A Dual Barcoding Approach to Bacterial Strain Nomenclature: Genomic Taxonomy of Klebsiella pneumoniae Strains

Autor: Hennart Melanie, Guglielmini Julien, Bridel Sébastien, Maiden Martin C.J., Jolley Keith A., Criscuolo Alexis, Brisse Sylvain
Přispěvatelé: Biodiversité et Epidémiologie des Bactéries pathogènes - Biodiversity and Epidemiology of Bacterial Pathogens, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Sorbonne Université (SU), Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Department of Zoology [Oxford], University of Oxford, M.H. was supported financially by the PhD grant 'Codes4strains' from the European Joint Programme One Health, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 773830. This work was supported financially by the French Government’s Investissement d’Avenir program Laboratoire d’Excellence 'Integrative Biology of Emerging Infectious Diseases' (ANR-10-LABX-62-IBEID) and by an award from the Bill and Melinda Gates Foundation (INV-025280). BIGSdb development is funded by a Wellcome Trust Biomedical Resource grant (218205/Z/19/Z). This work used the computational and storage services provided by the IT department at Institut Pasteur. This research was funded, in whole or in part, by Institut Pasteur and by European Union’s Horizon 2020 research and innovation programme.For the purpose of open access, the authors have applied a CC-BY public copyright license to any Author Manuscript version arising from this submission., This work builds partly on the classical 7-gene MLST database, which has been curated by Virginie Passet, Radek Izdebski, Carla Rodrigues, and Federica Palma. We thank Adrien Le Meur for help with the genome data set constitution and initial analyses of intra-outbreak variation., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), European Project: 773830,H2020-SFS-2017-1,MedVetKlebs (a component of European Joint Programme One Health)(2018)
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Molecular Biology and Evolution
Molecular Biology and Evolution, 2022, 39 (7), pp.msac135. ⟨10.1093/molbev/msac135⟩
ISSN: 0737-4038
1537-1719
DOI: 10.1093/molbev/msac135⟩
Popis: 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 threatKlebsiella pneumoniaeas 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.
Databáze: OpenAIRE
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