Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification

Accurately identifying the diverse microbes present in a sample, whether from the human gut, a soil sample, or a crime scene, is crucial for fields ranging from medicine to environmental science. Researchers rely on comprehensive DNA databases to match sequenced DNA fragments to known microbial species. However, the widely used NCBI nt database, while vast, poses significant challenges. Its massive size makes it difficult for many researchers to use effectively with taxonomic classifiers, and inconsistencies and contamination within the database can impact the accuracy of microbial identification. This work addresses these challenges by providing cleaned, updated, and validated nt-based databases specifically optimized for the widely used Centrifuge classification tool. This new resource demonstrably reduces errors and improves the reliability of microbial identification across diverse taxonomic groups. Moreover, by providing readily usable indexes, we overcome the size barrier, enabling researchers to leverage the full potential of the nt database for metagenomic analysis. Our findings underscore the need to treat reference databases as dynamic entities, emphasizing continuous quality control and versioning as essential practices for robust and reproducible metagenomics research.