Biology subjects

Maiden, M. C. J.

Publications and source records attributed to Maiden, M. C. J..

13 recordsLinked to original sources

bioRxiv2026

A stable, hierarchical LIN code system for Campylobacter jejuni and Campylobacter coli: A unified genomic nomenclature for lineage-level typing and global surveillance.

Campylobacter remains the leading cause of bacterial gastroenteritis worldwide, with C. jejuni accounting for around 90% of infection and C. coli accounting for most of the rest. Seven-locus multilocus sequence typing (MLST) has improved our understanding of host association and population structure, whilst core genome MLST (cgMLST), enables investigation of transmission events at high-resolution. However, the lack of a stable and standardised nomenclature for clustering of cgMLST data has limited reproducibility and long-term comparability between studies. Here we introduce a joint, hierarchical Life Identification Number (LIN) code system that provides reproducible, multi-level genomic identifiers for C. jejuni and C. coli lineages. Using an updated cgMLST v2 scheme (1,142 loci) and globally representative datasets of high-quality genomes selected from over 53,000 assemblies in the Campylobacter PubMLST database (https://pubmlst.org/organisms/campylobacter-jejunicoli), we firstly defined LIN codes on a dataset of 5,664 genomes. Pairwise allelic distances were computed using MSTclust, and 18 nested thresholds were defined through silhouette, adjusted Wallace and adjusted Rand Index (ARI) statistics to capture the population structure from species to outbreak level resolution. The LIN thresholds were then validated using a second dataset of 1,781 genomes from PubMLST and applied to a large water-associated outbreak dataset from New Zealand in 2016, containing clinical and ecological genomes. Further application of LIN codes was demonstrated by analyses of the C. jejuni ST-21 clonal complex and ST-6175 isolates, as well as the broader population structure of C. coli, using data from PubMLST. Across all datasets, LIN clusters were stable, largely monophyletic, and back-compatible with existing nomenclature, accurately distinguishing host-adapted and outbreak-associated lineages. By embedding cgMLST data within a stable and scalable nomenclature, the Campylobacter LIN system delivers consistent, automated genome-to-lineage assignment. This unified framework bridges population genetics and applied surveillance, enabling robust, real-time comparison of Campylobacter isolates across sources, studies, and time. Impact statementHuman cases of Campylobacter worldwide continue unabated. Tracing the source of Campylobacter infection is particularly challenging given the sporadic or multi-source nature of outbreaks, with potential transmission from foodborne, animal or environmental sources. Seven-locus MLST has greatly improved our broad understanding of Campylobacter population structure. However, whilst high-resolution cgMLST alleles and STs themselves do not change, longitudinal cluster analyses of cgMLST data have lacked a stable nomenclature, rendering them unsuitable for robust and comparable surveillance over time. Life Identification Number (LIN) codes provide a solution to this problem, establishing an automated and scalable nomenclature derived directly from cgMLST profiles, that is stable over time. We have implemented a joint C. jejuni and C. coli LIN code scheme in PubMLST, with scripts for real-time lineage assignment. LIN codes are back-compatible with existing MLST nomenclature, and we demonstrate their added practical value for exploring population structure and high-resolution outbreak investigation. LIN codes support surveillance of Campylobacter in a One Health context, by enabling consistent typing at multiple levels across different sources, laboratories and time. Data summary1. The isolate collections used to develop the LIN codes are publicly available and searchable as individual projects on the PubMLST database (https://pubmlst.org). O_LILIN code development (Dataset 1) (n=5,664 isolates, up to 200 isolates per clonal complex) C_LIO_LILIN code validation (Dataset 2) (n=1,781 isolates), up to 50 isolates per clonal complex C_LIO_LIOutbreak investigation (Dataset 3): New Zealand 2016 Havelock North waterborne outbreak, Gilpin et al (n=161 isolates) [1] C_LIO_LIPopulation structure exploration (clonal complex) (Dataset 4): ST-21 complex (n=1800 isolates, up to 100 isolates randomly selected from each country) C_LIO_LIPopulation structure exploration (sequence type) (Dataset 5): ST-6175 (n=321 isolates, genomes with good cgMLST v2 annotation) C_LI 2. The software for LIN code development is publicly available as follows: O_LIMSTclust for pairwise distance matrices https://gitlab.pasteur.fr/GIPhy/MSTclust [2] C_LIO_LIPython script to define LIN codes in a local dataset; (https://gitlab.pasteur.fr/BEBP/LINcoding) C_LIO_LIBIGSdb Perl script to define LIN codes from cgMLST profiles on the PubMLST database; (https://github.com/kjolley/BIGSdb/blob/develop/scripts/maintenance/lincodes.pl) C_LI

