A tissue-specific atlas of mouse protein phosphorylation and expression

Bioinformatic prediction and confirmation of beta-adducin as a novel substrate of glycogen synthase kinase 3

It is important to identify the true substrates of protein kinases because this illuminates the primary function of any kinase. Here, we used bioinformatics and biochemical validation to identify novel brain substrates of the Ser/Thr kinase glycogen synthase kinase 3 (GSK3). Briefly, sequence databases were searched for proteins containing a conserved GSK3 phosphorylation consensus sequence ((S/T)PXX(S/T)P or (S/T)PXXX(S/T)P), as well as other criteria of interest (e.g. brain proteins). Importantly, candidates were highlighted if they had previously been reported to be phosphorylated at these sites by large-scale phosphoproteomic studies. These criteria identified the brain-enriched cytoskeleton-associated protein β-adducin as a likely substrate of GSK3. To confirm this experimentally, it was cloned and subjected to a combination of cell culture and in vitro kinase assays that demonstrated direct phosphorylation by GSK3 in vitro and in cells. Phosphosites were mapped to three separate regions near the C terminus and confirmed using phosphospecific antibodies. Prior priming phosphorylation by Cdk5 enhanced phosphorylation by GSK3. Expression of wild type, but not non-phosphorylatable (GSK3 insensitive), β-adducin increased axon and dendrite elongation in primary cortical neurons. Therefore, phosphorylation of β-adducin by GSK3 promotes efficient neurite outgrowth in neurons.

Correct interpretation of comprehensive phosphorylation dynamics requires normalization by protein expression changes

The interpretation of quantitative phosphoproteomics studies is complicated because each differential phosphorylation event integrates both changes in protein expression and phosphorylation. Here we investigated this phenomenon by performing parallel comparisons of protein expression and phosphorylation in S. cerevisiae. In each of two experiments comparing yeast mutants bearing deletions in FUS3 or STE7 with their wild-type counterparts, we quantified over 4100 proteins, including all members of the yeast mating pathway. We also identified 12,499 unique phosphorylation sites in this work. We demonstrate the critical importance of controlling the protein-level false-discovery rate and provide a novel method to assess the accuracy of protein false-discovery rate estimates. For the first time, 96% of nonredundant phosphopeptide ratios could be calibrated by protein levels, allowing truly differential phosphorylation to be distinguished from altered protein expression. This revealed a starkly different view, with 25% of seemingly differential phosphopeptides now attributed to changes in protein expression. Combined protein expression and phosphorylation surveys uncovered both independent and concerted changes in protein expression and phosphorylation, while highlighting the partially redundant role of a second MAPK (Kss1) in the mating pathway.

A solid phase extraction-based platform for rapid phosphoproteomic analysis

Protein phosphorylation is among the most common and intensely studied post-translational protein modification. It plays crucial roles in virtually all cellular processes and has been implicated in numerous human diseases, including cancer. Traditional biochemical and genetic methods for identifying and monitoring sites of phosphorylation are laborious and slow and in recent years have largely been replaced by mass spectrometric analysis. Improved methods for phosphopeptide enrichment coupled with faster and more sensitive mass spectrometers have led to an explosion in the size of phosphoproteomic datasets. However, wider application of these methods is limited by equipment costs and the resultant high demand for instrument time as well as by a technology gap between biologists and mass spectrometrists. Here we describe a modified two-step enrichment strategy that employs lysC digestion and step elution from self-packed strong cation exchange (SCX) solid phase extraction (SPE) columns followed by immobilized metal ion affinity chromatography (IMAC) and LC-MS/MS analysis using a hybrid LTQ Orbitrap Velos mass spectrometer. The SCX procedure does not require an HPLC system, demands little expertise, and because multiple samples can be processed in parallel, can provide a large savings of time and labor. We demonstrate this method in conjunction with stable isotope labeling to quantitate peptides harboring >8000 unique phosphorylation sites in yeast in 12h of instrument analysis time and examine the impact of enzyme choice and instrument platform.

