Abstract
Plasmids are extrachromosomal genetic elements that replicate independently of the chromosome and play a vital role in the environmental adaptation of bacteria. Due to potential mobilization or conjugation capabilities, plasmids are important genetic vehicles for antimicrobial resistance genes and virulence factors with huge and increasing clinical implications. They are therefore subject to large genomic studies within the scientific community worldwide. As a result of rapidly improving next-generation sequencing methods, the quantity of sequenced bacterial genomes is constantly increasing, in turn raising the need for specialized tools to (i) extract plasmid sequences from draft assemblies, (ii) derive their origin and distribution, and (iii) further investigate their genetic repertoire. Recently, several bioinformatic methods and tools have emerged to tackle this issue; however, a combination of high sensitivity and specificity in plasmid sequence identification is rarely achieved in a taxon-independent manner. In addition, many software tools are not appropriate for large high-throughput analyses or cannot be included in existing software pipelines due to their technical design or software implementation. In this study, we investigated differences in the replicon distributions of protein-coding genes on a large scale as a new approach to distinguish plasmid-borne from chromosome-borne contigs. We defined and computed statistical discrimination thresholds for a new metric: the replicon distribution score (RDS), which achieved an accuracy of 96.6 %. The final performance was further improved by the combination of the RDS metric with heuristics exploiting several plasmid-specific higher-level contig characterizations. We implemented this workflow in a new high-throughput taxon-independent bioinformatics software tool called Platon for the recruitment and characterization of plasmid-borne contigs from short-read draft assemblies. Compared to PlasFlow, Platon achieved a higher accuracy (97.5 %) and more balanced predictions (F1=82.6 %) tested on a broad range of bacterial taxa and better or equal performance against the targeted tools PlasmidFinder and PlaScope on sequenced Escherichia coli isolates. Platon is available at: http://platon.computational.bio/.
Highlights
Plasmids are bacterial extrachromosomal DNA elements, which replicate independently of the chromosome
The majority of marker protein sequences (MPS) database sequences was relatively rarely detected on average. These findings endorse the incorporation of the statistical significance of each MPS replicon distribution as well as the scaling by the absolute difference of replicon hit count frequencies in order to raise the contribution of abundant protein sequences and decrease the contribution of rare protein sequences for which insufficient data is available in the reference replicon sets
Small contigs without sufficient protein sequences or contigs encoding for protein sequences which were either not covered by the MPS database or distributed between chromosomes and plasmids remained hard to classify correctly
Summary
Plasmids are bacterial extrachromosomal DNA elements, which replicate independently of the chromosome. They are mostly circular, have characteristic copy numbers per cell and carry genes that are usually not essential under normal conditions but rather allow bacteria to adapt to specific environments and conditions [1]. These genes, for instance, provide antibiotic or heavy metal resistances, are involved in alternative metabolic pathways or encode for virulence factors [2]. It is of huge importance to properly identify and analyze plasmids
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