microbiology↗

bioRxiv2025

Understanding the population structure of Moraxella catarrhalis using core genome multilocus sequence typing (cgMLST) and a life identification number (LIN) code classification system

Moraxella catarrhalis is an important cause of infectious exacerbations of chronic obstructive pulmonary disease and otitis media. Previously, seroresistant (SR) and serosensitive (SS) lineages that differed in virulence potential were described, which raised questions about their evolutionary relationship and species classification. To investigate the population structure of M. catarrhalis, we developed a core-genome multilocus sequence typing (cgMLST) scheme using 1,319 core genes, and a life identification number (LIN) barcode classification system. Whole-genome analyses of nearly 2,000 genomes confirmed two divergent SR and SS M. catarrhalis lineages with distinct evolutionary trajectories. SR genomes were more conserved, while SS genomes exhibited greater genetic variability. Virulence gene analyses revealed lineage-specific variations in ubiquitous surface proteins (UspA1 and UspA2) and lipooligosaccharide (LOS) types, and SR genomes had more diverse LOS variants. The bro {beta}-lactamase gene, and the mcb bacteriocin cluster, were more common in SR, which suggested different selective pressures and ecological adaptation. This cgMLST scheme and LIN code system provides a robust method for characterising M. catarrhalis, distinguishes between SR and SS lineages, and offers a unified framework for population structure analyses. Implemented within PubMLST, this open-access resource facilitates high-resolution genomic studies and supports the scientific community in understanding the evolutionary complexity of M. catarrhalis.

genomics↗

bioRxiv2025

Neisseria gonorrhoeae LIN codes: a Robust, Multi-Resolution Lineage Nomenclature

Investigation of the bacterial pathogen Neisseria gonorrhoeae is complicated by extensive horizontal gene transfer: a process which disrupts phylogenetic signals and impedes our understanding of population structure. The ability to consistently identify N. gonorrhoeae lineages is important for surveillance of this increasingly antimicrobial resistant organism, facilitating efficient communication regarding its epidemiology; however, conventional typing systems fail to reflect N. gonorrhoeae strain taxonomy in a reliable and stable manner. Here, a N. gonorrhoeae genomic lineage nomenclature, based on the barcoding system of Life Identification Number (LIN) codes, was developed using a refined 1430 core gene MLST (cgMLST). This hierarchical LIN code nomenclature conveys lineage information at multiple levels of resolution within one code, enabling it to provide immediate context to an isolates ancestry, and to relate to familiar, previously used typing schemes such as Ng cgMLST v1, 7-locus MLST, or NG-STAR clonal complex (CC). Clustering with LIN codes accurately reflects gonococcal diversity and population structure, providing insight into associations between genotype and phenotype for traits such as antibiotic resistance. These codes are automatically assigned and publicly accessible via the pubmlst.org/organisms/neisseria-spp database.

genomics↗

bioRxiv2025

Development of a core genome multilocus sequence typing (cgMLST) scheme and life identification number (LIN) code classification system for Staphylococcus aureus

