1887

Abstract

When analysing a large cohort of , using whole-genome sequencing, five human isolates (four from the skin and one from a blood culture) with aberrant phenotypic and genotypic traits were identified. They were phenotypically similar with yellow colonies, nearly identical 16S rRNA gene sequences and initially speciated as based on 16S rRNA gene sequence and MALDI-TOF MS. However, compared to , these five strains demonstrate: (i) considerable phylogenetic distance with an average nucleotide identity <95 % and inferred DNA–DNA hybridization <70  %; (ii) a pigmented phenotype; (iii) urease production; and (iv) different fatty acid composition. Based on the phenotypic and genotypic results, we conclude that these strains represent a novel species, for which the name sp. nov. is proposed. The novel species belong to the genus and is coagulase- and oxidase-negative and catalase-positive. The type strain, 51-48, is deposited in the Culture Collection University of Gothenburg (CCUG 73747) and in the Spanish Type Culture Collection (CECT 30011).

Funding
This study was supported by the:
  • Northern Norway Regional Health Authority (NO) (Award HNF1344-17)
    • Principle Award Recipient: Jorunn Pauline Cavanagh
Loading

Article metrics loading...

/content/journal/ijsem/10.1099/ijsem.0.004499
2020-10-13
2024-04-27
Loading full text...

Full text loading...

/deliver/fulltext/ijsem/70/12/6067.html?itemId=/content/journal/ijsem/10.1099/ijsem.0.004499&mimeType=html&fmt=ahah

