Virulence related sequences; insights provided by comparative genomics of Streptococcus uberis of differing virulence
© Hossain et al.; licensee BioMed Central. 2015
Received: 23 October 2014
Accepted: 8 April 2015
Published: 23 April 2015
Streptococcus uberis, a Gram-positive, catalase-negative member of the family Streptococcaceae is an important environmental pathogen responsible for a significant proportion of subclinical and clinical bovine intramammary infections. Currently, the genome of only a single reference strain (0140J) has been described. Here we present a comparative analysis of complete draft genome sequences of an additional twelve S. uberis strains.
Pan and core genome analysis revealed the core genome common to all strains to be 1,550 genes in 1,509 orthologous clusters, complemented by 115-246 accessory genes present in one or more S. uberis strains but absent in the reference strain 0140J. Most of the previously predicted virulent genes were present in the core genome of all 13 strains but gene gain/loss was observed between the isolates in CDS associated with clustered regularly interspaced short palindromic repeats (CRISPRs), prophage and bacteriocin production. Experimental challenge experiments confirmed strain EF20 as non-virulent; only able to infect in a transient manner that did not result in clinical mastitis. Comparison of the genome sequence of EF20 with the validated virulent strain 0140J identified genes associated with virulence, however these did not relate clearly with clinical/non-clinical status of infection.
The gain/loss of mobile genetic elements such as CRISPRs and prophage are a potential driving force for evolutionary change. This first “whole-genome” comparison of strains isolated from clinical vs non-clinical intramammary infections including the type virulent vs non-virulent strains did not identify simple gene gain/loss rules that readily explain, or be confidently associated with, differences in virulence. This suggests that a more complex dynamic determines infection potential and clinical outcome not simply gene content.
Implementation of the five point control measures for bovine mastitis including improved milking practice, post-milking teat disinfection, therapeutic and prophylactic antimicrobial administration, and the culling of persistently infected animals has made significant impact on the control of intramammary infections caused by contagious pathogens . However, these measures are less effective in controlling infections from environmental pathogens, which continue to be a major hurdle in the control of mastitis. Streptococcus uberis, a Gram-positive, catalase-negative member of the family Streptococcaceae is an important environmental pathogen implicated in bovine mastitis, accounting for a significant proportion of subclinical and clinical intramammary infections . Mastitis is defined as clinical when abnormality of the udder or secretion is observed, whereas, in subclinical mastitis the udder and the milk appears normal. The economic impact of both subclinical and clinical mastitis in the UK dairy industry is in excess of £200 million/annum with worldwide economic loss estimated at US$35 billion . Control of S. uberis through vaccination based strategies therefore has the potential to dramatically improve both the economics of milk production and animal welfare . Development of a vaccine against S. uberis has been hampered by a lack of information on the interaction between pathogen and the host . This lack of knowledge is exemplified in the paucity of information on S. uberis strains at the genomic level. Whilst over 900 strains of S. uberis have been typed using multi locus sequence typing (MLST; http://pubmlst.org/suberis/), only a single genome sequence has been reported, from S. uberis, strain 0140J (accession number AM946015), selected as a typical virulent UK strain . The genome of 0140J (1,852,352 bp) is one of the smallest sequenced Streptococcus genomes which range from 1.8 Mb-2.3 Mb . This suggests that through genome reduction, the 0140J genome has become condensed possibly reflecting restricted host-range. It is also possible that the 1,825 protein coding genes of 0140J harbour potential virulence genes which are absent in non-virulent strains, or that loss of accessory genes present in other strains may be associated with the virulence of 0140J.
DNA isolation and genome sequencing
Bacteria from a range of clinical and sub-clinical isolates (see Additional file 1) were inoculated into Todd-Hewitt Broth and grown at 37°C overnight with DNA extracted from cultures as previously described .
Genome assembly and annotation
Library preparation and sequencing of each strain was conducted at DeepSeq, Queens Medical Centre, Nottingham, UK. 1 μg of high molecular weight S. uberis genomic DNA were used to prepare Illumina libraries using the TrueSeq DNA LT Sample Prep Kit (Cat. no, FC-121-2001) as described in TrueSeq DNA sample preparation guide with the following modifications. DNA fragmentation was carried out in covaris S2 using the following parameters: Duty cycle - 10%, Intensity - 5, cycles per burst – 200, Time – 45 seconds, Mode – Frequency sweeping and temperature – 6°C. Gel method was used to size-select adapter ligated DNA to 600-700 bp to generate libraries with insert length of 500-600 bp for the increased MiSeq read length. Sequencing was performed on the MiSeq platform with V2 chemistry (Cat. no, MS-102-2003) to generate 2 × 250 bp paired end reads. The average number of reads per strain was 902,651. Reads were used to generate assemblies using Velvet (version 1.2.10) . Maximum N50 was used as the measure to determine optimal K-mer length using Velvetoptimiser (https://github.com/Victorian-Bioinformatics-Consortium/VelvetOptimiser) a minimum coverage of 10x was selected and the –exp_cov option ‘auto’ was used. CONTIGuator  was used to map resulting contigs to the reference genome 0140J for comparative analysis of genomic regions.
