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Objectives: The genomic epidemiology of group b streptococcal (GBS) isolates from the Rotunda maternity hospital, Dublin, 2008-2017, was investigated.Methods: Whole genome sequences of isolates (invasive, n = 114; non-invasive, n = 76) from infants and women were analysed using the PubMLST database (https://pubmlst.org/sagalactiae/).Results: Serotypes III (36%), Ia (18%), V (17%), II (11%) and Ib, (9%) and sequence types (ST) 17 (23%), ST-23 (14%), ST-1 (12%) and ST-19 (7%) were most common. Core genome MLST (cgMLST) differentiated isolates of the same ST, grouped STs into five lineages congruent with known clonal complexes and identified known mother-baby pairs and suspected linked infant cases. Clonal complex (CC) 17 accounted for 40% and 22% of infant and maternal invasive cases, respectively and 21% of non-invasive isolates. CC23 and CC19 were associated with maternal disease (30%) and carriage (24%), respectively. Erythromycin (26%) and clindamycin (18%) resistance increased over the study period and was associated with presence of the erm(B) gene (55%), CC1 (33%) and CC19 (24%). A multi-resistant integrative conjugative element incorporated in the PI-1 locus was detected in CC17, an ST-12 and ST-23 isolate confirming the global dissemination of this element. All isolates possessed one or more pilus islands. Genes encoding other potential protective proteins including Sip, C5a peptidase and Srr1 were present in 100%, 99.5% and 65.8% of isolates, respectively. The srr2 gene was unique to CC17.Conclusions: The PubMLST.org website provides a valuable framework for genomic GBS surveillance to inform on local and global GBS epidemiology, preventive and control measures. [ABSTRACT FROM AUTHOR]

Abstract Background The opportunities for bacterial population genomics that are being realised by the application of parallel nucleotide sequencing require novel bioinformatics platforms. These must be capable of the storage, retrieval, and analysis of linked phenotypic and genotypic information in an accessible, scalable and computationally efficient manner. Results The Bacterial Isolate Genome Sequence Database (BIGSDB) is a scalable, open source, web-accessible database system that meets these needs, enabling phenotype and sequence data, which can range from a single sequence read to whole genome data, to be efficiently linked for a limitless number of bacterial specimens. The system builds on the widely used mlstdbNet software, developed for the storage and distribution of multilocus sequence typing (MLST) data, and incorporates the capacity to define and identify any number of loci and genetic variants at those loci within the stored nucleotide sequences. These loci can be further organised into 'schemes' for isolate characterisation or for evolutionary or functional analyses. Isolates and loci can be indexed by multiple names and any number of alternative schemes can be accommodated, enabling cross-referencing of different studies and approaches. LIMS functionality of the software enables linkage to and organisation of laboratory samples. The data are easily linked to external databases and fine-grained authentication of access permits multiple users to participate in community annotation by setting up or contributing to different schemes within the database. Some of the applications of BIGSDB are illustrated with the genera Neisseria and Streptococcus. The BIGSDB source code and documentation are available at http://pubmlst.org/software/database/bigsdb/. Conclusions Genomic data can be used to characterise bacterial isolates in many different ways but it can also be efficiently exploited for evolutionary or functional studies. BIGSDB represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach.

Abstract Background The genus Neisseria contains two important yet very different pathogens, N. meningitidis and N. gonorrhoeae, in addition to non-pathogenic species, of which N. lactamica is the best characterized. Genomic comparisons of these three bacteria will provide insights into the mechanisms and evolution of pathogenesis in this group of organisms, which are applicable to understanding these processes more generally. Results Non-pathogenic N. lactamica exhibits very similar population structure and levels of diversity to the meningococcus, whilst gonococci are essentially recent descendents of a single clone. All three species share a common core gene set estimated to comprise around 1190 CDSs, corresponding to about 60% of the genome. However, some of the nucleotide sequence diversity within this core genome is particular to each group, indicating that cross-species recombination is rare in this shared core gene set. Other than the meningococcal cps region, which encodes the polysaccharide capsule, relatively few members of the large accessory gene pool are exclusive to one species group, and cross-species recombination within this accessory genome is frequent. Conclusion The three Neisseria species groups represent coherent biological and genetic groupings which appear to be maintained by low rates of inter-species horizontal genetic exchange within the core genome. There is extensive evidence for exchange among positively selected genes and the accessory genome and some evidence of hitch-hiking of housekeeping genes with other loci. It is not possible to define a 'pathogenome' for this group of organisms and the disease causing phenotypes are therefore likely to be complex, polygenic, and different among the various disease-associated phenotypes observed.

