Skip to content
1887

Journal of Medical Microbiology logo Journal of Medical Microbiology

Volume 73, Issue 8

Genomic oropharyngeal surveillance detects MALDI-TOF MS species misidentifications and reveals a novel clade No Access

Abstract

Commensal spp. are highly prevalent in the oropharynx as part of the healthy microbiome. can colonise the oropharynx too from where it can cause invasive meningococcal disease. To identify , clinical microbiology laboratories often rely on Matrix Assisted Laser Desorption/Ionisation Time of Flight Mass Spectrometry (MALDI-TOF MS).

may be misidentified by MALDI-TOF MS.

To conduct genomic surveillance of oropharyngeal spp. in order to: (i) verify MALDI-TOF MS species identification, and (ii) characterize commensal spp. genomes.

We analysed whole genome sequence (WGS) data from 119 spp. isolates from a surveillance programme for oropharyngeal spp. in Belgium. Different species identification methods were compared: (i) MALDI-TOF MS, (ii) Ribosomal Multilocus Sequence Typing (rMLST) and (iii) gene species identification. WGS data were used to further characterize species found with supplementary analyses of genomes.

Based on genomic species identification, isolates from the oropharyngeal surveilence study were composed of the following species: (=23) (=61), (=15), (=8), (=5), (=3), (=2), (=1) and (=1). Of these 119 isolates, four isolates identified as (=3) and (=1) by MALDI-TOF MS were determined to be (=1) (=2) and (=1) by rMLST. Phylogenetic analyses revealed that isolates from the general population (=3, cluster one) were distinct from those obtained from men who have sex with men (MSM, =2, cluster two). The latter contained genomes misidentified as using MALDI-TOF MS. These two clusters persisted after the inclusion of published WGS (=42). Both clusters were further defined through pangenome and Average Nucleotide Identity (ANI) analyses.

This study provides insights into the importance of genomic genus-wide surveillance studies to improve the characterization and identification of the genus.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): genome dynamics , genomic surveillance , MALDI-TOF MS , Neisseria cinerea , Neisseria meningitidis , rMLST , species boundaries and species identification
© 2024 The Authors
Loading

Article metrics loading...

/content/journal/jmm/10.1099/jmm.0.001871
2024-08-30
2025-06-24
Loading full text...

Full text loading...

