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antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences
Open accessAbstract
Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs. To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes. However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources. Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins and others). It aligns the identified regions at the gene cluster level to their nearest relatives from a database containing all other known gene clusters, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view. antiSMASH is available at http://antismash.secondarymetabolites.org.
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BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074
FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
Price, M. N., Dehal, P. S., & Arkin, A. P. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009490 · Cited by 14,894
OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes
Li, L., Stoeckert, C. J., & Roos, D. S. (2003) · Genome Research · doi:10.1101/gr.1224503 · Cited by 5,707
The Pfam protein families database
Finn, R. D., Mistry, J., Tate, J., Coggill, P., Heger, A., Pollington, J. E., Gavin, O. L., Gunasekaran, P., Ceric, G., Forslund, K., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp985 · Cited by 2,694
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Best practices for analysing microbiomes
Knight, R., Vrbanac, A., Taylor, B. C., Aksenov, A., Callewaert, C., Debelius, J., Gonzalez, A., Kosciolek, T., McCall, L.-I., McDonald, D., et al. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0029-9 · Cited by 2,030
Nakatsuji, T., Chen, T. H., Narala, S., Chun, K. A., Two, A. M., Yun, T., Shafiq, F., Kotol, P. F., Bouslimani, A., Melnik, A. V., et al. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aah4680 · Cited by 1,095
Improving the coverage of the cyanobacterial phylum using diversity driven genome sequencing
Shih, P. M., Wu, D., Latifi, A., Axen, S. D., Fewer, D. P., Talla, E., Calteau, A., Cai, F., Tandeau de Marsac, N., Rippka, R., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217107110 · Cited by 800
Small molecules from the human microbiota
Donia, M. S., & Fischbach, M. A. (2015) · Science · doi:10.1126/science.1254766 · Cited by 760
Self-citationDonia, M. S., Cimermancic, P., Schulze, C. J., Wieland Brown, L. C., Martin, J., Mitreva, M., Clardy, J., Linington, R. G., & Fischbach, M. A. (2014) · Cell · doi:10.1016/j.cell.2014.08.032 · Cited by 705
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Metadata
- Authors
- Medema, M. H., Blin, K., Cimermancic, P., de Jager, V., Zakrzewski, P., Fischbach, M. A., Weber, T., Takano, E., & Breitling, R.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-06-14
- Volume
- 39
- Issue
- suppl_2
- Pages
- W339-W346
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2135639274
- Cited by
- 2,006
- References
- 4
- FWCI
- 55.50
- Type
- journal article
- Language
- en
- Open access
- gold
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- 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. https://doi.org/10.1093/nar/gkr466
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