BugSigDB: accelerating microbiome research through systematic comparison to published microbial signatures

The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies, accompanied by information on study geography, health outcomes, host body site, and experimental, epidemiological, and statistical methods using controlled vocabulary. BugSigDB is seeded for initial release with >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and co-exclusion, and consensus signatures, allowing assessment of microbiome differential abundance within and across experimental conditions, environments, or body sites. Database-wide analysis revealed experimental conditions with the highest level of consistency in signatures reported by independent studies and identified commonalities among disease-associated signatures including frequent introgression of oral pathobionts into the gut. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number 5R01CA230551 (to LW, NS, CH, and HJ). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes BugSigDB is available via a Semantic MediaWiki web interface at https://bugsigdb.org, under open-source and open-data licenses described at https://bugsigdb.org/Project:About. Source code and open issue tracking are provided at https://github.com/waldronlab/BugSigDB. Weekly and semi-annual snapshots are provided in plain text file formats at https://github.com/waldronlab/BugSigDBExports for cross-language and cross-application compatibility; unprocessed snapshots are available as csv files at https://bugsigdb.org/Help:Export. The companion bugsigdbr R/Bioconductor package provides advanced data manipulation, including ontology-aware and taxonomy-aware features (https://bioconductor.org/packages/bugsigdbr).