Staphylococcus aureus infects both humans and animals, and antimicrobial resistance, including multidrug resistance, complicates treatment of S. aureus infections. Understanding S. aureus population structure and the distribution of genetic lineages is central to understanding the biology, epidemiology, and pathogenesis of this organism. This study exploited a large, publicly available dataset of nearly 27,000 S. aureus genomes to: i) develop a core genome multilocus sequence type (cgMLST) scheme; ii) stratify hierarchical clusters based on allelic similarity thresholds; and iii) define the clusters with a life identification number (LIN) code classification system. The cgMLST scheme characterised allelic variation at 1,716 core gene loci, and 13 classification thresholds were defined, which discriminated S. aureus variants across a range of genetic similarity thresholds. LIN code lineages and clonal complexes defined by seven-locus multilocus sequence typing were highly concordant, but the LIN codes permitted a wider range of genetic discrimination among S. aureus genomes. This S. aureus cgMLST scheme and LIN code system is a high-resolution, stable genotyping tool that enables detailed genomic analyses of S. aureus.

genomics↗

bioRxiv2025

The origin and evolution of the gonococcal beta-lactamase plasmid, and implications for public health

Neisseria gonorrhoeae is a leading cause of sexually transmitted infection (STI) and a priority AMR pathogen. Two narrow host range plasmids, pbla and pConj, have contributed to ending penicillin and tetracycline therapy, respectively, and undermine current prevention strategies including Doxy-PEP. Here, we investigated the origin and evolution of the beta-lactamase plasmid, pbla. We show that the interplay between pbla and pConj influences their co-occurrence and the spread of pbla in the gonococcal population. We demonstrate that pbla was acquired by the gonococcus on at least two occasions from Haemophilus ducreyi, and describe the subsequent evolutionary pathways taken by the three major pbla variants. Changes that mitigate fitness costs of pbla and the emergence of TEM beta-lactamases which confer increased resistance have contributed to the success of pbla. In particular, TEM-135, which has arisen in certain pbla variants, increases resistance to beta-lactams and only requires one amino acid change to become an extended spectrum beta-lactamase (ESBL). The evolution of pbla underscores the threat of plasmid-mediated resistance to current therapeutic and preventive strategies against gonococcal infection. Given the close relationship between pbla and pConj, widespread use of Doxy-PEP is likely to promote spread of pConj and pbla, and emergence of plasmid-mediated ESBL in the gonococcus, with dire public health consequences.

microbiology↗

bioRxiv2024

Development and Implementation of a Core Genome Multilocus Sequence Typing (cgMLST) scheme for Haemophilus influenzae

2.Haemophilus influenzae is part of the human nasopharyngeal microbiota and a pathogen causing invasive disease. The extensive genetic diversity observed in H. influenzae necessitates discriminatory analytical approaches to evaluate its population structure. This study developed a core genome MLST (cgMLST) scheme for H. influenzae using pangenome analysis tools and validated the cgMLST scheme using datasets consisting of complete reference genomes (N=14) and high-quality draft H. influenzae genomes (N=2,297). The draft genome dataset was divided into a development (N=921) and a validation dataset (N=1,376). The development dataset was used to identify potential core genes with the validation dataset used to refine the final core gene list to ensure the reliability of the proposed cgMLST scheme. Functional classifications were made for all resulting core genes. Phylogenetic analyses were performed using both allelic profiles and nucleotide sequence alignments of the core genome to test congruence, as assessed by Spearmans correlation and Ordinary Least Square linear regression tests. Preliminary analyses using the development dataset identified 1,067 core genes, which were refined to 1,037 with the validation dataset. More than 70% of core genes were predicted to encode proteins essential for metabolism or genetic information processing. Phylogenetic and statistical analyses indicated that the core genome allelic profile accurately represented phylogenetic relatedness among the isolates (R2 = 0.945). We used this cgMLST scheme to define a high-resolution population structure for H. influenzae, which enhances the genomic analysis of this clinically relevant human pathogen. 3. Impact statementDiscriminating H. influenzae variants and evaluating population structure has been challenging and largely unstandardised. To address this, we have developed a cgMLST scheme for H. influenzae. Since an accurate typing approach relies on precise reflection of the underlying population structure, we explored various methods to define the scheme. The core genes included in this scheme were predicted to encode functions in essential biological pathways, such as metabolism and genetic information processing, and could be reliably assembled from short-read sequence data. Single-linkage clustering, based on core genome allelic profiles, showed high congruence to genealogy reconstructed by Maximum-Likelihood (ML) methods from the core genome nucleotide alignment. The cgMLST scheme v1 enables rapid and accurate depiction of high-resolution H. influenzae population structure, and making this scheme accessible via the PubMLST database, ensures that microbiology reference laboratories and public health authorities worldwide can use it for genomic surveillance. 4. Data summaryThe H. influenzae cgMLST scheme is accessible via https://pubmlst.org/organisms/haemophilus-influenzae. The list of isolate IDs available publicly from pubmlst.org is provided in Supplementary File 1. The pipeline for cgMLST scheme development and validation is published at https://www.protocols.io/private/EF6DB7FE429311EEB8630A58A9FEAC02. All in-house R and Python scripts for data processing and analysis are available from https://gitfront.io/r/user-4399403/ZHt8DArALHcY/cgmlst-hinf/.

