PT  - JOURNAL ARTICLE
AU  - Mislav Acman
AU  - Lucy van Dorp
AU  - Joanne M. Santini
AU  - Francois Balloux
TI  - Large-scale network analysis captures biological features of bacterial plasmids
AID  - 10.1101/785212
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 785212
4099  - http://biorxiv.org/content/early/2019/09/28/785212.short
4100  - http://biorxiv.org/content/early/2019/09/28/785212.full
AB  - Most bacteria exchange genetic material through Horizontal Gene Transfer (HGT). The primary vehicles for HGT are plasmids and plasmid-borne transposable elements, though their population structure and dynamics remain poorly understood. Here, we quantified genetic similarity between more than 10,000 bacterial plasmids and reconstructed a network based on their shared k-mer content. Using a community detection algorithm, we assigned plasmids into cliques which are highly correlated with plasmid gene content, bacterial host range, GC content, as well as replicon and mobility (MOB) type classifications. Resolving the plasmid population structure further allowed identification of candidates for yet-undescribed replicon genes. Our work provides biological insights into the dynamics of plasmids and plasmid-borne mobile elements, with the latter representing the main drivers of HGT at broad phylogenetic scales. Our results illustrate the potential of network-based analyses for the bacterial ‘mobilome’ and open up the prospect of a natural, exhaustive classification framework for bacterial plasmids.