Abstract Background Transferrin binding protein B (tbpB), an outer membrane lipoprotein, is required for the acquisition of iron from human transferrin. Two tbpB families have been documented in Neisseria meningitidis: an isotype I tbpB gene of 1.8 kb and an isotype II tbpB gene of 2.1 kb, the former expressed by meningococci in the disease-associated ST-11 clonal complex and the latter found among meningococci belonging to the hyper-invasive clonal complexes including ST-8, ST-18, ST-32, ST-41/44 as well as N. gonorrhoeae isolates. The origin of the isotype I tbpB gene is unknown, however several features in common with non-pathogenic Neisseria and the ST-11 clonal complex N. meningitidis isolate FAM18 have been documented leading to the hypothesis that the isotype I tbpB gene may also be shared between non-pathogenic Neisseria and ST-11 meningococci. As a result, the diversity of the tbpB gene was investigated in a defined collection of Neisseria species. Results Two families of isotype I tbpB were identified: family A containing conserved genes belonging to ST-11 meningococci, N. polysaccharea and N. lactamica isolates and family B including more diverse isotype I tbpB genes from N. sicca, N. mucosa, N. flava, N. subflava as well as N. cinerea, N. flavescens and N. polysaccharea isolates. Three isotype II tbpB families were identified with: family C containing diverse tbpB genes belonging to N. polysaccharea, N. lactamica, N. gonorrhoeae and N. meningitidis isolates, family D including another subset of isotype II tbpB genes from N. lactamica isolates and family E solely composed of N. gonorrhoeae tbpB genes. Conclusion This study reveals another instance of similarity between meningococci of the ST-11 clonal complex and non-pathogenic Neisseria with the origin of the isotype I tbpB gene resulting from a horizontal genetic transfer event occurring between these two populations.

Abstract Background Various typing methods have been developed for Neisseria gonorrhoeae, but none provide the combination of discrimination, reproducibility, portability, and genetic inference that allows the analysis of all aspects of the epidemiology of this pathogen from a single data set. Multilocus sequence typing (MLST) has been used successfully to characterize the related organisms Neisseria meningitidis and Neisseria lactamica. Here, the same seven locus Neisseria scheme was used to characterize a diverse collection of N. gonorrhoeae isolates to investigate whether this method would allow differentiation among isolates, and to distinguish these three species. Results A total of 149 gonococcal isolates were typed and submitted to the Neisseria MLST database. Although relatively few (27) polymorphisms were detected among the seven MLST loci, a total of 66 unique allele combinations (sequence types, STs), were observed, a number comparable to that seen among isolate collections of the more diverse meningococcus. Patterns of genetic variation were consistent with high levels of recombination generating this diversity. There was no evidence for geographical structuring among the isolates examined, with isolates collected in Liverpool, UK, showing levels of diversity similar to a global collection of isolates. There was, however, evidence that populations of N. meningitidis, N. gonorrhoeae and N. lactamica were distinct, with little support for frequent genetic recombination among these species, with the sequences from the gdh locus alone grouping the species into distinct clusters. Conclusion The seven loci Neisseria MLST scheme was readily adapted to N. gonorrhoeae isolates, providing a highly discriminatory typing method. In addition, these data permitted phylogenetic and population genetic inferences to be made, including direct comparisons with N. meningitidis and N. lactamica. Examination of these data demonstrated that alleles were rarely shared among the three species. Analysis of variation at a single locus, gdh, provided a rapid means of identifying misclassified isolates and determining whether mixed cultures were present.

Abstract Background Bacterial typing schemes based on the sequences of genes encoding surface antigens require databases that provide a uniform, curated, and widely accepted nomenclature of the variants identified. Due to the differences in typing schemes, imposed by the diversity of genes targeted, creating these databases has typically required the writing of one-off code to link the database to a web interface. Here we describe agdbNet, widely applicable web database software that facilitates simultaneous BLAST querying of multiple loci using either nucleotide or peptide sequences. Results Databases are described by XML files that are parsed by a Perl CGI script. Each database can have any number of loci, which may be defined by nucleotide and/or peptide sequences. The software is currently in use on at least five public databases for the typing of Neisseria meningitidis, Campylobacter jejuni and Streptococcus equi and can be set up to query internal isolate tables or suitably-configured external isolate databases, such as those used for multilocus sequence typing. The style of the resulting website can be fully configured by modifying stylesheets and through the use of customised header and footer files that surround the output of the script. Conclusion The software provides a rapid means of setting up customised Internet antigen sequence databases. The flexible configuration options enable typing schemes with differing requirements to be accommodated.

