MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies

Abstract

Large-scale bacterial population genetics studies are now routine due to cost-effective Illumina short-read sequencing. However, analysing plasmid content remains difficult due to incomplete assembly of plasmids. Bacterial isolates can contain any number of plasmids and assembly remains complicated due to the presence of repetitive elements. Numerous tools have been developed to analyse plasmids but the performance and functionality of the tools are variable. The MOB-suite was developed as a set of modular tools for reconstruction and typing of plasmids from draft assembly data to facilitate characterization of plasmids. Using a set of closed genomes with publicly available Illumina data, the MOB-suite identified contigs of plasmid origin with both high sensitivity and specificity (95 and 88 %, respectively). In comparison, plasmidfinder demonstrated high specificity (99 %) but limited sensitivity (50 %). Using the same dataset of 377 known plasmids, MOB-recon accurately reconstructed 207 plasmids so that they were assigned to a single grouping without other plasmid or chromosomal sequences, whereas plasmidSPAdes was only able to accurately reconstruct 102 plasmids. In general, plasmidSPAdes has a tendency to merge different plasmids together, with 208 plasmids undergoing merge events. The MOB-suite reduces the number of errors but produces more hybrid plasmids, with 84 plasmids undergoing both splits and merges. The MOB-suite also provides replicon typing similar to plasmidfinder but with the inclusion of relaxase typing and prediction of conjugation potential. The MOB-suite is written in Python 3 and is available from https://github.com/phac-nml/mob-suite.

Detection of extended-spectrum beta-lactamase (ESBL) genes and plasmid replicons in Enterobacteriaceae using PlasmidSPAdes assembly of short-read sequence data

“…Retrieval rates of ESBL genes and plasmid replicons are similar to the retrieval rate of plasmid DNA by plasmidSPAdes in earlier studies ( [10][11][12] ), in which long-read sequence data were used as a reference for plasmid DNA detection. However, these studies included Enterobacteriaceae sequences belonging to different undefined datasets, used only the default setting of the plasmidSPAdes algorithm, and did not evaluate which steps in the plasmidSPAdes algorithm were critical in the plasmid assembly.…”

“…Repeated sequences, often shared between plasmid and chromosomal DNA, hinder the assembly of the bacterial genome from short-read sequence data, often resulting in contigs of which the origin, either plasmid or chromosomal, cannot be resolved. In recent years, several tools to study plasmids using WGS data were developed and include PLACNET, PlasmidFinder, cBar, HyAsP, MOB-suite, PlasmidTron, Recycler, and PlasmidSPAdes ( [4][5][6][7][8][9][10][11]. Only Recycler and PlasmidSPAdes are fully automated computer programs that aim to de novo reconstruct whole plasmid sequences from short-read sequence data ( 7,8 ).…”

Type IV CRISPR-Cas systems are highly diverse and involved in competition between plasmids

“…The mobility of all plasmids (conjugative, mobilizable or non-mobilizable) in PLSDB was predicted with mobtyper 89 with an E-value cut-off of 1e-10. For calculating whether certain mobility types were enriched in targeted plasmids, the number of matches were scaled such that the sum for each spacer was 1, which ensured that each spacer only counted once, no matter how many matches it had.…”

Platon: identification and characterization of bacterial plasmid contigs in short-read draft assemblies exploiting protein-sequence-based replicon distribution scores

“…To detect oriT sequences, Platon conducts a BLAST+ [32] homology search against oriT sequences of the MOB-suite [38] database filtering for both 90% sequence coverage and identity.…”