Mass spectrometry-driven phosphoproteomics: patterning the systems biology mosaic.

Protein phosphorylation is the best-studied posttranslational modification and plays a role in virtually every biological process. Phosphoproteomics is the analysis of protein phosphorylation on a proteome-wide scale, and mainly uses the same instrumentation and analogous strategies as conventional mass spectrometry (MS)-based proteomics. Measurements can be performed either in a discovery-type, also known as shotgun mode, or in a targeted manner which monitors a set of a priori known phosphopeptides, such as members of a signal transduction pathway, across biological samples. Here, we delineate the different experimental levels at which measures can be taken to optimize the scope, reliability, and information content of phosphoproteomic analyses. Various chromatographic and chemical protocols exist to physically enrich phosphopeptides from proteolytic digests of biological samples. Subsequent mass spectrometric analysis revolves around peptide ion fragmentation to generate sequence information and identify the backbone sequence of phosphopeptides as well as the phosphate group attachment site(s), and different modes of fragmentation like collision-induced dissociation (CID), electron transfer dissociation (ETD), and higher energy collisional dissociation (HCD) have been established for phosphopeptide analysis. Computational tools are important for the identification and quantification of phosphopeptides and mapping of phosphorylation sites, the deposition of large-scale phosphoproteome datasets in public databases, and the extraction of biologically meaningful information by data mining, integration with other data types, and descriptive or predictive modeling. Finally, we discuss how orthogonal experimental approaches can be employed to validate newly identified phosphorylation sites on a biochemical, mechanistic, and physiological level.

Src tyrosine kinase signaling antagonizes nuclear localization of FOXO and inhibits its transcription factor activity.

Biochemical experiments in mammalian cells have linked Src family kinase activity to the insulin signaling pathway. To explore the physiological link between Src and a central insulin pathway effector, we investigated the effect of different Src signaling levels on the Drosophila transcription factor dFOXO in vivo. Ectopic activation of Src42A in the starved larval fatbody was sufficient to drive dFOXO out of the nucleus. When Src signaling levels were lowered by means of loss-of-function mutations or pharmacological inhibition, dFOXO localization was shifted to the nucleus in growing animals, and transcription of the dFOXO target genes d4E-BP and dInR was induced. dFOXO loss-of-function mutations rescued the induction of dFOXO target gene expression and the body size reduction of Src42A mutant larvae, establishing dFOXO as a critical downstream effector of Src signaling. Furthermore, we provide evidence that the regulation of FOXO transcription factors by Src is evolutionarily conserved in mammalian cells.

Targeted proteome investigation via selected reaction monitoring mass spectrometry.

Due to the enormous complexity of proteomes which constitute the entirety of protein species expressed by a certain cell or tissue, proteome-wide studies performed in discovery mode are still limited in their ability to reproducibly identify and quantify all proteins present in complex biological samples. Therefore, the targeted analysis of informative subsets of the proteome has been beneficial to generate reproducible data sets across multiple samples. Here we review the repertoire of antibody- and mass spectrometry (MS) -based analytical tools which is currently available for the directed analysis of predefined sets of proteins. The topics of emphasis for this review are Selected Reaction Monitoring (SRM) mass spectrometry, emerging tools to control error rates in targeted proteomic experiments, and some representative examples of applications. The ability to cost- and time-efficiently generate specific and quantitative assays for large numbers of proteins and posttranslational modifications has the potential to greatly expand the range of targeted proteomic coverage in biological studies. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

Modularity and hormone sensitivity of the Drosophila melanogaster insulin receptor/target of rapamycin interaction proteome.

