M. tuberculosis microvariation is common and is associated with transmission: Analysis of three years prospective universal sequencing in England.

BACKGROUND: The prevalence, association with disease status, and public health impact of infection with mixtures of M. tuberculosis strains is unclear, in part due to limitations of existing methods for detecting mixed infections. METHODS: We developed an algorithm to identify mixtures of M. tuberculosis strains using next generation sequencing data, assessing performance using simulated sequences. We identified mixed M. tuberculosis strains when there was at least one mixed nucleotide position, and where both the mixture's components were present in similar isolates from other individuals, compatible with transmission of the component strains. We determined risk factors for mixed infection among isolations of M. tuberculosis in England using logistic regression. We used survival analyses to assess the association between mixed infection and putative transmission. FINDINGS: 6,560 isolations of TB were successfully sequenced in England 2016-2018. Of 3,691 (56%) specimens for which similar sequences had been isolated from at least two other individuals, 341 (9.2%) were mixed. Mixed infection was more common in lineages other than Lineage 4. Among the 1,823 individuals with pulmonary infection with Lineage 4 M. tuberculosis, mixed infection was associated with significantly increased risk of subsequent isolation of closely related organisms from a different individual (HR 1.43, 95% CI 1.05,1.94), indicative of transmission. INTERPRETATION: Mixtures of transmissible strains occur in at least 5% of tuberculosis infections in England; when present in pulmonary disease, such mixtures are associated with an increased risk of tuberculosis transmission. FUNDING: Public Health England; NIHR Health Protection Research Units; European Union.

BugMat and FindNeighbour: command line and server applications for investigating bacterial relatedness.

BACKGROUND: Large scale bacterial sequencing has made the determination of genetic relationships within large sequence collections of bacterial genomes derived from the same microbial species an increasingly common task. Solutions to the problem have application to public health (for example, in the detection of possible disease transmission), and as part of divide-and-conquer strategies selecting groups of similar isolates for computationally intensive methods of phylogenetic inference using (for example) maximal likelihood methods. However, the generation and maintenance of distance matrices is computationally intensive, and rapid methods of doing so are needed to allow translation of microbial genomics into public health actions. RESULTS: We developed, tested and deployed three solutions. BugMat is a fast C++ application which generates one-off in-memory distance matrices. FindNeighbour and FindNeighbour2 are server-side applications which build, maintain, and persist either complete (for FindNeighbour) or sparse (for FindNeighbour2) distance matrices given a set of sequences. FindNeighbour and BugMat use a variation model to accelerate computation, while FindNeighbour2 uses reference-based compression. Performance metrics show scalability into tens of thousands of sequences, with options for scaling further. CONCLUSION: Three applications, each with distinct strengths and weaknesses, are available for distance-matrix based analysis of large bacterial collections. Deployed as part of the Public Health England solution for M. tuberculosis genomic processing, they will have wide applicability.

Supporting the consumption and co-authoring of locative media experiences for a rural village community: design and field trial evaluation of the SHARC2.0 framework.

Locative Media Experiences (LMEs) have significant potential in enabling visitors to engage with the places that they visit through an appreciation of local history. For example, a visitor to Berlin that is exploring remnants of the Berlin Wall may be encouraged to appreciate (or in part experience) the falling of the Berlin wall by consuming multimedia directly related to her current location such as listening to audio recordings of the assembled crowds on 10th November 1989. However, despite the growing popularity of enabling technologies (such as GPS-equipped smart phones and tablets), the availability of tools that support the authoring of LMEs is limited. In addition, mobile apps that support the consumption of LMEs typically adopt an approach that precludes users from being able to respond with their own multimedia contributions. In this article we describe the design and evaluation of the SHARC2.0 framework that has been developed as part of our long-term and participatory engagement with the rural village of Wray in the north of England. Wray has very limited cellular data coverage which has placed a requirement on the framework and associated tools to operate without reliance on network connectivity. A field study is presented which featured a LME relating to Wray's local history and which contained multimedia content contributed by members of the community including historic photos (taken from an existing 'Digital Noticeboard' system), audio-clips (from a local historian and village residents) and video (contributed during a design workshop). The novelty of our approach relates to the ability of multiple authors to contribute to a LME in-situ, and the utilisation of personal cloud storage for storing the contents associated with a multi-authored LME.