Mining amphibian and insect transcriptomes for antimicrobial peptide sequences with rAMPage
Date
2022
Authors
Lin, Diana
Sutherland, Darcy
Aninta, Sambina Islam
Louie, Nathan
Nip, Ka Ming
Li, Chenkai
Yanai, Anat
Coombe, Lauren
Warren, René L.
Helbing, Caren C.
Journal Title
Journal ISSN
Volume Title
Publisher
Antibiotics
Abstract
Antibiotic 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.
Description
Keywords
antimicrobial peptide, AMP discovery, genome mining, antimicrobial resistance
Citation
Lin, 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/antibiotics11070952