MSQuant, an open source platform for mass spectrometry-based quantitative proteomics

IsoQuant: a software tool for stable isotope labeling by amino acids in cell culture-based mass spectrometry quantitation

Accurate protein identification and quantitation are critical when interpreting the biological relevance of large-scale shotgun proteomics data sets. Although significant technical advances in peptide and protein identification have been made, accurate quantitation of high-throughput data sets remains a key challenge in mass spectrometry data analysis and is a labor intensive process for many proteomics laboratories. Here, we report a new SILAC-based proteomics quantitation software tool, named IsoQuant, which is used to process high mass accuracy mass spectrometry data. IsoQuant offers a convenient quantitation framework to calculate peptide/protein relative abundance ratios. At the same time, it also includes a visualization platform that permits users to validate the quality of SILAC peptide and protein ratios. The program is written in the C# programming language under the Microsoft .NET framework version 4.0 and has been tested to be compatible with both 32-bit and 64-bit Windows 7. It is freely available to noncommercial users at http://www.proteomeumb.org/MZw.html .

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data

Background

The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates.

Results

VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data.

Conclusions

VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

Probing the specificity of protein-protein interactions by quantitative chemical proteomics

Chemical proteomics is a versatile tool to investigate protein-small molecule interactions, but can be extended to probe also secondary binding investigating small molecule-protein 1-protein 2 interactions, providing insight into protein scaffolds. This application of chemical proteomics has in particular been applied extensively to cyclic nucleotide (cAMP, cGMP) signaling. cAMP regulates cellular functions primarily by activating cAMP-dependent protein kinase (PKA). Compartmentalization of PKA plays an important role in the specificity of cAMP signaling events and is mediated by interaction of the regulatory subunit (PKA-R) with A-kinase anchoring proteins (AKAPs), which often form the core of even larger protein machineries. The selective binding of AKAPs to one of the major isoforms PKA-R type I (PKA-RI) and PKA-R type II (PKA-RII) is an important feature of cAMP/PKA signaling. However, this specificity is not well established for most AKAPs. Here, we describe a chemical proteomics approach that combines cAMP-based affinity chromatography with quantitative mass spectrometry to investigate PKA-R isoform/AKAP specificity directly in lysates of cells and tissues of any origin. With this tool, several novel PKA-R/AKAP specificities can be easily resolved.

Proteomic analysis of stem cell differentiation and early development

Genomics methodologies have advanced to the extent that it is now possible to interrogate the gene expression in a single cell but proteomics has traditionally lagged behind and required much greater cellular input and was not quantitative. Coupling protein with gene expression data is essential for understanding how cell behavior is regulated. Advances primarily in mass spectrometry have, however, greatly improved the sensitivity of proteomics methods over the last decade and the outcome of proteomic analyses can now also be quantified. Nevertheless, it is still difficult to obtain sufficient tissue from staged mammalian embryos to combine proteomic and genomic analyses. Recent developments in pluripotent stem cell biology have in part addressed this issue by providing surrogate scalable cell systems in which early developmental events can be modeled. Here we present an overview of current proteomics methodologies and the kind of information this can provide on the biology of human and mouse pluripotent stem cells.

Cross-talk between phosphorylation and lysine acetylation in a genome-reduced bacterium

The effect of kinase, phosphatase and N-acetyltransferase deletions on proteome phosphorylation and acetylation was investigated in Mycoplasma pneumoniae. Bi-directional cross-talk between post-transcriptional modifications suggests an underlying regulatory molecular code in prokaryotes.

Post-translational modifications (PTMs) change the chemical properties of proteins, conferring diversity beyond the amino-acid sequence. Proteins are often modified on multiple sites. A PTM code has been proposed, whereby modifications at specific positions influence further modifications. These regulatory circuits though have rarely been studied on a large-scale; conservation in prokaryotes remains elusive.

Here, we studied two important PTMs– phosphorylation and lysine acetylation in the small bacterium Mycoplasma pneumoniae. We combined genetics and quantitative mass spectrometry to measure the effect of systematic kinase, phosphatase and N-acetyltransferase deletions on proteome abundance, phosphorylation and lysine acetylation.

The data set represents a comprehensive analysis of both phosphorylation and lysine acetylation in a single prokaryote. It reveals (1) proteins often carry multiple modifications and multiple types of PTMs, reminiscent of the PTM code proposed in eukaryotes, (2) phosphorylation exerts pleiotropic effect on proteins abundances, phosphorylation, but also lysine acetylation, (3) the cross-talk between the two PTMs is bi-directional and (4) PTMs are frequently located at interaction interfaces and in multifunctional proteins, illustrating how PTMs could modulate protein functions affecting the way they interact.

The study provides an unbiased and quantitative view on cross-talk between phosphorylation and lysine acetylation. It suggests that these regulatory circuits are a fundamental principle of regulation that might have evolved before the divergence of prokaryotes and eukaryotes.

