Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii.
Endocarditis
/ microbiology
Endocarditis, Bacterial
/ microbiology
Endocardium
/ microbiology
Genome, Bacterial
High-Throughput Nucleotide Sequencing
Humans
Machine Learning
Mouth
/ microbiology
Phylogeny
Streptococcal Infections
/ microbiology
Streptococcus gordonii
/ classification
Streptococcus sanguis
/ classification
Symbiosis
/ physiology
Virulence
Virulence Factors
/ classification
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
17 02 2020
17 02 2020
Historique:
received:
22
01
2019
accepted:
28
01
2020
entrez:
19
2
2020
pubmed:
19
2
2020
medline:
18
11
2020
Statut:
epublish
Résumé
Streptococcus gordonii and Streptococcus sanguinis belong to the Mitis group streptococci, which mostly are commensals in the human oral cavity. Though they are oral commensals, they can escape their niche and cause infective endocarditis, a severe infection with high mortality. Several virulence factors important for the development of infective endocarditis have been described in these two species. However, the background for how the commensal bacteria, in some cases, become pathogenic is still not known. To gain a greater understanding of the mechanisms of the pathogenic potential, we performed a comparative analysis of 38 blood culture strains, S. sanguinis (n = 20) and S. gordonii (n = 18) from patients with verified infective endocarditis, along with 21 publicly available oral isolates from healthy individuals, S. sanguinis (n = 12) and S. gordonii (n = 9). Using whole genome sequencing data of the 59 streptococci genomes, functional profiles were constructed, using protein domain predictions based on the translated genes. These functional profiles were used for clustering, phylogenetics and machine learning. A clear separation could be made between the two species. No clear differences between oral isolates and clinical infective endocarditis isolates were found in any of the 675 translated core-genes. Additionally, random forest-based machine learning and clustering of the pan-genome data as well as amino acid variations in the core-genome could not separate the clinical and oral isolates. A total of 151 different virulence genes was identified in the 59 genomes. Among these homologs of genes important for adhesion and evasion of the immune system were found in all of the strains. Based on the functional profiles and virulence gene content of the genomes, we believe that all analysed strains had the ability to become pathogenic.
Identifiants
pubmed: 32066773
doi: 10.1038/s41598-020-59549-4
pii: 10.1038/s41598-020-59549-4
pmc: PMC7026040
doi:
Substances chimiques
Virulence Factors
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2728Références
Jakubovics, N. S., Yassin, S. A. & Rickard, A. H. Community Interactions of Oral Streptococci. Advances in Applied Microbiology 87, (Elsevier Inc., 2014).
Caufield, P. W. et al. Natural history of Streptococcus sanguinis in the oral cavity of infants: Evidence for a discrete window of infectivity. Infect. Immun. 68, 4018–4023 (2000).
pubmed: 10858217
pmcid: 101685
doi: 10.1128/IAI.68.7.4018-4023.2000
Jakubovics, N. & Kolenbrander, P. The road to ruin: the formation of disease-associated oral biofilms: Formation of oral biofilms. Oral Dis. 16, 729–739 (2010).
pubmed: 20646235
doi: 10.1111/j.1601-0825.2010.01701.x
pmcid: 20646235
Nobbs, A. H., Lamont, R. J. & Jenkinson, H. F. Streptococcus Adherence and Colonization. Microbiol. Mol. Biol. Rev. 73, 407–450 (2009).
pubmed: 19721085
pmcid: 2738137
doi: 10.1128/MMBR.00014-09
Mitchell, J. Streptococcus mitis: walking the line between commensalism and pathogenesis: Review of S. mitis biology and pathogenesis. Mol. Oral Microbiol. 26, 89–98 (2011).
pubmed: 21375700
doi: 10.1111/j.2041-1014.2010.00601.x
pmcid: 21375700
Plaut, A. G. The IgA1 Proteases of Pathogenic Bacteria. Annu. Rev. Microbiol. 37, 603–622 (1983).
pubmed: 6416146
doi: 10.1146/annurev.mi.37.100183.003131
pmcid: 6416146
Steinmoen, H., Knutsen, E. & Havarstein, L. S. Induction of natural competence in Streptococcus pneumoniae triggers lysis and DNA release from a subfraction of the cell population. Proc. Natl. Acad. Sci. 99, 7681–7686 (2002).
pubmed: 12032343
doi: 10.1073/pnas.112464599
pmcid: 12032343
Andam, C. P. & Hanage, W. P. Mechanisms of genome evolution of Streptococcus. Infect. Genet. Evol. 33, 334–342 (2015).
pubmed: 25461843
doi: 10.1016/j.meegid.2014.11.007
pmcid: 25461843
Roberts, A. P. & Kreth, J. The impact of horizontal gene transfer on the adaptive ability of the human oral microbiome. Front. Cell. Infect. Microbiol. 4, 1–9 (2014).