genomics↗

bioRxiv2024

Bacterial strain nomenclature in the genomic era: Life Identification Numbers using a gene-by-gene approach

Unified strain taxonomies are needed for the epidemiological surveillance of bacterial pathogens and international communication in microbiological research. Core genome multilocus sequence typing (cgMLST) holds great promise for standardized high-resolution strain genotyping. However, this approach faces challenges including classification instability and disconnection of new nomenclature from widely adopted classical MLST identifiers. This essay discusses the cgMLST-based Life Identification Number (LIN) method, recently proposed as a stable multilevel strain taxonomy system applicable to most bacterial pathogens. We describe how LIN codes are implemented and used in practice for precise strain definitions and epidemiological tracking. Glossary Multilocus sequence typing (MLST)A genotyping method applied mostly to microbial strains to study population structure and epidemiology, based on comparing the nucleotide sequences of a small number (typically seven) of housekeeping protein-coding genes. In MLST, allele numbers are assigned to each sequence variant (allele) of a given gene. The MLST genotype of a bacterial strain is defined by the combination of the allele numbers observed at the genes that are included in the genotyping scheme. A sequence type (ST) is assigned to each unique combination of alleles, called an MLST profile. MLST was invented in 1998 and became a de-facto standard taxonomy of bacterial strains, albeit at low resolution. Core genome MLSTAn extension of MLST that analyzes sequence variation across hundreds to thousands of conserved (core) genes, shared by all strains of a species, providing higher resolution typing for genomic epidemiology and evolutionary studies. cgMLST schemes typically comprise 2000 to 4000 genes, depending on the genome size and genetic variation (in terms of presence/absence of genes) within bacterial species. A core genome sequence type (cgST) can be assigned to unique cgMLST profiles, i.e., a unique combination of cgMLST allelic numbers. Whole Genome Sequencing (WGS)A method that determines the complete DNA sequence of an organisms genome in a single process, providing comprehensive information for comparative genetic analyses based on cgMLST or other analytic methods. Single Nucleotide Polymorphisms (SNPs)Variations at a single base position in the DNA sequence among individuals isolates, strains or species, used as genetic markers for studying for example, evolutionary relationships or strain identity. Average nucleotide identity (ANI)A measure of genomic similarity between two organisms, calculated as the average percentage of identical nucleotides in orthologous genomic regions; commonly used to assess species-level relatedness in prokaryotes. TaxonomyHere, we apply the word taxonomy to bacterial strains as a system of classifying, naming and identifying strains based on shared genetic characteristics as defined by e.g., cgMLST.

microbiology↗

bioRxiv2023

Development of the Pneumococcal Genome Library, a core genome multilocus sequence typing scheme, and a taxonomic life identification number barcoding system to investigate and define pneumococcal population structure

