Whole Genome Analyses Accurately Identify Neisseria spp. and Limit Taxonomic Ambiguity

• Published in: International journal of molecular sciences Vol. 23; no. 21; p. 13456
• Main Authors: Khoder, May, Osman, Marwan, Kassem, Issmat I., Rafei, Rayane, Shahin, Ahmad, Fournier, Pierre Edouard, Rolain, Jean-Marc, Hamze, Monzer
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-11-2022; MDPI
• Subjects: Clinical isolates; Deoxyribonucleic acid; DNA; Fatty acids; Genes; Genomes; Genomics; Gonorrhea; Hybridization; identification; Ionization; Life Sciences; Motility; Neisseria; Neisseria spp; Nucleotides; Phylogenetics; Phylogeny; Proteins; Semen; Strains (organisms); Taxonomy; Transfer RNA; Virulence; whole genome sequencing; whole genome sequencing; identification; taxonomy; Neisseria spp
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms232113456

Genome sequencing facilitates the study of bacterial taxonomy and allows the re-evaluation of the taxonomic relationships between species. Here, we aimed to analyze the draft genomes of four commensal Neisseria clinical isolates from the semen of infertile Lebanese men. To determine the phylogenetic relationships among these strains and other Neisseria spp. and to confirm their identity at the genomic level, we compared the genomes of these four isolates with the complete genome sequences of Neisseria gonorrhoeae and Neisseria meningitidis and the draft genomes of Neisseria flavescens, Neisseria perflava, Neisseria mucosa, and Neisseria macacae that are available in the NCBI Genbank database. Our findings revealed that the WGS analysis accurately identified and corroborated the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) species identities of the Neisseria isolates. The combination of three well-established genome-based taxonomic tools (in silico DNA-DNA Hybridization, Ortho Average Nucleotide identity, and pangenomic studies) proved to be relatively the best identification approach. Notably, we also discovered that some Neisseria strains that are deposited in databases contain many taxonomical errors. The latter is very important and must be addressed to prevent misdiagnosis and missing emerging etiologies. We also highlight the need for robust cut-offs to delineate the species using genomic tools.