References

  1. de Block T, Laumen JGE, Van Dijck C, Abdellati S, De Baetselier I et al. Wgs of commensal Neisseria reveals acquisition of a new ribosomal protection protein (Msrd) as a possible explanation for high level azithromycin resistance in Belgium. Pathogens 2021; 10:384 [View Article] [PubMed]
     [Google Scholar]
  2. Manoharan-Basil SS, González N, Laumen JGE, Kenyon C. Horizontal gene transfer of fluoroquinolone resistance-conferring genes from commensal Neisseria to Neisseria gonorrhoeae: a global phylogenetic analysis of 20,047 isolates. Front Microbiol 2022; 13:793612 [View Article] [PubMed]
     [Google Scholar]
  3. Deasy AM, Guccione E, Dale AP, Andrews N, Evans CM et al. Nasal inoculation of the commensal Neisseria lactamica inhibits carriage of neisseria meningitidis by young adults: a controlled human infection study. Clin Infect Dis 2015; 60:1512–1520 [View Article] [PubMed]
     [Google Scholar]
  4. Lu M, Xuan S, Wang Z. Oral microbiota: a new view of body health. Food Sci Hum Wellness 2019; 8:8–15 [View Article]
     [Google Scholar]
  5. Custodio R, Johnson E, Liu G, Tang CM, Exley RM. Commensal Neisseria cinerea impairs Neisseria meningitidis microcolony development and reduces pathogen colonisation of epithelial cells. PLoS Pathog 2020; 16:1–21 [View Article] [PubMed]
     [Google Scholar]
  6. Rosier BT, Moya-Gonzalvez EM, Corell-Escuin P, Mira A. Isolation and characterization of nitrate-reducing bacteria as potential probiotics for oral and systemic health. Front Microbiol 2020; 11:1–19 [View Article] [PubMed]
     [Google Scholar]
  7. Dorey RB, Theodosiou AA, Read RC, Jones CE. The nonpathogenic commensal Neisseria: friends and foes in infectious disease. Curr Opin Infect Dis 2019; 32:490–496 [View Article] [PubMed]
     [Google Scholar]
  8. Walsh L, Clark SA, Derrick JP, Borrow R. Beyond the usual suspects: reviewing infections caused by typically-commensal Neisseria species. J Infect 2023; 87:1–11 [View Article] [PubMed]
     [Google Scholar]
  9. Kenyon C, Laumen J, Manoharan-Basil S. Choosing new therapies for Gonorrhoea: we need to consider the impact on the pan-Neisseria genome. a viewpoint. Antibiotics 2021; 10:515 [View Article] [PubMed]
     [Google Scholar]
  10. Goytia M, Wadsworth CB. Canary in the coal mine: how resistance surveillance in commensals could help curb the spread of AMR in pathogenic Neisseria. mBio 2022; 13:e0199122 [View Article] [PubMed]
     [Google Scholar]
  11. Kanesaka I, Ohno A, Morita M, Katsuse AK, Morihana T et al. Epigenetic effects of ceftriaxone-resistant Neisseria gonorrhoeae FC428 mosaic-like sequences found in PenA sequences unique to Neisseria subflavaand related species. J Antimicrob Chemother 2023; 78:1–8 [View Article] [PubMed]
     [Google Scholar]
  12. Unitt A, Maiden M, Harrison O. Characterizing the diversity and commensal origins of penA mosaicism in the genus Neisseria. Microbial Genomics 2024; 10:1–12 [View Article]
     [Google Scholar]
  13. Jolley KA, Bliss CM, Bennett JS, Bratcher HB, Brehony C et al. Ribosomal multilocus sequence typing: universal characterization of bacteria from domain to strain. Microbiology 2012; 158:1005–1015 [View Article] [PubMed]
     [Google Scholar]
  14. Bennett JS, Watkins ER, Jolley KA, Harrison OB, Maiden MCJ. Identifying Neisseria species by use of the 50S ribosomal protein L6 (rplF) gene. J Clin Microbiol 2014; 52:1375–1381 [View Article] [PubMed]
     [Google Scholar]
  15. Hong E, Bakhalek Y, Taha MK. Identification of Neisseria meningitidis by MALDI-TOF MS may not be reliable. Clin Microbiol Infect 2019; 25:717–722 [View Article] [PubMed]
     [Google Scholar]
  16. Kawahara-Matsumizu M, Yamagishi Y, Mikamo H. Misidentification of Neisseria cinerea as Neisseria meningitidis by Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS). Jpn J Infect Dis 2018; 71:85–87 [View Article] [PubMed]
     [Google Scholar]