doi: 10.3389/fcimb.2014.00124
Douglas, C. W. I., Heath, J., Hampton, K. K. & Preston, F. E. Identity of viridans streptococci isolated from cases of infective endocarditis. J. Med. Microbiol. 39, 179–182 (1993).
pubmed: 8366515
doi: 10.1099/00222615-39-3-179
pmcid: 8366515
Beynon, R. P., Bahl, V. K. & Prendergast, B. D. Infective endocarditis. BMJ Rev. 333, 334–339 (2006).
doi: 10.1136/bmj.333.7563.334
Murdoch, D. R. et al. Clinical Presentation, Etiology, and Outcome of Infective Endocarditis in the 21st Century. Original Investigation 169, 463–473 (2010).
Dayer, M. J. et al. Incidence of infective endocarditis in England, 2000–13: A secular trend, interrupted time-series analysis. The Lancet 385, 1219–1228 (2015).
doi: 10.1016/S0140-6736(14)62007-9
Eddy, S. R. Hidden Markov models. Curr. Opin. Struct. Biol. 6, 361–365 (1996).
pubmed: 8804822
doi: 10.1016/S0959-440X(96)80056-X
pmcid: 8804822
Attwood, T. K. The quest to deduce protein function from sequence: The role of pattern databases. Int. J. Biochem. Cell Biol. 32, 139–155 (2000).
pubmed: 10687950
doi: 10.1016/S1357-2725(99)00106-5
pmcid: 10687950
Conte, L. L et al. SCOP: a Structural Classification of Proteins database. 28, 257–259 (2000).
Kitts, P. A. et al. Assembly: a resource for assembled genomes at NCBI. Nucleic Acids Res. 44, D73–D80 (2016).
pubmed: 26578580
doi: 10.1093/nar/gkv1226
pmcid: 26578580
Finn, R. D. et al. Pfam: The protein families database. Nucleic Acids Res. 42, 290–301 (2014).
doi: 10.1093/nar/gkt830
Camacho, C. et al. BLAST+: Architecture and applications. BMC Bioinformatics 10, 1–9 (2009).
doi: 10.1186/1471-2105-10-421
Chen, L. et al. VFDB: A reference database for bacterial virulence factors. Nucleic Acids Res. 33, 325–328 (2005).
doi: 10.1093/nar/gki008
Chen, L., Xiong, Z., Sun, L., Yang, J. & Jin, Q. VFDB 2012 update: Toward the genetic diversity and molecular evolution of bacterial virulence factors. Nucleic Acids Res. 40, 641–645 (2012).
doi: 10.1093/nar/gkr989
Yang, J., Chen, L., Sun, L., Yu, J. & Jin, Q. VFDB 2008 release: an enhanced web-based resource for comparative pathogenomics. Nucleic Acids Res. 36, D539–D542 (2007).
pubmed: 17984080
pmcid: 2238871
doi: 10.1093/nar/gkm951
Tatusov, R. L. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33–36 (2000).
pubmed: 10592175
pmcid: 102395
doi: 10.1093/nar/28.1.33
Moreillon, P., Que, Y. A. & Bayer, A. S. Pathogenesis of streptococcal and staphylococcal endocarditis. Infect. Dis. Clin. North Am. 16, 297–318 (2002).
pubmed: 12092474
doi: 10.1016/S0891-5520(01)00009-5
pmcid: 12092474
Agarwal, V. et al. Enolase of Streptococcus pneumoniae Binds Human Complement Inhibitor C4b-Binding Protein and Contributes to Complement Evasion. J. Immunol. 189, 3575–3584 (2012).
pubmed: 22925928
doi: 10.4049/jimmunol.1102934
pmcid: 22925928
Teles, C., Smith, A., Ramage, G. & Lang, S. The role of streptococcal plasmin(ogen) binding in infective endocarditis. Eur. J. Clin. Microbiol. Infect. Dis. 30, 127–129 (2011).
pubmed: 20835741
doi: 10.1007/s10096-010-1053-5
pmcid: 20835741
Janoff, E. N. et al. Pneumococcal IgA1 protease subverts specific protection by human IgA1. Mucosal Immunol. 7, 249–256 (2014).
pubmed: 23820749
doi: 10.1038/mi.2013.41
pmcid: 23820749
Kilian, M., Mestecky, J. & Schrohenloher, R. E. Pathogenic Species of the Genus Haemophilus and Streptococcus pneumoniae Produce Immunoglobulin Al Protease. Infect Immun. 26, 7 (1979).
