Mining amphibian and insect transcriptomes for antimicrobial peptide sequences with rAMPage

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dc.contributor.authorLin, Diana
dc.contributor.authorSutherland, Darcy
dc.contributor.authorAninta, Sambina Islam
dc.contributor.authorLouie, Nathan
dc.contributor.authorNip, Ka Ming
dc.contributor.authorLi, Chenkai
dc.contributor.authorYanai, Anat
dc.contributor.authorCoombe, Lauren
dc.contributor.authorWarren, René L.
dc.contributor.authorHelbing, Caren C.
dc.contributor.authorHoang, Linda M. N.
dc.contributor.authorBirol, Inanc
dc.date.accessioned2022-11-12T15:21:45Z
dc.date.available2022-11-12T15:21:45Z
dc.date.copyright2022en_US
dc.date.issued2022
dc.description.abstractAntibiotic resistance is a global health crisis increasing in prevalence every day. To combat this crisis, alternative antimicrobial therapeutics are urgently needed. Antimicrobial peptides (AMPs), a family of short defense proteins, are produced naturally by all organisms and hold great potential as effective alternatives to small molecule antibiotics. Here, we present rAMPage, a scalable bioinformatics discovery platform for identifying AMP sequences from RNA sequencing (RNA-seq) datasets. In our study, we demonstrate the utility and scalability of rAMPage, running it on 84 publicly available RNA-seq datasets from 75 amphibian and insect species—species known to have rich AMP repertoires. Across these datasets, we identified 1137 putative AMPs, 1024 of which were deemed novel by a homology search in cataloged AMPs in public databases. We selected 21 peptide sequences from this set for antimicrobial susceptibility testing against Escherichia coli and Staphylococcus aureus and observed that seven of them have high antimicrobial activity. Our study illustrates how in silico methods such as rAMPage can enable the fast and efficient discovery of novel antimicrobial peptides as an effective first step in the strenuous process of antimicrobial drug development.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipThis work was supported by funds from Genome Canada, and Genome BC as part of the PeptAid (291PEP) and AnnoVis (281ANV) projects. Additional support was provided by the Canadian Agricultural Partnership, a federal–provincial–territorial initiative. The program is delivered by the Investment Agriculture Foundation of BC (INV106). Further funds were received from the Office of the Vice President, Research and Innovation of the University of British Columbia.en_US
dc.identifier.citationLin, D., Sutherland, D., Aninta, S., Louie, N., Nip, K., ... Birol, I. (2022). “Mining amphibian and insect transcriptomes for antimicrobial peptide sequences with rAMPage.” Antibiotics, 11(7), 952. https://doi.org/10.3390/antibiotics11070952en_US
dc.identifier.urihttps://doi.org/10.3390/antibiotics11070952
dc.identifier.urihttp://hdl.handle.net/1828/14418
dc.language.isoenen_US
dc.publisherAntibioticsen_US
dc.subjectantimicrobial peptide
dc.subjectAMP discovery
dc.subjectgenome mining
dc.subjectantimicrobial resistance
dc.subject.departmentDepartment of Biochemistry and Microbiology
dc.titleMining amphibian and insect transcriptomes for antimicrobial peptide sequences with rAMPageen_US
dc.typeArticleen_US

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