Abstract Background DNA adenine methyltransferase (Dam) activity is absent in many, but not all, disease isolates of Neisseria meningitidis, as a consequence of the insertion of a restriction endonuclease-encoding gene, the 'dam replacing gene' (drg) at the dam locus. Here, we report the results of a survey to assess the prevalence of drg in a globally representative panel of disease-associated meningococci. Results Of the known meningococcal hyper-invasive lineages investigated, drg was absent in all representatives of the ST-8 and ST-11 clonal complexes tested, but uniformly present in the representatives of the other hyper-invasive lineages present in the isolate collection (the ST-1, ST-4, ST-5, ST-32 and ST-41/44 clonal complexes). The patterns of sequence diversity observed in drg were consistent with acquisition of this gene from a source organism with a different G+C content, at some time prior to the emergence of present-day meningococcal clonal complexes, followed by spread through the meningococcal population by horizontal genetic exchange. During this spread a number of alleles have arisen by mutation and intragenic recombination. Conclusion These findings are consistent with the idea that possession of the drg gene may contribute to the divergence observed among meningococcal clonal complexes, but does not have a direct mechanistic involvement in virulence.

Abstract Background Multi-locus sequence typing (MLST) is a method of typing that facilitates the discrimination of microbial isolates by comparing the sequences of housekeeping gene fragments. The mlstdbNet software enables the implementation of distributed web-accessible MLST databases that can be linked widely over the Internet. Results The software enables multiple isolate databases to query a single profiles database that contains allelic profile and sequence definitions. This separation enables isolate databases to be established by individual laboratories, each customised to the needs of the particular project and with appropriate access restrictions, while maintaining the benefits of a single definitive source of profile and sequence information. Databases are described by an XML file that is parsed by a Perl CGI script. The software offers a large number of ways to query the databases and to further break down and export the results generated. Additional features can be enabled by installing third-party (freely available) tools. Conclusion Development of a distributed structure for MLST databases offers scalability and flexibility, allowing participating centres to maintain ownership of their own data, without introducing duplication and data integrity issues.

Objective: Invasive meningococcal disease (IMD) outbreaks in men who have sex with men (MSM) have been associated with meningococcal colonisation of the urethra and rectum, but little is known about this colonisation or co-colonisation with the closely related gonococcus. Whole genome sequencing (WGS) was employed to explore these phenomena.Methods: Meningococci isolated from the urogenital tract and rectum (n=23) and coincident gonococci (n=14) were analysed by WGS along with contemporary meningococci from IMD (n=11). All isolates were obtained from hospital admissions in Brighton, UK, 2011-2013. Assembled WGS were deposited in the PubMLST/neisseria database (http://pubmlst.org/neisseria) and compared at genomic loci common to gonococci or meningococci.Results: As expected, most meningococci from IMD were encapsulated and belonged to hyperinvasive lineages. So too were meningococci found in the urogenital tract and rectum, contrasting to those asymptomatically carried in the nasopharynx where such meningococci are rare. Five hyperinvasive meningococcal lineages and four distinct gonococcal genotypes were recovered, including multiresistant ST-1901 (NG MAST-1407) gonococci.Conclusions: These data were consistent with a predisposition for potentially virulent encapsulated hyperinvasive meningococci to colonise the urethra and rectum, which suggests their involvement in MSM IMD outbreaks. The coincidence of multiresistant gonococci raises wider public health concerns. [ABSTRACT FROM AUTHOR]

Understanding the processes whereby diversity arises and is maintained in pathogen populations is pivotal for designing disease control interventions. A particular problem is the maintenance of strain structure in bacterial pathogen populations despite frequent genetic exchange. Although several theoretical frameworks have been put forward to explain this widespread phenomenon, few have focused on the role of genes encoding metabolic functions, despite an increasing recognition of their importance in pathogenesis and transmission. In this article, we review the literature for evidence of metabolic niches within the host and discuss theoretical frameworks which examine ecological interactions between metabolic genes. We contend that metabolic competition is an important phenomenon which contributes to the maintenance of population structure and diversity of many bacterial pathogens. [ABSTRACT FROM AUTHOR]

Advances in high-throughput nucleotide sequencing and bioinformatics make the study of genomes at the population level feasible. Preliminary population genomic studies have explored the relationships among three closely related bacteria, Neisseria meningitidis, Neisseria gonorrhoeae and Neisseria lactamica, which exhibit very different phenotypes with respect to human colonisation. The data obtained have been especially valuable in the establishing of the role of horizontal genetic exchange in bacterial speciation and shaping population structure. In the meningococcus, they have been used to define invasive genetic types, search for virulence factors and potential vaccine components and investigate the effects of vaccines on population structure. These are generic approaches and their application to the Neisseria provides a foretaste for their application to the wider bacterial world. [Copyright &y& Elsevier]

