Achieving pan-microbiome biological insights via the dbBact knowledge base

Area of Science:

• Microbiology
• Bioinformatics
• Computational Biology

Background:

• 16S rRNA amplicon sequencing is a common method for studying microbial communities.
• Vast amounts of data exist, but integrating findings across studies is challenging.
• A centralized, curated resource is needed to contextualize microbiome research.

Purpose of the Study:

• To introduce dbBact, a novel pan-microbiome resource.
• To create a collaborative repository of 16S rRNA amplicon sequence variants (ASVs) and associated ontology terms.
• To provide computational tools for querying user datasets against the dbBact database.

Main Methods:

• Manual curation of data from over 1000 studies.
• Assignment of multiple ontology terms to ASVs.
• Development of computational tools for database querying.
• Reanalysis of 16 published microbiome studies using dbBact.

Main Results:

• dbBact contains data from >1000 studies, linking 360,000 ASVs with 6,500 ontology terms.
• Reanalysis revealed novel inter-host similarities and potential intra-host bacterial sources.
• Identified commonalities across diseases and lower host-specificity in disease-associated bacteria.
• Demonstrated detection of environmental sources, reagent contaminants, and cross-sample contamination.

Conclusions:

• dbBact facilitates a broader understanding of microbial communities by integrating diverse study data.
• The resource aids in identifying contamination and understanding host-microbe interactions.
• Combining cross-habitat and cross-study information enhances biological process interpretation.