- Volume 2, Issue 9, 2016

Shiga toxin-producing Escherichia coli (STEC) O157:H7 is a public health threat and outbreaks occur worldwide. Here, we investigate genomic differences between related STEC O157:H7 that caused two outbreaks, eight weeks apart, at the same restaurant. Short-read genome sequencing divided the outbreak strains into two sub-clusters separated by only three single-nucleotide polymorphisms in the core genome while traditional typing identified them as separate phage types, PT8 and PT54. Isolates did not cluster with local strains but with those associated with foreign travel to the Middle East/North Africa. Combined long-read sequencing approaches and optical mapping revealed that the two outbreak strains had undergone significant microevolution in the accessory genome with prophage gain, loss and recombination. In addition, the PT54 sub-type had acquired a 240 kbp multi-drug resistance (MDR) IncHI2 plasmid responsible for the phage type switch. A PT54 isolate had a general fitness advantage over a PT8 isolate in rich medium, including an increased capacity to use specific amino acids and dipeptides as a nitrogen source. The second outbreak was considerably larger and there were multiple secondary cases indicative of effective human-to-human transmission. We speculate that MDR plasmid acquisition and prophage changes have adapted the PT54 strain for human infection and transmission. Our study shows the added insights provided by combining whole-genome sequencing approaches for outbreak investigations.

Enrichment of DNA by hybridisation is an important tool which enables users to gather target-focused next-generation sequence data in an economical fashion. Current in-solution methods capture short fragments of around 200–300 nt, potentially missing key structural information such as recombination or translocations often found in viral or bacterial pathogens. The increasing use of long-read third-generation sequencers requires methods and protocols to be adapted for their specific requirements. Here, we present a variation of the traditional bait–capture approach which can selectively enrich large fragments of DNA or cDNA from specific bacterial and viral pathogens, for sequencing on long-read sequencers. We enriched cDNA from cultured influenza virus A, human cytomegalovirus (HCMV) and genomic DNA from two strains of Mycobacterium tuberculosis (M. tb) from a background of cell line or spiked human DNA. We sequenced the enriched samples on the Oxford Nanopore MinION™ and the Illumina MiSeq platform and present an evaluation of the method, together with analysis of the sequence data. We found that unenriched influenza A and HCMV samples had no reads matching the target organism due to the high background of DNA from the cell line used to culture the pathogen. In contrast, enriched samples sequenced on the MinION™ platform had 57 % and 99 % best-quality on-target reads respectively.

Translating the Oxford Nanopore MinION sequencing technology into medical microbiology requires on-going analysis that keeps pace with technological improvements to the instrument and release of associated analysis software. Here, we use a multidrug-resistant Enterobacter kobei isolate as a model organism to compare open source software for the assembly of genome data, and relate this to the time taken to generate actionable information. Three software tools (PBcR, Canu and miniasm) were used to assemble MinION data and a fourth (SPAdes) was used to combine MinION and Illumina data to produce a hybrid assembly. All four had a similar number of contigs and were more contiguous than the assembly using Illumina data alone, with SPAdes producing a single chromosomal contig. Evaluation of the four assemblies to represent the genome structure revealed a single large inversion in the SPAdes assembly, which also incorrectly integrated a plasmid into the chromosomal contig. Almost 50 %, 80 % and 90 % of MinION pass reads were generated in the first 6, 9 and 12 h, respectively. Using data from the first 6 h alone led to a less accurate, fragmented assembly, but data from the first 9 or 12 h generated similar assemblies to that from 48 h sequencing. Assemblies were generated in 2 h using Canu, indicating that going from isolate to assembled data is possible in less than 48 h. MinION data identified that genes responsible for resistance were carried by two plasmids encoding resistance to carbapenem and to sulphonamides, rifampicin and aminoglycosides, respectively.

The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.