PlasmidTron: assembling the cause of phenotypes and genotypes from NGS data

Area of Science:

• Genomics
• Microbiology
• Bioinformatics

Background:

• Whole-genome sequencing generates rich metadata, but linking it to specific genes or traits is challenging.
• Identifying mobile genetic elements (MGEs), such as plasmids carrying antimicrobial resistance genes, is difficult with short-read sequencing data due to assembly issues.
• MGEs have distinct evolutionary histories from their hosts, leading to non-phylogenetic distribution patterns.

Purpose of the Study:

• To develop a method for associating phenotypic data with mobile DNA elements in bacterial populations.
• To identify unknown MGEs and their linked genes using whole-genome sequencing and phenotypic information.
• To overcome limitations in assembling MGEs from short-read data.

Main Methods:

• PlasmidTron utilizes phenotypic data (e.g., antibiograms, virulence factors, geographical origin) to identify traits on randomly reassorting DNA.
• Employs a k-mer-based approach to detect reads associated with phylogenetically unlinked phenotypes.
• Performs de novo assembly of identified reads to generate contigs efficiently and at scale.

Main Results:

• PlasmidTron can associate unknown DNA sequences, like plasmid backbones, with specific molecular markers (e.g., resistance genes).
• The tool effectively identifies traits linked to MGEs by leveraging their independent distribution patterns.
• Demonstrates a scalable and efficient method for MGE identification from bacterial population studies.

Conclusions:

• PlasmidTron offers a novel approach to link phenotypic traits to mobile genetic elements using genomic data.
• The tool facilitates the identification of clinically relevant genes and their mobile DNA carriers.
• Enables a deeper understanding of the genetic basis of bacterial traits and their transmission.