Secret-AAR

Secret-AAR predicts and analyzes the secretome of Mycobacterium abscessus (MAB) clinical isolates to characterize excreted and secreted (ES) proteins relevant to antigenicity, virulence, and potential therapeutic targets.

Key Features:

• Comprehensive secretome prediction: Predicts secretomes for the reference strain ATCC 19977 and fifteen clinical isolates across the three MAB subspecies: M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense.
• Antigenic analysis: Identifies ES proteins with high antigenic densities and reports higher antigenic density and larger predicted secretomes for rough (R) versus smooth (S) colony morphotypes.
• Comparative secretome profiling: Reports that approximately 18% of encoded proteins are predicted as secreted and that over 85% of predicted secreted proteins are shared among the three subspecies.
• Homology to M. tuberculosis secretome: Identifies 337 ES proteins with homologues in Mycobacterium tuberculosis secretomes, including 222 proteins with experimental support for secretion.
• Drug-target homology mapping: Notes that some predicted ES proteins show homology to known drug targets listed in the DrugBank database.
• Pathogenicity-associated domains: Indicates a higher abundance of proteins related to quorum-sensing and Mce domains in MAB compared to the Mycobacterium tuberculosis complex (MTBC).
• Essential gene correlation: Cross-references the ATCC 19977 predicted secretome with essential genes and identifies 99 secreted proteins required for in vitro growth.

Scientific Applications:

• Vaccine and diagnostic development: Prioritizes highly antigenic ES proteins for design of diagnostic assays and vaccine candidates against MAB.
• Therapeutic target discovery: Facilitates identification of secreted proteins homologous to known DrugBank targets for therapeutic exploration.
• Pathogenicity research: Supports investigation of quorum-sensing and Mce domain-associated proteins to elucidate MAB virulence mechanisms.

Methodology:

Integrates genomic data analysis, protein prediction algorithms, and comparative genomics for secretome characterization.