Salinity and oxidative stress are major factors affecting and limiting the productivity of agricultural crops. The molecular and biochemical processes governing the plant response to abiotic stress have often been researched in a reductionist manner. Here, we report a systemic approach combining metabolic labeling and phosphoproteomics to capture early signaling events with quantitative metabolome analysis and enzyme activity assays to determine the effects of salt and oxidative stress on plant physiology. K+ and Na+ transporters showed coordinated changes in their phosphorylation pattern, indicating the importance of dynamic ion homeostasis for adaptation to salt stress. Unique phosphorylation sites were found for Arabidopsis (Arabidopsis thaliana) SNF1 kinase homolog10 and 11, indicating their central roles in the stress-regulated responses. Seven Sucrose Non-fermenting1-Related Protein Kinase2 kinases showed varying levels of phosphorylation at multiple serine/threonine residues in their kinase domain upon stress, showing temporally distinct modulation of the various isoforms. Salinity and oxidative stress also lead to changes in protein phosphorylation of proteins central to photosynthesis, in particular the kinase State Transition Protein7 required for state transition and light-harvesting II complex proteins. Furthermore, stress-induced changes of the phosphorylation of enzymes of central metabolism were observed. The phosphorylation patterns of these proteins were concurrent with changes in enzyme activity. This was reflected by altered levels of metabolites, such as the sugars sucrose and fructose, glycolysis intermediates, and amino acids. Together, our study provides evidence for a link between early signaling in the salt and oxidative stress response that regulates the state transition of photosynthesis and the rearrangement of primary metabolism.

Glaucophyta, rhodophyta, and chloroplastida represent the three main evolutionary lineages that diverged from a common ancestor after primary endosymbiosis. Comparative analyses between members of these three lineages are a rich source of information on ancestral plastid features. We analyzed the composition and the cleavage site of cyanelle transit peptides from the glaucophyte Cyanophora paradoxa by terminal amine labeling of substrates (TAILS), and compared their characteristics to those of representatives of the chloroplastida. Our data show that transit peptide architecture is similar between members of these two lineages. This entails a comparable modular structure, an overrepresentation of serine or alanine and similarities in the amino acid composition around the processing peptidase cleavage site. The most distinctive difference is the overrepresentation of phenylalanine in the N-terminal 1–10 amino acids of cyanelle transit peptides. A quantitative proteome analysis with periplasm-free cyanelles identified 42 out of 262 proteins without the N-terminal phenylalanine, suggesting that the requirement for phenylalanine in the N-terminal region is not absolute. Proteins in this set are on average of low abundance, suggesting that either alternative import pathways are operating specifically for low abundance proteins or that the gene model annotation is incorrect for proteins with fewer EST sequences. We discuss these two possibilities and provide examples for both interpretations.

In eukaryotic cells many diverse cellular functions are regulated by reversible protein phosphorylation. In recent years, phosphoproteomics has become a powerful tool for studying protein phosphorylation because it enables unbiased localization, and site-specific quantification of in vivo phosphorylation of hundreds of proteins in a single experiment. A common strategy for identifying phosphoproteins and their phosphorylation sites from complex biological samples is the enrichment of phosphopeptides from digested cellular lysates followed by mass spectrometry. However, despite high sensitivity of modern mass spectrometers the large dynamic range of protein abundance and the transient nature of protein phosphorylation remained major pitfalls in MS-based phosphoproteomics. This is particularly true for plants in which the presence of secondary metabolites and endogenous compounds, the overabundance of ribulose-1,5-bisphosphate carboxylase and other components of the photosynthetic apparatus, and the concurrent difficulties in protein extraction necessitate two-step phosphoprotein/phosphopeptide enrichment strategies (Nakagami et al., Plant Cell Physiol 53:118–124, 2012).Approaches for label-free peptide quantification are advantageous due to their low cost and experimental simplicity, but they lack precision. These drawbacks can be overcome by metabolic labeling of whole plants with heavy nitrogen (15N) which allows combining two samples very early in the phosphoprotein enrichment workflow. This avoids sample-to-sample variation introduced by the analytical procedures and it results in robust relative quantification values that need no further standardization. The integration of 15N metabolic labeling into tandem metal-oxide affinity chromatography (MOAC) (Hoehenwarter et al., Mol Cell Proteomics 12:369–380, 2013) presents an improved and highly selective approach for the identification and accurate site-specific quantification of low-abundance phosphoproteins that is based on the successive enrichment of light and heavy nitrogen-labeled phosphoproteins and peptides. This improved strategy combines metabolic labeling of whole plants with the stable heavy nitrogen isotope (15N), protein extraction under denaturing conditions, phosphoprotein enrichment using Al(OH)3-based MOAC, and tryptic digest of enriched phosphoproteins followed by TiO2-based MOAC of phosphopeptides and quantitative phosphopeptide measurement by liquid chromatography (LC) and high-resolution accurate mass (HR/AM) mass spectrometry (MS). Thus, tandem MOAC effectively targets the phosphate moiety of phosphoproteins and phosphopeptides and allows probing of the phosphoproteome to unprecedented depth, while 15N metabolic labeling enables accurate relative quantification of measured peptides and direct comparison between samples.