Biochemistry and Pharmacology - Research Publications
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ItemAnalysis of Salmonella enterica Serovar Typhimurium Variable-Number Tandem-Repeat Data for Public Health Investigation Based on Measured Mutation Rates and Whole-Genome Sequence Comparisons(AMER SOC MICROBIOLOGY, 2014-08)Variable-number tandem repeats (VNTRs) mutate rapidly and can be useful markers for genotyping. While multilocus VNTR analysis (MLVA) is increasingly used in the detection and investigation of food-borne outbreaks caused by Salmonella enterica serovar Typhimurium (S. Typhimurium) and other bacterial pathogens, MLVA data analysis usually relies on simple clustering approaches that may lead to incorrect interpretations. Here, we estimated the rates of copy number change at each of the five loci commonly used for S. Typhimurium MLVA, during in vitro and in vivo passage. We found that loci STTR5, STTR6, and STTR10 changed during passage but STTR3 and STTR9 did not. Relative rates of change were consistent across in vitro and in vivo growth and could be accurately estimated from diversity measures of natural variation observed during large outbreaks. Using a set of 203 isolates from a series of linked outbreaks and whole-genome sequencing of 12 representative isolates, we assessed the accuracy and utility of several alternative methods for analyzing and interpreting S. Typhimurium MLVA data. We show that eBURST analysis was accurate and informative. For construction of MLVA-based trees, a novel distance metric, based on the geometric model of VNTR evolution coupled with locus-specific weights, performed better than the commonly used simple or categorical distance metrics. The data suggest that, for the purpose of identifying potential transmission clusters for further investigation, isolates whose profiles differ at one of the rapidly changing STTR5, STTR6, and STTR10 loci should be collapsed into the same cluster.
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ItemA platform for leveraging next generation sequencing for routine microbiology and public health use(BIOMED CENTRAL LTD, 2015-12)Even with the advent of next-generation sequencing (NGS) technologies which have revolutionised the field of bacterial genomics in recent years, a major barrier still exists to the implementation of NGS for routine microbiological use (in public health and clinical microbiology laboratories). Such routine use would make a big difference to investigations of pathogen transmission and prevention/control of (sometimes lethal) infections. The inherent complexity and high frequency of data analyses on very large sets of bacterial DNA sequence data, the ability to ensure data provenance and automatically track and log all analyses for audit purposes, the need for quick and accurate results, together with an essential user-friendly interface for regular non-technical laboratory staff, are all critical requirements for routine use in a public health setting. There are currently no systems to answer positively to all these requirements, in an integrated manner. In this paper, we describe a system for sequence analysis and interpretation that is highly automated and tackles the issues raised earlier, and that is designed for use in diagnostic laboratories by healthcare workers with no specialist bioinformatics knowledge.