A list of plasmid prediction tools
Published:
In his recent publication Recovering Escherichia coli Plasmids in the Absence of Long-Read Sequencing Data Julian Paganini reviewed software tools to predict bacterial plasmids from sequencing data.
Entangling this net is difficult without long read sequences. However, we attempted to reconstruct the entire AMR nested genetic complex using only short-read WGS data in a dataset of vancomycin-resistant E. faecium isolates from Dutch hospitals from 2012 to 2015. We compared a core-genome phylogeny to transposon typing data and a plasmid network.
This plasmid network was enabled by machine learning and graph-based techniques coupled with a network analysis of the shared plasmid k-mer content. It allowed us to elucidate not only clonal relatedness but also plasmid and transposon level dissemination of AMR. And while we found that most vanA spread in our data set was dominated by clonal dissemination, there were clear pockets of plasmids or transposon-dominated spread.
Our study is now available as a preprint.