Skip to main content
Springer logoLink to Springer
. 2026 Jan 10;45(4):1115–1122. doi: 10.1007/s10096-025-05367-3

Molecular characterization of Neisseria meningitidis isolates from healthy individuals in Meigu County, Sichuan Province, 2021–2024

Hongyu Liao 1,#, Mingxiu Li 1,2,#, Linzi Zeng 1, Rongmei Yuan 1, Shu Huang 1, Wenbo Li 1, Xiaorong Yang 1,2,
PMCID: PMC13086647  PMID: 41518555

Abstract

To explore the molecular characteristics of Neisseria meningitidis carried by healthy individuals in Meigu County, Liangshan Yi Autonomous Prefecture, Sichuan Province, and to provide scientific evidence for preventing and controlling epidemic meningitis, this study analyzed 240 N. meningitidis isolates collected from 2021 to 2024. PCR-based genogrouping and second-generation whole-genome sequencing (WGS) were performed. The results showed that genogroup B was the most common, accounting for 65%. Multilocus Sequence Typing(MLST) analysis identified 78 sequence types(STs), with ST-18,628 and ST-2146 being the most frequent. Notably, 41% of the STs (ST-18,620 to ST-18,856) were newly identified. While 29 STs were allocated to six known clonal complexes, 49 STs couldn’t be assigned to any. Genogroup B N. meningitidis (MenB) isolates showed high heterogeneity and the most common clonal complexes were CC4821, CC175, CC198. The NG N. meningitidis isolates were predominately CC198, CC4821, CC5. Genogroup W N. meningitidis (MenW) isolates were predominately CC4821. Genogroup Y N. meningitidis (MenY) isolates were belonged to CC175.Three AMR genes were detected, with mtrC and mtrD having the highest detection rate. Also, sixty-eight virulence genes were found. Core genome SNP analysis indicated same-year isolates clustered phylogenetically. In conclusion, the N. meningitidis isolates in Meigu County have diverse virulence genes and a high rate of novel STs, showing a regional epidemic trend, and continuous monitoring is necessary.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10096-025-05367-3.

Keywords: Neisseria meningitidis, Molecular characteristics, Whole-genome sequencing (WGS), AMR genes, Virulence genes

Introduction

Neisseria meningitidis can cause epidemic meningitis. N. meningitidis isolates are classified into 12 serogroups-A, B, C, H, I, K, L, W, X, Y, Z, and E-based on the structure of their capsular polysaccharides [1]. In the past, >95% of invasive cases were attributable to serogroups A, B, C, W, X and Y. During 2010–2019, serogroup B remained the predominant cause of invasive meningococcal disease(IMD) globally, while the incidence of serogroups W and Y rose significantly [2, 3]. Global surveillance data indicate that overall IMD incidence was generally low across all regions during 2010–2019 and ranged from 0.0 to 10.2 per 100,000 [3]. During 2015–2017, China reported an average IMD incidence of 0.0078 per 100,000 and a case fatality rate of 12%. From 2015 to 2017, Sichuan Province reported 16 IMD cases, the fifth-highest in the country [4]. Currently, the pathogen causing IMD in most regions is serogroup B N. meningitidis, which more easily affects young people [5]. In China, before 2014, serogroup C and serogroup W were the major circulating serogroup. After 2015, IMD cases caused by serogroup B N. meningitidis were increasing, the proportion of serogroup B reached 52% [6]. To date, cases of serogroup B meningitis have been detected in over 70% of provinces [7].

In China, the publicly funded meningococcal polysaccharide vaccine (MenPV) programme currently consists of a four-dose series: two doses of serogroup-A univalent MenPV administered between 6 and 18 months of age, followed by one dose of bivalent A-C MenPV at 3 years and a further A-C booster at 6 years. Vaccination with quadrivalent meningococcal conjugate vaccine (MenACWY) is elective and incurred out-of-pocket [8]. Two recombinant serogroup B vaccines, 4CMenB (Bexsero, GSK, London, UK) [9] and MenB-FHbp (Trumenba, bivalent rLP2086, Pfizer, New York, NY, USA) [10] are not currently available in China.

N. meningitidis often colonizes the mucosa of the nasopharynx, and its adhesion and colonization are the first steps in disease development. The nasopharyngeal carriage rate of N. meningitidis in healthy populations is 1%−14% in Asia [11]. In the Americas, the highest carriage rates were concentrated among university students in Cuba(32%) and the United States(24%) [12]. In China, the carriage rate of N. meningitidis varied between provinces, can be as high as 16% [13]. Recent studies have shown that highly pathogenic strains may be present within non-invasive isolates, emphasizing the necessity of enhancing the surveillance of carriers within the healthy population [14].

