Neisseria meningitidis (meningococcus) is a cosmopolitan bacterium that is often found in the upper respiratory tract of asymptomatic humans. However, N. meningitidis also causes meningeal inflammation and/or sepsis in humans with a periodic resurgence in incidence and high mortality rates. The pathogen is highly diverse genetically and antigenically, so that genotyping is considered important for vaccine matching to circulating strains. Annual incidence of meningococcal disease in Kazakhstan ranges between 0.2 and 2.5 cases per 100 thousand population. In total, 78 strains of N. meningitidis were isolated from clinical patients and contact persons during the years 2017-2018 in Kazakhstan. Of these, 41 strains including four from the patients and 37 from contacts, were sequenced using Illumina MiSeq. In silico typing was completed using the Neisseria pipeline 1.2 on the Galaxy Workflow Management System and PubMLST. Whole genome SNP (single nucleotide polymorphisms) trees were built using BioNumerics 8. Seven-gene multilocus sequence typing (MLST) identified ten sequence types (ST), two of which have not been previously described (ST-16025; ST-16027). ST-16025 was detected in two patients with invasive meningococcal disease in 2017 and 2018 in Akmola region and 16 contacts in 2017 in Turkistan region. This prevalent type ST-16025 demonstrates considerable intertypic diversity as it consists of three subcomplexes with a distance of more than 2000 SNPs. Invasive and carrier strains belong to different serogroups (MenB and MenC), PorA and FetA_VR. Two invasive strains were MenB, one MenC and one MenW (Hajj lineage). The strains from the contact persons were: MenC (n = 18), cnl (n = 9), MenY (n = 7), MenW (n = 1), MenB (n = 1) and one unidentifiable. Different numbers of alleles were present: 12, 11, 7, and 7 alleles for PorA, FetA, fHbp, and NHBA, respectively. This study is the first report of the genetic diversity of N. meningitidis strains in Kazakhstan. Despite limitations with the studied sample size, important conclusions can be drawn based on data produced. This study provides evidence for regulatory authorities with regard to changing routine diagnostic protocols to increase the collecting of samples for WGS.
Copyright: © 2022 Shevtsov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.