iDiv Annual Conference 2026

Microbial Community Database (MiCoDa), a Curated Repository for Global Microbiome Data Reuse

Not scheduled

20m

Poster Approaches of integrative biodiversity research

Speaker

Dr Clara Arboleda-Baena (Department of Applied Microbial Ecology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, 04318, Germany)

Description

The rapid growth of metabarcoding data for studying bacteria worldwide requires extensive curation and bioinformatics expertise, while the computational demands of processing large sequencing datasets often limit data reuse by researchers without specialized infrastructure or training. Here, we present the Microbial Community Database (MiCoDa), a curated repository of published and pre-processed 16S rRNA gene amplicon datasets ready for reuse by experts and non-experts alike. MiCoDa includes tractable species and facilitates microbiome synthesis through a standardized and scalable approach. Datasets are harmonized using the same region of the 16S rRNA gene to improve comparability across studies, while metadata quality is enhanced through human and machine-assisted curation, yielding reliable and interoperable annotations. MiCoDa V2 contains 31,361 samples and 800,678 Amplicon Sequence Variants (ASVs) spanning global environments. Of all samples, 55% belong to the host-associated microbiome (Organisms realm; 17,303 samples), 20% to Water (6,315), 19% to Mineral (5,992), and 5.5% to other environments (1,751), covering all continents and oceans. MiCoDa applies consistent taxonomic definitions across environmental realms. Of the 800,678 ASVs, 15.8% are specific to water ecosystems, 34.2% are organism-associated, and 32.1% are specific to mineral environments, while 4.5% are shared across all three realms. Gammaproteobacteria, Bacteroidia, Alphaproteobacteria, Cyanobacteriia, and Verrucomicrobiae are consistently dominant across all realms. Parcubacteria are enriched in water, Anaerolineae and Dehalococcoidia in mineral ecosystems, and Bacilli and Clostridia in organism associated environments. Relationships between abundance and occupancy (AOR) among prevalent taxa highlight microbial taxa with broad environmental distributions. Overall, MiCoDa bridges key gaps in microbial data integration and reuse, enabling large-scale synthetic, biogeographical, macroecological, and distributional analyses while lowering computational barriers for microbial ecology researchers.