ggMOB

ggMOB constructs a frequency-based genus-genus mobilization network from whole-genome sequence data of over 180,000 bacterial genomes spanning 1,345 genera to map conjugative features and associated cargo genes and to elucidate patterns relevant to antimicrobial resistance dissemination.

Key Features:

• Whole-genome scale network construction: Builds a frequency-based genus-genus network from whole-genome sequence data encompassing >180,000 genomes across 1,345 genera.
• Conjugation feature identification and quantification: Identifies known conjugation features within bacterial genomes and quantifies their presence across genera, revealing that more than half of analyzed genomes contain one or more conjugation features shared with other genomes.
• Cargo gene mapping: Associates candidate cargo genes with conjugation features to map potential horizontally transferred genetic content between genera.
• Antimicrobial resistance (AMR) analysis: Demonstrates that AMR gene representation is over five times higher in conjugative genomes compared to non-conjugative genomes.
• Phylogenetic and accessory genome insights: Clusters genomes by conjugation profiles to compare patterns that both concord and discord with classical phylogeny, implicating accessory genomes in variable evolutionary trajectories.

Scientific Applications:

• Horizontal gene transfer studies: Enables analysis of conjugation-mediated gene transfer dynamics across bacterial genera.
• AMR dissemination research: Facilitates investigation of the role of conjugation in the spread of antimicrobial resistance genes.
• Virulence and cargo gene tracking: Supports tracing dissemination of virulence factors and other cargo genes associated with conjugative elements.
• Microbial community gene exchange analysis: Allows study of genus-genus gene exchange within complex microbial communities, including unculturable species.

Methodology:

Constructs a frequency-based genus-genus network from whole-genome sequence data, identifies conjugation features and associated cargo genes, and clusters genomes by conjugation profiles for comparative analysis across genera.