SRST2: Rapid genomic surveillance for public health and hospital microbiology labs

By Michael Inouye, Harriet Dashnow, Lesley-Ann Raven, Mark B. Schultz, Bernard J. Pope, T. Tomita, Justin Zobel, Kathryn E. Holt. bioRxiv, 2014

996 citations recorded by the source corpus.

Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data.Source code is available from http://katholt.github.io/srst2/.

Subfields: Molecular Biology, Molecular Medicine, Plant Science

View Paper: https://www.semanticscholar.org/paper/5dbae1fe7c5041a3d36d4bcd787c09909c4180f5

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Citations in the corpus

Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis (2015, background): “The full list of chromosomal mutations, genes and accession codes can be found in Supplementary Tables 12–14.”
Rapid and precise alignment of raw reads against redundant databases with KMA (2018, methodology): “Examples of these are SRST2 [3] and MGmapper [7] which both pre- and post-process the sequences for mapping with Bowtie2 and BWA-MEM, respectively.”
Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health (2015, methodology): “Inouye M, et al. (2014) SRST2: Rapid genomic surveillance for public health and hospital microbiology labs.”
ResFinder – an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes (2022, methodology): “Initially, clustering of the database was considered with a workflow similar to that of SRST2 [33], as well as a sole mapping approach such as KmerResistance [34].”
ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads (2017, methodology): “Several of the VSE samples contain low-level contamination with VanA-B sequences [2]; here, in most cases only ARIBA flagged the genes as partially present at a low read depth, and SRST2 and KmerResistance did not make any prediction about the presence of these genes (Supplementary Table 1).”