Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Highly Accessed Software

Short read sequence typing (SRST): multi-locus sequence types from short reads

Michael Inouye12, Thomas C Conway3, Justin Zobel3 and Kathryn E Holt1*

Author Affiliations

1 Department of Microbiology and Immunology, The University of Melbourne, Melbourne, Australia

2 Department of Pathology, The University of Melbourne, Melbourne, Australia

3 NICTA Victoria Research Laboratory, Department of Computing & Information Systems, The University of Melbourne, Melbourne, Australia

For all author emails, please log on.

BMC Genomics 2012, 13:338  doi:10.1186/1471-2164-13-338

Published: 24 July 2012

Abstract

Background

Multi-locus sequence typing (MLST) has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven) to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context.

Results

We present a software tool, SRST, for quick and accurate retrieval of sequence types from short read sets, using inputs easily downloaded from public databases. SRST uses read mapping and an allele assignment score incorporating sequence coverage and variability, to determine the most likely allele at each MLST locus. Analysis of over 3,500 loci in more than 500 publicly accessible Illumina read sets showed SRST to be highly accurate at allele assignment. SRST output is compatible with common analysis tools such as eBURST, Clonal Frame or PhyloViz, allowing easy comparison between novel genome data and MLST data. Alignment, fastq and pileup files can also be generated for novel alleles.

Conclusions

SRST is a novel software tool for accurate assignment of sequence types using short read data. Several uses for the tool are demonstrated, including quality control for high-throughput sequencing projects, plasmid MLST and analysis of genomic data during outbreak investigation. SRST is open-source, requires Python, BWA and SamTools, and is available from http://srst.sourceforge.net webcite.

Keywords:
MLST; Short read; Illumina; Sequence analysis; Plasmid; Chromosome; Microbiology; Bacteria; Population analysis; Outbreak