Dataset Information

A pilot study of rapid whole-genome sequencing for the investigation of a Legionella outbreak.

ABSTRACT: Epidemiological investigations of Legionnaires' disease outbreaks rely on the rapid identification and typing of clinical and environmental Legionella isolates in order to identify and control the source of infection. Rapid bacterial whole-genome sequencing (WGS) is an emerging technology that has the potential to rapidly discriminate outbreak from non-outbreak isolates in a clinically relevant time frame.We performed a pilot study to determine the feasibility of using bacterial WGS to differentiate outbreak from non-outbreak isolates collected during an outbreak of Legionnaires' disease. Seven Legionella isolates (three clinical and four environmental) were obtained from the reference laboratory and sequenced using the Illumina MiSeq platform at Addenbrooke's Hospital, Cambridge. Bioinformatic analysis was performed blinded to the epidemiological data at the Wellcome Trust Sanger Institute.We were able to distinguish outbreak from non-outbreak isolates using bacterial WGS, and to confirm the probable environmental source. Our analysis also highlighted constraints, which were the small number of Legionella pneumophila isolates available for sequencing, and the limited number of published genomes for comparison.We have demonstrated the feasibility of using rapid WGS to investigate an outbreak of Legionnaires' disease. Future work includes building larger genomic databases of L pneumophila from both clinical and environmental sources, developing automated data interpretation software, and conducting a cost-benefit analysis of WGS versus current typing methods.

SUBMITTER: Reuter S

PROVIDER: S-EPMC3553392 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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A pilot study of rapid whole-genome sequencing for the investigation of a Legionella outbreak.

Reuter Sandra S Harrison Timothy G TG Köser Claudio U CU Ellington Matthew J MJ Smith Geoffrey P GP Parkhill Julian J Peacock Sharon J SJ Bentley Stephen D SD Török M Estée ME

BMJ open 20130109 1

<h4>Objectives</h4>Epidemiological investigations of Legionnaires' disease outbreaks rely on the rapid identification and typing of clinical and environmental Legionella isolates in order to identify and control the source of infection. Rapid bacterial whole-genome sequencing (WGS) is an emerging technology that has the potential to rapidly discriminate outbreak from non-outbreak isolates in a clinically relevant time frame.<h4>Methods</h4>We performed a pilot study to determine the feasibility ...[more]

PMID: 23306006

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Project description:Whole genome sequencing (WGS) has become the new gold standard for bacterial outbreak investigation, due to the high resolution available for typing. While sequencing is currently predominantly performed on Illumina devices, the preceding library preparation can be performed using various protocols. Enzymatic fragmentation library preparation protocols are fast, have minimal hands-on time, and work with small quantities of DNA. The aim of our study was to compare three library preparation protocols for molecular typing: Nextera XT (Illumina); Nextera Flex (Illumina); and QIAseq FX (Qiagen). We selected 12 ATCC strains from human Gram-positive and Gram-negative pathogens with %G+C-content ranging from 27% (Fusobacterium nucleatum) to 73% (Micrococcus luteus), each having a high quality complete genome assembly available, to allow in-depth analysis of the resulting Illumina sequence data quality. Additionally, we selected isolates from previously analyzed cases of vancomycin-resistant Enterococcus faecium (VRE) (n = 7) and a local outbreak of Klebsiella aerogenes (n = 5). The number of protocol steps and time required were compared, in order to test the suitability for routine laboratory work. Data analyses were performed with standard tools commonly used in outbreak situations: Ridom SeqSphere+ for cgMLST; CLC genomics workbench for SNP analysis; and open source programs. Nextera Flex and QIAseq FX were found to be less sensitive than Nextera XT to variable %G+C-content, resulting in an almost uniform distribution of read-depth. Therefore, low coverage regions are reduced to a minimum resulting in a more complete representation of the genome. Thus, with these two protocols, more alleles were detected in the cgMLST analysis, producing a higher resolution of closely related isolates. Furthermore, they result in a more complete representation of accessory genes. In particular, the high data quality and relative simplicity of the workflow of Nextera Flex stood out in this comparison. This thorough comparison within an ISO/IEC 17025 accredited environment will be of interest to those aiming to optimize their clinical microbiological genome sequencing.

Project description:BACKGROUND: Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. METHODS AND FINDINGS: During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed "Hamburg clone") started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. CONCLUSIONS: Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context.

Project description:Whole-genome sequencing (WGS) makes it possible to determine the relatedness of bacterial isolates at a high resolution, thereby helping to characterize outbreaks. However, for Staphylococcus aureus, the accumulation of within-host diversity during carriage might limit the interpretation of sequencing data. In this study, we hypothesized the converse, namely, that within-host diversity can in fact be exploited to reveal the involvement of long-term carriers (LTCs) in outbreaks. We analyzed WGS data from 20 historical outbreaks and applied phylogenetic methods to assess genetic relatedness and to estimate the time to most recent common ancestor (TMRCA). The findings were compared with the routine investigation results and epidemiological evidence. Outbreaks with epidemiological evidence for an LTC source had a mean estimated TMRCA (adjusted for outbreak duration) of 243 days (95% highest posterior density interval [HPD], 143 to 343 days) compared with 55 days (95% HPD, 28 to 81 days) for outbreaks lacking epidemiological evidence for an LTC (P = 0.004). A threshold of 156 days predicted LTC involvement with a sensitivity of 0.875 and a specificity of 1. We also found 6/20 outbreaks included isolates with differing antimicrobial susceptibility profiles; however, these had only modestly increased pairwise diversity (mean 17.5 single nucleotide variants [SNVs] [95% confidence interval {CI}, 17.3 to 17.8]) compared with isolates with identical antibiograms (12.7 SNVs [95% CI, 12.5 to 12.8]) (P < 0.0001). Additionally, for 2 outbreaks, WGS identified 1 or more isolates that were genetically distinct despite having the outbreak pulsed-field gel electrophoresis (PFGE) pulsotype. The duration-adjusted TMRCA allowed the involvement of LTCs in outbreaks to be identified and could be used to decide whether screening for long-term carriage (e.g., in health care workers) is warranted. Requiring identical antibiograms to trigger investigation could miss important contributors to outbreaks.

Dataset Information

A pilot study of rapid whole-genome sequencing for the investigation of a Legionella outbreak.

Publications

A pilot study of rapid whole-genome sequencing for the investigation of a Legionella outbreak.

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