期刊
NUCLEIC ACIDS RESEARCH
卷 50, 期 D1, 页码 D736-D740出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab940
关键词
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资金
- University of Tubingen
- German Research Foundation (DFG) [INST 37/935-1 FUGG]
- German Center for Infection Research [DZIF TTU09.716]
- Novo Nordisk Foundation [NNF20CC0035580, NNF16OC0021746]
Due to the continuous evolution of drug resistant bacteria, new antibiotics are urgently needed. Genome mining algorithms have uncovered millions of uncharacterized BGCs, but compound identification and characterization remain challenges. Researchers prioritized promising BGCs using self-resistance based strategies to predict the biological activities of potentially novel antibiotics.
As a result of the continuous evolution of drug resistant bacteria, new antibiotics are urgently needed. Encoded by biosynthetic gene clusters (BGCs), antibiotic compounds are mostly produced by bacteria. With the exponential increase in the number of publicly available, sequenced genomes and the advancements of BGC prediction tools, genome mining algorithms have uncovered millions of uncharacterized BGCs for further evaluation. Since compound identification and characterization remain bottlenecks, a major challenge is prioritizing promising BGCs. Recently, researchers adopted self-resistance based strategies allowing them to predict the biological activities of natural products encoded by uncharacterized BGCs. Since 2017, the Antibiotic Resistant Target Seeker (ARTS) facilitated this so-called target-directed genome mining (TDGM) approach for the prioritization of BGCs encoding potentially novel antibiotics. Here, we present the ARTS database, available at https://arts-db.ziemertlab.com/. The ARTS database provides pre-computed ARTS results for >70,000 genomes and metagenome assembled genomes in total. Advanced search queries allow users to rapidly explore the fundamental criteria of TDGM such as BGC proximity, duplication and horizontal gene transfers of essential housekeeping genes. Furthermore, the ARTS database provides results interconnected throughout the bacterial kingdom as well as links to known databases in natural product research.
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