Investigating the genomic epidemiology of major bacterial pathogens is integral to understanding transmission, evolution, colonisation, disease, antimicrobial resistance, and vaccine impact. Furthermore, the recent accumulation of large numbers of whole genome sequences for many bacterial species enhances the development of robust genome-wide typing schemes to define the overall bacterial population structure and lineages within it. Using previously published data, we developed the Pneumococcal Genome Library (PGL), a curated dataset of 30,976 genomes and contextual data for carriage and disease pneumococci recovered between 1916-2018 in 82 countries. We leveraged the size and diversity of the PGL to develop a core genome multilocus sequence typing (cgMLST) scheme comprised of 1,222 loci. Finally, using multilevel single-linkage clustering, we stratified pneumococci into hierarchical clusters based on allelic similarity thresholds, and defined these with a taxonomic life identification number (LIN) barcoding system. The PGL, cgMLST scheme, and LIN barcodes represent a high-quality genomic resource and fine-scale clustering approaches for the analysis of pneumococcal populations, which support the genomic epidemiology and surveillance of this leading global pathogen. Impact statementMany thousands of pneumococcal genomes are available in the public domain, and this creates opportunities for the scientific community to re-use existing data; however, these data are most useful when the contextual data (provenance and phenotype) are also linked to the genomes. Therefore, we created a curated, open-access database in PubMLST that contained nearly 31,000 published pneumococcal genomes and the corresponding contextual data for each genome. This large and diverse pneumococcal database was used to create a novel cgMLST scheme and multilevel clustering method to define genetic lineages with high resolution and a standardised nomenclature. These are open-access resources for all to use and provide a unified framework for the characterisation of global pneumococcal populations.

genomics↗

bioRxiv2021

A dual barcoding approach to bacterial strain nomenclature: Genomic taxonomy of Klebsiella pneumoniae strains

Sublineages within microbial species can differ widely in their ecology and pathogenicity, and their precise definition is important in basic research and industrial or public health applications. Whereas the classification and naming of prokaryotes is unified at the species level and higher taxonomic ranks, universally accepted definitions of sublineages within species are largely missing, which introduces confusion in population biology and epidemiological surveillance. Here we propose a broadly applicable genomic classification and nomenclature approach for bacterial strains, using the prominent public health threat Klebsiella pneumoniae as a model. Based on a 629-gene core genome multilocus sequence typing (cgMLST) scheme, we devised a dual barcoding system that combines multilevel single linkage (MLSL) clustering and life identification numbers (LIN). Phylogenetic and clustering analyses of >7,000 genome sequences captured population structure discontinuities, which were used to guide the definition of 10 infra-specific genetic dissimilarity thresholds. The widely used 7-gene multilocus sequence typing (MLST) nomenclature was mapped onto MLSL sublineages (threshold: 190 allelic mismatches) and clonal group (threshold: 43) identifiers for backwards nomenclature compatibility. The taxonomy is publicly accessible through a community-curated platform (https://bigsdb.pasteur.fr/klebsiella), which also enables external users genomic sequences identification. The proposed strain taxonomy combines two phylogenetically informative barcodes systems that provide full stability (LIN codes) and nomenclatural continuity with previous nomenclature (MLSL). This species-specific dual barcoding strategy for the genomic taxonomy of microbial strains is broadly applicable and should contribute to unify global and cross-sector collaborative knowledge on the emergence and microevolution of bacterial pathogens.

microbiology↗

bioRxiv2020

Emergence and evolution of antimicrobial resistance genes and mutations in Neisseria gonorrhoeae

