Microbial Bioactives
Microbial Bioactives | Online ISSN 2209-2161
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Volume 4 Number 1 2021
REVIEWS (Open Access)
Unlocking Silent Biosynthetic Gene Clusters: Multi-Omics Strategies for Discovering Novel Microbial Secondary Metabolites
Md. Fakruddin 1*, SM Bakhtiar Ul Islam 1*
Microbial Bioactives 4 (1) 1-8 https://doi.org/10.25163/microbbioacts.4110711
Submitted: 07 January 2021 Revised: 01 March 2021 Accepted: 08 March 2021 Published: 10 March 2021
Abstract
Microbial secondary metabolites have shaped modern medicine for decades, yet an unexpectedly large portion of microbial biosynthetic potential still remains hidden within cryptic or transcriptionally silent biosynthetic gene clusters (BGCs). In recent years, advances in genome sequencing, metagenomics, and computational biology have begun to expose this “microbial dark matter,” revealing a chemical landscape far richer than what traditional cultivation-based approaches once suggested. This systematic review synthesizes current evidence on the discovery, activation, and functional assessment of microbial BGCs, with particular emphasis on integrated omics-driven workflows. Following PRISMA 2020 guidelines, studies investigating genome mining, heterologous expression, chemical elicitation, ribosome engineering, and metabolomic profiling were critically evaluated to understand how these approaches collectively improve natural product discovery. Across the reviewed literature, integrated strategies consistently appeared more effective than single-platform approaches in uncovering bioactive metabolites with antibacterial and antitumor potential. Interestingly, ecological context also emerged as an important determinant of biosynthetic diversity, particularly within marine and host-associated microbiomes. At the same time, the review highlights persistent challenges involving annotation bias, incomplete databases, methodological heterogeneity, and limited experimental validation of predicted clusters. Overall, the findings suggest that combining genomics, activation technologies, and metabolomics is gradually transforming microbial natural product discovery from a largely empirical process into a more predictive, systems-oriented discipline with substantial therapeutic potential.
Keywords: Biosynthetic gene clusters; microbial secondary metabolites; genome mining; metagenomics; natural product discovery; systematic review
References
Blin, K., Wolf, T., Chevrette, M. G., Lu, X., Schwalen, C. J., Kautsar, S. A., … & Weber, T. (2017). antiSMASH 4.0-Improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Research, 45(W1), W36-W41. https://doi.org/10.1093/nar/gkx319
Bode, H. B., Bethe, B., Höfs, R., & Zeeck, A. (2002). Big effects from small changes: Possible ways to explore nature's chemical diversity. Chembiochem, 3(7), 619-627. https://doi.org/10.1002/1439-7633(20020703)3:7<619::AID-CBIC619>3.0.CO;2-9
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Wiley. https://doi.org/10.1002/9780470743386
Brakhage, A. A., & Schroeckh, V. (2011). Fungal secondary metabolites-Strategies to activate silent gene clusters. Fungal Genetics and Biology, 48(1), 15-22. https://doi.org/10.1016/j.fgb.2010.04.004
Chai, Y.-J., Cui, C.-B., Li, C.-W., Wu, C.-J., Tian, C.-K., & Hua, W. (2012). Activation of the dormant secondary metabolite production by introducing gentamicin-resistance in a marine-derived Penicillium purpurogenum G59. Marine Drugs, 10(3), 559-582. https://doi.org/10.3390/md10030559
Charlop-Powers, Z., Owen, J. G., Reddy, B. V. B., Ternei, M. A., Guimarães, D. O., de Frias, U. A., … Brady, S. F. (2015). Global biogeographic sampling of bacterial secondary metabolism. eLife, 4, e05048. https://doi.org/10.7554/eLife.05048
Cháve_z, A., Forero, A., García-Huante, Y., Romero, A., Sánchez, M., Rocha, D., … Ruiz, B. (2010). Production of microbial secondary metabolites: Regulation by the carbon source. Critical Reviews in Microbiology, 36(2), 146-167. https://doi.org/10.3109/10408410903489576
Cimermancic, P., Medema, M. H., Claesen, J., Kurita, K., Brown, L. C., Mavrommatis, K., … & Fischbach, M. A. (2014). Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell, 158(2), 412-421. https://doi.org/10.1016/j.cell.2014.06.034
Cuadrat, R. R. C., Ionescu, D., Dávila, A. M. R., & Grossart, H.-P. (2018). Recovering genomics clusters of secondary metabolites from lakes using genome-resolved metagenomics. Frontiers in Microbiology, 9, 251. https://doi.org/10.3389/fmicb.2018.00251
DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7(3), 177–188. https://doi.org/10.1016/0197-2456(86)90046-2
Donia, M. S., Cimermancic, P., Schulze, C. J., Wieland, B., Laura, C., Martin, J., … Fischbach, M. A. (2014). A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics. Cell, 158(6), 1402-1414. https://doi.org/10.1016/j.cell.2014.08.032
Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629
Handelsman, J. (2004). Metagenomics: Application of genomics to uncultured microorganisms. Microbiology and Molecular Biology Reviews, 68(4), 669-685. https://doi.org/10.1128/MMBR.68.4.669-685.2004
Hentschel, U., Hopke, J., Horn, M., Friedrich, A. B., Wagner, M., Steinert, M., … Hacker, J. (2002). Molecular evidence for a uniform microbial community in sponges from different oceans. Applied and Environmental Microbiology, 68(9), 4431-4440. https://doi.org/10.1128/AEM.68.9.4431-4440.2002
Hertweck, C. (2009). Hidden biosynthetic treasures brought to light. Nature Chemical Biology, 5(7), 450-452. https://doi.org/10.1038/nchembio0709-450
Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (2022). Cochrane handbook for systematic reviews of interventions (Version 6.3). Cochrane. http://www.training.cochrane.org/handbook
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta-analyses. BMJ, 327(7414), 557–560. https://doi.org/10.1136/bmj.327.7414.557
Keller, N. P., Turner, G., & Bennett, J. W. (2005). Fungal secondary metabolism-from biochemistry to genomics. Nature Reviews Microbiology, 3(12), 937-947. https://doi.org/10.1038/nrmicro1286
Li, Y., Li, Z., Yamanaka, K., Xu, Y., Zhang, W., Vlamakis, H., … Qian, P.-Y. (2015). Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis. Scientific Reports, 5, 9383. https://doi.org/10.1038/srep09383
Macintyre, L., Zhang, T., Viegelmann, C., Martinez, I. J., Cheng, C., Dowdells, C., Abdelmohsen, U. R., Gernert, C., Hentschel, U., & Edrada-Ebel, R. (2014). Metabolomic Tools for Secondary Metabolite Discovery from Marine Microbial Symbionts. Marine Drugs, 12(6), 3416-3448. https://doi.org/10.3390/md12063416
Medema, M. H., & Fischbach, M. A. (2015b). Computational approaches to natural product discovery. Nature Chemical Biology, 11(9), 639-648. https://doi.org/10.1038/nchembio.1884
Medema, M. H., Kottmann, R., Yilmaz, P., Cummings, M., Biggins, J. B., Blin, K., ... & Zhang, C. (2015a). Minimum information about a biosynthetic gene cluster. Nature chemical biology, 11(9), 625-631.https://doi.org/10.1038/nchembio.1890
Newman, D. J., & Cragg, G. M. (2016). Natural products as sources of new drugs from 1981 to 2014. Journal of Natural Products, 79(3), 629-661. https://doi.org/10.1021/acs.jnatprod.5b01055
O'Neill, J. (2014). Antimicrobial resistance: Tackling a crisis for the health and wealth of nations. Review on Antimicrobial Resistance. https://amr-review.org/sites/default/files/AMR%20Review%20Paper%20-%20Tackling%20a%20crisis%20for%20the%20health%20and%20wealth%20of%20nations_1.pdf
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Palazzotto, E., & Weber, T. (2018). Omics and multi-omics approaches to study the biosynthesis of secondary metabolites in microorganisms. Current Opinion in Microbiology, 45, 109-116.
https://doi.org/10.1016/j.mib.2018.03.004
Pimentel-Elardo, S. M., et al. (2015). Activity-independent discovery of secondary metabolites using chemical elicitation and cheminformatic inference. ACS Chemical Biology, 10(11), 2616-2623. https://doi.org/10.1021/acschembio.5b00612
Stewart, E. J. (2012). Growing unculturable bacteria. Journal of Bacteriology, 194(16), 4151-4160. https://doi.org/10.1128/JB.00345-12
Subramani, R., & Aalbersberg, W. (2013). Culturable rare actinomycetes: Marine natural product discovery. Applied Microbiology and Biotechnology, 97, 9291-9321.
https://doi.org/10.1007/s00253-013-5229-7
Taylor, J., Hafner, M., Yerushalmi, E., Smith, R., Bellasio, J., Vardavas, R., … & Rubin, J. (2014). Estimating the economic costs of antimicrobial resistance. RAND Corporation. https://www.rand.org/pubs/research_reports/RR911.html
Utermann, C., Echelmeyer, V. A., Oppong-Danquah, E., Blümel, M., & Tasdemir, D. (2021). Diversity, bioactivity profiling and untargeted metabolomics of the cultivable gut microbiota of Ciona intestinalis. Marine Drugs, 19(1), 6. https://doi.org/10.3390/md19010006
Weber, T., & Kim, H. U. (2016). The secondary metabolite bioinformatics portal. Synthetic and Systems Biotechnology, 1(2), 69-79. https://doi.org/10.1016/j.synbio.2015.12.002
Wilson, M. C., & Piel, J. (2013). Metagenomic approaches for exploiting uncultivated bacteria as a resource for novel biosynthetic enzymology. Chemistry & Biology, 20(5), 636-647.
https://doi.org/10.1016/j.chembiol.2013.04.011
Yamanaka, K., Reynolds, K. A., Kersten, R. D., Ryan, K. S., Gonzalez, D. J., Nizet, V., … Moore, B. S. (2014). Direct cloning and refactoring of a silent gene cluster yields taromycin A. PNAS, 111(5), 1957-1962. https://doi.org/10.1073/pnas.1319584111
Zhang, M. M., Qiao, Y., Ang, E. L., & Zhao, H. (2017). Using natural products for drug discovery: The impact of the genomics era. Expert Opinion on Drug Discovery, 12(5), 475-487.
https://doi.org/10.1080/17460441.2017.1303478
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