  17. Cunningham SA, Mainella JM, Patel R. Misidentification of Neisseria polysaccharea as Neisseria meningitidis with the use of matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 2014; 52:2270–2271 [View Article] [PubMed]
     [Google Scholar]
  18. Unalan-Altintop T, Karagoz A, Hazirolan G. A diagnostic challenge in clinical laboratory: misidentification of Neisseria subflava as Neisseria meningitidis by MALDI-TOF MS. Acta Microbiol Immunol Hung 2020; 67:258–260 [View Article] [PubMed]
     [Google Scholar]
  19. von Kietzell M, Richter H, Bruderer T, Goldenberger D, Emonet S et al. Meningitis and bacteremia due to neisseria cinerea following a percutaneous rhizotomy of the trigeminal ganglion. J Clin Microbiol 2016; 54:233–235 [View Article]
     [Google Scholar]
  20. Bennett JS, Jolley KA, Earle SG, Corton C, Bentley SD et al. A genomic approach to bacterial taxonomy: an examination and proposed reclassification of species within the genus Neisseria. . Microbiology 2012; 158:1570–1580 [View Article]
     [Google Scholar]
  21. Bennett JS, Jolley KA, Maiden MCJ. Genome sequence analyses show that Neisseria oralis is the same species as “Neisseria mucosa var. Heidelbergensis.”. Int J Syst Evol Microbiol 2013; 63:3920–3926 [View Article] [PubMed]
     [Google Scholar]
  22. Diallo K, MacLennan J, Harrison OB, Msefula C, Sow SO et al. Genomic characterization of novel Neisseria species. Sci Rep 2019; 9:13742 [View Article] [PubMed]
     [Google Scholar]
  23. Mustapha MM, Lemos APS, Griffith MP, Evans DR, Marx R et al. Two cases of newly characterized Neisseria species, Brazil. Emerg Infect Dis 2020; 26:366–369 [View Article] [PubMed]
     [Google Scholar]
  24. Laumen JGE, Van Dijck C, Abdellati S, De Baetselier I, Serrano G et al. Antimicrobial susceptibility of commensal Neisseria in a general population and men who have sex with men in Belgium. Sci Rep 2022; 12:1–10 [View Article] [PubMed]
     [Google Scholar]
  25. Van Dijck C, Tsoumanis A, Rotsaert A, Vuylsteke B, Van den Bossche D et al. Antibacterial mouthwash to prevent sexually transmitted infections in men who have sex with men taking HIV pre-exposure prophylaxis (PReGo): a randomised, placebo-controlled, crossover trial. Lancet Infect Dis 2021; 21:657–667 [View Article] [PubMed]
     [Google Scholar]
  26. Andrews S. A quality control tool for high throughput sequence data. n.d https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
  27. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
     [Google Scholar]
  28. Seemann T. shovill. n.d https://github.com/tseemann/shovill
  29. Prjibelski A, Antipov D, Meleshko D, Lapidus A. Using spades de novo assembler. Curr Protoc Bioinforma 2020; 70: [View Article]
     [Google Scholar]
  30. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article] [PubMed]
     [Google Scholar]
  31. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
     [Google Scholar]
  32. Jolley KA, Bray JE, Maiden MCJ. Open peer review open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications [version 1; peer review: 2 approved]. Wellcome Open Res 2018; 3:124 [View Article] [PubMed]
     [Google Scholar]
  33. Silva M, Machado MP, Silva DN, Rossi M, Moran-Gilad J et al. chewBBACA: a complete suite for gene-by-gene schema creation and strain identification. Microb Genom 2018; 4:e000166 [View Article] [PubMed]
     [Google Scholar]
  34. Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. Nat Commun 2010; 6:1–8 [View Article] [PubMed]
     [Google Scholar]
  35. Zhou Z, Alikhan N-F, Sergeant MJ, Luhmann N, Vaz C et al. GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Res 2018; 28:1395–1404 [View Article] [PubMed]
     [Google Scholar]
  36. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 2013; 30:772–780 [View Article] [PubMed]
     [Google Scholar]
  37. Nguyen L, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2014; 32:268–274 [View Article]
     [Google Scholar]
