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| DOOR database | |
|---|---|
| Name | DOOR database |
| Type | Biological database |
| Scope | Prokaryotic operons and transcriptional units |
| Country | International |
| Established | 2003 |
| Provider | Academic consortium |
| Disciplines | Microbiology; Genomics; Bioinformatics |
DOOR database
The DOOR database is a curated repository focused on prokaryotic operons and transcriptional units that supports research in microbiology, genomics, and bioinformatics. It aggregates computational predictions and literature-derived annotations to enable comparative analyses across bacterial and archaeal genomes. The resource interfaces with community standards and complements other molecular resources to aid study of gene regulation, functional genomics, and evolutionary biology.
DOOR integrates operon predictions across many prokaryotic genomes and links gene organization to functional annotation, comparative genomics, and pathway resources. It interoperates with large-scale initiatives and databases such as National Center for Biotechnology Information, European Molecular Biology Laboratory, UniProt, Ensembl, KEGG, STRING, Pfam, InterPro, Gene Ontology, PATRIC, RefSeq, GenBank, Enzyme Commission, Swiss-Prot, BRENDA, BioCyc, EcoCyc, RegulonDB, IMG/M, JGI, MG-RAST, NCBI Taxonomy, SILVA, Rfam, PROSITE, TIGRFAMs, COG database, eggNOG, MetaCyc, Reactome, ChEMBL, DrugBank, PDB, SCOP, DDBJ, WormBase.
Initial efforts to compile operon predictions originated in the early 2000s alongside genome sequencing projects led by institutions such as Sanger Centre, Genome Research Limited, Wellcome Trust, Human Genome Project, DOE, J. Craig Venter Institute, and consortia behind Escherichia coli K-12 and Bacillus subtilis reference genomes. Development drew on computational methods from groups at Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, Harvard University, University of Cambridge, University of Oxford, Max Planck Society, CNRS, KAIST, Shanghai Jiao Tong University, University of Tokyo, Seoul National University, University of Melbourne, University of Toronto, McGill University, ETH Zurich, University of São Paulo, EMBL-EBI, and Cold Spring Harbor Laboratory. Funding and validation involved collaborations with projects such as 1000 Genomes Project for comparative method transfer and with model-organism databases like Saccharomyces Genome Database and FlyBase for annotation standards.
DOOR contains predicted operons, transcriptional units, gene neighborhood maps, and cross-references to protein family and pathway resources. Data span taxonomic groups represented in repositories produced by RefSeq, GenBank, EMBL-Bank, PATRIC, IMG/M, and metagenomic datasets managed by MG-RAST and Human Microbiome Project. Annotations include links to structural data from Protein Data Bank, to functional classification from KEGG, COG database, eggNOG, and to regulatory resources such as RegulonDB, DBTBS, EcoCyc, and PromBase.
Operon prediction in DOOR relies on intergenic distance heuristics, gene orientation, conservation across species, and comparative synteny methods developed in bioinformatics groups at institutions like University of California, San Diego, University of Washington, University of Illinois, and University of Pennsylvania. The pipeline incorporates homology searches using tools connected to BLAST, HMMER, and profile databases including Pfam, TIGRFAMs, PROSITE, and InterProScan. Manual curation leverages literature indexed by PubMed, curated datasets from UniProtKB/Swiss-Prot, and experimental annotations from labs working on organisms such as Escherichia coli K-12, Bacillus subtilis 168, Mycobacterium tuberculosis H37Rv, Pseudomonas aeruginosa PAO1, Staphylococcus aureus NCTC 8325.
The DOOR platform provides web-based query and bulk download options, visualization of gene neighborhoods, and APIs for programmatic access used by researchers at Broad Institute, Sanger Institute, JGI, and many university centers. Tools include operon search, comparative genomics viewers, and integration scripts for pipeline use with workflow managers such as Galaxy, Snakemake, and Nextflow. Export formats align with community standards from organizations like FASTA, GFF3, and exchange with resources such as BioMart and Cytoscape for network visualization.
Researchers employ DOOR-derived operon maps in studies of transcriptional regulation, metabolic engineering, synthetic biology, antibiotic resistance, and evolutionary genomics. Use cases appear in publications from groups at MIT, Caltech, Stanford University, Harvard Medical School, Yale University, University of Chicago, Columbia University, University of Michigan, Imperial College London, ETH Zurich, Karolinska Institutet, University of Copenhagen, Seoul National University Hospital, Instituto Pasteur, Max Planck Institute for Molecular Genetics, and in industrial research at companies such as Genentech, Novartis, Pfizer, Roche, Merck, GSK, Thermo Fisher Scientific, Illumina, PacBio, and Oxford Nanopore Technologies. DOOR data have supported comparative studies involving model organisms like Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster by providing prokaryotic context for horizontal gene transfer and operon-based pathway reconstruction.
Limitations include reliance on in silico predictions that require experimental validation, coverage gaps for poorly sampled taxa, and challenges integrating high-throughput transcriptomic and single-cell datasets generated by platforms from Illumina, PacBio, and Oxford Nanopore Technologies. Future directions include incorporating RNA-seq-derived transcriptional boundaries, single-molecule transcriptomics, expanded taxonomic sampling from projects like Earth Microbiome Project and Human Microbiome Project, improved interoperability with resources such as UniProt, Ensembl Bacteria, and enhanced machine-learning models developed at institutions like DeepMind, Google Research, Microsoft Research, and Facebook AI Research.
Category:Biological databases