Globally, N. meningitidis remains broadly susceptible to prophylactic antibiotics, yet a consensus is emerging that penicillin-intermediate rates are steadily rising [15]. In China’s Hunan province, N. meningitidis exhibits an 86% resistance rate to trimethoprim–sulfamethoxazole, nearly 50% non-susceptibility to levofloxacin and ciprofloxacin, and a 1.4% resistance rate to penicillin [16]. Studies from Shanghai and elsewhere further indicate that clonal complex CC4821 is becoming the predominant vehicle for penicillin-intermediate/-resistant strains, highlighting the urgent need for enhanced genomic surveillance and updated vaccine strategies [17]. The main mechanisms of N. meningitidis resistance include penicillin resistance, macrolide antibiotic resistance, sulfonamide antibiotic resistance, and aminoglycoside antibiotic resistance [18]. The mechanism of macrolide antibiotic resistance in N. meningitidis mainly involves the overexpression of the mtrCDE efflux pump system. The MtrCDE efflux pump and its regulator FarA confer low-to-moderate resistance to first-line agents such as penicillin and ceftriaxone while enhancing tolerance to host defenses [19]. gyrA mutations may promote the emergence of hyper-invasive lineages and are prevalent across CC4821 strains, yet their precise role in the diversification of this clonal complex remains unclear [7].

In 2021, two IMD cases caused by serogroup B N. meningitidis were reported in Meigu County [20]. Since 2021, we have maintained carriage surveillance among healthy residents of Meigu County, a total of 240 N. meningitidis isolates were isolated from healthy individuals. Molecular epidemiologic profiles of these asymptomatic-derived, non-invasive isolates remain uncharacterised; the present study provides the first genomic dissection of this collection to close the regional knowledge gap. It is valuable for IMD control and prevention in Sichuan Province.

Materials and methods

Strain information

This study has passed the ethical review of the Ethics Committee of Sichuan Center for Disease Control and Prevention, with the approval number SCDCDIRB-2023-001.Oropharyngeal swab samples were accessed from healthy individuals for research in 18/07/2021 ~ 08/11/2024. Verbal informed consent of the participants was obtained before sample collection, and the “Record of verbal informed consent” was witnessed and filled out by personnel from a third-party institution. When the participant is a minor under the age of 18, their parents/legal guardians must be present, and their consent must be obtained first. Then, after using age-appropriate language explanations, the child’s own verbal consent must be obtained. From 2021 to 2024, a total of 240 N. meningitidis isolates were isolated from healthy individuals in Sichuan Province. Table 1 shows the basic information of these 240 isolates, including the number of isolates per year, age-group distribution, and gender distribution.

Table 1.

Distribution of N. meningitidis genogroups among healthy individuals in Meigu County, Sichuan Province, China from 2021 to 2024

Characteristics Isolate Count Genogroup
Non-groupable B group C group E group W group X group Y group
Year
2021 47 12(25.53) 22(46.81) 1(2.13) 0(0) 9(19.15) 0(0) 3(6.38)
2022 141 38(26.95) 90(63.83) 6(4.26) 1(0.71) 2(1.42) 1(0.71) 3(2.13)
2023 20 0(0) 18(90) 1(5) 0(0) 0(0) 1(5) 0(0)
2024 32 5(15.62) 26(81.25) 0(0) 0(0) 1(3.13) 0(0) 0(0)
Age
0 ~ 5 2 1(50) 1(50) 0(0) 0(0) 0(0) 0(0) 0(0)
6 ~ 10 86 18(20.93 ) 61(70.93) 4(4.65) 0(0) 1(1.16) 1(1.16) 1(1.16)
11 ~ 20 52 13(25) 26(50) 3(5.77) 0(0) 10(19.23) 0(0) 0(0)
21 ~ 44 56 12(21.43) 39(69.64) 1(1.79) 0(0) 1(1.79) 1(1.79) 2(3.57)
45— 44 11(25) 29(65.91) 0(0) 1(2.27) 0(0) 0(0) 3(6.82 )
Sex
Male 139 29(20.86) 94(67.63) 5(33.60) 0(0) 5(3.60) 1(0.72) 5 (3.60)
Female 101 26(25.74) 62(61.39) 3(2.97) 1(0.99) 7(6.93 ) 1(0.99) 1(0.99)
Total 240 55 156 8 1 12 2 6

Whole genome sequencing

The genomic DNA of N. meningitidis was extracted using the Bacterial Genomic DNA Extraction Kit (Tiangen Biotech Co., Ltd, China). After measuring the concentration with Qubit 2.0 (Thermo Fisher Scientific, United States), high-throughput sequencing of genomic DNA was performed using the Illumina NovaSeq 6000 (Illumina Inc., United States). All sequences were preprocessed with SOAPnuke to remove reads with N ratios greater than 10% and reads with quality values ≤ 20 accounting for 40% of the bases. Qualified clean data were imported into SPAdes v3.9.0 software for sequence assembly.

