Large-scale network analysis captures biological features of bacterial plasmids

Abstract

Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial 'mobilome' and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids.

Fig. 1. Summary of the dataset of complete bacterial plasmids.

a The distribution of host phylum represented in the plasmid dataset. b Functional annotation of plasmid-borne genes. The pie chart shows the proportion of unique CDSs with hypothetical function as predicted by Prokka, and CDSs (genes) with known/unknown biological function based on GO annotation. The bar chart provides the most common biological functions associated with plasmid-borne genes also considering the respective frequency of these genes on plasmid genomes. c The percentage of plasmids covered by the three classification methods: replicon and MOB-typing schemes, and clique assignment. d The distribution of pairwise plasmid similarities (Jaccard index).

Fig. 2. Optimization of OSLOM performance.

A range of Jaccard index (JI) thresholds were applied to the original plasmid network (Supplementary Fig. 3) with edges below a particular threshold being removed prior to OSLOM analysis. During the process, several criteria were considered: a clique to community ratio; b percentage of plasmids covered by the cliques; c the congruence with replicon typing measured by NMI score. NMI was calculated for all cliques containing plasmids assigned to a single or multiple replicon types (legend: All) and just to a single replicon type (legend: Single). Error bars (a, b) and light-coloured shading (c) provide ±2 standard deviations (SDs) of uncertainty. Standard deviation around every value on the y-axis across all JI thresholds assessed (points and bars) was calculated based on results of n = 5 iterations of the OSLOM software (see ‘Methods’). The dashed vertical line indicates the selected optimal JI threshold of 0.3.

Fig. 3. Sparse network of plasmids assigned to cliques by OSLOM algorithm (network density = 0.00128).

The network includes 5371 plasmids (nodes) assigned into 561 cliques (complete subgraphs). The completeness of identified cliques was evaluated based on the original network (Supplementary Fig. 3). 5008 unassigned plasmids, which formed disjoined singletons and pairs, were removed from the network. Coloured nodes indicate plasmids assigned to a single clique.

Fig. 4. The network of cliques.

Cliques, represented as vertices, are connected with an edge if the average Jaccard index (JI) between plasmids of two cliques is >0.01. The colour of the edges indicates the average JI, while the width is proportional to the number of connections between a pair of cliques. The shape and colour of the cliques indicates the phylum of the predominant bacterial host. The size and the transparency are proportional to the clique size and the internal JI, respectively. The cliques form multiple clusters, which have been named based on the genus of the bacterial host characteristic for a particular cluster. There are two exceptions—the Proteobacteria and the Dairy (Lactic) cluster whose respective genera distributions have been provided. The most common GO biological functions of the genes found on plasmids of Proteobacteria, Staphylococcus, Enterococcus and Dairy clusters were further assessed. During the assessment, the respective frequencies of the genes were considered. In case of Proteobacteria, the bar chart distribution of the biological functions is provided. The shared and core gene content of Staphylococcus, Enterococcus and Dairy clusters is presented in the Venn diagram with the numbers in the diagram indicating the number of core and shared genes.