Background: Bacterial typing schemes based on the sequences of genes encoding surface antigens require databases that provide a uniform, curated, and widely accepted nomenclature of the variants identified. Due to the differences in typing schemes, imposed by the diversity of genes targeted, creating these databases has typically required the writing of one-off code to link the database to a web interface. Here we describe agdbNet, widely applicable web database software that facilitates simultaneous BLAST querying of multiple loci using either nucleotide or peptide sequences. Results: Databases are described by XML files that are parsed by a Perl CGI script. Each database can have any number of loci, which may be defined by nucleotide and/or peptide sequences. The software is currently in use on at least five public databases for the typing of Neisseria meningitidis, Campylobacter jejuni and Streptococcus equi and can be set up to query internal isolate tables or suitably-configured external isolate databases, such as those used for multilocus sequence typing. The style of the resulting website can be fully configured by modifying stylesheets and through the use of customised header and footer files that surround the output of the script. Conclusion: The software provides a rapid means of setting up customised Internet antigen sequence databases. The flexible configuration options enable typing schemes with differing requirements to be accommodated. [ABSTRACT FROM AUTHOR]

The sexually transmitted infection (STI) gonorrhoea remains a major global public health concern. The World Health Organization (WHO) estimates that 87 million new cases in individuals who were 15 to 49 years of age occurred in 2016. The growing number of gonorrhoea cases is concerning given the rise in gonococci developing antimicrobial resistance (AMR). Therefore, a global action plan is needed to facilitate surveillance. Indeed, the WHO has made surveillance leading to the elimination of STIs (including gonorrhoea) a global health priority. The availability of whole genome sequence data offers new opportunities to combat gonorrhoea. This can be through (i) enhanced surveillance of the global prevalence of AMR, (ii) improved understanding of the population biology of the gonococcus, and (iii) opportunities to mine sequence data in the search for vaccine candidates. Here, we review the current status in Neisseria gonorrhoeae genomics. In particular, we explore how genomics continues to advance our understanding of this complex pathogen., Competing Interests: The authors declare that they have no competing interests.No competing interests were disclosed.No competing interests were disclosed., (Copyright: © 2021 Harrison OB et al.)

Background Campylobacter is a leading global cause of bacterial gastroenteritis, motivating research to identify sources of human infection. Population genetic studies have been increasingly applied to this end, mainly using multilocus sequence typing (MLST) data.ObjectivesThis review aimed to summarise approaches and findings of these studies and identify best practice lessons for this form of genomic epidemiology.MethodsWe systematically reviewed publications using MLST data to attribute human disease isolates to source. Publications were from January 2001, when this type of approach began. Searched databases included Scopus, Web of Science and PubMed. Information on samples and isolate datasets used, as well as MLST schemes and attribution algorithms employed, was obtained. Main findings were extracted, as well as any results' validation with subsequent correction for identified biases. Meta-analysis is not reported given high levels of heterogeneity.ResultsOf 2,109 studies retrieved worldwide, 25 were included, and poultry, specifically chickens, were identified as principal source of human infection. Ruminants (cattle or sheep) were consistently implicated in a substantial proportion of cases. Data sampling and analytical approaches varied, with five different attribution algorithms used. Validation such as self-attribution of isolates from known sources was reported in five publications. No publication reported adjustment for biases identified by validation.ConclusionsCommon gaps in validation and adjustment highlight opportunities to generate improved estimates in future genomic attribution studies. The consistency of chicken as the main source of human infection, across high income countries, and despite methodological variations, highlights the public health importance of this source.

Invasive meningococcal disease surveillance in Europe combines isolate characterisation and epidemiological data to support public health intervention. A representative European Meningococcal Strain Collection (EMSC) of IMD isolates was obtained, and whole genome sequenced to characterise 799 EMSC isolates from the epidemiological year July 2011-June 2012. To establish a genome library (GL), the isolate information was deposited in the pubMLST.org/neisseria database. Genomes were curated and annotated at 2,429 meningococcal loci, including those defining clonal complex, capsule, antigens, and antimicrobial resistance. Most genomes contained genes encoding B (n = 525; 65.7%) or C (n = 163; 20.4%) capsules; isolates were genetically highly diverse, with >20 genomic lineages, five of which comprising 60.7% (n = 485) of isolates. There were >350 antigenic fine-types: 307 were present once, the most frequent (P1.7-2,4:F5-1) comprised 8% (n = 64) of isolates. Each genome was characterised for Bexsero Antigen Sequence Typing (BAST): 25.5% (n = 204) of isolates contained alleles encoding the fHbp and/or the PorA VR1 vaccine component, but most genomes (n = 513; 64.2%) did not contain the NadA component. EMSC-GL will support an integrated surveillance of disease-associated genotypes in Europe, enabling the monitoring of hyperinvasive lineages, outbreak identification, and supporting vaccine programme implementation.