Genogrouping analysis

Serogroup-specific genes were amplified for identification purposes using triple nucleic acid detection kits (Shenzhen Shengke Yuan Biotechnology Co., Ltd., Shenzhen, China) for N. meningitidis genogroups A, B, C and X, Y, W. Genogroups E and Z were detected using the standard PCR method [21, 22]. Isolates that tested negative for all eight genogroups were defined as nongenogroupable (NG).

Molecular typing

The genomic sequences of N. meningitidis isolates were submitted to the PubMLST database (https://pubmlst.org/neisseria/). The allelic profiles of the MLST housekeeping genes were compared with the known sequences in the database to determine the sequence type (ST) and clonal complex (CC) of the isolates. The nucleotide sequences of the variable regions of the PorA outer membrane protein gene (porA VR1/VR2) and the iron uptake regulatory protein gene (fetA VR) were extracted and compared with the reference variants in the database to determine the antigenic subtypes. Newly identified MLST alleles, STs, and antigenic variants (porA or fetA) were registered and named through the standardized naming process of the international Neisseria MLST database (https://pubmlst.org/schemes/).

Detection of virulence and resistance genes

Virulence genes were identified from the assembled contigs (FASTA) using Abricate v1.0.1 with the Virulence Factor Database (VFDB, release 2025-01-14; http://www.mgc.ac.cn/VFs/). Hits were retained when nucleotide identity ≥ 80% and query coverage ≥ 70% (--minid 80 --mincov 70).

Antimicrobial-resistance genes were detected with the Resistance Gene Identifier (RGI v6.0.0) against the Comprehensive Antibiotic Resistance Database (CARD v3.2.5; https://card.mcmaster.ca/). Contigs were analysed in local mode with the following key parameters: --include_nudge (Loose hits ≥ 95% identity upgraded to Strict), --clean, --split_prodigal_jobs, and 8 threads. Only Perfect and Strict matches were retained for downstream comparisons across the 240 N. meningitidis isolates.

Phylogenetic analysis

Genomes were annotated with Prokka v1.14.6 to predict ORFs and their putative functions. The resulting.gff files were supplied to Roary v3.13.0 to construct the core-genome alignment (core_gene_alignment.aln). To obtain high-quality cgSNPs, the alignment was subsequently processed with snp-sites v2.5.1 to extract variable nucleotide positions. Recombinant regions were removed with Gubbins v3.2.1, leaving 38,742 high-confidence cgSNPs. A maximum-likelihood phylogeny was inferred from the cleaned cgSNP matrix with FastTree v2.1.11 under the GTR + Γ model; branch lengths represent the number of substitutions per variable site, without molecular-clock calibration. The tree was visualised in iTOL v7.1, where a scale bar corresponding to 0.001 substitutions per site was added for visual reference only and does not imply absolute time.

Results

Basic information of N. meningitidis isolates in healthy individuals

A total of 240 N. meningitis isolates were obtained between 2021 and 2024, with the highest proportion collected in 2022 (141 isolates, 59%). The age distribution of carriers revealed that the 6–10-year group (86 isolates, 36%) constituted the largest proportion, whereas the 0–5-year group (2 isolates, 0.8%) accounted for the lowest. Among the carriers, 139 (58%) were male and 101 (42%) were female (Table 1).

Genogroup distribution of N. meningitidis in healthy individuals

Genogrouping of 240 N. meningitis isolates showed that MenB dominated (156 isolates, 65%), followed by NG; (55 isolates, 23%), MenW (12 isolates, 5%), MenC (8 isolates, 3%), MenY (6 isolates, 3%), MenX (2 isolates, 0.8%) and MenE (1 strain, 0.4%). In the 11–20 years old age group, MenB accounted for 50%(26/52) and MenW for 19% (10/52). MenC was mainly concentrated in the 6-10 years old age group, accounting for 50% (4/8). The predominant genogroup for both males and females was MenB, accounting for 68% and 61%, respectively (Table 1).