Assembled contigs were annotated using the Rapid Annotations using Subsystem Technology (RAST) server . The pan-genome analysis pipeline (PGAP version 1.02)  was used for identification of orthologous genes between the twelve sequenced genomes and the reference genome 0140J using the Gene Family (GF) method (50% coverage and with an e-value cut-off 1e-10). Similarity of the samples based in gene presence/absence was conducted using hierarchical clustering. The pvclust package (http://cran.r-project.org/web/packages/pvclust/) was using a correlation distance measure and average agglomeration method.
PILER-CR  and CRISPRs web server [13-15] was used for rapid identification and classification of clustered regularly interspaced short palindromic Repeats (CRISPRs). The phage search tool (PHAST)  was used to identify, annotate and graphically display prophage sequences within the draft genomes. MUSCLE  was used for multiple alignments. The webserver snpTree  was used to identify SNP positions trees from the concatenated 1,377 core genes of 13 isolates. PhyML  was used for the generation of phylogenetic trees using a GTR model estimated gamma distribution and 4 substitution rate categories. 200 bootstrap replicates were conducted.
De novo assembly statistics of 12 Streptococcus uberis isolates
GenBank accession No.
Number of contigs (>200 bp)
Shortest contig size
Longest contig size
To determine the stability of pan/core genomes, the pan genome (total number of genes identified within a group of samples) and core genome size (those genes shared by a group of samples) was determined when between 2 and 13 genomes were combined in random order. For each combination size (2…13 genomes) 1000 permutations were conducted.
Challenge of lactating dairy cattle with S. uberis 0140J or EF20
To ascertain the virulence of two S. uberis strains, 5 dairy cows aged between 24-30 months were selected for experimental challenge at 4-8 weeks post calving, using a well-established intramammary infection model. Criteria for selection were: absence of signs of mastitis, no history of mastitis during the current lactation and absence of bacteria in milk samples taken 24-48 h prior to challenge with the associated somatic cell count (SCC) below 100,000 cells/ml. Animals were challenged in two mammary quarters after morning milking by infusion of 1 ml of pyrogen-free saline (Sigma) containing approximately 1 × 103 CFU of S. uberis 0140J or EF20 prepared as previously described .
Following challenge, animals were milked and inspected twice daily. Milk and udder quarters were assessed to determine the severity of disease using predetermined criteria for clinical end points (clotted and discoloured milk and/or udder quarter swollen or causing discomfort on palpation) as previously described . Milk collected from challenged quarters at each milking (up to 48 h) post-challenge was assessed for bacterial numbers and somatic cell counts. The number of viable bacteria present was estimated by plating of each milk sample onto ABA and the number of somatic cells present in milk samples was determined using a DeLaval portable cell counter in line with the manufacturer’s instructions.
Results and discussion
General features of Streptococcus uberis genomes
Analysis of the pan genome
The pan genome size (total number of genes within a group of genomes) was determined to give a measure of the relative complexity within the S. uberis genomes. With 10-12 S. uberis genomes the number of novel genes identified with the addition of an additional genome slows but does not plateau (Figure 4b), suggesting an open pangenome . Together these comparisons of the core and pan genomes suggest that sequencing the relatively small number of strains has captured the majority, but not all of variation of S. uberis genomes.