Genetic analysis in Drosophila melanogaster has been widely used to identify a system of genes that control cell growth in response to insulin and nutrients. Many of these genes encode components of the insulin receptor/target of rapamycin (InR/TOR) pathway. However, the biochemical context of this regulatory system is still poorly characterized in Drosophila. Here, we present the first quantitative study that systematically characterizes the modularity and hormone sensitivity of the interaction proteome underlying growth control by the dInR/TOR pathway. Applying quantitative affinity purification and mass spectrometry, we identified 97 high confidence protein interactions among 58 network components. In all, 22% of the detected interactions were regulated by insulin affecting membrane proximal as well as intracellular signaling complexes. Systematic functional analysis linked a subset of network components to the control of dTORC1 and dTORC2 activity. Furthermore, our data suggest the presence of three distinct dTOR kinase complexes, including the evolutionary conserved dTTT complex (Drosophila TOR, TELO2, TTI1). Subsequent genetic studies in flies suggest a role for dTTT in controlling cell growth via a dTORC1- and dTORC2-dependent mechanism.

Quantitative analysis of protein complex constituents and their phosphorylation states on a LTQ-Orbitrap instrument.

Cellular functions are largely carried out by noncovalent protein complexes that may exist within the cell as stable modules or as assemblies of dynamically changing composition, whose formation and decomposition are triggered in response to extracellular stimuli. The protein constituents of complexes often exhibit post-translational modifications such as phosphorylation that can impact their ability to interact with other proteins and thus to form multicomponent complexes. A complete characterization of a particular protein complex thus requires determining both, the identity of interacting proteins and their covalent modifications, in terms of attachment sites and stoichiometry. We have previously developed a protocol which identifies genuine constituents of partially purified protein complexes and concurrently determines their phosphorylation sites and levels in a single LC-MS/MS analysis performed on a MALDI-TOF/TOF instrument (Pflieger, D.; Junger, M. A.; Muller, M.; Rinner, O.; Lee, H.; Gehrig, P. M.; Gstaiger, M.; Aebersold, R. Mol. Cell. Proteomics 2008 , 7 , 326 - 346). The method combines fourplex iTRAQ labeling (isobaric tags for relative and absolute quantification) and phosphatase treatment of peptide samples derived from the tryptic digestion of isolated complexes. To test the performances of this method with nanoESI and different peptide fragmentation modes, possibly better suited for the identification of phosphorylated sequences than MALDI-TOF/TOF-MS, we have implemented it on the nanoESI-LTQ-Orbitrap instrument. The model protein beta-casein was used to optimize the conditions with respect to sensitivity and quantitative accuracy: a combination of CID fragmentation in the linear ion trap and Higher energy Collision Dissociation (HCD) appeared optimal to obtain reliable and robust identification and quantification data. The optimized conditions were then applied to identify and estimate the respective levels of phosphorylation sites on the purified, autoactivated tyrosine kinase domain of Fibroblast Growth Factor Receptor 3 (FGFR3-KD) and to analyze complexes formed around the insulin receptor substrate homologue CHICO immunopurified from Drosophila melanogaster cells that were either stimulated with insulin or left untreated. These new analyses allowed us to improve the assignment of the phosphorylation sites of some peptides previously detected by MALDI-TOF/TOF analysis and to identify additional phosphorylated sequences in CHICO and in the insulin receptor.

The Drosophila FoxA ortholog Fork head regulates growth and gene expression downstream of Target of rapamycin.