Antimicrobial resistance in Neisseria gonorrhoeae is a global health concern. Strains from two internationally circulating sequence types, ST-7363 and ST-1901, have acquired resistance to treatment with third-generation cephalosporins mainly due to the emergence of mosaic penA alleles. These two STs were first detected in Japan; however, when and how the mosaic penA alleles emerged and spread to other countries remains unknown. Here, we addressed the evolution of penA alleles by obtaining complete genomes from three Japanese ST-1901 clinical isolates harboring mosaic penA allele 34 (penA-34) dating from 2005 and generating a phylogenetic representation of 1,075 strains sampled from 37 countries. We also sequenced the genomes of 103 Japanese ST-7363 N. gonorrhoeae isolates from 1996-2005 and reconstructed a phylogeny including 88 previously sequenced genomes. Based on an estimate of the time of emergence of ST-1901 harboring mosaic penA-34 and ST-7363 harboring mosaic penA-10, and >300 additional genome sequences of Japanese strains representing multiple STs isolated in 1996-2015, we suggest that penA-34 in ST-1901 was generated from penA-10 via recombination with another Neisseria species, followed by a second recombination event with a gonococcal strain harboring wildtype penA-1. Following the acquisition of penA-10 in ST-7363, a dominant sub-lineage rapidly acquired fluoroquinolone resistance mutations at GyrA 95 and ParC 87-88, possibly due to independent mutations rather than horizontal gene transfer. Literature data suggest the emergence of these resistance determinants may reflect selection from the standard treatment regimens in Japan at that time. Our findings highlight how recombination and antibiotic use across and within Neisseria species intersect in driving the emergence and spread of drug-resistant gonorrhea. Author summaryAntimicrobial resistance is recognized as one of the greatest threats to human health, and Neisseria gonorrhoeae resistance is classified as one of the most urgent. The two major internationally spreading lineages resistant. to first line drugs likely originated in Japan, but when and how their genetic resistance determinants emerged remain unknown. In this study, we conducted an evolutionary analysis using clinical N. gonorrhoeae isolates from 37 countries, including a historical collection of Japanese isolates, to investigate the emergence of resistance in each of the two major lineages. We showed that the penA allele responsible for resistance to cephalosporins, the first-line treatment for gonorrhea, was possibly generated by two recombination events, one from another Neisseria species and one from another N. gonorrhoeae lineage. We also showed that mutations responsible for resistance to a previously widely used antibiotic treatment occurred twice independently in one of the two major lineages. The emergence of the genetic resistance determinants potentially reflects selection from the standard treatment regimen at that time. Our findings highlight how recombination (horizontal gene transfer) and antibiotic use across and within a bacterial species intersect in driving the emergence and spread of antimicrobial resistance genes and mutations.

microbiology↗

bioRxiv2020

Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR) Index: a Rapid and Accessible Tool that Exploits Genomic Data in Public Health and Clinical Microbiology Applications

As microbial genomics makes increasingly important contributions to clinical and public health microbiology, the interpretation of whole genome sequence data by non-specialists becomes essential. In the absence of capsule-based vaccines, two protein-based vaccines have been used for the prevention of invasive serogroup B meningococcal disease (IMD), since their licensure in 2013/14. These vaccines have different components and different coverage of meningococcal variants. Hence, decisions regarding which vaccine to use in managing serogroup B IMD outbreaks require information about the index case isolate including: (i) the presence of particular vaccine antigen variants; (ii) the expression of vaccine antigens; and (iii) the likely susceptibility of its antigen variants to antibody-dependent bactericidal killing. To obtain this information requires a multitude of laboratory assays, impractical in real-time clinical settings, where the information is most urgently needed. To facilitate assessment for public health and clinical purposes, we synthesised genomic and experimental data from published sources to develop and implement the Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR) Index, which is publicly-available on PubMLST (https://pubmlst.org). Using whole genome sequences or individual gene sequences obtained from IMD isolates or clinical specimens, MenDeVAR provides rapid evidence-based information on the presence and possible immunological cross-reactivity of different meningococcal vaccine antigen variants. The MenDeVAR Index enables practitioners who are not genomics specialists to assess the likely reactivity of vaccines for individual cases, outbreak management, or the assessment of public health vaccine programmes. MenDeVAR has been developed in consultation with, but independently of, both vaccine manufacturers.