MLST results

The 156 MenB isolates resolved into 62 sequence types (STs). ST-18,628* (CC4821) predominated, accounting for 12 isolates(8%), followed by ST-7962(10 isolates, 6%), ST-5542, ST-5664 (CC4821)(8 isolates each, 5%) (Table 2).

Table 2.

Distribution of sequence types and clonal complexes by genogroup among N. meningitis isolates from healthy individuals in Meigu County, Sichuan Province, China, 2021–2024

Genogroup Isolate Count Sequence type (n)a Clonal complexes (n)b
B 156 18,628*(12)、7962(10)、5542 (8)、5664 (8)、5656 (7)、18,643* (7)、5662 (6)、18,619* (6)、18,627*(5)、18,656* (5)、18,704* (5)、5829 (3)、14,781 (3)、18,498 (3)、18,623* (3)、18,625* (3) 18,647* (3)、2146 (2)、4821 (2)、5819 (2)、9454 (2)、12,790 (2)、14,767 (2)、18,618* (2)、18,629* (2)、18,641* (2)、18,661* (2)、18,684* (2)、18,685* (2)、18,790* (2)、18,818* (2)、7、17、230、3366、5615、5751、8178、8920、12,303、18,622*、18,633*、18,634*、18,664*、18,668*、18,669*、18,671*、18,680*、18,695*、18,699*、18,702*、18,709*、18,710*、18,713*、18,714*、18,715*、18,729*、18,786*、18,788*、18,829*、18,851*、18,856* CC4821 (51)、CC175 (2)、CC198 (2)、CC32、CC364、CC5、UA (98)
NG 55 2146(10)、18,498(5)、7(4)、5819 (4)、18,643* (4)、5664(3)、5540(2)、5656(2)、5662(2)、7960 (2)、18,627*(2)、175、3200、4821、8491、8676、10,108、15,927、18,619*、18,620*、18,623*、18,628*、18,629*、18,630*、18,749*、18,832* CC198(12)、CC4821 (11)、CC5 (4)、CC175 (3)、UA (25)
W 12 8491(7)、2146、5542、5662、8676、18,815* CC4821(7)、CC198、UA (4)
C 8 18,787*(6)、5542、18,796* UA(8)
Y 6 18,630*(4)、18,629*、175 CC175(6)
X 2 7、8676 CC5, UA
E 1 18,810* UA

a *Meant new designed STs

b UA: Unassigned

The 55 NG isolates were divided into 26 STs, ST-2146(CC198) exhibited the highest proportion(10 isolates, 18%), followed by ST-18,498 (5isolates, 9%), ST-7(CC5), ST-5819, and ST-18,643*(4 isolates each, 7%) (Table 2).

The 240 N. meningitidis isolates were divided into 78 STs, of which 32 were new STs (ST-18618 to ST-18851), accounting for 41%. Among them, 29 STs (103 isolates) were assigned to six clonal complexes, namely CC4821 (69 isolates, 67%), CC198 (15 isolates, 15%), CC175 (11 isolates, 11%), CC5 (6 isolates, 6%), CC32 (1 strain, 1%), and CC364 (1 isolate, 1%). The remaining 49 STs (137 isolates) were unassigned.

A total of 67 PorA-FetA combination types were identified, with the most common gene finetype being (PorA VR1, VR2: FetA VR) P1.21-2,28:F2-9(13 isolates, 5%), followed by P1.5-1,10 -4:F5-5(11 isolates, 5%) and P1.12-1,13-2:F4-21(7 isolates, 3%) (Table 3).

Table 3.

PorA types and ST types in different clonal complexes among N. meningitis isolates from healthy individuals in Meigu County, Sichuan Province, China, 2021–2024

Clonal complexes Strain Count PorA Type Strain Count PorA Subtypes (Strain Count)a ST Type Count ST Types (Strain Count)b
CC4821 69 61 P1.21-2, 28(12)、P1.20, 23 (9)、P1.20, 14 (6)、P1.20, 23-3 (5) 21 ST-18,628(13)、ST-5664 (11)、ST-8491 (8)、ST-18,619 (7)、ST-18,627 (7)、Others (20)
CC198 15 14 P1.18, 25-19(5)、P1.18, 25-1(3)、P1.18, 25 -34 (2) 2 ST-2146(13)、ST-7960 (2)
CC175 11 11 P1.5, 2(4)、P1.5-1, 2-2 (3)、P1.19, 5 (2) 3 ST-18,630(5)、ST-18,629 (4)、ST-175 (2)
CC5 6 6 P1.20, 9(6) 1 ST-7(6)
CC32 1 1 P1.12-14, 13-20(1) 1 ST-230(1)
CC364 1 1 P1.19, 13-13(1) 1 ST-18,714(1)
UAc 137 124 P1.21-2, 28(14)、P1.12-1, 13-2 (14)、P1.5-1, 10-4 (11)、P1.22, 23 (9) 49 ST-18,643(11)、ST-5542 (10)、ST-7962 (10)、ST-5656 (9)、ST-5662 (9)、ST-18,498 (8)、ST-5819 (6)、ST-18,787 (6)、ST-18,656 (5)、ST-18,704 (5)、ST-18,623 (4)、Others (54)

