metaTraits: a large-scale integration of microbial phenotypic trait information

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Microbial phenotypic traits are diverse but scattered across databases, limiting access, especially for uncultured organisms.
• Existing resources do not comprehensively integrate culture-derived and genome-based trait data.

Purpose of the Study:

• To develop metaTraits, a unified resource integrating microbial trait information from diverse sources.
• To enhance accessibility and interoperability of microbial trait data for broader research applications.

Main Methods:

• Integrated culture-derived trait data (BacDive, BV-BRC, JGI IMG, GOLD).
• Incorporated genome-based trait predictions for isolate and metagenome-assembled genomes (MAGs) from proGenomes and SPIRE.
• Harmonized >140 traits using standardized ontologies and linked records to original evidence and taxonomies (NCBI, GTDB).

Main Results:

• metaTraits covers over 2.2 million genomes with >140 harmonized traits.
• Traits span morphology, physiology, metabolism, environmental preferences, and lifestyle.
• The resource provides search, visualization, and annotation tools via an interactive website.

Conclusions:

• metaTraits significantly improves accessibility and interoperability of microbial trait data.
• Enables comprehensive trait-based analyses of microbiomes across various environments.
• Facilitates research on both cultured and uncultured microbial taxa.