Comparison of virulence factors
SNP distribution of (a) known virulence genes (b) sortase anchored proteins
Gene size (bp)
Alignment size (bp)
PauA (Streptokinase precursor)
Hemolysin like protein
Sortase A (srtA)
C5a peptidase precursor
Fibronectin- binding protein
putative fructan beta-fructosidase precursor
lactoferrin binding protein
putative surface-anchored protein
putative surface-anchored 2′,3′-cyclic-nucleotide 2′-Phosphodiesterase
putative surface-anchored subtilase family protein
putative surface-anchored protein
collagen-like surface-anchored protein
C5A peptidase precursor
putative zinc carboxypeptidase
putative surface-anchored protein
Analysis of the has operon
The hyaluronic acid capsule of S. pyogenes has been found to play a significant role in the pathogenesis of invasive Group A Streptococcus (GAS) bacteria , . S. uberis strains isolated from cases of bovine mastitis display variable amounts of hyaluronic acid capsule  suggesting that the capsule may be associated with infection. However, Field et al 2003 showed that capsule negative mutants can still cause mastitis  and the availability of more capsule in clinical isolates than the environmental isolates  may be due to the fact that capsule prevents desiccation in the environment and allows it to persist longer, increasing chances of subsequent infection or even gut colonisation. In S. uberis 0140J the arrangement of the hyaluronic acid biosynthetic genes comprising the has operon, differs from the typical “hasABC” arrangement common to GAS . HasA (SUB1697) encoding hyaluronan synthase and hasB (SUB1696) encoding UDP-glucose dehydrogenase are arranged as in other GAS. However the hasC homologue (SUB1691), encoding UDP-glucose pyrophosphorylase, is encoded in the reverse orientation and separated from hasAB by approximately 3 kb of genome encoding CDSs thought to be unrelated to capsule biosynthesis . It is unlikely that this arrangement affects capsule production, as in GAS capsule is dependent only upon functional hasA and hasB, but not hasC . All the isolates sequenced here except strain B362 have hasABC in a similar arrangement to that found in 0140J. In nine S. uberis strains a paralog of hasB (SUB1027) was identified. The non-capsular, non-virulent isolate EF20 lacks SUB1027 and this gene is also missing from isolates B362, 6780 and B190.
Analysis of CRISPR-Cas proteins
Analysis of prophage regions
Distribution of prophage regions among 13 isolates
Location compared to 0140J
Analysis of bacteriocin production
Bacteriocins are proteinaceous antibiotics produced by bacteria, which kill or inhibit the growth of other bacteria, often providing an advantage in competitive colonization environments. Uberolysin is a novel cyclic bacteriocin produced by S. uberis encoded by the operon spanning SUB0032-SUB0036. This operon is absent in EF20 and isolate C9359 but is present in all other sequenced strains. Analysis of the 0140J genome identified five genes encoding putative bacteriocin proteins (SUB0502, SUB0505, SUB0506, SUB0509 and SUB0512) , of which SUB502-SUB505 are again absent in EF20 and also isolates B362 and 6780 both of which belong to the ST-86 complex. Whilst bacteriocin production does not define clinical and sub-clinical strains, the absence of almost all bacteriocins in the EF20 genome could put it at a competitive disadvantage with other environmental strains in the dairy cow environment and may reflect (but not explain) it’s non-virulent status.
The comparison of multiple strains of closely related bacteria provides a valuable resource for the understanding of biological systems. The comparison of 12 newly sequenced strains together with the type 0140J strain of Streptococcus uberis allows a first comparison of bacteria isolated from clinical and non-clinical infections and the generation of a draft genome of EF20 strain together with the existing 0140J genome, allows for the first time comparison of two naturally occurring strains of S. uberis with defined virulence. The comparison of the strains did not suggest an obvious “smoking gun” gene either present or absent between the virulent or avirulent strains to suggest a previously unknown virulence factor. In addition the genome content did not differentiate between clinical and non-clinical strains. However, it is worth considering that the status as clinical or non-clinical refers to the state of the host animal from which the isolate was obtained, not to the causative agent. For example the proven non-virulent strain EF20 was isolated from a clinical case and hence is named as a clinical strain but this may have been due to other factors such as a co-infection with another bacterial species/strain and importantly, the genetics of the host. Thus, whilst the data here present a detailed comparison of S. uberis bacterial strains, to fully understand virulence and causation of disease, we must take a holistic approach encompassing bacteria, host and environment.
Sequence reads and assembled contigs are available at GenBank under accession JANW00000000, JATB00000000, JATD00000000, JATK00000000, JATE00000000, JATC00000000, JATI00000000, JATF00000000, JATA00000000, JATG00000000, JATJ00000000, JATH00000000.
We acknowledge the financial support of BBSRC (grant numbers E0181141 (PI = TC) and E0181732 (PI = JL, CoI = PW, supported researcher = SE), DFERA (grant number OD1717 PI = JL) and the University of Nottingham. MH was supported by a University of Nottingham Vice Chancellors international scholarship award. We gratefully acknowledge Adam Blanchard School of Veterinary Medicine and Science and Tom Giles and Andrew Warry Advanced Data Analysis Centre University of Nottingham for helpful discussions.
