Large-scale network analysis captures biological features of bacterial plasmids
Mislav Acman, Lucy van Dorp, Joanne M. Santini and Francois Balloux
Received Date: 3rd October 19
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.
Read in full at bioRxiv.
This is an abstract of a preprint hosted on an independent third party site. It has not been peer reviewed but is currently under consideration at Nature Communications.