Metagenomics Used to Identify Organisms in Outbreaks of Serious Infectious Disease
11 Apr 2013 --- Researchers have been able to reconstruct the genome sequence of an outbreak strain of Shiga-toxigenic Escherichia coli (STEC), which caused over 50 deaths in Germany, using an approach known as metagenomics which bypasses the need for growing bacteria in the lab.
An international team coordinated by Mark Pallen, Professor of Microbial Genomics at Warwick Medical School, was able to reconstruct the genome sequence through the direct sequencing of DNA extracted from microbiologically complex samples. The study, published in a genomics-themed issue of JAMA on 10 April, highlights the potential of this approach to identify and characterise bacterial pathogens directly from clinical specimens.
Metagenomics has been used previously in a clinical diagnostic setting to identify the cause of outbreaks of viral infection, but this is its first reported use in an outbreak of bacterial infection.
Professor Pallen explained the significance of the STEC outbreak, “The outbreak of Shiga-toxigenic Escherichia coli illustrated the effects of a bacterial epidemic on a wealthy, modern, industrialized society, with more than 3,000 cases and more than 50 deaths reported in Germany between May and June of 2011.”
He added, “During an outbreak such as this, rapid and accurate pathogen identification and characterisation is essential for the management of individual cases and the outbreak as a whole. Traditionally, clinical bacteriology has relied primarily on laboratory isolation of bacteria in pure culture to identify and characterise an outbreak strain. Often, however laboratory culture proves slow, difficult, or even impossible and recognition of an outbreak strain can be difficult if it belongs to an unknown variety or species for which specific laboratory tests and diagnostic criteria don’t already exist.”
Professor Pallen led the team, which included two other recently appointed Warwick microbiologists, Chrystala Constantinidou and Jacqueline Chan, together with scientists from the University of Birmingham, the University of Glasgow, the University Medical Centre Hamburg-Eppendorf in Germany and the sequencing company Illumina, to develop and exploit novel sequencing and analytic approaches.
In this retrospective investigation, 45 samples were selected from faecal specimens obtained from patients in Germany with diarrhoea during the 2011 STEC outbreak. Samples were sequenced in summer 2012, followed by a 3-phase analysis in late 2012-early 2013.
In phase 1, a draft genome of the outbreak strain was constructed, using data obtained the HiSeq 2500 instrument in rapid-run mode. In an innovative new approach devised by Nick Loman (Birmingham) and Chris Quince (Glasgow), outbreak-specific sequences were identified by subtracting sequences from the outbreak metagenome that were present in faecal samples from healthy individuals.
In phase 2, the depth of coverage of the outbreak strain genome was determined in each sample. 10 samples gave greater than 10-fold coverage and 26 samples yielded greater than 1-fold coverage. Sequences from the Shiga-toxin genes were detected in two-thirds of the STEC-positive samples. In phase 3, sequences from each sample were compared with sequences from known bacteria to identify potential pathogens other than the outbreak strain, including Clostridium difficile, Campylobacter jejuni, Campylobacter concisus, and Salmonella enterica.
Professor Pallen summarises what this means for the identification of future outbreaks, “There are numerous drawbacks to the use of nineteenth-century approaches such as microscopy and culture when it comes to classification. Our results illustrate the potential of metagenomics as an open-ended, culture-independent approach for the identification and characterization of bacterial pathogens during an outbreak.
“There are challenges, of course, including speeding up and simplifying workflows, reducing costs and improving diagnostic sensitivity. However, given the dizzying pace of progress in high-throughput sequencing, these are not likely to remain problems for very long.”