a For clone groups with a PorA type count > 5, list only the top 2–4 types

b For clonal complexes with more than 5 ST types, only the top 2–4 types are listed

c UA: Unassigned

Detection of virulence and resistance genes

A total of 68 virulence genes were detected in 240 N. meningitidis isolates. The core virulence gene spectrum included (carriage rate 100%) iron uptake-related genes: mntA, mntB, mntC; DNA repair genes: recN; pilus assembly genes: pilW, pilT2, pilZ; and lipooligosaccharide synthesis genes: rfaF.

Through comparison with the CARD database (v3.2.5), the detection results of antimicrobial resistance (AMR) genes showed that three AMR genes (farA, mtrC, and mtrD) were detected, all of which were antibiotic efflux pump genes. The carriage rates of each category of resistance genes were as follows: farA gene carriage rate was 1% (3/240), mtrC gene carriage rate was 3% (7/240), and mtrD gene carriage rate was 1% (3/240). The carriage rate of isolates carrying two resistance genes (mtrC and mtrD) was 1% (3/240).

Phylogenetic analysis

The phylogenetic tree constructed based on cgSNP was shown in Fig. 1. The 240 isolates could be divided into three main lineages: The CC4821 clade highlighted in brownish-yellow in Fig. 1 contained 68 samples (14 in 2021, 38 in 2022, 5 in 2023, and 11 in 2024); the blue-green-colored lineage CC198 contained 15 samples (1 in 2021, 10 in 2022, 1 in 2023, and 4 in 2024); and the bright yellow-colored lineage CC175 contained 11 samples (4 in 2021, 5 in 2022, and 2 in 2024). From the phylogenetic tree, the kinship between isolates of different clonal complexes could be observed, that is, isolates of the same ST type showed a clustering pattern in the dendrogram.

Fig. 1.

Fig. 1

Phylogenetic tree constructed based on the core genome using the maximum likelihood method

Discussion

During a three-year study of N. meningitidis carriage among healthy individuals in Meigu County, it was found that the predominant genogroup carried by local healthy individuals was MenB. This is consistent with the carriage patterns observed in Xinjiang [23].From 2013 to 2018, the pharyngeal carriage rates of N. meningitidis among healthy individuals were 15.5% in Xinjiang, 11.86% in Jiangsu Province, 11.72% in Zhejiang Province, 8.26% in Hubei Province, 7.15% in Shaanxi Province, 6.67% in Yunnan Province, 5.42% in Beijing Municipality, and 5.12% in Hebei Province; rates in all other surveyed regions remained below 5% [13].

MLST is a sequence-based typing method that has been widely used for the molecular characterization of N. meningitidis [24, 25]. In this study, 78 sequence types (STs) were detected, among which ST-2146, ST-18,628, ST-5664, and ST-18,643 were the most common. There were 32 new STs (accounting for 41%). Zhang Y reported twenty STs, eight of which were newly assigned [26], the frequency of these novel STs aligns closely with our findings. Shevtsov A’s research shows that MLST identified ten STs, two of which were previously undescribed. Notably, 46% of the N. meningitidis isolates belonged to these novel STs [27]. Efforts to eliminate the disease are complicated by N. meningitidis-one of the most genetically versatile organisms known-which displays extraordinary diversity and constant antigenic change [28].

In NG CC198 isolates, 10 were ST-2146 type, and the other two non-ST-2146 isolates (ST-7960) differed from ST-2146 by one MLST locus, indicating that all NG CC198 isolates may originate from the same clone, which is consistent with the findings of Xu Zheng on the molecular typing of non-serogroupable N. meningitidis [29]. Various PorA types and ST types were observed among isolates carried by healthy individuals, indicating substantial genetic diversity that may have implications for transmission dynamics. Genomic comparative analysis shows that the evolution of the isolates may be influenced by their dissemination and adaptation to new ecological niches, such as capsule switching and adaptation to new ecological niches, which may promote their spread [30].

