deceased \u003cem\u003eGalleria mellonella\u003c/em\u003e were collected in biohazard bags labeled as \u0026quot;infectious waste\u0026quot; followed by autoclaving (121\u0026deg;C, 15 min) and incineration according to laboratory biosafety protocols. Moribund larvae (e.g., melanized but not fully expired) were rapidly frozen at -20\u0026deg;C prior to identical sterilization and disposal procedures. These measures comply with institutional biosafety regulations. We confirm that informed consent for sample collection and subsequent data release was obtained from all cattle owners prior to sample collection.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatasets presented in this study are in online repositories (names of the repository/repositories and accession number(s) are in the article or Supplementary Material). All whole genome sequence data used in this study are available without restriction from NCBI (BioProject no. PRJNA 933979).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported financially by the National Natural Science Foundation of China (No. 31772813), the High-end Foreign Experts Recruitment Program (No. G2022108009L)\u0026nbsp;and Natural Science Foundation of Beijing, China (No. 6244052).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003euthorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYue Wang, Siyu Meng, Halihaxi Bahetijiang, Haoxia Li, Tian Wang, Talgat Assabayev: Writing - original draft, Data curation, analysed data, Investigation. Zhaoju Deng, Herman W Barkema, John P Kastelic, Bo Han: Writing - review \u0026amp; editing. Bo Han: conceived and designed the experiment, Supervision, Investigation. All authors approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank our laboratory members who assisted us with the research and the manuscript, for their skillful technical assistance, invaluable comments, and suggestions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBarkema HW, von Keyserlingk MAG, Kastelic JP, Lam T, Luby C, Roy JP, \u003cem\u003eet al.\u003c/em\u003e Invited review: Changes in the dairy industry affecting dairy cattle health and welfare. J Dairy Sci. 2015;98(11):7426\u0026ndash;7445.\u003c/li\u003e\n\u003cli\u003eAdkins P, Fox LK, Godden S, Jayarao BM, Keefe G, Kelton D,\u003cem\u003e et al.\u003c/em\u003e, editors. Laboratory handbook on bovine mastitis 3rd Edition. MN, USA: National Mastitis Council; 2017.\u003c/li\u003e\n\u003cli\u003eChurakov M, Katholm J, Rogers S, Kao R, Zadoks RN. 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Front Microbiol\u003cem\u003e.\u003c/em\u003e 2022;13:896296.\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":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Streptococcus agalactiae, bovine mastitis, whole-genome sequencing, phenotypes, virulence genes","lastPublishedDoi":"10.21203/rs.3.rs-6746409/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6746409/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eStreptococcus agalactiae\u003c/em\u003e is a contagious pathogen responsible for bovine mastitis, leading to significant economic losses in the global dairy industry. Our objectives were to determine the population structure, to profile the antimicrobial resistance and to investigate the pathogenicity and genes associated with pathogenicity in \u003cem\u003eS. agalactiae\u003c/em\u003e isolated from Chinese dairy herds. A total of 266 milk samples were collected on three dairy farms in Ningxia (herd A) and Hebei provinces (herds B \u0026amp; C) with outbreaks of bovine mastitis from September 2020 to April 2021. There were 116 isolates identified as \u003cem\u003eStreptococcus agalactiae\u003c/em\u003e by 16S rRNA sequencing. Twenty-seven \u003cem\u003eS. agalactiae\u003c/em\u003e isolates were randomly selected using a stratified approach from the three farms for whole genome sequencing analysis and phenotypic analyses, including antimicrobial resistance profiling, identification of adhesion, invasion and virulence factor genes using \u003cem\u003ein vitro\u003c/em\u003e bovine mammary epithelial cell models and \u003cem\u003ein vivo Galleria mellonella\u003c/em\u003e models. Multilocus sequence typing and serotyping showed that all isolates belonged to sequence type ST103 and serotype Ia. In total, 34 genes were identified as virulence factor genes in \u003cem\u003eStreptococcus\u003c/em\u003e species. Isolates from herd C had significantly higher virulence than those from herd B. Genome-wide association analysis revealed 166 virulence-related genes, 221 adhesion-related genes and 218 invasion-related genes. Furthermore, 47 genes were associated with pathogenicity in infecting \u003cem\u003eG. mellonella\u003c/em\u003e. Resistance to tetracycline and macrolides was related to the presence of antimicrobial resistance genes \u003cem\u003etetO, tetM\u003c/em\u003e, and \u003cem\u003eermB\u003c/em\u003e. Pan-genome analyses revealed that 1,421 \u003cem\u003eS. agalactiae\u003c/em\u003e isolates (27 from our study and 1,394 from the NCBI genome database) had 20,955 genes, including 666 and 20,289 genes in the core and accessory genomes, respectively. This study characterized the phenotypic and genotypic profiles for \u003cem\u003eS. agalactiae\u003c/em\u003e, and identified associations between phenotypic traits and genetic determinants of virulence and antimicrobial resistance, providing new insights into controlling \u003cem\u003eS. agalactiae\u003c/em\u003e mastitis in Chinese dairy herds.\u003c/p\u003e","manuscriptTitle":"Phenotypic and genotypic characterization of ST103 Serotype Ia Streptococcus agalactiae isolated from bovine mastitis in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-10 11:59:42","doi":"10.21203/rs.3.rs-6746409/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-21T07:13:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-19T07:55:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-18T18:39:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-18T01:01:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198141219860684490857119022395947211592","date":"2025-07-12T14:57:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24505773172975351129897048285163632592","date":"2025-07-11T14:07:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288037388207850155406034823340274338632","date":"2025-07-10T01:39:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200665768543202313490391465261698185885","date":"2025-07-09T17:22:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121819516279767676320903107689169511673","date":"2025-07-09T13:59:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-09T06:45:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-08T16:14:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-17T23:52:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-17T01:52:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2025-06-17T01:48:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6115010-89ff-48fe-9b3f-c5addd67af1d","owner":[],"postedDate":"July 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:01:25+00:00","versionOfRecord":{"articleIdentity":"rs-6746409","link":"https://doi.org/10.1186/s12866-025-04315-7","journal":{"identity":"bmc-microbiology","isVorOnly":false,"title":"BMC Microbiology"},"publishedOn":"2025-10-14 15:57:33","publishedOnDateReadable":"October 14th, 2025"},"versionCreatedAt":"2025-07-10 11:59:42","video":"","vorDoi":"10.1186/s12866-025-04315-7","vorDoiUrl":"https://doi.org/10.1186/s12866-025-04315-7","workflowStages":[]},"version":"v1","identity":"rs-6746409","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6746409","identity":"rs-6746409","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}