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Mini Review: Genome Mining Approaches for the Identification of Secondary Metabolite Biosynthetic Gene Clusters in Streptomyces

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Downloaded from orbit.dtu.dk on: Oct 05, 2021 Mini review: Genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces Lee, Namil; Hwang, Soonkyu; Kim, Jihun; Cho, Suhyung; Palsson, Bernhard; Cho, Byung Kwan Published in: Computational and Structural Biotechnology Journal Link to article, DOI: 10.1016/j.csbj.2020.06.024 Publication date: 2020 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Lee, N., Hwang, S., Kim, J., Cho, S., Palsson, B., & Cho, B. K. (2020). Mini review: Genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces. Computational and Structural Biotechnology Journal, 18, 1548-1556. https://doi.org/10.1016/j.csbj.2020.06.024 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Computational and Structural Biotechnology Journal 18 (2020) 1548–1556 journal homepage: www.elsevier.com/locate/csbj Review Mini review: Genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces ⇑ Namil Lee a, Soonkyu Hwang a, Jihun Kim a, Suhyung Cho a, Bernhard Palsson b,c,d, Byung-Kwan Cho a,e,f, a Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea b Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA c Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA d Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby 2800, Denmark e Innovative Biomaterials Research Center, KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea f Intelligent Synthetic Biology Center, Daejeon 34141, Republic of Korea article info abstract Article history: Streptomyces are a large and valuable resource of bioactive and complex secondary metabolites, many of Received 28 February 2020 which have important clinical applications. With the advances in high throughput genome sequencing Received in revised form 12 June 2020 methods, various in silico genome mining strategies have been developed and applied to the mapping Accepted 14 June 2020 of the Streptomyces genome. These studies have revealed that Streptomyces possess an even more signif- Available online 21 June 2020 icant number of uncharacterized silent secondary metabolite biosynthetic gene clusters (smBGCs) than previously estimated. Linking smBGCs to their encoded products has played a critical role in the discov- Keywords: ery of novel secondary metabolites, as well as, knowledge-based engineering of smBGCs to produce Streptomyces altered products. In this mini review, we discuss recent progress in Streptomyces genome sequencing Secondary metabolites Biosynthetic gene clusters and the application of genome mining approaches to identify and characterize smBGCs. Furthermore, Genome mining we discuss several challenges that need to be overcome to accelerate the genome mining process and ultimately support the discovery of novel bioactive compounds. Ó 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative- commons.org/licenses/by-nc-nd/4.0/). Contents 1. Introduction ........................................................................................................ 1549 2. Current status of the Streptomyces genome sequencing projects . .................................................. 1549 2.1. Features of Streptomyces genomes . ........................................................................... 1549 2.2. Currently available Streptomyces genomes . ........................................................... 1549 2.3. Importance of high-quality genome sequences for genome mining . ........................................ 1550 3. Genome mining for smBGCs . ........................................................................................ 1551 3.1. Classical approaches for the identification of smBGCs . ........................................................... 1551 3.2. In silico tools for genome mining of smBGCs. ........................................................... 1551 3.3. Characterizing smBGCs identified by genome mining . ........................................................... 1551 4. Summary and outlook . ........................................................................................ 1554 CRediT authorship contribution statement . ..................................................................... 1554 Declaration of Competing Interest . ..................................................................... 1554 Acknowledgments . ........................................................................................ 1554 Author contributions . ........................................................................................ 1554 References . ........................................................................................................ 1554 ⇑ Corresponding author at: Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea. E-mail address: [email protected] (B.-K. Cho). https://doi.org/10.1016/j.csbj.2020.06.024 2001-0370/Ó 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). N. Lee et al. / Computational and Structural Biotechnology Journal 18 (2020) 1548–1556 1549 1. Introduction standing of the secondary metabolite biosynthetic pathways of these bacteria. Streptomyces species are filamentous Gram-positive bacteria This mini review focuses on the genome mining approaches for found in the soil and a member of the largest genus of Actinobac- smBGC identification from Streptomyces genome data and their teria. They are well-known for their ability to produce a wide array utility in discovering novel bioactive compounds. We briefly of bioactive secondary metabolites, which have a number of antivi- describe the current status of the Streptomyces genome sequencing ral, antifungal, anticancer, immunosuppressive, and antibiotic projects and the importance of high-quality genomic data for functions. The large number of secondary metabolites produced smBGC identification. Next, we introduce several in silico genome by these bacteria allow them to compete in diverse microbial com- mining tools that have been developed for this purpose and munities and survive in various habitats including soils, rivers, describe the characterization process of several key examples. lakes, and marine ecosystems [1]. Since the first report of Strepto- Finally, we highlight future challenges that need to be overcome myces ability to produce antibiotics in the 1940s, a significant for the efficient discovery of novel secondary metabolites from number of novel antibiotics have been characterized by screening Streptomyces. the antimicrobial activity of soil Streptomyces against the target pathogens. Most of the currently available antibiotic classes were 2. Current status of the Streptomyces genome sequencing discovered in and produced from Streptomyces species isolated projects between 1940 and 1962. However, after two decades of success using traditional biochemical screening approaches, since cultured 2.1. Features of Streptomyces genomes soil microorganism constitutes less than 0.1% of the total of soil microorganisms, the rediscovery rate of known species and com- Unlike other bacteria, Streptomyces have large linear chromo- pounds has continuously increased and reached 99% in the late somes with high G + C content. The origin of replication (oriC) is 1980s, with no new classes of antibiotics being approved since usually located at the center of the linear chromosome and termi- [2,3]. Meanwhile, with the rapid emergence of broad-spectrum nal inverted repeats sequences (TIRs), which covalently bind with antibiotic resistance, it is increasingly important that we isolate the terminal proteins, are found at each end [15]. Interestingly, novel classes of antimicrobial compounds. This search for new the lengths and sequences of the TIRs are highly variable between bioactive products has reinvigorated the field of Streptomyces species, and the number of TIR iterations does not correlate with research [4]. the size of the genome [16]. The most distinct feature of the Strep- One bottleneck in the traditional screening methods is that tomyces genome is the high degree of chromosomal instability, Streptomyces often downregulates or inactivates
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  • Supplementary Figures and Tables

