Dataset Information

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

ABSTRACT:

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Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways.

Importance

Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery.

SUBMITTER: Xu M

PROVIDER: S-EPMC5038051 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

Xu Min M Wang Yemin Y Zhao Zhilong Z Gao Guixi G Huang Sheng-Xiong SX Kang Qianjin Q He Xinyi X Lin Shuangjun S Pang Xiuhua X Deng Zixin Z Tao Meifeng M

Applied and environmental microbiology 20160916 19

<h4>Unlabelled</h4>Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, wh ...[more]

PMID: 27451447

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Project description:BACKGROUND:Heterologous expression of secondary metabolite gene clusters is used to achieve increased production of desired compounds, activate cryptic gene clusters, manipulate clusters from genetically unamenable strains, obtain natural products from uncultivable species, create new unnatural pathways, etc. Several Streptomyces species are genetically engineered for use as hosts for heterologous expression of gene clusters. S. lividans TK24 is one of the most studied and genetically tractable actinobacteria, which remain untapped. It was therefore important to generate S. lividans chassis strains with clean metabolic backgrounds. RESULTS:In this study, we generated a set of S. lividans chassis strains by deleting endogenous gene clusters and introducing additional φC31 attB loci for site-specific integration of foreign DNA. In addition to the simplified metabolic background, the engineered S. lividans strains had better growth characteristics than the parental strain in liquid production medium. The utility of the developed strains was validated by expressing four secondary metabolite gene clusters responsible for the production of different classes of natural products. Engineered strains were found to be superior to the parental strain in production of heterologous natural products. Furthermore, S. lividans-based strains were better producers of amino acid-based natural products than other tested common hosts. Expression of a Streptomyces albus subsp. chlorinus NRRL B-24108 genomic library in the modified S. lividans ΔYA9 and S. albus Del14 strains resulted in the production of 7 potentially new compounds, only one of which was produced in both strains. CONCLUSION:The constructed S. lividans-based strains are a great complement to the panel of heterologous hosts for actinobacterial secondary metabolite gene expression. The expansion of the number of such engineered strains will contribute to an increased success rate in isolation of new natural products originating from the expression of genomic and metagenomic libraries, thus raising the chance to obtain novel biologically active compounds.

Project description:BackgroundFrequent use of antibiotics has led to the emergence of antibiotic resistance in bacteria. Lantibiotic compounds are ribosomally synthesized antimicrobial peptides against which bacteria are not able to produce resistance, hence making them a good alternative to antibiotics. Nisin is the oldest and the most widely used lantibiotic, in food preservation, without having developed any significant resistance against it. Having their antimicrobial potential and a limited number, there is a need to identify novel lantibiotics.Methodology/findingsIdentification of novel lantibiotic biosynthetic clusters from an ever increasing database of bacterial genomes, can provide a major lead in this direction. In order to achieve this, a strategy was adopted to identify novel lantibiotic biosynthetic clusters by screening the sequenced genomes for LanT homolog, which is a conserved lantibiotic transporter specific to type IB clusters. This strategy resulted in identification of 54 bacterial strains containing the LanT homologs, which are not the known lantibiotic producers. Of these, 24 strains were subjected to a detailed bioinformatic analysis to identify genes encoding for precursor peptides, modification enzyme, immunity and quorum sensing proteins. Eight clusters having two LanM determinants, similar to haloduracin and lichenicidin were identified, along with 13 clusters having a single LanM determinant as in mersacidin biosynthetic cluster. Besides these, orphan LanT homologs were also identified which might be associated with novel bacteriocins, encoded somewhere else in the genome. Three identified gene clusters had a C39 domain containing LanT transporter, associated with the LanBC proteins and double glycine type precursor peptides, the only known example of such a cluster is that of salivaricin.ConclusionThis study led to the identification of 8 novel putative two-component lantibiotic clusters along with 13 having a single LanM and 3 with LanBC genes. Putative lantibiotic clusters identified here hold the potential for the discovery of novel lantibiotic(s).

Dataset Information

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

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Importance

Publications

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

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