Green leaf volatiles co-opt proteins involved in molecular pattern signalling in plant cells

The green leaf volatiles (GLVs) Z-3-hexen-1-ol (Z3-HOL) and Z-3-hexenyl acetate (Z3-HAC) are airborne infochemicals released from damaged plant tissues that induce defenses and developmental responses in receiver plants, but little is known about their mechanism of action. We found that Z3-HOL and Z3-HAC induce similar but distinctive physiological and signaling responses in tomato seedlings and cell cultures. In seedlings, Z3-HAC showed a stronger root growth inhibition effect than Z3-HOL. In cell cultures, the two GLVs induced distinct changes in MAP kinase (MAPK) activity and proton fluxes as well as rapid and massive changes in the phosphorylation status of proteins within 5 min. Many of these phosphoproteins are involved in reprogramming the proteome from cellular homoeostasis to stress and include pattern recognition receptors, a receptor-like cytoplasmic kinase, MAPK cascade components, calcium signaling proteins and transcriptional regulators. These are well-known components of damage-associated molecular pattern (DAMP) signaling pathways. These rapid changes in the phosphoproteome may underly the activation of defense and developmental responses to GLVs. Our data provide further evidence that GLVs function like DAMPs and indicate that GLVs coopt DAMP signaling pathways.

Automating Complex, Multistep Processes on a Single Robotic Platform to Generate Reproducible Phosphoproteomic Data

Mass spectrometry-based phosphoproteomics holds promise for advancing drug treatment and disease diagnosis; however, its clinical translation has thus far been limited. This is in part due to an unstandardized and segmented sample preparation process that involves cell lysis, protein digestion, peptide desalting, and phosphopeptide enrichment. Automating this entire sample preparation process will be key in facilitating standardization and clinical translation of phosphoproteomics. While peptide desalting and phosphopeptide enrichment steps have been individually automated, integrating these two extractions and, further, the entire process requires more advanced robotic platforms as well as automation-friendly extraction tools. Here we describe a fully automated peptide desalting and phosphopeptide enrichment method using IMCStips on a Hamilton STAR. Using our established automated method, we identified more than 10,000 phosphopeptides from 200 µg of HCT116 cell lysate without fractionation with >85% phosphopeptide specificities. Compared with titania-based Spin Tip products, the automated IMCStips-based method gave 50% higher phosphopeptide identifications. The method reproducibility was further assessed using multiple reaction monitoring (MRM) to show >50% phosphopeptide recoveries after the automated phosphopeptide extraction with coefficients of variation (CVs) of <20% over a 3-week period. The established automated method is a step toward standardization of the sample preparation of phosphopeptide samples and could be further expanded upon to create a fully automated "cells to phosphopeptides" method.