Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation

PLoS Comput Biol. 2019 Jul 23;15(7):e1007208. doi: 10.1371/journal.pcbi.1007208. eCollection 2019 Jul.

Abstract

Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Computational Biology
  • Computer Simulation
  • Databases, Genetic / statistics & numerical data
  • Disease Outbreaks / statistics & numerical data
  • Evolution, Molecular*
  • Gene Transfer, Horizontal*
  • Genetic Variation
  • Genome, Bacterial
  • Helicobacter pylori / genetics
  • Humans
  • Metagenome*
  • Metagenomics / methods*
  • Metagenomics / statistics & numerical data
  • Methicillin-Resistant Staphylococcus aureus / genetics
  • Models, Genetic*
  • Mutation
  • Staphylococcal Infections / epidemiology
  • Staphylococcal Infections / microbiology

Grants and funding

We gratefully acknowledge financial support by Deutsche Forschungsgemeinschaft (DFG), grant number RE3474/2-1 and RE3474/2-2 to BYR (http://www.dfg.de/en/research_funding/index.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.