BMC Caller

BMC Caller identifies and analyzes bacterial microcompartments (BMCs) in genomic sequence data by detecting and categorizing shell proteins and BMC loci using Hidden Markov Model (HMM) protein profiles to support classification of shell architecture (hexagonal and pentagonal units) and encapsulated metabolic enzymes.

Key Features:

• HMM-based Sequence Comparison: Uses Hidden Markov Model (HMM) protein profiles to survey genomic sequences and detect BMC components within chromosomal loci.
• Loci Visualization: Generates visualizations of BMC loci to display gene organization and shell protein arrangements.
• Classification and Typing: Classifies shell proteins using a function-agnostic naming system and assigns BMC functional types when known.
• Database Integration: Provides links to similar proteins within an internal database and to external structure prediction websites for obtaining structural models of shell proteins.
• Comprehensive Repository: Hosts a reference database of previously analyzed BMC loci with detailed entries for each BMC protein and phylogenetic insights into shell proteins.
• Discovery Support: Maintains a reference of known BMC types to support identification of novel BMC types and inference of associated metabolic capabilities.

Scientific Applications:

• BMC Locus Identification: Detection and annotation of BMC loci and constituent shell and cargo proteins in genomes.
• Structural Characterization: Support for structural analysis of shell proteins via links to structure prediction resources and models.
• Phylogenetic Analysis: Investigation of evolutionary relationships among BMC shell proteins.
• Metabolic Inference: Inferring metabolic pathways and organismal metabolic capabilities from BMC type and cargo enzyme composition.

Methodology:

Survey and categorization of BMC components by comparing genomic sequences against Hidden Markov Model (HMM) protein profiles; generation of BMC loci visualizations; classification of shell proteins with a function-agnostic naming system; linking to an internal protein database and external structure prediction websites; and provision of phylogenetic insights for shell proteins.