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      Engineering of Streptomyces lividans for heterologous expression of secondary metabolite gene clusters

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          Abstract

          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.

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          Most cited references65

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          Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2).

          Streptomyces coelicolor is a representative of the group of soil-dwelling, filamentous bacteria responsible for producing most natural antibiotics used in human and veterinary medicine. Here we report the 8,667,507 base pair linear chromosome of this organism, containing the largest number of genes so far discovered in a bacterium. The 7,825 predicted genes include more than 20 clusters coding for known or predicted secondary metabolites. The genome contains an unprecedented proportion of regulatory genes, predominantly those likely to be involved in responses to external stimuli and stresses, and many duplicated gene sets that may represent 'tissue-specific' isoforms operating in different phases of colonial development, a unique situation for a bacterium. An ancient synteny was revealed between the central 'core' of the chromosome and the whole chromosome of pathogens Mycobacterium tuberculosis and Corynebacterium diphtheriae. The genome sequence will greatly increase our understanding of microbial life in the soil as well as aiding the generation of new drug candidates by genetic engineering.
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            antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification

            Abstract Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.
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              Microbial drug discovery: 80 years of progress

              Microbes have made a phenomenal contribution to the health and well-being of people throughout the world. In addition to producing many primary metabolites, such as amino acids, vitamins and nucleotides, they are capable of making secondary metabolites, which constitute half of the pharmaceuticals on the market today and provide agriculture with many essential products. This review centers on these beneficial secondary metabolites, the discovery of which goes back 80 years to the time when penicillin was discovered by Alexander Fleming.
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                Author and article information

                Contributors
                a.luzhetskyy@mx.uni-saarland.de
                Journal
                Microb Cell Fact
                Microb. Cell Fact
                Microbial Cell Factories
                BioMed Central (London )
                1475-2859
                9 January 2020
                9 January 2020
                2020
                : 19
                : 5
                Affiliations
                [1 ]ISNI 0000 0001 2167 7588, GRID grid.11749.3a, Pharmazeutische Biotechnologie, , Universität des Saarlandes, ; Saarbrücken, Germany
                [2 ]ISNI 0000 0001 2167 7588, GRID grid.11749.3a, Pharmazeutische Biologie, , Universität des Saarlandes, ; Saarbrücken, Germany
                [3 ]GRID grid.461899.b, Helmholtz-Institut für Pharmazeutische Forschung Saarland, ; Saarbrücken, Germany
                Article
                1277
                10.1186/s12934-020-1277-8
                6950998
                31918711
                f0b6dc32-5098-47e0-8576-53a9090b0960
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 20 May 2019
                : 2 January 2020
                Funding
                Funded by: European Commission
                Award ID: 613877
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Biotechnology
                heterologous expression,streptomyces,natural product,heterologous host,gene cluster
                Biotechnology
                heterologous expression, streptomyces, natural product, heterologous host, gene cluster

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