Multiple Classes of Antimicrobial Peptides in Amaranthus tricolor Revealed by Prediction, Proteomics, and Mass Spectrometric Characterization.
Tessa B MoyerJessie L AllenLindsey Neil ShawLeslie M HicksPublished in: Journal of natural products (2021)
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.
Keyphrases
- mass spectrometry
- protein kinase
- multidrug resistant
- acinetobacter baumannii
- klebsiella pneumoniae
- high throughput
- staphylococcus aureus
- single cell
- dna damage response
- liquid chromatography
- drug resistant
- high resolution
- gram negative
- gas chromatography
- capillary electrophoresis
- escherichia coli
- biofilm formation
- pseudomonas aeruginosa
- molecular docking
- machine learning
- small molecule
- multiple sclerosis
- ms ms
- gene expression
- deep learning
- oxidative stress
- dna methylation
- antimicrobial resistance
- fatty acid
- climate change