Proteomics

Dataset Information

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Mass spectrometry guided by transcriptomics reveals multiple classes of predicted antimicrobial peptides in Amaranthus tricolor

ABSTRACT: Traditional medicinal plants are rich reservoirs of antimicrobial agents, including antimicrobial peptides (AMPs). Herein, Amaranthus tricolor AMPs predicted in silico are identified via proteomics profiling. Bottom-up proteomics identified seven novel peptides spanning three AMP classes including lipid transfer proteins, snakins and defensins. Characterization via top-down peptidomic analysis of Atr-SN1, Atr-DEF1, and Atr-LTP1 revealed unexpected proteolytic processing and enumerated disulfide bonds. These results highlight the potential for integrating AMP prediction algorithms with complementary -omics approaches to accelerate characterization of biologically relevant AMP peptidoforms.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Amaranthus Tricolor

TISSUE(S): Leaf

SUBMITTER: Leslie Hicks  

LAB HEAD: Leslie M. Hicks

PROVIDER: PXD022242 | Pride | 2021-04-08

REPOSITORIES: Pride

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Dataset's files

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Action DRS
20200626_TEB_ATRSCX_Seppack_SCX4_20p_real_1e4x_2ul.wiff Wiff
20200626_TEB_ATRSCX_Seppack_SCX4_20p_real_1e4x_2ul.wiff.scan Wiff
20200626_TEB_ATRSCX_Seppack_SCX4_20p_real_1e4x_2ul_pepion.csv Csv
20200703_TEB_atr_scx4_spe20_ra_10x_2uL.wiff Wiff
20200703_TEB_atr_scx4_spe20_ra_10x_2uL.wiff.scan Wiff
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Publications

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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