ABSTRACT: Transcriptome sequencing and comparative analysis during the induction of in vitro flowering in Amaranthus tricolor Transcriptome or Gene expression
Project description:Plant defensins are a broadly distributed family of antimicrobial peptides which have been primarily studied for agriculturally relevant antifungal activity. Recent studies have probed defensins against gram negative bacteria revealing evidence for multiple mechanisms of action including membrane lysis and ribosomal inhibition. In this study, a γ-core motif synthetic analog ( Atr-DEF2(G39-C55) ) of Amaranthus tricolor DEF2 (Atr-DEF2) is used to probe plant defensin antibacterial mechanism of action via proteomics.
Project description:PepSAVI-MS, a mass spectrometry-based peptidomics pipeline, was implemented for antimicrobial peptide (AMP) discovery in the medicinal plant Amaranthus tricolor. This investigation revealed a novel 1.7 kDa AMP, deemed Atr-AMP1. Initial efforts to determine the sequence of Atr-AMP1 utilized chemical derivatization and enzymatic digestion to provide information about specific residues and post-translational modifications. EThcD (electron-transfer/higher-energy collision dissociation) produced extensive backbone fragmentation and facilitated de novo sequencing, the results of which were consistent with orthogonal characterization experiments. Additionally, multistage HCD (higher-energy collisional dissociation) facilitated discrimination between isobaric leucine and isoleucine. These results revealed a positively-charged proline-rich peptide present in a heterogeneous population of multiple peptidoforms, possessing several post-translational modifications including a disulfide bond, methionine oxidation, and proline hydroxylation.
Project description: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.
