Ribosomal Multi-Locus Sequence Typing: universal characterisation of bacteria from domain to strain
By Keith A. Jolley, C. Bliss, Julia S. Bennett, Holly B. Bratcher, Carina Brehony, F. Colles, H. Wimalarathna, Odile B. Harrison, S. Sheppard, Alison J. Cody and 1 more. Microbiology, 2012
596 citations recorded by the source corpus.
Summary No single characterisation scheme currently encompasses all levels of bacterial diversity, from domain to strain. We propose Ribosomal Multi Locus Sequence Typing (rMLST), an approach which indexes variation of the 53 genes encoding the bacterial ribosome protein subunits (rps genes), as a means of integrated microbial taxonomy and typing. As with MLST, rMLST employs curated reference sequences to identify gene variants efficiently and rapidly. The rps loci are ideal targets for a universal characterization scheme as they are: (i) present in all bacteria; (ii) distributed around the chromosome; and (iii) encode proteins which are under stabilising selection for functional conservation. Collectively, the rps loci exhibit variation that resolves bacteria in to groups at all taxonomic and most typing levels providing significantly more resolution than 16S small subunit rRNA gene phylogenies. A web-accessible expandable database, comprising whole genome data from more than 1900 bacterial isolates, including 28 draft genomes assembled de novo from the EBI sequence read archive, has been assembled. The rps gene variation catalogued in this database permits rapid and computationally non-intensive identification of the phylogenetic position of any bacterial sequence at the domain, phylum, class, order, family, genus, species and strain levels. The groupings generated with rMLST data are consistent with current nomenclature schemes and independent of the clustering algorithm used. This approach is applicable to the other domains of life, potentially providing a rational and universal approach to the classification of life that is based on one of its fundamental features, the translation mechanism.
Subfields: Food Science, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/d183462984977317060f07fa75de6dafb08de433
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- Ole Lund
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Citations in the corpus
- Benchmarking of Methods for Genomic Taxonomy (2014, methodology): “In a publication from 2012, Jolley et al. suggested that 53 genes encoding ribosomal proteins be used for bacterial classification in an approach called ribosomal MLST (rMLST) (16).”
- PLSDB: a resource of complete bacterial plasmids (2018, methodology): “The advantage of these markers for the detection of putative chromosomal sequences is their presence in all bacteria, their distribution around the chromosome, and their functional conservation (18).”
- PhyloSift: phylogenetic analysis of genomes and metagenomes (2014, methodology): “Among the uses of phylogenetic analysis in metagenomics are: improved classification 68 of sequences using phylogenetic methods, functional prediction for genes, alternative metrics of alpha 69 and beta diversity, improved identification of operational taxonomic units (OTUs), and sequence binning 70”
- The EnteroBase user's guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity (2019, methodology): “2010) and all rMLST schemes (Jolley et al. 2012) are coordinated on a daily basis with the schemes that are maintained at PubMLST (https:// pubmlst.”
- The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies (2016, methodology): “In addition to providing genoserotyping-based serovar prediction [13,14], this resource integrates several additional sequence-based typing analyses that include MLST [29], rMLST [30], and cgMLST [23,24] into a single web-based tool.”
- GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens (2017, unknown): “Expanded MLST schemes can include all 53 genes encoding ribosomal proteins (rMLST) (Jolley et al. 2012), thousands of core genes that are present in most isolates of a species or genus (core genome MLST, cgMLST) (Mellmann et al. 2011; Maiden et al.…”