  38. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article] [PubMed]
     [Google Scholar]
  39. 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]
  40. Price MN, Dehal PS, Arkin AP. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 2009; 26:1641–1650 [View Article] [PubMed]
     [Google Scholar]
  41. Hadfield J, Croucher NJ, Goater RJ, Abudahab K, Aanensen DM et al. Phandango: an interactive viewer for bacterial population genomics. Bioinformatics 2018; 34:292–293 [View Article] [PubMed]
     [Google Scholar]
  42. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J et al. BLAST+: architecture and applications. BMC Bioinformatics 2009; 10:1–9 [View Article] [PubMed]
     [Google Scholar]
  43. Seemann T. Abricate. n.d https://github.com/tseemann/abricate
  44. Krüger N-J, Stingl K. Two steps away from novelty--principles of bacterial DNA uptake. Mol Microbiol 2011; 80:860–867 [View Article] [PubMed]
     [Google Scholar]
  45. Chen L, Zheng D, Liu B, Yang J, Jin Q. VFDB 2016: hierarchical and refined dataset for big data analysis—10 years on. Nucleic Acids Res 2016; 44:D694–D697 [View Article]
     [Google Scholar]
  46. Martin DP, Murrell B, Golden M, Khoosal A, Muhire B. RDP4: detection and analysis of recombination patterns in virus genomes. Virus Evol 2015; 1:1–5 [View Article] [PubMed]
     [Google Scholar]
  47. Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018; 9:1–8 [View Article] [PubMed]
     [Google Scholar]
  48. Frye SA, Nilsen M, Tønjum T, Ambur OH. Dialects of the DNA Uptake Sequence in Neisseriaceae. PLoS Genet 2013; 9:e1003458 [View Article] [PubMed]
     [Google Scholar]
  49. Ngai S, Weiss D, Bell JA, Majrud D, Zayas G et al. Carriage of Neisseria meningitidis in men who have sex with men presenting to public sexual health clinics, New York City. Sex Transm Dis 2020; 47:541–548 [View Article] [PubMed]
     [Google Scholar]
  50. Deak E, Green N, Humphries RM. Microbiology test reliability in differentiation of Neisseria meningitidis and Neisseria polysaccharea. . J Clin Microbiol 2014; 52:3496 [View Article] [PubMed]
     [Google Scholar]
  51. Goytia M, Thompson ST, Jordan SVL, King KA. Antimicrobial resistance profiles of human commensal Neisseria species. Antibiotics 2021; 10:538 [View Article] [PubMed]
     [Google Scholar]
  52. Cuénod A, Aerni M, Bagutti C, Bayraktar B, Boz ES et al. Quality of MALDI-TOF mass spectra in routine diagnostics: results from an international external quality assessment including 36 laboratories from 12 countries using 47 challenging bacterial strains. Clin Microbiol Infect 2023; 29:190–199 [View Article] [PubMed]
     [Google Scholar]
  53. Liébana-Martos C. Interpretation of results, advantages disadvantages, and limitations of MALDI-TOF. Use Mass Spectrom Technol Clin Microbiol 201875–86 [View Article]
     [Google Scholar]
  54. Rychert J. Benefits and limitations of MALDI-TOF mass spectrometry for the identification of microorganisms. J Infect 2019; 2:1–5 [View Article]
     [Google Scholar]
  55. Zong Z. Genome-based taxonomy for bacteria: a recent advance. Trends Microbiol 2020; 28:871–874 [View Article] [PubMed]
     [Google Scholar]
  56. Murray CS, Gao Y, Wu M. Re-evaluating the evidence for a universal genetic boundary among microbial species. Nat Commun 2021; 12:1–5 [View Article] [PubMed]
     [Google Scholar]
  57. Rodriguez-R LM, Jain C, Conrad RE, Aluru S, Konstantinidis KT. Reply to: “re-evaluating the evidence for a universal genetic boundary among microbial species.”. Nat Commun 2021; 12:4060 [View Article] [PubMed]
     [Google Scholar]
  58. Hanage WP, Fraser C, Spratt BG. Fuzzy species among recombinogenic bacteria. BMC Biol 2005; 3:1–7 [View Article] [PubMed]
     [Google Scholar]
  59. Corander J, Connor TR, O’Dwyer CA, Kroll JS, Hanage WP. Population structure in the Neisseria, and the biological significance of fuzzy species. J R Soc Interface 2012; 9:1208–1215 [View Article] [PubMed]