doi: 10.1128/IAI.26.1.143-149.1979
Kilian, M., Mikkelsen, L. & Henrichsen, J. Taxonomic Study of Viridans Streptococci: Description of Streptococcus gordonii sp. nov. and Emended Descriptions of Streptococcus sanguis (White and Niven 1946), Streptococcus oralis (Bridge and Sneath 1982), and Streptococcus mitis (Andrewes and Horder 1906). Int. J. Syst. Bacteriol. 39, 471–484 (1989).
doi: 10.1099/00207713-39-4-471
Reinholdt, J. Molecular Aspects of Immunoglobulin Al Degradation by Oral Streptococci. Infect Immun. 58, 9 (1990).
doi: 10.1128/IAI.58.5.1186-1194.1990
Henrichsen, J. Six Newly Recognized Types of Streptococcus pneumoniae. J. Clin. Microbiol. 33 (1995).
pubmed: 8567920
pmcid: 228570
doi: 10.1128/JCM.33.10.2759-2762.1995
Hostetter, M. K. Serotypic Variations Among Virulent Pneumococci in Deposition and Degradation of Covalently Bound C3b: Implications for Phagocytosis and Antibody Production. J. Infect. Dis. 153, 682–693 (1986).
pubmed: 3950449
doi: 10.1093/infdis/153.4.682
Morona, J. K., Paton, J. C., Miller, D. C. & Morona, R. Tyrosine phosphorylation of CpsD negatively regulates capsular polysaccharide biosynthesis in Streptococcus pneumoniae: Regulation of capsule biosynthesis in S. pneumoniae. Mol. Microbiol. 35, 1431–1442 (2002).
doi: 10.1046/j.1365-2958.2000.01808.x
Kilian, M. et al. Evolution of Streptococcus pneumoniae and Its Close Commensal Relatives. PLoS ONE 3, e2683 (2008).
pubmed: 18628950
pmcid: 2444020
doi: 10.1371/journal.pone.0002683
Kilian, M., Riley, D. R., Jensen, A., Bruggemann, H. & Tettelin, H. Parallel Evolution of Streptococcus pneumoniae and Streptococcus mitis to Pathogenic and Mutualistic Lifestyles. mBio 5 (2014).
Skov Sørensen, U. B., Yao, K., Yang, Y., Tettelin, H. & Kilian, M. Capsular Polysaccharide Expression in Commensal Streptococcus Species: Genetic and Antigenic Similarities to Streptococcus pneumoniae. mBio 7 (2016).
Rasmussen, L. H. et al. In silico assessment of virulence factors in strains of streptococcus oralis and Streptococcus mitis isolated from patients with infective endocarditis. J. Med. Microbiol. 66, 1316–1323 (2017).
pubmed: 28874232
doi: 10.1099/jmm.0.000573
Fan, J. et al. Ecto-5′-nucleotidase: A candidate virulence factor in Streptococcus sanguinis experimental endocarditis. PLoS ONE 7, 1–10 (2012).
Plummer, C. et al. A serine-rich glycoprotein of Streptococcus sanguis mediates adhesion to platelets via GPIb. Br. J. Haematol. 129, 101–109 (2005).
pubmed: 15801962
doi: 10.1111/j.1365-2141.2005.05421.x
Takahashi, Y., Sandberg, A. L., Ruhl, S., Muller, J. & Cisar, J. O. A specific cell surface antigen of Streptococcus gordonii is associated with bacterial hemagglutination and adhesion to alpha2-3-linked sialic acid-containing receptors. Infect. Immun. 65, 5042–5051 (1997).
pubmed: 9393794
pmcid: 175727
doi: 10.1128/IAI.65.12.5042-5051.1997
Zheng, W. et al. Distinct Biological Potential of Streptococcus gordonii and Streptococcus sanguinis Revealed by Comparative Genome Analysis. Sci. Rep. 7, 1–16 (2017).
doi: 10.1038/s41598-016-0028-x
Thompson, C. C., Emmel, V. E., Fonseca, E. L., Marin, M. A. & Vicente, A. C. P. Streptococcal taxonomy based on genome sequence analyses. F1000 Research 67, 1–9 (2013).
Sabharwal, A., Liao, Y.-C., Lin, H.-H., Haase, E. M. & Scannapieco, F. A. Draft Genome Sequences of 18 Oral Streptococcus Strains That Encode Amylase-Binding Proteins. Genome Announc. 3 (2015).
Rasmussen, L. H., Dargis, R., Christensen, J. J., Skovgaard, O. & Nielsen, X. C. Draft Genome Sequence of Type Strain Streptococcus gordonii ATCC 10558. Genome Announc. 4 (2016).