From 2021 to 2024, there were significant differences in the number of virulence-related genes among N. meningitidis isolates in Meigu County. Isolates carrying 63 virulence genes had the highest proportion(21%). Key virulence genes encoding iron ion uptake, DNA repair, pilus synthesis, and cell wall synthesis were present in all isolates. These genes are crucial for the basic physiological functions and pathogenicity of bacteria and are the foundation for the survival and dissemination of N. meningitidis in the host. To support vital metabolic pathways-ranging from DNA replication and respiratory-chain electron transport to the detoxification of oxygen, peroxide and superoxide radicals-meningococci must acquire iron. Because the host milieu is virtually devoid of free iron, the bacteria have evolved multiple uptake systems built around high-affinity outer-membrane receptors that pirate the metal directly from host iron-bearing proteins [31]. Type IV pili are a central virulence attribute of N. meningitidis. These slender, membrane-anchored filaments mediate attachment to human cells, bacterial aggregation, twitching motility, and competence [32]. In this study, the virulence gene carriage profile of N. meningitidis isolates carried by healthy individuals in Meigu County showed unique combination characteristics. This uniqueness may be closely related to the genetic background of the local hosts, specific environmental conditions, and the evolutionary history of the bacteria themselves, reflecting the adaptation of bacteria to the local ecological environment. Therefore, it is necessary to continue genomic surveillance of N. meningitidis populations and conduct more detailed studies on microevolution to prevent emerging N. meningitidis lineages from posing a serious threat to public helth.

In this study, three resistance-related genes (farA, mtrC, and mtrD) were detected. The overexpression of mtrC/mtrD is directly related to efflux pump-mediated resistance, while the farA gene may participate in resistance auxiliary mechanisms by modifying cell membrane lipid structures. The carriage rate of resistant genes in the isolates isolated from the healthy population in this region was lower than that in studies by Lingbo Wang, Tefera [33, 34]. The relatively isolated geographical location of the area, low population mobility, low medical consultation frequency, underdeveloped animal husbandry, and less antibiotic use were potential factors leading to this phenomenon.

A limitation of the present work was that phenotypic antimicrobial-susceptibility testing was not performed on the recovered isolates. Consequently, the genotype–phenotype correlation remains undetermined, and the mere detection of resistance genes does not confirm expressed resistance.This section will be expanded in future work.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

X. R. Y. designed the studies and obtained funding; H. Y. L., S. H., and L. Z. Z. performed the experiments;R. M. Y. analyzed the results; M. X.L. wrote the article; W. B. L. contributed to article revision. All authors read and approved the submitted version.

Funding information

This work was supported by the Sichuan Science and Technology Program (No. 2022ZDZX0017).

Data Availability

The genomic sequences of Neisseria meningitidis isolates were submitted to the PubMLST database (https://pubmlst.org/organisms/neisseria-spp),the ID number of each strain was shown in the attached table-"Isolate".

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Hongyu Liao and Mingxiu Li contributed equally to this work.