genomics↗

bioRxiv2018

Characterisation of carried and invasive Neisseria meningitidis isolates in Shanghai, China from 1950 to 2016: implications for serogroup B vaccine implementation

BackgroundSerogroup B invasive meningococcal disease (IMD) is increasing in China, little is known however, about these meningococci. This study characterises a collection of isolates associated with IMD and carriage in Shanghai and assesses current vaccine strategies.\n\nMethodsIMD epidemiological data in Shanghai from 1950-2016 were obtained from the National Notifiable Diseases Registry System, with 460 isolates collected for analysis including, 169 from IMD and 291 from carriage. Serogroup B meningococcal (MenB) vaccine coverage was evaluated using Bexsero(R) Antigen Sequence Type (BAST).\n\nResultsSeven IMD epidemic periods have been observed in Shanghai since 1950, with incidence peaking from February to April. Analyses were divided according to the period of meningococcal polysaccharide vaccine (MPV) introduction: (i) pre-MPV-A, 1965-1980; (ii) post-MPV-A, 1981-2008; and (iii) post-MPV-A+C, 2009-2016. IMD incidence decreased from 55.4/100,000 to 0.71 then to 0.02, and corresponded with shifts from serogroup A ST-5 complex (MenA:cc5) to MenC:cc4821 then MenB:cc4821. MenB IMD became predominant (63.2%) in the post-MPV-A+C period, of which 50% were caused by cc4821, with the highest incidence in infants (0.45/100,000) and a case-fatality rate of 9.5%. IMD was positively correlated with carriage rates. Data indicate that fewer than 25% of MenB isolates in the post-MPV-A+C period may be covered by the vaccines Bexsero(R), Trumenba(R), or a PorA-based vaccine, NonaMen.\n\nConclusionsA unique IMD epidemiology is found in China, changing periodically from hyperepidemic to low-level endemic disease. MenB IMD now dominates in Shanghai, with isolates harbouring diverse antigenic variants potentially beyond coverage with licenced OMV- and protein-based MenB vaccines.\n\nSummaryMeningococcal disease in Shanghai, China is described and current vaccine approaches evaluated. Since 1950, MenA:cc5 shifted to MenC:cc4821 then MenB:cc4821, with MenB dominating since 2009. Distinct antigens potentially beyond coverage with licensed OMV- and protein-based MenB vaccines were found.

epidemiology↗

bioRxiv2017

Heterogeneity Among Estimates Of The Core Genome And Pan-Genome In Different Pneumococcal Populations

BackgroundUnderstanding the structure of a bacterial population is essential in order to understand bacterial evolution, or which genetic lineages cause disease, or the consequences of perturbations to the bacterial population. Estimating the core genome, the genes common to all or nearly all strains of a species, is an essential component of such analyses. The size and composition of the core genome varies by dataset, but our hypothesis was that variation between different collections of the same bacterial species should be minimal. To test this, the genome sequences of 3,121 pneumococci recovered from healthy individuals in Reykjavik (Iceland), Southampton (United Kingdom), Boston (USA) and Maela (Thailand) were analysed.\n\nResultsThe analyses revealed a supercore genome (genes shared by all 3,121 pneumococci) of only 303 genes, although 461 additional core genes were shared by pneumococci from Reykjavik, Southampton and Boston. Overall, the size and composition of the core genomes and pan-genomes among pneumococci recovered in Reykjavik, Southampton and Boston were very similar, but pneumococci from Maela were distinctly different. Inspection of the pan-genome of Maela pneumococci revealed several >25 Kb sequence regions that were homologous to genomic regions found in other bacterial species.\n\nConclusionsSome subsets of the global pneumococcal population are highly heterogeneous and thus our hypothesis was rejected. This is an essential point of consideration before generalising the findings from a single dataset to the wider pneumococcal population.

genomics↗