- Bramley AJ, Dodd FH. Reviews of the progress of dairy science: mastitis control–progress and prospects. J Dairy Res. 1984;51(3):481–512.View ArticlePubMedGoogle Scholar
- Bradley AJ, Leach KA, Breen JE, Green LE, Green MJ. Survey of the incidence and aetiology of mastitis on dairy farms in England and Wales. Vet Rec. 2007;160(8):253–7.View ArticlePubMedGoogle Scholar
- Bradley AJ, Barkema H, Biggs A, Green MJ, Lam T. Control of mastitis and enhancement of milk quality. In: Green MJ, editor. Dairy Herd Health. Oxfordshire, UK: CABI; 2012.Google Scholar
- Bradley AB H, Biggs A, Green M, Lam T. Control of mastitis and enhancement of milk quality. In: Green M, editor. Dairy herd health. UK: CPI Group (UK) Ltd; 2012.Google Scholar
- Leigh JA. Streptococcus uberis: a permanent barrier to the control of bovine mastitis? Vet J. 1999;157(3):225–38.View ArticlePubMedGoogle Scholar
- Ward PN, Holden MT, Leigh JA, Lennard N, Bignell A, Barron A, et al. Evidence for niche adaptation in the genome of the bovine pathogen Streptococcus uberis. BMC Genomics. 2009;10:54.View ArticlePubMed CentralPubMedGoogle Scholar
- Leigh JA, Egan SA, Ward PN, Field TR, Coffey TJ. Sortase anchored proteins of Streptococcus uberis play major roles in the pathogenesis of bovine mastitis in dairy cattle. Vet Res. 2010;41(5):63.View ArticlePubMed CentralPubMedGoogle Scholar
- Zerbino DR. Using the Velvet de novo assembler for short-read sequencing technologies. Curr Protoc Bioinformatics. 2010;11:11–5.Google Scholar
- Galardini M, Biondi EG, Bazzicalupo M, Mengoni A. CONTIGuator: a bacterial genomes finishing tool for structural insights on draft genomes. Source Code Biol Med. 2011;6:11.View ArticlePubMed CentralPubMedGoogle Scholar
- Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75.View ArticlePubMed CentralPubMedGoogle Scholar
- Zhao Y, Wu J, Yang J, Sun S, Xiao J, Yu J. PGAP: Pan-Genomes Analysis Pipeline. Bioinformatics. 2011;28(3):416–8.View ArticlePubMed CentralPubMedGoogle Scholar
- Edgar RC. PILER-CR: fast and accurate identification of CRISPR repeats. BMC Bioinformatics. 2007;8:18.View ArticlePubMed CentralPubMedGoogle Scholar
- Grissa I, Vergnaud G, Pourcel C. CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acids Res. 2007;35:W52–7.View ArticlePubMed CentralPubMedGoogle Scholar
- Grissa I, Vergnaud G, Pourcel C. The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats. BMC Bioinformatics. 2007;8:172.View ArticlePubMed CentralPubMedGoogle Scholar
- Grissa I, Vergnaud G, Pourcel C. CRISPRcompar: a website to compare clustered regularly interspaced short palindromic repeats. Nucleic Acids Res. 2008;36:W145–8.View ArticlePubMed CentralPubMedGoogle Scholar
- Zhou Y, Liang Y, Lynch KH, Dennis JJ, Wishart DS. PHAST: a fast phage search tool. Nucleic Acids Res. 2011;39:W347–52.View ArticlePubMed CentralPubMedGoogle Scholar
- Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.View ArticlePubMed CentralPubMedGoogle Scholar
- Leekitcharoenphon P, Kaas RS, Thomsen MC, Friis C, Rasmussen S, Aarestrup FM. snpTree--a web-server to identify and construct SNP trees from whole genome sequence data. BMC Genomics. 2012;13(7):S6.View ArticlePubMed CentralPubMedGoogle Scholar
- Guindon S, Gascuel O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 2003;52(5):696–704.View ArticlePubMedGoogle Scholar
- Francisco AP, Vaz C, Monteiro PT, Melo-Cristino J, Ramirez M, Carrico JA. PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods. BMC Bioinformatics. 2012;13:87.View ArticlePubMed CentralPubMedGoogle Scholar
- Field TR, Ward PN, Pedersen LH, Leigh JA. The hyaluronic acid capsule of Streptococcus uberis is not required for the development of infection and clinical mastitis. Infect Immun. 2003;71(1):132–9.View ArticlePubMed CentralPubMedGoogle Scholar
