We describe a method to identify cross-linked peptides from complex samples and large protein sequence databases. The advance was achieved by combining isotopically tagged cross-linkers, chromatographic enrichment, targeted proteomics, and a novel search engine called xQuest. This software reduces the search space by an upstream candidatepeptide search before the recombination step; we show that xQuest can identify cross-linked peptides from a total E. coli lysate with an unrestricted database search.

The ability to routinely analyze and quantitatively measure changes in protein phosphorylation on a proteome-wide scale is essential for biological and clinical research. We assessed the ability of three common phosphopeptide isolation methods (phosphoramidate chemistry (PAC), immobilized metal affinity chromatography (IMAC) and titanium dioxide) to reproducibly, specifically and comprehensively isolate phosphopeptides from complex mixtures. Phosphopeptides were isolated from aliquots of a tryptic digest of the cytosolic fraction of Drosophila melanogaster Kc167 cells and analyzed by liquid chromatography-electrospray ionization tandem mass spectrometry. Each method reproducibly isolated phosphopeptides. The methods, however, differed in their specificity of isolation and, notably, in the set of phosphopeptides isolated. The results suggest that the three methods detect different, partially overlapping segments of the phosphoproteome and that, at present, no single method is sufficient for a comprehensive phosphoproteome analysis.

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LC-MS/MSOver the past decade, MS has emerged as the method of choice for the identification and quantification of proteins in very complex biological samples (1). In the most widely used implementation, referred to as shotgun proteomics, protein samples are first digested, and the resulting peptide mixtures are then chromatographically separated and finally sequenced by automated MS/MS. Because of its conceptual and experimental simplicity, the shotgun approach has become a very popular method for the identification of proteins in a wide range of biological samples and, in combination with stable isotope labeling, for quantitative proteomics studies (2-4). Recent technical improvements in MS instrumentation, database searching, and result validation as well as advances in database annotation now make it possible to routinely identify hundreds to a few thousands of proteins in complex biological samples (5-8).Despite this impressive progress, shotgun proteomics is not yet capable of characterizing whole proteomes and presents obvious biases, among them the discrimination against protein species of low abundance (5,8). This is primarily a consequence of limited sequencing speed of current LC-ESI-MS/MS systems that are incapable of analyzing each precursor ion detected in complex samples together with the redundant selection of a subset of precursor ions even if precautions like dynamic exclusion are applied. Therefore, even in repeat analyses of the same sample exhaustive identification of the low intensity precursors is not achieved (9 -11).In contrast to these approaches based on data-dependent acquisition (DDA) 1 precursor ion selection, directed peptide sequencing provides the advantage of focusing the MS/MS analysis on non-redundant and information-rich precursor ions, thereby better managing the analysis time and increasing the depth of analysis (12, 13). In this regard, a two-stage strategy by which all MS1 features that represent peptides are extracted from LC-MS maps and subsequently subjected to targeted sequencing, in principle, should lead to the identification of all detectable precursors (14). Because the acquisition of MS1 and MS2 spectra is naturally decoupled in MALDI-MS/MS, this platform is well suited for directed sequencing and has been applied to selectively analyze differential expression or modifications of proteins (15,16).The same principle is also applicable to ESI-MS, which has the potential to provide much higher sequencing speed in From the ‡Institute

Extracellular pH and the Na⁺/H⁺ exchanger (NHE1) modulate tumor cell migration. Yet, the pH nanoenvironment at the outer surface of the cell membrane (pH_em) where cell/matrix interaction occurs and matrix metalloproteinases work was never measured. We present a method to measure this pH nanoenvironment using proton-sensitive dyes to label the outer leaflet of the plasma membrane or the glycocalyx of human melanoma cells. Polarized cells generate an extracellular proton gradient at their surface that increases from the rear end to the leading edge of the lamellipodium along the direction of movement. This gradient collapses upon NHE1 inhibition by HOE642. NHE1 stimulation by intracellular acidification increases the difference in pH_em between the tips of lamellipodia and the cell body in a Na⁺ dependent way. Thus, cells create a pH nanoenvironment that promotes cell migration by facilitating cell adhesion at their front and the release of cell/matrix contacts at their rear part.