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EvoMining reveals the origin and fate of natural product biosynthetic enzymes.

ABSTRACT: Natural products (NPs), or specialized metabolites, are important for medicine and agriculture alike, and for the fitness of the organisms that produce them. NP genome-mining aims at extracting biosynthetic information from the genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process, the likelihood of identifying truly novel systems by this approach is low. To overcome this limitation, we previously introduced EvoMining, a genome-mining approach that incorporates evolutionary principles. Here, we release and use our latest EvoMining version, which includes novel visualization features and customizable databases, to analyse 42 central metabolic enzyme families (EFs) conserved throughout Actinobacteria, Cyanobacteria, Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these 42 families are lineage specific, opening the metabolic space related to 'shell' enzymes. These enzymes, which have been overlooked, are EFs with orthologues present in most of the genomes of a taxonomic group, but not in all. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving Archaea and Bacteria adaptive evolution. By defining the origin and fate of enzymes, EvoMining complements traditional genome-mining approaches as an unbiased strategy and opens the door to gaining insights into the evolution of NP biosynthesis. We anticipate that EvoMining will be broadly used for evolutionary studies, and for generating predictions of unprecedented chemical scaffolds and new antibiotics. This article contains data hosted by Microreact.

SUBMITTER: Selem-Mojica N

PROVIDER: S-EPMC6939163 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAntibiotic resistance is a growing problem that can be ameliorated by the discovery of novel drug candidates. Bacterial associates are often the source of pharmaceutically active natural products isolated from marine invertebrates, and thus, important targets for drug discovery. While the microbiomes of many marine organisms have been extensively studied, microbial communities from chemically-rich nudibranchs, marine invertebrates that often possess chemical defences, are relatively unknown.MethodsWe applied both culture-dependent and independent approaches to better understand the biochemical potential of microbial communities associated with nudibranchs. Gram-positive microorganisms isolated from nudibranchs collected in the Red Sea were screened for antibacterial and antitumor activity. To assess their biochemical potential, the isolates were screened for the presence of natural product biosynthetic gene clusters, including polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) genes, using PCR. The microbiomes of the nudibranchs were investigated by high-throughput sequencing of 16S rRNA amplicons.ResultsIn screens against five model microorganisms, 51% of extracts displayed antimicrobial activity against more than one organism, and 19% exhibited antitumor activity against Ehrlich's ascites carcinoma. Sixty-four percent of isolates contained PKS and NRPS genes, suggesting their genomes contain gene clusters for natural product biosynthesis. Thirty-five percent were positive for more than one class of biosynthetic gene. These strains were identified as belonging to the Firmicutes and Actinobacteria phyla via 16S rRNA gene sequencing. In addition, 16S rRNA community amplicon sequencing revealed all bacterial isolates were present in the uncultured host-associated microbiome, although they were a very small percentage of the total community. Taken together, these results indicate that bacteria associated with marine nudibranchs are potentially a rich source of bioactive compounds and natural product biosynthetic genes.

Project description:The genus Streptomyces is known to harbor numerous biosynthetic gene clusters (BGCs) of potential utility in synthetic biology applications. However, it is often difficult to link uncharacterized BGCs with the secondary metabolites they produce. Proteomining refers to the strategy of identifying active BGCs by correlating changes in protein expression with the production of secondary metabolites of interest. In this study, we devised a shotgun proteomics-based workflow to identify active BGCs during fermentation when a variety of compounds are being produced. Mycelia harvested during the non-producing growth phase served as the background. Proteins that were differentially expressed were clustered based on the proximity of the genes in the genome to highlight active BGCs systematically from label-free quantitative proteomics data. Our software tool is easy-to-use and requires only 1 point of comparison where natural product biosynthesis was significantly different. We tested our proteomining clustering method on three Streptomyces species producing different compounds. In Streptomyces coelicolor A3(2), we detected the BGCs of calcium-dependent antibiotic, actinorhodin, undecylprodigiosin, and coelimycin P1. In Streptomyces chrestomyceticus BCC24770, 7 BGCs were identified. Among them, we independently re-discovered the type II PKS for albofungin production previously identified by genome mining and tedious heterologous expression experiments. In Streptomyces tenebrarius, 5 BGCs were detected, including the known apramycin and tobramycin BGC as well as a newly discovered caerulomycin A BGC in this species. The production of caerulomycin A was confirmed by LC-MS and the inactivation of the caerulomycin A BGC surprisingly had a significant impact on the secondary metabolite regulation of S. tenebrarius. In conclusion, we developed an unbiased, high throughput proteomics-based method to complement genome mining methods for the identification of biosynthetic pathways in Streptomyces sp.

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EvoMining reveals the origin and fate of natural product biosynthetic enzymes.

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