- Smith AJ, Ward PN, Field TR, Jones CL, Lincoln RA, Leigh JA. MtuA, a lipoprotein receptor antigen from Streptococcus uberis, is responsible for acquisition of manganese during growth in milk and is essential for infection of the lactating bovine mammary gland. Infect Immun. 2003;71(9):4842–9.View ArticlePubMed CentralPubMedGoogle Scholar
- Hill AW. Pathogenicity of two strains of Streptococcus uberis infused into lactating and non-lactating bovine mammary glands. Res Vet Sci. 1988;45(3):400–4.PubMedGoogle Scholar
- Tettelin H, Masignani V, Cieslewicz MJ, Donati C, Medini D, Ward NL, et al. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial “pan-genome”. Proc Natl Acad Sci. 2005;102(39):13950–5.View ArticlePubMed CentralPubMedGoogle Scholar
- Bruen T, Phillipe H, Bryant D. A quick and robust statistical test to detect the presence of recombination. Genetics. 2006;17:2665–81.Google Scholar
- Martin PR, Hoiby EA. Streptococcal serogroup A epidemic in Norway 1987-1988. Scand J Infect Dis. 1990;22(4):421–9.View ArticlePubMedGoogle Scholar
- Cho KH, Caparon MG. Patterns of virulence gene expression differ between biofilm and tissue communities of Streptococcus pyogenes. Mol Microbiol. 2005;57(6):1545–56.View ArticlePubMedGoogle Scholar
- Ward PN, Field TR, Ditcham WG, Maguin E, Leigh JA. Identification and disruption of two discrete loci encoding hyaluronic acid capsule biosynthesis genes hasA, hasB, and hasC in Streptococcus uberis. Infect Immun. 2001;69(1):392–9.View ArticlePubMed CentralPubMedGoogle Scholar
- Ashbaugh CD, Alberti S, Wessels MR. Molecular analysis of the capsule gene region of group A Streptococcus: the hasAB genes are sufficient for capsule expression. J Bacteriol. 1998;180(18):4955–9.PubMed CentralPubMedGoogle Scholar
- Egan SA, Ward PN, Watson M, Field TR, Leigh JA. Vru (Sub0144) controls expression of proven and putative virulence determinants and alters the ability of Streptococcus uberis to cause disease in dairy cattle. Microbiology. 2012;158(Pt 6):1581–92.View ArticlePubMed CentralPubMedGoogle Scholar
- Flores AR, Olsen RJ, Wunsche A, Kumaraswami M, Shelburne 3rd SA, Carroll RK, et al. Natural variation in the promoter of the gene encoding the Mga regulator alters host-pathogen interactions in group a Streptococcus carrier strains. Infect Immun. 2013;81(11):4128–38.View ArticlePubMed CentralPubMedGoogle Scholar
- Deveau H, Garneau JE, Moineau S. CRISPR/Cas system and its role in phage-bacteria interactions. Annu Rev Microbiol. 2010;64:475–93.View ArticlePubMedGoogle Scholar
- Horvath P, Barrangou R. CRISPR/Cas, the immune system of bacteria and archaea. Science. 2010;327(5962):167–70.View ArticlePubMedGoogle Scholar
- Karginov FV, Hannon GJ. The CRISPR system: small RNA-guided defense in bacteria and archaea. Mol Cell. 2010;37(1):7–19.View ArticlePubMed CentralPubMedGoogle Scholar
- Koonin EV, Makarova KS. CRISPR-Cas: an adaptive immunity system in prokaryotes. F1000 Biol Rep. 2009;1:95.PubMed CentralPubMedGoogle Scholar
- Sorek R, Kunin V, Hugenholtz P. CRISPR–a widespread system that provides acquired resistance against phages in bacteria and archaea. Nat Rev Microbiol. 2008;6(3):181–6.View ArticlePubMedGoogle Scholar
- van der Oost J, Jore MM, Westra ER, Lundgren M, Brouns SJ. CRISPR-based adaptive and heritable immunity in prokaryotes. Trends Biochem Sci. 2009;34(8):401–7.View ArticlePubMedGoogle Scholar
- Makarova KS, Haft DH, Barrangou R, Brouns SJ, Charpentier E, Horvath P, et al. Evolution and classification of the CRISPR-Cas systems. Nat Rev Microbiol. 2011;9(6):467–77.View ArticlePubMedGoogle Scholar
- Brussow H, Canchaya C, Hardt WD. Phages and the evolution of bacterial pathogens: from genomic rearrangements to lysogenic conversion. Microbiol Mol Biol Rev. 2004;68(3):560–602.View ArticlePubMed CentralPubMedGoogle Scholar
- Alikhan NF, Petty NK, Ben Zakour NL, Beatson SA. BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics. 2011;12:402.View ArticlePubMed CentralPubMedGoogle Scholar
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