PHYLOSCANNER: Inferring Transmission from Within- and Between-Host Pathogen Genetic Diversity.

Wymant C., Hall M., Ratmann O., Bonsall D., Golubchik T., de Cesare M., Gall A., Cornelissen M., Fraser C., STOP-HCV Consortium, The Maela Pneumococcal Collaboration, and The BEEHIVE Collaboration .

A central feature of pathogen genomics is that different infectious particles (virions and bacterial cells) within an infected individual may be genetically distinct, with patterns of relatedness among infectious particles being the result of both within-host evolution and transmission from one host to the next. Here, we present a new software tool, phyloscanner, which analyses pathogen diversity from multiple infected hosts. phyloscanner provides unprecedented resolution into the transmission process, allowing inference of the direction of transmission from sequence data alone. Multiply infected individuals are also identified, as they harbor subpopulations of infectious particles that are not connected by within-host evolution, except where recombinant types emerge. Low-level contamination is flagged and removed. We illustrate phyloscanner on both viral and bacterial pathogens, namely HIV-1 sequenced on Illumina and Roche 454 platforms, HCV sequenced with the Oxford Nanopore MinION platform, and Streptococcus pneumoniae with sequences from multiple colonies per individual. phyloscanner is available from https://github.com/BDI-pathogens/phyloscanner.

DOI

10.1093/molbev/msx304

Type

Journal article

Publication Date

2018-03-01T00:00:00+00:00

Volume

35

Pages

719 - 733

Total pages

14

Addresses

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.

Keywords

STOP-HCV Consortium, The Maela Pneumococcal Collaboration, and The BEEHIVE Collaboration

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