Protein post-translational modifications (PTMs) represent important regulatory states that when combined have been hypothesized to act as molecular codes and to generate a functional diversity beyond genome and transcriptome. We systematically investigate the interplay of protein phosphorylation with other post-transcriptional regulatory mechanisms in the genome-reduced bacterium Mycoplasma pneumoniae. Systematic perturbations by deletion of its only two protein kinases and its unique protein phosphatase identified not only the protein-specific effect on the phosphorylation network, but also a modulation of proteome abundance and lysine acetylation patterns, mostly in the absence of transcriptional changes. Reciprocally, deletion of the two putative N-acetyltransferases affects protein phosphorylation, confirming cross-talk between the two PTMs. The measured M. pneumoniae phosphoproteome and lysine acetylome revealed that both PTMs are very common, that (as in Eukaryotes) they often co-occur within the same protein and that they are frequently observed at interaction interfaces and in multifunctional proteins. The results imply previously unreported hidden layers of post-transcriptional regulation intertwining phosphorylation with lysine acetylation and other mechanisms that define the functional state of a cell.

Sorafenib-induced mitochondrial complex I inactivation and cell death in human neuroblastoma cells

Sorafenib is a multikinase inhibitor that is approved for use against renal cell and hepatocellular carcinoma. We found that sorafenib potently induced cell death in human neuroblastoma cells. To understand the molecular basis of sorafenib-mediated cell death in human SH-SY5Y cells, we performed a temporal quantitative proteome analysis. The results showed significant quantitative changes of 193 unique proteins. Bioinformatics-assisted pathway analysis of the regulated proteins revealed that mitochondrial proteins, especially components of the electron transport chain and the mitochondrial ribosomes, were significantly affected upon exposure to sorafenib. The observed down-regulation of the respiratory chain complex I (NADH dehydrogenase) was accompanied with loss of mitochondrial transmembrane potential (Δψm) and complete impairment of complex I enzyme activity. The destabilization of complex I subunits was consistent, rapid, and independent of caspase activation as well as Bcl-2 overexpression. This study provides an overview of the molecular machinery driving sorafenib-mediated cell death in neuroblastoma cells and suggests that sorafenib could be a potential therapeutic drug for the treatment of neuroblastoma.

Identification of autophagosome-associated proteins and regulators by quantitative proteomic analysis and genetic screens

Autophagy is one of the major intracellular catabolic pathways, but little is known about the composition of autophagosomes. To study the associated proteins, we isolated autophagosomes from human breast cancer cells using two different biochemical methods and three stimulus types: amino acid deprivation or rapamycin or concanamycin A treatment. The autophagosome-associated proteins were dependent on stimulus, but a core set of proteins was stimulus-independent. Remarkably, proteasomal proteins were abundant among the stimulus-independent common autophagosome-associated proteins, and the activation of autophagy significantly decreased the cellular proteasome level and activity supporting interplay between the two degradation pathways. A screen of yeast strains defective in the orthologs of the human genes encoding for a common set of autophagosome-associated proteins revealed several regulators of autophagy, including subunits of the retromer complex. The combined spatiotemporal proteomic and genetic data sets presented here provide a basis for further characterization of autophagosome biogenesis and cargo selection.

The use of heavy nitrogen in quantitative proteomics experiments in plants

In the growing field of plant systems biology, there is an undisputed need for methods allowing accurate quantitation of proteins and metabolites. As autotrophic organisms, plants can easily metabolize different nitrogen isotopes, resulting in proteins and metabolites with distinct molecular mass that can be separated on a mass spectrometer. In comparative quantitative experiments, treated and untreated samples are differentially labeled by nitrogen isotopes and jointly processed, thereby minimizing sample-to-sample variation. In recent years, heavy nitrogen labeling has become a widely used strategy in quantitative proteomics and novel approaches have been developed for metabolite identification. Here, we present an overview of currently used experimental strategies in heavy nitrogen labeling in plants and provide background on the history and function of this quantitation technique.

Characterization of the redox activity and disulfide bond formation in apurinic/apyrimidinic endonuclease

