Digital Microbe: a genome-informed data integration framework for team science on emerging model organisms.

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• Genomic data generation is accelerating, transforming biological understanding but posing challenges for collaborative research.
• Lack of standardized data collation and preservation hinders community efforts around shared microbial datasets.
• Microbial genomes exhibit variability in architecture, gene annotations, and identifiers, complicating comparative studies.

Purpose of the Study:

• To introduce "Digital Microbes" as a framework for interoperable and reproducible collaborative science.
• To demonstrate how community-curated, (pan)genomic data packages can overcome data integration barriers.
• To showcase the application of Digital Microbes in analyzing complex microbial datasets.

Main Methods:

• Development of open-source, community-curated data packages based on (pan)genomic foundations.
• Integration of data packages within a unified software environment for real-time research alignment.
• Application of the Digital Microbes framework to specific microbial systems: *Ruegeria pomeroyi* DSS-3 and *Alteromonas* pangenome.

Main Results:

• Two Digital Microbes were established: one for *Ruegeria pomeroyi* DSS-3 with over 100 transcriptomic datasets, and another for the *Alteromonas* pangenome comprising 339 genomes.
• The integrated framework facilitates the addition of new data layers, enabling novel scientific insights.
• Demonstrated the generation of reproducible findings through collation of public (pan)genome-informed data.

Conclusions:

• Digital Microbes provide a robust solution for managing and integrating complex microbial genomic data.
• This framework enhances collaborative research by ensuring interoperability and reproducibility.
• The Digital Microbes approach facilitates the discovery of novel scientific insights from large-scale genomic datasets.