Higher-energy collision-activated dissociation without a dedicated collision cell

Beam-type collisional activation dissociation (HCD) offers many advantages over resonant excitation collision-activated dissociation, including improved identification of phosphorylated peptides and compatibility with isobaric tag-based quantitation (e.g. tandem mass tag (TMT) and iTRAQ). However, HCD typically requires specially designed and dedicated collision cells. Here we demonstrate that HCD can be performed in the ion injection pathway of a mass spectrometer with a standard atmospheric inlet (iHCD). Testing this method on complex peptide mixtures revealed similar identification rates to collision-activated dissociation (2883 versus 2730 IDs for iHCD/CAD, respectively) and precursor-product-conversion efficiency comparable to that achieved within a dedicated collision cell. Compared with pulsed-q dissociation, a quadrupole ion trap-based method that retains low-mass isobaric tag reporter ions, iHCD yielded isobaric tag for relative and absolute quantification reporter ions 10-fold more intense. This method involves no additional hardware and can theoretically be implemented on any mass spectrometer with an atmospheric inlet.

Phosphoryl-EZH-ion

Polycomb group (PcG) proteins regulate gene expression in embryonic and adult stem cells, but the mechanisms responsible for PcG gene targeting and regulation remain largely unknown. Recent evidence shows that EZH2, the enzymatic subunit of Polycomb Repressive Complex 2 (PRC2), is a nuclear phosphoprotein linking cell-cycle-intrinsic or extracellular signals to specific epigenetic signatures.

Genome-wide evolutionary conservation of N-glycosylation sites

Although posttranslational protein modifications are generally thought to perform important cellular functions, recent studies showed that a large fraction of phosphorylation sites are not evolutionarily conserved. Whether the same is true for other protein modifications, such as N-glycosylation is an open question. N-glycosylation is a form of cotranslational and posttranslational modification that occurs by enzymatic addition of a polysaccharide, or glycan, to an asparagine (N) residue of a protein. Examining a large set of experimentally determined mouse N-glycosylation sites, we find that the evolutionary rate of glycosylated asparagines is significantly lower than that of nonglycosylated asparagines of the same proteins. We further confirm that the conservation of glycosylated asparagines is accompanied by the conservation of the canonical motif sequence for glycosylation, suggesting that the above substitution rate difference is related to glycosylation. Interestingly, when solvent accessibility is considered, the substitution rate disparity between glycosylated and nonglycosylated asparagines is highly significant at solvent accessible sites but not at solvent inaccessible sites. Thus, although the solvent inaccessible glycosylation sites were experimentally identified, they are unlikely to be genuine or physiologically important. For solvent accessible asparagines, our analysis reveals a widespread and strong functional constraint on glycosylation, unlike what has been observed for phosphorylation sites in most studies, including our own analysis. Because the majority of N-glycosylation occurs at solvent accessible sites, our results show an overall functional importance for N-glycosylation.

Effective representation and storage of mass spectrometry-based proteomic data sets for the scientific community

Mass spectrometry-based proteomics has emerged as a technology of choice for global analysis of cell signaling networks. However, reporting and sharing of MS data are often haphazard, limiting the usefulness of proteomics to the signaling community. We argue that raw data should always be provided with proteomics studies together with detailed peptide and protein identification and quantification information. Statistical criteria for peptide identification and their posttranslational modifications have largely been established for individual projects. However, the current practice of indiscriminately incorporating these individual results into databases such as UniProt is problematic. Because of the vast differences in underlying data quality, we advocate a differentiated annotation of data by level of reliability. Requirements for the reporting of quantitative data are being developed, but there are few mechanisms for community-wide sharing of these data.

The potential cost of high-throughput proteomics

Improvements in speed and mass accuracy of mass spectrometers revolutionized proteomics, with high-throughput proteomics enabling the profiling of complete proteomes and thousands of posttranslational modification sites. The limits of high-throughput proteomics are constantly pushed to new frontiers, and mass spectrometry-based proteomics may eventually permit the analysis of protein expression profiles in less than a day. Increased data acquisition speed has led to a dramatic increase in the total number of tandem mass spectrometry (MS/MS) spectra, such that millions of MS/MS spectra are now acquired in a given set of analyses. Many of these spectra are insufficiently validated; instead, statistical tools are commonly used to estimate false-positive or false-discovery rates for these data sets. Many laboratories may not realize the costs associated with using these widely available, but minimally validated, data sets. The costs associated with use of these data can include missed opportunities for biological insight, the pollution of databases with increasing numbers of false-positive identifications, and time spent by biologists investigating false leads, resulting in a lack of faith in proteomics data. Improved strategies for data validation need to be implemented, along with a change in the culture of high-throughput proteomics, linking proteomics closer to biology.