Lefébure, T. & Stanhope, M. J. Evolution of the core and pan-genome of Streptococcus: Positive selection, recombination, and genome composition. Genome Biol. 8, 1–17 (2007).
doi: 10.1186/gb-2007-8-5-r71
Aziz, R. K. et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics 9, 75 (2008).
pubmed: 18261238
pmcid: 2265698
doi: 10.1186/1471-2164-9-75
Meyer, F., Overbeek, R. & Rodriguez, A. FIGfams: yet another set of protein families. Nucleic Acids Res. 37, 6643–6654 (2009).
pubmed: 19762480
pmcid: 2777423
doi: 10.1093/nar/gkp698
Rasmussen, L. H. et al. Whole genome sequencing as a tool for phylogenetic analysis of clinical strains of Mitis group streptococci. Eur. J. Clin. Microbiol. Infect. Dis. 35, 1615–1625 (2016).
pubmed: 27325438
doi: 10.1007/s10096-016-2700-2
pmcid: 27325438
Awadalla, P. The evolutionary genomics of pathogen recombination. Nat. Rev. Genet. 4, 50 (2003).
pubmed: 12509753
doi: 10.1038/nrg964
pmcid: 12509753
Feil, E. J. et al. Recombination within natural populations of pathogenic bacteria: Short-term empirical estimates and long-term phylogenetic consequences. Proc. Natl. Acad. Sci. 98, 182–187 (2001).
pubmed: 11136255
doi: 10.1073/pnas.98.1.182
pmcid: 11136255
Hao, W. The fate of laterally transferred genes: Life in the fast lane to adaptation or death. Genome Res. 16, 636–643 (2006).
pubmed: 16651664
pmcid: 1457040
doi: 10.1101/gr.4746406
Spratt, B. The relative contributions of recombination and point mutation to the diversification of bacterial clones. Curr. Opin. Microbiol. 4, 602–606 (2001).
pubmed: 11587939
doi: 10.1016/S1369-5274(00)00257-5
pmcid: 11587939
Bankevich, A. et al. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing. J. Comput. Biol. 19, 455–477 (2012).
pubmed: 22506599
pmcid: 3342519
doi: 10.1089/cmb.2012.0021
Earl, D. et al. Assemblathon 1: A competitive assessment of de novo short read assembly methods. Genome Res. 21, 2224–2241 (2011).
pubmed: 21926179
pmcid: 3227110
doi: 10.1101/gr.126599.111
NCBI Resource Coordinators. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 44, D7–D19 (2016).
doi: 10.1093/nar/gkv1290
Lukjancenko, O., Thomsen, M. C., Larsen, M. V. & Ussery, D. W. PanFunPro: PAN-genome analysis based on Functional PROfiles. F1000Research 2 (2013).
Hyatt, D. et al. Prodigal: Prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11 (2010).
Wilson, D. et al. SUPERFAMILY - Sophisticated comparative genomics, data mining, visualization and phylogeny. Nucleic Acids Res. 37, 380–386 (2009).
doi: 10.1093/nar/gkn762
Zdobnov, E. M. & Apweiler, R. InterProScan - An integration platform for the signature-recognition methods in InterPro. Bioinformatics 17, 847–848 (2001).
pubmed: 11590104
doi: 10.1093/bioinformatics/17.9.847
pmcid: 11590104
Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: Accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).
pubmed: 3516142
pmcid: 3516142
doi: 10.1093/bioinformatics/bts565
Li, W. & Godzik, A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).
doi: 10.1093/bioinformatics/btl158
Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).
pubmed: 15034147
pmcid: 15034147
doi: 10.1093/nar/gkh340
R Core Team. R: A Language and Environment for Statistical Computing (2015).
Warnes, G. R. et al. gplots: Various R Programming Tools for Plotting Data (2016).
Guindon, S. et al. New Algorithms and Mehtods to Estimate Maximum-Likelihood Phylogenies: Asessing the Performance of PhyML 2.0. Syst. Biol. 59, 307–321 (2010).
doi: 10.1093/sysbio/syq010
Hunter, J. D. & Droettboom, M. Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering, 9, 90–95 (2007).
Fabian Pedregosa et. al. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825–2830 (2011).
Wes McKinney. Data Structures for Statistical Computing in Python. Proceedings of the 9th Python in Science Conference, 51–56 (2010).
van der Walt, S., Colbert, S. C. & Varoquaux, G. The NumPy Array: A Structure for Efficient Numerical Computation. Computing in Science & Engineering. 13, 22–30 (2011).
Page, A. J. et al. SNP-sites: rapid efficient extraction of SNPs from multi- FASTA alignments. Microb. Genomics 5 (2016).
Henikoff, S. & Henikoff, J. G. Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. 89, 10915–10919 (1992).
pubmed: 1438297
doi: 10.1073/pnas.89.22.10915
pmcid: 1438297
Huerta-Cepas, J. et al. EGGNOG 4.5: A hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 44, D286–D293 (2016).
pubmed: 26582926
doi: 10.1093/nar/gkv1248
pmcid: 26582926
Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).
pubmed: 28460117
pmcid: 5850834
doi: 10.1093/molbev/msx148