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Multiple Classes of Antimicrobial Peptides in Amaranthus tricolor Revealed by Prediction, Proteomics, and Mass Spectrometric Characterization.


ABSTRACT: Traditional medicinal plants are rich reservoirs of antimicrobial agents, including antimicrobial peptides (AMPs). Advances in genomic sequencing, in silico AMP predictions, and mass spectrometry-based peptidomics facilitate increasingly high-throughput bioactive peptide discovery. Herein, Amaranthus tricolor aerial tissue was profiled via MS-based proteomics/peptidomics, identifying AMPs predicted in silico. Bottom-up proteomics identified seven novel peptides spanning three AMP classes including lipid transfer proteins, snakins, and a defensin. Characterization via top-down peptidomic analysis of Atr-SN1, Atr-DEF1, and Atr-LTP1 revealed unexpected proteolytic processing and enumerated disulfide bonds. Bioactivity screening of isolated Atr-LTP1 showed activity against the high-risk ESKAPE bacterial pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, and Enterobacter cloacae). These results highlight the potential for integrating AMP prediction algorithms with complementary -omics approaches to accelerate characterization of biologically relevant AMP peptidoforms.

SUBMITTER: Moyer TB 

PROVIDER: S-EPMC8601116 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Multiple Classes of Antimicrobial Peptides in <i>Amaranthus tricolor</i> Revealed by Prediction, Proteomics, and Mass Spectrometric Characterization.

Moyer Tessa B TB   Allen Jessie L JL   Shaw Lindsey N LN   Hicks Leslie M LM  

Journal of natural products 20210212 2


Traditional medicinal plants are rich reservoirs of antimicrobial agents, including antimicrobial peptides (AMPs). Advances in genomic sequencing, in silico AMP predictions, and mass spectrometry-based peptidomics facilitate increasingly high-throughput bioactive peptide discovery. Herein, <i>Amaranthus tricolor</i> aerial tissue was profiled via MS-based proteomics/peptidomics, identifying AMPs predicted in silico. Bottom-up proteomics identified seven novel peptides spanning three AMP classes  ...[more]

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