Genome mining tools

Actinobacteria are talented producers of secondary metabolites, many of which have useful biological activities. Thanks to the development of many targeted genome mining tools for bacteria, we can now identify previously uncharacterised biosynthetic gene clusters (BGCs) for natural products.

Some useful genome mining resources are listed below:

antiSMASH:¹ https://antismash.secondarymetabolites.org/#!/start

• Twitter: https://twitter.com/antiSMASH_dev

PRISM:² http://grid.adapsyn.com/prism/#!/prism

BAGEL:³ http://bagel4.molgenrug.nl/

CLUSEAN:⁴ https://omictools.com/clusean-tool

ClusterFinder:⁵ https://github.com/petercim/ClusterFinder

CASSIS:⁶ https://sbi.hki-jena.de/cassis/

ARTS:⁷ https://arts3.ziemertlab.com/

2metDB:⁸ https://sourceforge.net/projects/secmetdb/

PKMiner:⁹ http://pks.kaist.ac.kr/pkminer/

SBSPKS:¹⁰ http://www.nii.ac.in/sbspks2.html

RiPPMINER:¹¹ http://www.nii.ac.in/~priyesh/lantipepDB/new_predictions/index.php

RODEO:¹² http://www.ripprodeo.org/manual.html

RiPPER:¹³ https://github.com/streptomyces/ripper

BiG-SCAPE: https://omictools.com/big-scape-tool

EvoMining: https://github.com/nselem/EvoMining/wiki

1. Medema, M.H., Blin, K., Cimermancic, P., de Jager, V., Zakrzewski, P., Fischbach, M.A., Weber, T., Takano, E., Breitling, R. (2011) antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences Nucleic Acids Research 1; 39 doi: 10.1093/nar/gkr466
2. Skinnider, M.A., Merwin, N. J., Johnston, C. W., Magarvey, N. A. (2017) PRISM 3: expanded prediction of natural product chemical structures from microbial genomes et al, Nucleic Acids Research doi: 10.1093/nar/gkx320
3. Van Heel, A.J., de Jong, A., Song, C., Viel, J. H., Kok, J., Kuipers, O. P. (2018) BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins Nucleic Acids Research 2;46 doi: org/10.1093/nar/gky383.
4. Weber, T., Rausch, C., Lopez, P., Hoof, I., Gaykova, V., Huson, D. H., Wohlleben, W. (2009) CLUSEAN: a computer-based framework for the automated analysis of bacterial secondary metabolite biosynthetic gene clusterset al, Journal of Biotechnology, 140:13-7 doi: 10.1016/j.jbiotec.2009.01.007
5. Cimermancic, P., Medema, M.H., Claesen, J., Kurita, K., Wieland Brown, L.C., Mavrommatis, K., Pati, A., Godfrey, P.A., Koehrsen, M., Clardy, J., Birren, B.W., Takano, E., Sali, A., Linington, R.G., Fischbach, M.A. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters (2014) et al, Cell 158:412-21 doi: 10.1016/j.cell.2014.06.034
6. Wolf, T., Shelest, V., Nath, N., Shelest, E. (2015) CASSIS and SMIPS: promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes Bioinformatics, 32:1138-43 doi: 10.1093/bioinformatics/btv713.
7. Alanjary, M., Kronmiller, B., Adamek, M., Blin, K., Weber, T., Huson, D., Philmus, B., Ziemert, N. (2017) The Antibiotic Resistant Target Seeker (ARTS), an exploration engine for antibiotic cluster prioritization and novel drug target discovery Nucleic Acids Research doi: 10.1093/nar/gkx360
8. Bachmann, B. O., and Ravel, J., (2009) Chapter 8. Methods for in silico prediction of microbial polyketide and nonribosomal peptide biosynthetic pathways from DNA sequence data Methods in Enzymology 458:181-217 doi: 10.1016/S0076-6879(09)04808-3
9. Kim, J., and Yi, G.S. (2012) PKMiner: a database for exploring type II polyketide synthases BMC Microbiology 8;12:169. doi: 10.1186/1471-2180-12-169.
10. Anand, S., Prasad, M.V., Yadav, G., Kumar, N., Shehara, J., Ansari, M.Z., Mohanty, D. (2010) SBSPKS: structure based sequence analysis of polyketide synthases Nucleic Acids Research ;38(Web Server issue):W487-96. doi: 10.1093/nar/gkq340.
11. Agrawal, P., Khater, S., Gupta, M., Sain, N., Mohanty, D. (2017) RiPPMiner: a bioinformatics resource for deciphering chemical structures of RiPPs based on prediction of cleavage and cross-links Nucleic Acids Research 3;45 doi: 10.1093/nar/gkx408.
12. Tietz, J. I., Schwalen, C.J., Patel, P.S., Maxson, T., Blair, P.M., Tai, H.C., Zakai, U.I., Mitchell, D.A. (2017) A new genome-mining tool redefines the lasso peptide biosynthetic landscape Nature Chemical Biology 13(5):470-478 doi: 10.1038/nchembio.2319.
13. Santos-Aberturas, J., Chandra, G., Frattaruolo, L., Lacret, R., Pham, T. H., Vior, N. M., Eyles, T. H., Truman, A. W. (2019) Uncovering the unexplored diversity of thioamidated ribosomal peptides in Actinobacteria using the RiPPER genome mining tool Nucleic Acids Research, 47;(9):4624–4637 doi: 10.1093/nar/gkz192