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The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification.

ABSTRACT: Antimicrobial resistance is a worldwide health crisis for which new antibiotics are needed. One strategy for antibiotic discovery is identifying unique antibiotic biosynthetic gene clusters that may produce novel compounds. The aim of this study was to demonstrate how an integrated approach that combines genome mining, comparative genomics, and functional genetics can be used to successfully identify novel biosynthetic gene clusters that produce antimicrobial natural products. Secondary metabolite clusters of an antibiotic producer are first predicted using genome mining tools, generating a list of candidates. Comparative genomic approaches are then used to identify gene suites present in the antibiotic producer that are absent in closely related non-producers. Gene sets that are common to the two lists represent leading candidates, which can then be confirmed using functional genetics approaches. To validate this strategy, we identified the genes responsible for antibiotic production in Pantoea agglomerans B025670, a strain identified in a large-scale bioactivity survey. The genome of B025670 was first mined with antiSMASH, which identified 24 candidate regions. We then used the comparative genomics platform, EDGAR, to identify genes unique to B025670 that were not present in closely related strains with contrasting antibiotic production profiles. The candidate lists generated by antiSMASH and EDGAR were compared with standalone BLAST. Among the common regions was a 14 kb cluster consisting of 14 genes with predicted enzymatic, transport, and unknown functions. Site-directed mutagenesis of the gene cluster resulted in a reduction in antimicrobial activity, suggesting involvement in antibiotic production. An integrated approach that combines genome mining, comparative genomics, and functional genetics yields a powerful, yet simple strategy for identifying potentially novel antibiotics.

SUBMITTER: Williams AN

PROVIDER: S-EPMC7744662 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification.

Williams Ashley N AN Sorout Naveen N Cameron Alexander J AJ Stavrinides John J

Frontiers in genetics 20201203

Antimicrobial resistance is a worldwide health crisis for which new antibiotics are needed. One strategy for antibiotic discovery is identifying unique antibiotic biosynthetic gene clusters that may produce novel compounds. The aim of this study was to demonstrate how an integrated approach that combines genome mining, comparative genomics, and functional genetics can be used to successfully identify novel biosynthetic gene clusters that produce antimicrobial natural products. Secondary metaboli ...[more]

PMID: 33343637

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Project description:The complete 1,751,377-bp sequence of the genome of the thermophilic archaeon Methanobacterium thermoautotrophicum deltaH has been determined by a whole-genome shotgun sequencing approach. A total of 1,855 open reading frames (ORFs) have been identified that appear to encode polypeptides, 844 (46%) of which have been assigned putative functions based on their similarities to database sequences with assigned functions. A total of 514 (28%) of the ORF-encoded polypeptides are related to sequences with unknown functions, and 496 (27%) have little or no homology to sequences in public databases. Comparisons with Eucarya-, Bacteria-, and Archaea-specific databases reveal that 1,013 of the putative gene products (54%) are most similar to polypeptide sequences described previously for other organisms in the domain Archaea. Comparisons with the Methanococcus jannaschii genome data underline the extensive divergence that has occurred between these two methanogens; only 352 (19%) of M. thermoautotrophicum ORFs encode sequences that are >50% identical to M. jannaschii polypeptides, and there is little conservation in the relative locations of orthologous genes. When the M. thermoautotrophicum ORFs are compared to sequences from only the eucaryal and bacterial domains, 786 (42%) are more similar to bacterial sequences and 241 (13%) are more similar to eucaryal sequences. The bacterial domain-like gene products include the majority of those predicted to be involved in cofactor and small molecule biosyntheses, intermediary metabolism, transport, nitrogen fixation, regulatory functions, and interactions with the environment. Most proteins predicted to be involved in DNA metabolism, transcription, and translation are more similar to eucaryal sequences. Gene structure and organization have features that are typical of the Bacteria, including genes that encode polypeptides closely related to eucaryal proteins. There are 24 polypeptides that could form two-component sensor kinase-response regulator systems and homologs of the bacterial Hsp70-response proteins DnaK and DnaJ, which are notably absent in M. jannaschii. DNA replication initiation and chromosome packaging in M. thermoautotrophicum are predicted to have eucaryal features, based on the presence of two Cdc6 homologs and three histones; however, the presence of an ftsZ gene indicates a bacterial type of cell division initiation. The DNA polymerases include an X-family repair type and an unusual archaeal B type formed by two separate polypeptides. The DNA-dependent RNA polymerase (RNAP) subunits A', A", B', B" and H are encoded in a typical archaeal RNAP operon, although a second A' subunit-encoding gene is present at a remote location. There are two rRNA operons, and 39 tRNA genes are dispersed around the genome, although most of these occur in clusters. Three of the tRNA genes have introns, including the tRNAPro (GGG) gene, which contains a second intron at an unprecedented location. There is no selenocysteinyl-tRNA gene nor evidence for classically organized IS elements, prophages, or plasmids. The genome contains one intein and two extended repeats (3.6 and 8.6 kb) that are members of a family with 18 representatives in the M. jannaschii genome.

Dataset Information

The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification.

Publications

The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification.

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