Geoff Smith

BACKGROUND: Isolates of methicillin-resistant Staphylococcus aureus (MRSA) belonging to a single lineage are often indistinguishable by means of current typing techniques. Whole-genome sequencing may provide improved resolution to define transmission pathways and characterize outbreaks. METHODS: We investigated a putative MRSA outbreak in a neonatal intensive care unit. By using rapid high-throughput sequencing technology with a clinically relevant turnaround time, we retrospectively sequenced the DNA from seven isolates associated with the outbreak and another seven MRSA isolates associated with carriage of MRSA or bacteremia in the same hospital. RESULTS: We constructed a phylogenetic tree by comparing single-nucleotide polymorphisms (SNPs) in the core genome to a reference genome (an epidemic MRSA clone, EMRSA-15 [sequence type 22]). This revealed a distinct cluster of outbreak isolates and clear separation between these and the nonoutbreak isolates. A previously missed transmission event was detected between two patients with bacteremia who were not part of the outbreak. We created an artificial "resistome" of antibiotic-resistance genes and demonstrated concordance between it and the results of phenotypic susceptibility testing; we also created a "toxome" consisting of toxin genes. One outbreak isolate had a hypermutator phenotype with a higher number of SNPs than the other outbreak isolates, highlighting the difficulty of imposing a simple threshold for the number of SNPs between isolates to decide whether they are part of a recent transmission chain. CONCLUSIONS: Whole-genome sequencing can provide clinically relevant data within a time frame that can influence patient care. The need for automated data interpretation and the provision of clinically meaningful reports represent hurdles to clinical implementation. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.).

The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations.

IMPORTANCE: Identification of the bacterium responsible for an outbreak can aid in disease management. However, traditional culture-based diagnosis can be difficult, particularly if no specific diagnostic test is available for an outbreak strain. OBJECTIVE: To explore the potential of metagenomics, which is the direct sequencing of DNA extracted from microbiologically complex samples, as an open-ended clinical discovery platform capable of identifying and characterizing bacterial strains from an outbreak without laboratory culture. DESIGN, SETTING, AND PATIENTS: In a retrospective investigation, 45 samples were selected from fecal specimens obtained from patients with diarrhea during the 2011 outbreak of Shiga-toxigenic Escherichia coli (STEC) O104:H4 in Germany. Samples were subjected to high-throughput sequencing (August-September 2012), followed by a 3-phase analysis (November 2012-February 2013). In phase 1, a de novo assembly approach was developed to obtain a draft genome of the outbreak strain. In phase 2, the depth of coverage of the outbreak strain genome was determined in each sample. In phase 3, sequences from each sample were compared with sequences from known bacteria to identify pathogens other than the outbreak strain. MAIN OUTCOMES AND MEASURES: The recovery of genome sequence data for the purposes of identification and characterization of the outbreak strain and other pathogens from fecal samples. RESULTS: During phase 1, a draft genome of the STEC outbreak strain was obtained. During phase 2, the outbreak strain genome was recovered from 10 samples at greater than 10-fold coverage and from 26 samples at greater than 1-fold coverage. Sequences from the Shiga-toxin genes were detected in 27 of 40 STEC-positive samples (67%). In phase 3, sequences from Clostridium difficile, Campylobacter jejuni, Campylobacter concisus, and Salmonella enterica were recovered. CONCLUSIONS AND RELEVANCE: These results suggest the potential of metagenomics as a culture-independent approach for the identification of bacterial pathogens during an outbreak of diarrheal disease. Challenges include improving diagnostic sensitivity, speeding up and simplifying workflows, and reducing costs.