Bioinformatics-coupled molecular approaches for unravelling potential antimicrobial peptides coding genes in Brazilian native and crop plant species
- PMID: 20088767
- DOI: 10.2174/138920310791112138
Bioinformatics-coupled molecular approaches for unravelling potential antimicrobial peptides coding genes in Brazilian native and crop plant species
Abstract
As eukaryotes, plants include in innate defense antimicrobial peptides (AMP), usually small cysteine or glycine-rich peptides effective against a wide range of pathogens. The main classes of AMPs are represented by alpha/beta-defensins, lipid-transfer proteins, thionins, cyclotides, snakins and hevein-like, according to amino acid sequence homology. In spite of increasing number of described AMPs from plants, last decade advances in methodologies for gene expression and the huge amounts of genomic, proteomic and other "-omics" data lead to new prospection strategies of novel potential candidates. Organised user-friendly databases are available to be searched and enlarged with newly discovered plant-derived AMPs. Bioinformatics has allowed the application of in silico-associated molecular tools aiming to screen and identify genes coding for these peptides, starting from genome, transcriptomes, proteome or metabolome from various cultivated or wild plants. As expected, crop plants have been the main target for AMP research and application, also because the higher availability of molecular data. However, wild plant species biodiversity and results for AMP search have increased the importance of characterization in native plants. Enormous plant diversity in Brazilian ecosystems summed to croplands provides potential targets to identify novel candidates for plant AMP. Despite these opportunities, bioinformatics tools are restricted to species whose "-omics" are available, otherwise only heterology-based analyses are feasible, as it has been the case of most Brazilian plant AMP prospection research groups. Still rare, but promising results indicate that this research field on Brazilian crop/native species presents a growing trend of application in agriculture, medicine and industry.
Similar articles
-
[Defense peptides of plant immune system].Bioorg Khim. 2012 Jan-Feb;38(1):7-17. doi: 10.1134/s1068162012010062. Bioorg Khim. 2012. PMID: 22792701 Review. Russian.
-
The use of versatile plant antimicrobial peptides in agribusiness and human health.Peptides. 2014 May;55:65-78. doi: 10.1016/j.peptides.2014.02.003. Epub 2014 Feb 16. Peptides. 2014. PMID: 24548568 Review.
-
Investigation of Antimicrobial Peptide Genes Associated with Fungus and Insect Resistance in Maize.Int J Mol Sci. 2017 Sep 15;18(9):1938. doi: 10.3390/ijms18091938. Int J Mol Sci. 2017. PMID: 28914754 Free PMC article.
-
PhytAMP: a database dedicated to antimicrobial plant peptides.Nucleic Acids Res. 2009 Jan;37(Database issue):D963-8. doi: 10.1093/nar/gkn655. Epub 2008 Oct 4. Nucleic Acids Res. 2009. PMID: 18836196 Free PMC article.
-
Antimicrobial peptides from different plant sources: Isolation, characterisation, and purification.Phytochemistry. 2018 Oct;154:94-105. doi: 10.1016/j.phytochem.2018.07.002. Epub 2018 Jul 17. Phytochemistry. 2018. PMID: 30031244 Review.
Cited by
-
EST-based in silico identification and in vitro test of antimicrobial peptides in Brassica napus.BMC Genomics. 2015 Sep 2;16(1):653. doi: 10.1186/s12864-015-1849-x. BMC Genomics. 2015. PMID: 26330304 Free PMC article.
-
Prediction of antimicrobial peptides based on sequence alignment and feature selection methods.PLoS One. 2011 Apr 13;6(4):e18476. doi: 10.1371/journal.pone.0018476. PLoS One. 2011. PMID: 21533231 Free PMC article.
-
A novel PCR-based method for high throughput prokaryotic expression of antimicrobial peptide genes.BMC Biotechnol. 2012 Mar 23;12:10. doi: 10.1186/1472-6750-12-10. BMC Biotechnol. 2012. PMID: 22439858 Free PMC article.
-
Plant Antimicrobial Peptides: State of the Art, In Silico Prediction and Perspectives in the Omics Era.Bioinform Biol Insights. 2020 Sep 2;14:1177932220952739. doi: 10.1177/1177932220952739. eCollection 2020. Bioinform Biol Insights. 2020. PMID: 32952397 Free PMC article. Review.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Research Materials