    Supplementary Figures and Tables

    Supplementary Material Title: Isolation and Identification of an Anthracimycin Analogue from Nocardiopsis kunsanensis, a Halophile from a Saltern, by Genomic Mining Strategy Authors: Fernanda L. Sirota1,#,*, Falicia Goh1,#, Kia-Ngee Low1,#, Lay-Kien Yang1, Sharon C. Crasta1, Birgit Eisenhaber1, Frank Eisenhaber1,2, Yoganathan Kanagasundaram1,*, Siew Bee Ng1,* Table S1 Suppl. Table S1 - List of top organisms with the highest number of domain hits no. domain hits Organisms psi-blast blast Streptomyces sp. CNH365 41 41 Streptomyces sp. NRRL F-5065 41 41 Streptomyces sp. T676 41 41 Streptomyces sp. TP-A0875 41 41 Nocardiopsis kunsanensis 41 40 Sorangium cellulosum 40 39 Bacillus amyloliquefaciens 39 36 Bacillus subtilis 39 36 Streptococcus pneumoniae 39 33 Table S2 Suppl. Table 2 – Blast 2 sequences results with E-value 0.0 for all of them accession no. (length) query subject query cover identity Streptomyces sp. T676 N. kunsanensis atcC1 CTQ34880 (1108) WP_017577639# (1084) 98% 60% atcD2 CTQ34881 (6561) WP_017577638* (6332) 99% 50% atcE3 CTQ34882 (4468) WP_017577637* (4336) 99% 54% atcF4 CTQ34883 (3869) WP_020480252* (3763) 99% 55% 1 atcC; trans-AT; acylhydrolase, acyltransferase (malonyl-CoA), FMN-dependent enoylreductase 2 atcD; polyketide synthase, modules 1-4 3 atcE; polyketide synthase, modules 5-7 4 atcF; polyketide synthase, modules 8-10 # [acyl-carrier-protein] S-malonyltransferase * hypothetical protein Figure S1 Structure elucidation of (a) anthracimycin (1) in N. kunsanensis, (b-c) anthracimycin standard in Streptomyces sp. T676 and (d) their comparison with anthracimycin BII- 2619. 1 (a) H NMR spectrum of anthracimycin (1) from N. kunsanensis in CDCl3 at 400 MHz. 1 (b) H NMR spectrum of anthracimycin standard from Streptomyces sp.