Applying rearrangement distances to enable plasmid epidemiology with pling

Area of Science:

• Genomics
• Bioinformatics
• Evolutionary Biology

Background:

• Plasmids are crucial vectors for antibiotic resistance gene transmission.
• Current bioinformatics tools struggle to accurately analyze plasmid evolution due to rapid structural changes.
• Existing methods like replicon typing or k-mer analysis have limitations in reflecting true plasmid relatedness.

Purpose of the Study:

• To develop a novel model and computational workflow for accurate plasmid evolutionary and epidemiological analysis.
• To address the limitations of existing methods in handling plasmid rearrangements, gene gain/loss, and transposable elements.
• To improve the clustering of plasmids for better understanding of their transmission dynamics.

Main Methods:

• Utilized the Double Cut and Join Indel (DCJ-Indel) model to represent plasmids as sequences of signed integers (genes/blocks).
• Calculated plasmid distance based on the minimum number of rearrangement events and indels required for transformation.
• Developed the pling software workflow integrating DCJ-Indel and containment distances for TE-aware plasmid network construction.

Main Results:

• The DCJ-Indel model provides more meaningful plasmid distances compared to traditional methods.
• The pling workflow demonstrates superior performance and interpretability in plasmid clustering.
• The TE-aware network construction effectively mitigates over-clustering caused by transposable elements.

Conclusions:

• The DCJ-Indel model and pling software represent a significant advancement in plasmid analysis.
• Accurate plasmid tracking is essential for combating antibiotic resistance.
• This approach enhances our ability to study plasmid evolution and epidemiology.