Improving the sensitivity of protein–protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/β mass detection scheme and establishes protein–peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher sensitivity over standard techniques. In experiments using real data sets, it also identified 65.6% more cross-link spectrum matches and 48.7% more unique cross-links.

Isotopically dimethyl labeling was applied in a quantitative post-translational modification (PTM) proteomic study of phosphoproteomic changes in the drought responses of two contrasting soybean cultivars. A total of 9457 phosphopeptides were identified subsequently, corresponding to 4571 phosphoprotein groups and 3889 leading phosphoproteins, which contained nine kinase families consisting of 279 kinases. These phosphoproteins contained a total of 8087 phosphosites, 6106 of which were newly identified and constituted 54% of the current soybean phosphosite repository. These phosphosites were converted into the highly conserved kinase docking sites by bioinformatics analysis, which predicted six kinase families that matched with those newly found nine kinase families. The overly post-translationally modified proteins (OPP) occupies 2.1% of these leading phosphoproteins. Most of these OPPs are photoreceptors, mRNA-, histone-, and phospholipid-binding proteins, as well as protein kinase/phosphatases. The subgroup population distribution of phosphoproteins over the number of phosphosites of phosphoproteins follows the exponential decay law, Y = 4.13e−0.098X − 0.04. Out of 218 significantly regulated unique phosphopeptide groups, 188 phosphoproteins were regulated by the drought-tolerant cultivar under the water loss condition. These significantly regulated phosphoproteins (SRP) are mainly enriched in the biological functions of water transport and deprivation, methionine metabolic processes, photosynthesis/light reaction, and response to cadmium ion, osmotic stress, and ABA response. Seventeen and 15 SRPs are protein kinases/phosphatases and transcription factors, respectively. Bioinformatics analysis again revealed that three members of the calcium dependent protein kinase family (CAMK family), GmSRK2I, GmCIPK25, and GmAKINβ1 kinases, constitute a phosphor-relay-mediated signal transduction network, regulating ion channel activities and many nuclear events in this drought-tolerant cultivar, which presumably contributes to the development of the soybean drought tolerance under water deprivation process.

Improving the sensitivity of protein-protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/β mass detection scheme and establishes protein-peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic datasets and hybrid simulated datasets, ECL-PF achieved three-fold higher sensitivity over standard techniques. In experiments using real datasets, it also identified 91.6% more cross-link spectrum matches and 52.6% more unique cross-links.