References

  1. Götz F, Bannerman T, Schleifer K. The genera Staphylococcus and Macrococcus . In Dworkin M, Falkow S, Rosenberg E, Schleifer K, Stackebrandt E. (editors) The Prokayotes, vol 4: Bacteria: Firmicutes, Cyanobacteria New York, NY: Springer US; 2006 pp 5–75
    [Google Scholar]
  2. Becker K, Heilmann C, Peters G. Coagulase-negative staphylococci. Clin Microbiol Rev 2014; 27:870–926 [View Article][PubMed]
    [Google Scholar]
  3. Tong SYC, Davis JS, Eichenberger E, Holland TL, Fowler VG. Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin Microbiol Rev 2015; 28:603–661 [View Article][PubMed]
    [Google Scholar]
  4. Fluit AC. Livestock-associated Staphylococcus aureus . Clin Microbiol Infect 2012; 18:735–744 [View Article]
    [Google Scholar]
  5. Cavanagh JP, Wolden R, Heise P, Esaiassen E, Klingenberg C et al. Antimicrobial susceptibility and body site distribution of community isolates of coagulase-negative staphylococci. APMIS 2016; 124:973–978 [View Article][PubMed]
    [Google Scholar]
  6. Pain M, Hjerde E, Klingenberg C, Cavanagh JP. Comparative genomic analysis of Staphylococcus haemolyticus reveals key to hospital adaptation and pathogenicity. Front Microbiol 2019; 10:1–13 [View Article]
    [Google Scholar]
  7. Cavanagh JP, Hjerde E, Holden MTG, Kahlke T, Klingenberg C et al. Whole-genome sequencing reveals clonal expansion of multiresistant Staphylococcus haemolyticus in European hospitals. J Antimicrob Chemother 2014; 69:2920–2927 [View Article][PubMed]
    [Google Scholar]
  8. Freney J, Kloos WE, Hajek V, Webster JA, Bes M et al. Recommended minimal standards for description of new staphylococcal species. Int J Syst Evol Microbiol 1999; 49:489–502 [View Article]
    [Google Scholar]
  9. Chun J, Oren A, Ventosa A, Christensen H, Arahal DR et al. Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int J Syst Evol Microbiol 2018; 68:461–466 [View Article][PubMed]
    [Google Scholar]
  10. Chachaty E, Saulnier P. Isolating chromosomal DNA from. In Rapley R. editor The Nucleic Acid Protocols Handbook New Jersey: Humana Press; 2000
    [Google Scholar]
  11. Chin CS, Alexander DH, Marks P, Klammer AA, Drake J et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 2013; 10:563–569 [View Article][PubMed]
    [Google Scholar]
  12. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 2014; 9:e112963 [View Article][PubMed]
    [Google Scholar]
  13. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint 2013; 00:1–3
    [Google Scholar]
  14. Naushad S, Barkema HW, Luby C, Condas LAZ, Nobrega DB et al. Comprehensive phylogenetic analysis of bovine non-aureus staphylococci species based on whole-genome sequencing. Front Microbiol 2016; 7:1990 [View Article][PubMed]
    [Google Scholar]
  15. Stødkilde K, Poehlein A, Brüggemann H. Draft genome sequence of a new staphylococcal species isolated from human skin. Microbiol Resour Announc 2020; 9:e01499–19 [View Article][PubMed]
    [Google Scholar]
  16. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article][PubMed]
    [Google Scholar]
  17. Yoon SH, Ha SM, Kwon S, Lim J, Kim Y et al. Introducing EzBioCloud: a taxonomically United database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol 2017; 67:1613–1617 [View Article][PubMed]
    [Google Scholar]
  18. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 2016; 33:1870–1874 [View Article][PubMed]
    [Google Scholar]
  19. Edgar RC. Muscle: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797 [View Article][PubMed]
    [Google Scholar]
  20. Edler D, Klein J, Antonelli A, Silvestro D. raxmlGUI 2.0 beta: a graphical interface and toolkit for phylogenetic analyses using RAxML. bioRxiv 2019; 800912:
    [Google Scholar]
  21. Yugueros J, Temprano A, Berzal B, Sánchez M, Hernanz C et al. Glyceraldehyde-3-phosphate dehydrogenase-encoding gene as a useful taxonomic tool for Staphylococcus spp. J Clin Microbiol 2000; 38:4351–4355 [View Article][PubMed]
    [Google Scholar]
  22. Martineau F, Picard FJ, Ke D, Paradis S, Roy PH et al. Development of a PCR assay for identification of staphylococci at genus and species levels. J Clin Microbiol 2001; 39:2541–2547 [View Article]
    [Google Scholar]
  23. Poyart C, Quesne G, Boumaila C, Trieu-Cuot P. Rapid and accurate species-level identification of coagulase-negative staphylococci by using the sodA gene as a target. J Clin Microbiol 2001; 39:4296–4301 [View Article][PubMed]
    [Google Scholar]
  24. Drancourt M, Raoult D. rpoB gene sequence-based identification of Staphylococcus species. J Clin Microbiol 2002; 40:1333–1338 [View Article][PubMed]
    [Google Scholar]
  25. Shah MM, Iihara H, Noda M, Song SX, Nhung PH et al. dnaJ gene sequence-based assay for species identification and phylogenetic grouping in the genus Staphylococcus . Int J Syst Evol Microbiol 2007; 57:25–30 [View Article][PubMed]
    [Google Scholar]
  26. Goh SH, Potter S, Wood JO, Hemmingsen SM, Reynolds RP et al. Hsp60 gene sequences as universal targets for microbial species identification. J Clin Microbiol 1996; 34:818–823
    [Google Scholar]
  27. Landeta G, Reverón I, Carrascosa AV, Rivas Bdelas, Muñoz R. Use of recA gene sequence analysis for the identification of Staphylococcus equorum strains predominant on dry-cured hams. Food Microbiol 2011; 28:1205–1210 [View Article][PubMed]
    [Google Scholar]
  28. Poirier S, Rué O, Peguilhan R, Coeuret G, Zagorec M et al. Deciphering intra-species bacterial diversity of meat and seafood spoilage microbiota using gyrB amplicon sequencing: a comparative analysis with 16S rDNA V3-V4 amplicon sequencing. PLoS One 2018; 13:e0204629–26 [View Article][PubMed]
    [Google Scholar]
  29. Cavanagh JP, Klingenberg C, Hanssen AM, Fredheim EA, Francois P et al. Core genome conservation of Staphylococcus haemolyticus limits sequence based population structure analysis. J Microbiol Methods 2012; 89:159–166 [View Article][PubMed]
