Profiling a Community-Specific Function Landscape for Bacterial Peptides Through Protein-Level Meta-Assembly and...

Area of Science:

• Microbiology
• Bioinformatics
• Proteomics

Background:

• Small proteins, encoded by small open reading frames, are increasingly recognized for their crucial roles in cellular processes and disease.
• Bacterial small proteins remain largely unexplored due to challenges in isolation and culturing from natural communities.
• Metagenomic approaches are essential for characterizing bacterial peptides in complex microbial ecosystems.

Purpose of the Study:

• To develop a comprehensive toolkit, metaBP, for exploring the small protein universe within metagenomic samples.
• To enable the characterization of bacterial peptides, including those with sample-specific mutations.
• To reveal microbial community ecology from a small protein perspective.

Main Methods:

• metaBP toolkit takes raw sequencing reads as input.
• Performs protein-level meta-assembly and computes bacterial peptide homolog groups.
• Integrates general protein annotation tools and a small protein-specific machine learning module, metaBP-ML.

Main Results:

• metaBP facilitates the discovery of bacterial peptides and their functional groups from metagenomic data.
• metaBP-ML enhances the discovery of bacterial peptide functions, increasing annotation yields up to fivefold.
• The toolkit provides a comprehensive landscape of bacterial peptides, including those with mutations.

Conclusions:

• metaBP is a novel toolkit for discovering small proteins using protein-level assembly and clustering.
• metaBP-ML offers significant advantages in functional annotation of bacterial peptides in microbial communities.
• metaBP enables the profiling of functional bacterial peptides from metagenomic samples, revealing unique small protein landscapes.