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

Palma, Federica; Hennart, Melanie; Jolley, Keith A.; Crestani, Chiara; Wyres, Kelly L.; Bridel, Sebastien; Yeats, Corin A.; Brancotte, Bryan; Raffestin, Brice; David, Sophia; Lam, Margaret M. C.; Izdebski, Radosław; Passet, Virginie; Rodrigues, Carla; Rethoret-Pasty, Martin; Maiden, Martin C. J.; Aanensen, David M.; Holt, Kathryn E.; Criscuolo, Alexis; Brisse, Sylvain

doi:10.1101/2024.03.11.584534

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…Therefore, in the last few years, a significant effort has been made towards the development of clusteringbased nomenclatures. For instance, for cgMLST, Enterobase and INNUENDO propose nomenclature systems based on the hierarchical clustering at different resolution levels 20,92 , and other approaches relying on Life Identification Numbers (LIN) were recently released 93,94 .…”

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confidence: 99%

Multi-country and intersectoral assessment of cluster congruence between different bioinformatics pipelines for genomics surveillance of foodborne bacterial pathogens

Mixão,

Pinto,

Brendebach

et al. 2024

Preprint

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Food and waterborne disease (FWD) surveillance requires Whole-Genome Sequencing (WGS)-based systems following a One Health approach. However, different laboratories employ different WGS pipelines in their routine surveillance activities, casting doubt on the comparability of their results and hindering optimal communication at intersectoral and international levels. Through a collaborative effort involving eleven European institutes across seven countries and spanning the food, animal and human health sectors, we aimed to assess the inter-laboratory comparability of WGS clustering results for four important foodborne pathogens: Listeria monocytogenes, Salmonella enterica, Escherichia coli and Campylobacter jejuni. Each participating institute (n=9) applied its surveillance pipeline over the same WGS datasets (>2000 isolates per species), and, for each pipeline, genetic clusters were identified at each possible allele/SNP distance threshold. Inter-pipeline clustering congruence was assessed by calculating a Congruence Score (relying on Adjusted Wallace and Adjusted Rand coefficients) across all resolution levels, followed by an in-depth comparative analysis of cluster composition at outbreak level. An additional cluster congruence assessment was performed between WGS and traditional typing, which, depending on the species, included Sequence Type (ST), Clonal Complex (CC) and/or serotype. Our results revealed a general high concordance between allele-based pipelines at all resolution levels for all species, except for C. jejuni, where the different resolution power of available allele-based schemas led to marked discrepancies. Still, this study identified non-negligible differences in allele-based pipeline performance for outbreak cluster detection, suggesting that a threshold flexibilization is important for the detection of similar outbreak signals by different laboratories. These results, together with the observation that different STs, CCs and serotypes exhibit remarkably different genetic diversity, should inform future threshold selections for outbreak case definitions. In conclusion, this study provides valuable insights into the comparability of pipelines commonly used for routine genomics surveillance, and reinforces the need, while demonstrating the feasibility, of conducting continuous and comprehensive WGS pipeline comparability assessments. Ultimately, it opens good perspectives for a smoother international and intersectoral cooperation and communication towards a sustainable and efficient One Health FWD surveillance.

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Section: (Which Was Not Certified By Peer Review)mentioning

confidence: 99%

Multi-country and intersectoral assessment of cluster congruence between different bioinformatics pipelines for genomics surveillance of foodborne bacterial pathogens

Mixão,

Pinto,

Brendebach

et al. 2024

Preprint

View full text Add to dashboard Cite

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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

Jansen van Rensburg,

Berger,

Yassine

et al. 2024

Microbial Genomics

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Investigating the genomic epidemiology of major bacterial pathogens is integral to understanding transmission, evolution, colonization, 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 the 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 and 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 1222 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.

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A genome-wide One Health study ofKlebsiella pneumoniaein Norway reveals overlapping populations but few recent transmission events across reservoirs

Hetland,

Winkler,

Kaspersen

et al. 2024

Preprint

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Members of theKlebsiella pneumoniaespecies complex (KpSC) are opportunistic pathogens that cause severe and difficult-to-treat infections. KpSC are common in non-human niches, but the clinical relevance of these populations is disputed. Utilising 3,255 whole-genome sequenced isolates from human, animal and marine sources collected during 2001-2020 in Norway, we showed the KpSC populations in different niches were distinct but overlapping. Notably, human infection isolates showed greatest connectivity with each other, followed by isolates from human carriage, pigs, and bivalves. Nearly 5% of human infection isolates had close relatives (≤22 substitutions) amongst animal and marine isolates, despite temporally and geographically distant sampling of these sources. Infection prevention measures are essential to limit transmission within human clinical settings and reduce disease burden. However, as colonisation often precedes infection, preventing transmission that leads to colonisation, e.g. transmission between animals and humans in the community, and in the food chain, could also be beneficial.

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

Cited by 3 publications

References 49 publications

Multi-country and intersectoral assessment of cluster congruence between different bioinformatics pipelines for genomics surveillance of foodborne bacterial pathogens

Multi-country and intersectoral assessment of cluster congruence between different bioinformatics pipelines for genomics surveillance of foodborne bacterial pathogens

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

A genome-wide One Health study ofKlebsiella pneumoniaein Norway reveals overlapping populations but few recent transmission events across reservoirs

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