References

  • 1.Harrison OB, Claus H, Jiang Y, Bennett JS, Bratcher HB, Jolley KA, Maiden M (2013) Description and nomenclature of neisseria meningitidis capsule locus. Emerg Infect Dis 19:566–573. 10.3201/eid1904.111799 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Stephens DS (2009) Biology and pathogenesis of the evolutionarily successful, obligate human bacterium neisseria meningitidis. Vaccine 27:71–77. 10.1016/j.vaccine.2009.04.070 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Pardo de Santayana C, Tin Tin Htar M, Findlow J, Balmer P (2023) Epidemiology of invasive meningococcal disease worldwide from 2010–2019: a literature review. Epidemiol Infect 151:e57. 10.1017/S0950268823000328 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Li J, Wu D, Yin Z, Li Y (2019) Analysis of epidemic characteristics for meningococcal meningitis in China during 2015–2017. Chin J Prev Med 53:159–163. 10.3760/cma.j.issn.0253-9624.2019.02.007 [DOI] [PubMed] [Google Scholar]
  • 5.Shen S, Findlow J, Peyrani P (2024) Global epidemiology of meningococcal disease-causing serogroups before and after the COVID-19 pandemic: a narrative review. Infect Dis Ther 13:2489–2507. 10.1007/s40121-024-01063-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Xu J, Chen Y, Yue M, Yu J, Han F, Xu L, Shao Z (2022) Prevalence of neisseria meningitidis serogroups in invasive meningococcal disease in China, 2010–2020: a systematic review and meta-analysis. Hum Vaccin Immunother. 10.1080/21645515.2022.2071077 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Chen H, Li M, Tu S, Zhang X, Wang X, Zhang Y, Zhao C, Guo Y, Wang H (2022) Metagenomic data from cerebrospinal fluid permits tracing the origin and spread of neisseria meningitidis CC4821 in China. Commun Biol 5:839. 10.1038/s42003-022-03792-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Xu Y, Li Y, Wang S, Li M, Xu M, Ye Q (2021) Meningococcal vaccines in China. Hum Vaccines Immunother 17:2197–2204. 10.1080/21645515.2020.1857201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Gorringe AR, Pajón R (2012) Bexsero: a multicomponent vaccine for prevention of meningococcal disease. Hum Vaccin Immunother 8:174–183. 10.4161/hv.18500 [DOI] [PubMed] [Google Scholar]
  • 10.Shirley M, Dhillon S (2015) Bivalent rLP2086 vaccine (Trumenba(®)): a review in active immunization against invasive meningococcal group B disease in individuals aged 10–25 years. Biodrugs 29:353–361. 10.1007/s40259-015-0139-0 [DOI] [PubMed] [Google Scholar]
  • 11.Serra L, Presa J, Christensen H, Trotter C (2020) Carriage of neisseria meningitidis in low and middle income countries of the Americas and Asia: a review of the literature. Infect Dis Ther 9:209–240. 10.1007/s40121-020-00291-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Santos-Neto JF, Ferreira VM, Feitosa CA, Martinez-Silveira MS, Campos LC (2019) Carriage prevalence of neisseria meningitidis in the Americas in the 21st century: a systematic review. Braz J Infect Dis 23:254–267. 10.1016/j.bjid.2019.06.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Yue M, Xu J, Yu J, Shao Z (2022) Carriage prevalence of neisseria meningitidis in China, 2005–2022: a systematic review and meta-analysis. BMC Infect Dis 22:594. 10.1186/s12879-022-07586-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Liu X, Wang H, Xu L, Dai H, Che J, Xu J, Chen Y, Zhang M, Shao Z (2025) Pathogenicity of invasive and non-invasive CC4821 neisseria meningitidis. BMC Microbiol 25:476. 10.1186/s12866-025-04231-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Taha MK, Deghmane AE (2022) Evolution of resistance to antibiotics in neisseria meningitidis: any reasons for concern? J Infect Dis 225:1869–1870. 10.1093/infdis/jiac095 [DOI] [PubMed] [Google Scholar]
  • 16.Liu R, Fang M, Xia X, He Z, Dai D, Qin D, Zhan Z (2023) Surveillance of carriage and antibiotic susceptibility of neisseria meningitidis among a healthy population in Hunan province, 2008–2021. Chin J Vaccines Immuniz 9:326–331 [Google Scholar]
  • 17.Chen M, Shao Y, Luo J, Yuan L, Wang M, Guo Q (2023) Penicillin and cefotaxime resistance of Quinolone-Resistant neisseria meningitidis clonal complex 4821, Shanghai, China, 1965–2020. Emerg Infect Dis 29:341–350. 10.3201/eid2902.221066 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Willerton L, Lucidarme J, Walker A, Lekshmi A, Clark S A,Walsh L, Bai X, Lee-Jones L, Borrow R (2021) Antibiotic resistance among invasive neisseria meningitidi isolates in England, Wales and Northern Ireland (2010/11 to 2018/19). PLoS One 16:e0260677. 10.1371/journal.pone.0260677 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Darby EM, Trampari E, Siasat P, Gaya MS, Alav I, Webber MA, Blair JMA (2024) Molecular mechanisms of antibiotic resistance revisited. Nat Rev Microbiol 21:280–295. 10.1038/s41579-022-00820-y [DOI] [PubMed] [Google Scholar]