Forkhead transcription factors of the FoxO subfamily regulate gene expression programs downstream of the insulin signaling network. It is less clear which proteins mediate transcriptional control exerted by Target of rapamycin (TOR) signaling, but recent studies in nematodes suggest a role for FoxA transcription factors downstream of TOR. In this study we present evidence that outlines a similar connection in Drosophila, in which the FoxA protein Fork head (FKH) regulates cellular and organismal size downstream of TOR. We find that ectopic expression and targeted knockdown of FKH in larval tissues elicits different size phenotypes depending on nutrient state and TOR signaling levels. FKH overexpression has a negative effect on growth under fed conditions, and this phenotype is not further exacerbated by inhibition of TOR via rapamycin feeding. Under conditions of starvation or low TOR signaling levels, knockdown of FKH attenuates the size reduction associated with these conditions. Subcellular localization of endogenous FKH protein is shifted from predominantly cytoplasmic on a high-protein diet to a pronounced nuclear accumulation in animals with reduced levels of TOR or fed with rapamycin. Two putative FKH target genes, CG6770 and cabut, are transcriptionally induced by rapamycin or FKH expression, and silenced by FKH knockdown. Induction of both target genes in heterozygous TOR mutant animals is suppressed by mutations in fkh. Furthermore, TOR signaling levels and FKH impact on transcription of the dFOXO target gene d4E-BP, implying a point of crosstalk with the insulin pathway. In summary, our observations show that an alteration of FKH levels has an effect on cellular and organismal size, and that FKH function is required for the growth inhibition and target gene induction caused by low TOR signaling levels.

Quantitative proteomic analysis of protein complexes: concurrent identification of interactors and their state of phosphorylation.

Protein complexes have largely been studied by immunoaffinity purification and (mass spectrometric) analysis. Although this approach has been widely and successfully used it is limited because it has difficulties reliably discriminating true from false protein complex components, identifying post-translational modifications, and detecting quantitative changes in complex composition or state of modification of complex components. We have developed a protocol that enables us to determine, in a single LC-MALDI-TOF/TOF analysis, the true protein constituents of a complex, to detect changes in the complex composition, and to localize phosphorylation sites and estimate their respective stoichiometry. The method is based on the combination of fourplex iTRAQ (isobaric tags for relative and absolute quantification) isobaric labeling and protein phosphatase treatment of substrates. It was evaluated on model peptides and proteins and on the complex Ccl1-Kin28-Tfb3 isolated by tandem affinity purification from yeast cells. The two known phosphosites in Kin28 and Tfb3 could be reproducibly shown to be fully modified. The protocol was then applied to the analysis of samples immunopurified from Drosophila melanogaster cells expressing an epitope-tagged form of the insulin receptor substrate homologue Chico. These experiments allowed us to identify 14-3-3epsilon, 14-3-3zeta, and the insulin receptor as specific Chico interactors. In a further experiment, we compared the immunopurified materials obtained from tagged Chico-expressing cells that were either treated with insulin or left unstimulated. This analysis showed that hormone stimulation increases the association of 14-3-3 proteins with Chico and modulates several phosphorylation sites of the bait, some of which are located within predicted recognition motives of 14-3-3 proteins.

An integrated chemical, mass spectrometric and computational strategy for (quantitative) phosphoproteomics: application to Drosophila melanogaster Kc167 cells.

Current methods for phosphoproteome analysis have several limitations. First, most methods for phosphopeptide enrichment lack the specificity to truly purify phosphopeptides. Second, fragmentation spectra of phosphopeptides, in particular those of phosphoserine and phosphothreonine containing peptides, are often dominated by the loss of the phosphate group(s) and therefore lack the information required to identify the peptide sequence and the site of phosphorylation, and third, sequence database search engines and statistical models for data validation are not optimized for the specific fragmentation properties of phosphorylated peptides. Consequently, phosphoproteomic data are characterized by large and unknown rates of false positive and false negative phosphorylation sites. Here we present an integrated chemical, mass spectrometric and computational strategy to improve the efficiency, specificity and confidence in the identification of phosphopeptides and their site(s) of phosphorylation. Phosphopeptides were isolated with high specificity through a simple derivatization procedure based on phosphoramidate chemistry. Identification of phosphopeptides, their site(s) of phosphorylation and the corresponding phosphoproteins was achieved by the optimization of the mass spectrometric data acquisition procedure, the computational tools for database searching and the data post processing. The strategy was applied to the mapping of phosphorylation sites of a purified transcription factor, dFOXO and for the global analysis of protein phosphorylation of Drosophila melanogaster Kc167 cells.

