Mining and unearthing hidden biosynthetic potential.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 34162873.
- Also identified by DOI 10.1038/s41467-021-24133-5 and PMC identifier 8222398.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Genetically encoded small molecules (secondary metabolites) play eminent roles in ecological interactions, as pathogenicity factors and as drug leads. Yet, these chemical mediators often evade detection, and the discovery of novel entities is hampered by low production and high rediscovery rates. These limitations may be addressed by genome mining for biosynthetic gene clusters, thereby unveiling cryptic metabolic potential. The development of sophisticated data mining methods and genetic and analytical tools has enabled the discovery of an impressive array of previously overlooked natural products. This review shows the newest developments in the field, highlighting compound discovery from unconventional sources and microbiomes.
Medical subject headings
- Computational Biology
- Data Mining
- Genome, Bacterial
- Genome, Plant
- Genomics