  • 20.Liao H, Tu M, Yang X, Li W, Fang Y (2022) Investigation of neisseria meningitidis carriage among close contacts of two cases of serogroup B meningococcal disease in Meigu County in 2021. J Prev Med Inform 38:1154–1157 [Google Scholar]
  • 21.National Health Commission of the People’s Republic of China (2019) Diagnosis for meningococcal meningitis: WS295-2019[S]. People’s Medical Publishing House, Beijing [Google Scholar]
  • 22.World Health Organization, Centers for Disease Control and Prevention(U.S.) (2019) Laboratory methods for the diagnosis of meningitis caused by neisseria meningitidis, streptococcus pneumoniae, and haemophilus influenzae: WHO manual, 2nd ed. World Health Organization [Google Scholar]
  • 23.Nazaerbieke H, Fu WH, Lan ZG et al (2024) Epidemiological characteristics of meningococcal meningitis and neisseria meningitidis carriage in healthy population in Southern Xinjiang 2011 to 2022. Dis Surveill 39(7):841–845. 10.3784/jbjc.202310300574 [Google Scholar]
  • 24.Nykrynova M, Barton V, Bezdicek M, Lengerova M, Skutkova H (2022) Identification of highly variable sequence fragments in unmapped reads for rapid bacterial genotyping. BMC Genomics 23:445. 10.1186/s12864-022-08550-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Takahashi H, Morita M, Kamiya H, Fukusumi M, Sunagawa M, Nakamura-Miwa H, Akeda Y, Shimuta K, Ohnishi M (2023) Genomic characterization of Japanese meningococcal strains isolated over a 17-year period between 2003 and 2020 in Japan. Vaccine 41:416–426. 10.1016/j.vaccine.2022.10.083 [DOI] [PubMed] [Google Scholar]
  • 26.Zhang Y, Deng X, Jiang Y, Zhang J, Zhan L, Mei L, Lu H, Yao P, He H (2022) The epidemiology of meningococcal disease and carriage, genotypic characteristics and antibiotic resistance of neisseria meningitidis isolates in Zhejiang Province, China, 2011–2021. Front Microbiol 12:801196. 10.3389/fmicb.2021.801196 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Shevtsov A, Aushakhmetova Z, Amirgazin A, Khegay O, Kamalova D, Sanakulova B et al (2022) Whole genome sequence analysis of neisseria meningitidis strainsisolates Circulating in Kazakhstan, 2017–2018. PLoS ONE 17:e0279536. 10.1371/journal.pone.0279536 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Caugant DA, Brynildsrud OB (2020) Neisseria meningitidis: using genomics to understand diversity, evolution and pathogenesis. Nat Rev Microbiol 18:84–96. 10.1038/s41579-019-0282-6 [DOI] [PubMed] [Google Scholar]
  • 29.Xu Z, Zhu BQ, Gao Y, Xu L, Shao ZJ (2014) Molecular typing of non sero-groupable neisseria meningitidis in China. Disease Surveillance 29:688–692. 10.3784/j.issn.1003-9961.2014.09.005 [Google Scholar]
  • 30.Zhao P, Zhu B, Zhang A, Xu L, Gao Y, Yu J, Shao Z (2020) Distribution characteristics of capsule locus of neisseria meningitidis clonal complex 4821 in China. Disease Surveillance 35:508–512. 10.3784/j.issn.1003-9961.2020.06.011 [Google Scholar]
  • 31.Schoen C, Kischkies L, Elias J, Ampattu BJ (2014) Metabolism and virulence in neisseria meningitidis. Front Cell Infect Microbiol 4:114. 10.3389/fcimb.2014.00114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Engman J, Negrea A, Sigurlásdóttir S, Geörg M, Eriksson J, Eriksson OS, Kuwae A, Sjölinder H, Jonsson A (2016) Neisseria meningitidis polynucleotide phosphorylase affects aggregation, adhesion, and virulence. Infect Immun. 10.1128/iai.01463-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Wang L, Deng X, Zhang Y, Yang Z, Wu Z, Yao W, Yao P, He H, Wu B (2025) Prevalence, genomic features, and antibiotic sensitivities of isolates from patients with invasive meningococcal disease and healthy carriers in Zhejiang Province, 2015–2023. Diagn Microbiol Infect Dis 113:116843. 10.1016/j.diagmicrobio.2025.116843 [DOI] [PubMed] [Google Scholar]
  • 34.Tefera Z, Mekonnen F, Tiruneh M, Belachew T (2020) Carriage rate of neisseria meningitidis, antibiotic susceptibility pattern and associated risk factors among primary school children in Gondar town, Northwest Ethiopia. BMC Infect Dis 20:358. 10.1186/s12879-020-05080-w [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data Availability Statement

The genomic sequences of Neisseria meningitidis isolates were submitted to the PubMLST database (https://pubmlst.org/organisms/neisseria-spp),the ID number of each strain was shown in the attached table-"Isolate".


Articles from European Journal of Clinical Microbiology & Infectious Diseases are provided here courtesy of Springer

RESOURCES