    [Google Scholar]
  30. Na SI, Kim YO, Yoon SH, Ha SM, Baek I et al. UBCG: up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction. J Microbiol 2018; 56:281–285 [View Article][PubMed]
    [Google Scholar]
  31. Felsenstein J. Confidence Limits on Phylogenies : An Approach Using the Bootstrap. Evolution 1985; 39:783–791
    [Google Scholar]
  32. Richter M, Rosselló-Móra R, Oliver Glöckner F, Peplies J. JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison. Bioinformatics 2016; 32:929–931 [View Article][PubMed]
    [Google Scholar]
  33. Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 2013; 14:60 [View Article][PubMed]
    [Google Scholar]
  34. Gardner SN, Slezak T, Hall BG. kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinformatics 2015; 31:2877–2878 [View Article][PubMed]
    [Google Scholar]
  35. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015; 31:3691–3693 [View Article][PubMed]
    [Google Scholar]
  36. Liu B, Zheng D, Jin Q, Chen L, Yang J. VFDB 2019: a comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res 2019; 47:D687–D692 [View Article][PubMed]
    [Google Scholar]
  37. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P et al. Card 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res 2017; 45:D566–D573 [View Article][PubMed]
    [Google Scholar]
  38. Feldgarden M, Brover V, Haft DH, Prasad AB, Slotta DJ et al. Validating the AMRFINder tool and resistance gene database by using antimicrobial resistance genotype-phenotype correlations in a collection of isolates. Antimicrob Agents Chemother 2019; 63:1–20 [View Article]
    [Google Scholar]
  39. Doster E, Lakin SM, Dean CJ, Wolfe C, Young JG et al. MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data. Nucleic Acids Res 2020; 48:D561–569 [View Article][PubMed]
    [Google Scholar]
  40. Novotna G, Janata J. A new evolutionary variant of the streptogramin A resistance protein, Vga(A)LC, from Staphylococcus haemolyticus with shifted substrate specificity towards lincosamides. Antimicrob Agents Chemother 2006; 50:4070–4076 [View Article][PubMed]
    [Google Scholar]
  41. Tessé S, Trueba F, Berthet N, Hot C, Chesneau O. Resistance genes underlying the LSA phenotype of Staphylococcal isolates from France. Antimicrob Agents Chemother 2013; 57:4543–4546 [View Article][PubMed]
    [Google Scholar]
  42. Gentry DR, McCloskey L, Gwynn MN, Rittenhouse SF, Scangarella N et al. Genetic characterization of Vga ABC proteins conferring reduced susceptibility to pleuromutilins in Staphylococcus aureus . Antimicrob Agents Chemother 2008; 52:4507–4509 [View Article][PubMed]
    [Google Scholar]
  43. Truong-Bolduc QC, Hooper DC. The transcriptional regulators NorG and MgrA modulate resistance to both quinolones and β-lactams in Staphylococcus aureus . J Bacteriol 2007; 189:2996–3005 [View Article][PubMed]
    [Google Scholar]
  44. Cocchiaro JL, Kumar Y, Fischer ER, Hackstadt T, Valdivia RH. Cytoplasmic lipid droplets are translocated into the lumen of the Chlamydia trachomatis parasitophorous vacuole. Proc Natl Acad Sci U S A 2008; 105:9379–9384 [View Article][PubMed]
    [Google Scholar]
  45. Cunha MdeLRS, Sinzato YK, Silveira LVA. Comparison of methods for the identification of coagulase-negative staphylococci. Mem Inst Oswaldo Cruz 2004; 99:855–860 [View Article][PubMed]
    [Google Scholar]
  46. Schleifer KH, Kloos WE. Isolation and characterization of Staphylococci from human skin I. amended descriptions of Staphylococcus epidermidis and Staphylococcus saprophyticus and descriptions of three new species: Staphylococcus cohnii, Staphylococcus haemolyticus, and Staphylococcus xylosus . Int J Syst Bacteriol 1975; 25:50–61 [View Article]
    [Google Scholar]
  47. Sasser M. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids, MIDI-Tech Note 101. 1990 pp 1–6
    [Google Scholar]
  48. Zamora L, Fernández-Garayzábal JF, Svensson-Stadler LA, Palacios MA, Domínguez L et al. Flavobacterium oncorhynchi sp. nov., a new species isolated from rainbow trout (Oncorhynchus mykiss). Syst Appl Microbiol 2012; 35:86–91 [View Article]
    [Google Scholar]
  49. De Carvalho C, Caramujo M. The various roles of fatty acids. Molecules 2018; 23:2583 [View Article]
    [Google Scholar]
  50. Welch DF. Applications of cellular fatty acid analysis. Clin Microbiol Rev 1991; 4:422–438 [View Article]
    [Google Scholar]
  51. Kotilainen P, Huovinen P, Eerola E. Application of gas-liquid chromatographic analysis of cellular fatty acids for species identification and typing of coagulase-negative staphylococci. J Clin Microbiol 1991; 29:315–322 [View Article]
    [Google Scholar]
  52. Kaneda T. Iso- and anteiso-fatty acids in bacteria: biosynthesis, function, and taxonomic significance. Microbiol Rev 1991; 55:288–302 [View Article]
    [Google Scholar]
  53. Onyango LA, Alreshidi MM. Adaptive metabolism in staphylococci: survival and persistence in environmental and clinical settings. J Pathog 2018; 2018:1–11 [View Article]
    [Google Scholar]
  54. Schumann P. Peptidoglycan structure. Methods Microbiol 2011; 38:101–129
    [Google Scholar]
  55. The European Committee on Antimicrobial Suceptibility Testing Breakpoint tables for interpretation of MICs and zone diameters, version 9.0; 2019
  56. Frey Y, Rodriguez JP, Thomann A, Schwendener S, Perreten V. Genetic characterization of antimicrobial resistance in coagulase-negative staphylococci from bovine mastitis milk. J Dairy Sci 2013; 96:2247–2257 [View Article]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/ijsem/10.1099/ijsem.0.004499
Loading
/content/journal/ijsem/10.1099/ijsem.0.004499
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error