mobileOG-db

mobileOG-db provides a curated database of bacterial mobile genetic element (MGE) protein families to support accurate annotation and analysis of MGE life-cycle functions.

Key Features:

• Comprehensive curation: Built from analysis of 10,776,849 protein sequences sourced from eight established MGE databases and comprising 6,140 manually curated protein families linked to integration/excision, replication/recombination/repair, transfer, stability/transfer/defense, and phage-specific functions.
• Protein-level focus to reduce false positives: Emphasizes protein families directly involved in MGE life cycles to distinguish hallmark MGE functions from accessory homologs that can produce false positives.
• Structured classification: Entries are organized into five major mobileOG categories and over 50 minor categories and are assigned MGE-class labels (e.g., plasmid or integrative element).
• Tiered annotation scheme: Annotations are tiered by evidence, incorporating experimental support where available and distinguishing experimentally supported entries from those inferred through bioinformatics.
• Pipeline compatibility: Provides structured classifications and language intended for integration into MGE detection pipelines and colocalization analyses.

Scientific Applications:

• MGE annotation: Supplies candidate hallmark proteins to aid identification and classification of bacterial mobile genetic elements.
• Antibiotic resistance and evolutionary research: Enables analysis of MGEs implicated in antibiotic resistance mechanisms, phenotypic or metabolic diversity, and evolutionary processes within bacterial genera.
• Bioinformatics workflow integration: Supports incorporation of curated MGE protein families and classification schemes into genomic analysis and colocalization workflows.

Methodology:

Constructed by analyzing 10,776,849 protein sequences from eight MGE databases, manually curating 6,140 protein families, organizing entries into five major and >50 minor categories with MGE-class labels, and applying a tiered annotation scheme combining experimental evidence and bioinformatics inference for use in MGE annotation and colocalization analyses.