     [Google Scholar]
  60. Hanage WP. Fuzzy species revisited. BMC Biol 2013; 11:10–12 [View Article] [PubMed]
     [Google Scholar]
  61. Moe GR, Zuno-Mitchell P, Lee SS, Lucas AH, Granoff DM. Functional activity of anti-neisserial surface protein A monoclonal antibodies against strains of Neisseria meningitidis serogroup B. Infect Immun 2001; 69:3762–3771 [View Article] [PubMed]
     [Google Scholar]
  62. Fegan JE, Calmettes C, Islam EA, Ahn SK, Chaudhuri S et al. Utility of hybrid transferrin binding protein antigens for protection against pathogenic Neisseria species. Front Immunol 2019; 10:1–4 [View Article] [PubMed]
     [Google Scholar]
  63. Jolley KA, Wilson DJ, Kriz P, McVean G, Maiden MCJ. The influence of mutation, recombination, population history, and selection on patterns of genetic diversity in Neisseria meningitidis. Mol Biol Evol 2005; 22:562–569 [View Article] [PubMed]
     [Google Scholar]
  64. Joseph B, Schwarz RF, Linke B, Blom J, Becker A et al. Virulence evolution of the human pathogen Neisseria meningitidis by recombination in the core and accessory genome. PLoS One 2011; 6:e18441 [View Article] [PubMed]
     [Google Scholar]
  65. Perkins-Balding D, Ratliff-Griffin M, Stojiljkovic I. Iron transport systems in Neisseria meningitidis. Microbiol Mol Biol Rev 2004; 68:154–171 [View Article] [PubMed]
     [Google Scholar]
  66. Harrison OB, Evans NJ, Blair JM, Grimes HS, Tinsley CR et al. Epidemiological evidence for the role of the hemoglobin receptor, hmbR, in meningococcal virulence. J Infect Dis 2009; 200:94–98 [View Article] [PubMed]
     [Google Scholar]
  67. Deghmane A-E, Haeghebaert S, Hong E, Jousset A, Barret A-S et al. Emergence of new genetic lineage, ST-9316, of Neisseria meningitidis group W in Hauts-de-France region, France 2013-2018. J Infect 2020; 80:519–526 [View Article] [PubMed]
     [Google Scholar]
  68. Clemence MEA, Maiden MCJ, Harrison OB. Characterization of capsule genes in non-pathogenic Neisseria species. Microb Genom 2018; 4:e000208 [View Article] [PubMed]
     [Google Scholar]
  69. Kenyon CR, Schwartz IS. Effects of sexual network connectivity and antimicrobial drug use on antimicrobial resistance in Neisseria gonorrhoeae. Emerg Infect Dis 2018; 24:1195–1203 [View Article]
     [Google Scholar]
  70. Gaspari V, Djusse ME, Morselli S, Rapparini L, Foschi C et al. Non-pathogenic Neisseria species of the oropharynx as a reservoir of antimicrobial resistance: a cross-sectional study. Front Cell Infect Microbiol 2023; 13:1–8 [View Article] [PubMed]
     [Google Scholar]
  71. Dong HV, Pham LQ, Nguyen HT, Nguyen MXB, Nguyen TV et al. Decreased cephalosporin susceptibility of oropharyngeal Neisseria species in antibiotic-using men who have sex with men in Hanoi, Vietnam. Clin Infect Dis 2020; 70:1169–1175 [View Article] [PubMed]
     [Google Scholar]
  72. Nakayama SI, Shimuta K, Furubayashi K-I, Kawahata T, Unemo M et al. New ceftriaxone- and multidrug-resistant Neisseria gonorrhoeae strain with a novel mosaic penA gene isolated in Japan. Antimicrob Agents Chemother 2016; 60:4339–4341 [View Article] [PubMed]
     [Google Scholar]
  73. Sánchez-Busó L, Cole MJ, Spiteri G, Day M, Jacobsson S et al. Europe-wide expansion and eradication of multidrug-resistant Neisseria gonorrhoeae lineages: a genomic surveillance study. Lancet Microbe 2022; 3:e452–e463 [View Article] [PubMed]
     [Google Scholar]
/content/journal/jmm/10.1099/jmm.0.001871
Loading
Genomic oropharyngeal Neisseria surveillance detects MALDI-TOF MS species misidentifications and reveals a novel Neisseria cinerea clade
J. Med. Microbiol. 73, 001871 (2024); https://doi.org/10.1099/jmm.0.001871
/content/journal/jmm/10.1099/jmm.0.001871
/content/journal/jmm/10.1099/jmm.0.001871
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Most cited Most Cited RSS feed

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