Added value for tandem mass spectrometry shotgun proteomics data validation through isoelectric focusing of peptides.

A very popular approach in proteomics is the so-called "shotgun LC-MS/MS" strategy. In its mostly used form, a total protein digest is separated by ion exchange fractionation in the first dimension followed by off- or on-line RP LC-MS/MS. We replaced the first dimension by isoelectric focusing in the liquid phase using the Off-Gel device producing 15 fractions. As peptides are separated by their isoelectric point in the first dimension and hydrophobicity in the second, those experimentally derived parameters (pI and R(T)) can be used for the validation of potentially identified peptides. We applied this strategy to a cellular extract of Drosophila Kc167 cells and identified peptides with two different database search engines, namely PHENYX and SEQUEST, with PeptideProphet validation of the SEQUEST results. PHENYX returned 7582 potential peptide identifications and SEQUEST 7629. The SEQUEST results were reduced to 2006 identifications by validation with PeptideProphet. Validation of the PeptideProphet, SEQUEST and PHENYX results by pI and R(T) parameters confirmed 1837 PeptideProphet identifications while in the remainder of the SEQUEST results another 1130 peptides were found to be likely hits. The validation on PHENYX resulted in the fixation of a solid p-value threshold of <1 x 10(-04) that sets by itself the correct identification confidence to >95%, and a final count of 2034 highly confident peptide identifications was achieved after pI and R(T) validation. Although the PeptideProphet and PHENYX datasets have a very high confidence the overlap of common identifications was only at 79.4%, to be explained by the fact that data interpretation was done searching different protein databases with two search engines of different algorithms. The approach used in this study allowed for an automated and improved data validation process for shotgun proteomics projects producing MS/MS peptide identification results of very high confidence.

Long-lived Drosophila with overexpressed dFOXO in adult fat body.

Reduced activity of the insulin/insulin-like growth factor signaling (IIS) pathway increases life-span in diverse organisms. We investigated the timing of the effect of reduced IIS on life-span and the role of a potential target tissue, the fat body. We overexpressed dFOXO, a downstream effector of IIS, in the adult Drosophila fat body, which increased life-span and reduced fecundity of females but had no effect on male life-span. The role of FOXO transcription factors and the adipose tissue are therefore evolutionarily conserved in the regulation of aging, and reduction of IIS in the adult is sufficient to mediate its effects on life-span and fecundity.

The Drosophila forkhead transcription factor FOXO mediates the reduction in cell number associated with reduced insulin signaling.

BACKGROUND: Forkhead transcription factors belonging to the FOXO subfamily are negatively regulated by protein kinase B (PKB) in response to signaling by insulin and insulin-like growth factor in Caenorhabditis elegans and mammals. In Drosophila, the insulin-signaling pathway regulates the size of cells, organs, and the entire body in response to nutrient availability, by controlling both cell size and cell number. In this study, we present a genetic characterization of dFOXO, the only Drosophila FOXO ortholog. RESULTS: Ectopic expression of dFOXO and human FOXO3a induced organ-size reduction and cell death in a manner dependent on phosphoinositide (PI) 3-kinase and nutrient levels. Surprisingly, flies homozygous for dFOXO null alleles are viable and of normal size. They are, however, more sensitive to oxidative stress. Furthermore, dFOXO function is required for growth inhibition associated with reduced insulin signaling. Loss of dFOXO suppresses the reduction in cell number but not the cell-size reduction elicited by mutations in the insulin-signaling pathway. By microarray analysis and subsequent genetic validation, we have identified d4E-BP, which encodes a translation inhibitor, as a relevant dFOXO target gene. CONCLUSION: Our results show that dFOXO is a crucial mediator of insulin signaling in Drosophila, mediating the reduction in cell number in insulin-signaling mutants. We propose that in response to cellular stresses, such as nutrient deprivation or increased levels of reactive oxygen species, dFOXO is activated and inhibits growth through the action of target genes such as d4E-BP.