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

Chris Wymant,Christophe Fraser,Mariateresa De Cesare,David Bonsall,Oliver Ratmann,Astrid Gall,Marion Cornelissen,Matthew Hall,Tanya Golubchik

doi:10.1093/molbev/msx304

Abstract

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.

Highlights

The infectious transmission process imposes a hierarchical structure of relatedness on pathogen genomes
The genotype of an individual infectious particle is the result of both withinhost evolution and transmission between hosts; a population sample collected from multiple hosts, with multiple genotypes for each host, simultaneously encodes the history of both processes
Host subgraphs result from ancestral host-state reconstruction: they are defined as connected regions of the phylogeny that have all been assigned the same host state

Summary

Introduction

The infectious transmission process imposes a hierarchical structure of relatedness on pathogen genomes. The genotype of an individual infectious particle is the result of both withinhost evolution and transmission between hosts; a population sample collected from multiple hosts, with multiple genotypes for each host, simultaneously encodes the history of both processes. Despite the existence of many tools for analysing pathogen genomes, none, to our knowledge, are adapted to exploiting this hierarchical genealogical structure. The development of methods that use pathogen genomes to infer transmission events, along with their direction, is a priority. A critical recent insight is that including multiple pathogen genomes per infected individual in such methods makes this inference easier: it is equivalent to the simpler process of inferring ancestry (Romero-Severson et al 2016)

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