HMDB

HMDB catalogs curated hydrocarbon monooxygenase genes to enable identification of microbial hydrocarbon degradation potential in genomic and metagenomic datasets.


Key Features:

  • Curated Gene Database: HMDB contains 38 genes that encode 11 distinct monooxygenases responsible for the hydroxylation of eight different hydrocarbons.
  • Background Noise Reduction: HMDB incorporates 10,095 homologous gene sequences from enzymes that utilize non-hydrocarbon substrates to minimize false positives.
  • Comprehensive Validation: HMDB was validated against 264,402 prokaryote genomes from RefSeq and 51 metagenomes from SRA, demonstrating high sensitivity and a low false positive rate.
  • Search Methods: HMDB recommends using the classic BLAST method with a best-hit strategy for querying the database.

Scientific Applications:

  • Aerobic hydrocarbon degradation profiling: Identification and analysis of monooxygenase-mediated hydrocarbon degradation pathways in environmental microorganisms under aerobic conditions.
  • Metagenomic screening and gene identification: Rapid detection and characterization of monooxygenase genes in large-scale metagenomic datasets.
  • Bioremediation and carbon cycle research: Supporting studies of microbial contributions to oil pollution remediation and the global carbon cycle through targeted gene-level evidence.

Methodology:

Development involved systematic gene curation, inclusion of 10,095 homologous genes as background noise to distinguish true hydrocarbon monooxygenases from similar non-hydrocarbon enzymes, and validation by screening 264,402 RefSeq prokaryote genomes and 51 SRA metagenomes; classic BLAST with a best-hit strategy is recommended for queries.

Topics

Details

Cost:
Free of charge
Tool Type:
workflow
Added:
2/26/2024
Last Updated:
2/26/2024

Operations

Publications

Wang S, Yun Y, Tian X, Su Z, Liao Z, Li G, Ma T. HMDB: A curated database of genes involved in hydrocarbon monooxygenation reaction with homologous genes as background. Journal of Hazardous Materials. 2023;460:132397. doi:10.1016/j.jhazmat.2023.132397. PMID:37639797.

PMID: 37639797
Funding: - National Key Research and Development Program of China: 2018YFA0902101 - National Natural Science Foundation of China: 42173079