Apurinic/apyrimidinic endonuclease (APE1) is an unusual nuclear redox factor in which the redox-active cysteines identified to date, C65 and C93, are surface inaccessible residues whose activities may be influenced by partial unfolding of APE1. To assess the role of the five remaining cysteines in APE1's redox activity, double-cysteine mutants were analyzed, excluding C65A, which is redox-inactive as a single mutant. C93A/C99A APE1 was found to be redox-inactive, whereas other double-cysteine mutants retained the same redox activity as that observed for C93A APE1. To determine whether these three cysteines, C65, C93, and C99, were sufficient for redox activity, all other cysteines were substituted with alanine, and this protein was shown to be fully redox-active. Mutants with impaired redox activity failed to stimulate cell proliferation, establishing an important role for APE1's redox activity in cell growth. Disulfide bond formation upon oxidation of APE1 was analyzed by proteolysis of the protein followed by mass spectrometry analysis. Within 5 min of exposure to hydrogen peroxide, a single disulfide bond formed between C65 and C138 followed by the formation of three additional disulfide bonds within 15 min; 10 total disulfide bonds formed within 1 h. A single mixed-disulfide bond involving C99 of APE1 was observed for the reaction of oxidized APE1 with thioredoxin (TRX). Disulfide-bonded APE1 or APE1-TRX species were further characterized by size exclusion chromatography and found to form large complexes. Taken together, our data suggest that APE1 is a unique redox factor with properties distinct from those of other redox factors.

Efficient enrichment of phosphopeptides by magnetic TiO₂-coated carbon-encapsulated iron nanoparticles

Titanium dioxide (TiO₂) has been widely used for phosphopeptide enrichment. Several approaches have been reported to produce magnetic TiO₂ affinity probes. In this report, we present a facile approach to immobilize TiO₂ onto poly(acrylic acid)-functionalized magnetic carbon-encapsulated iron nanoparticles as affinity probes for efficient enrichment of phosphopeptides. By using the new magnetic TiO₂ affinity probes, denoted as TiO₂-coated Fe@CNPs, rapid and effective MALDI-TOF MS profiling of phosphopeptides was demonstrated in different model systems such as tryptic digests of β-casein, and complex β-casein/BSA mixture. The TiO₂-coated Fe@CNPs out-performed the commercial TiO₂-coated magnetic beads for detection of phosphopeptides from tryptic digests of β-casein/BSA mixture with a molar ratio of 1:100. The new TiO₂-coated magnetic probes were also proven to be applicable for real life samples. The magnetic TiO₂-coated Fe@CNPs were employed to selectively isolate phosphopeptides from tryptic digests of HeLa cell lysates and out-performed the commercial magnetic TiO₂ beads in the number of identified phosphopeptides and phosphorylation sites. In a 200-μg equivalent of HeLa cell lysates, we identified 1415 unique phosphopeptides and 1093 phosphorylation sites, indicating the good performance of the new approach.

Hydroponic isotope labeling of entire plants and high-performance mass spectrometry for quantitative plant proteomics

Hydroponic isotope labeling of entire plants (HILEP) combines hydroponic plant cultivation and metabolic labeling with stable isotopes using (15)N-containing inorganic salts to label whole and mature plants. Employing (15)N salts as the sole nitrogen source for HILEP leads to the production of healthy-looking plants which contain (15)N proteins labeled to nearly 100%. Therefore, HILEP is suitable for quantitative plant proteomic analysis, where plants are grown in either (14)N- or (15)N-hydroponic media and pooled when the biological samples are collected for relative proteome quantitation. The pooled (14)N-/(15)N-protein extracts can be fractionated in any suitable way and digested with a protease for shotgun proteomics, using typically reverse phase liquid chromatography nanoelectrospray ionization tandem mass spectrometry (RPLC-nESI-MS/MS). Best results were obtained with a hybrid ion trap/FT-MS mass spectrometer, combining high mass accuracy and sensitivity for the MS data acquisition with speed and high-throughput MS/MS data acquisition, increasing the number of proteins identified and quantified and improving protein quantitation. Peak processing and picking from raw MS data files, protein identification, and quantitation were performed in a highly automated way using integrated MS data analysis software with minimum manual intervention, thus easing the analytical workflow. In this methodology paper, we describe how to grow Arabidopsis plants hydroponically for isotope labeling using (15)N salts and how to quantitate the resulting proteomes using a convenient workflow that does not require extensive bioinformatics skills.

Software tools for MS-based quantitative proteomics: a brief overview

Proteomics is turning more and more towards quantitative measurements of biological systems. This in turn has spurred the development of numerous experimental methods that enable such measurements. Vast quantities of mostly mass spectrometric data are often generated as a result which requires the use of software tools that turns raw data into useful quantitative information from which knowledge about the biological system can eventually be derived. This chapter gives a brief overview of available software tools for mass spectrometry based quantitative proteomics.

Investigating the cell cycle-associated dynamics of histone modifications using quantitative mass spectrometry

In eukaryotic cells, posttranslational modifications (PTMs) on histones regulate chromatin structure and thus impact nearly all chromatin-templated events, including replication, transcription, and DNA repair. During S phase, newly synthesized histones are deposited onto DNA, leading to dilution of total chromatin-associated modifications. To maintain genome organization in daughter cells, histone PTMs must be reestablished in the subsequent cell cycle. Owing to their importance for determining cellular fate, the mechanisms that underlie the inheritance of epigenetic mark from parent cells by daughter cells are of great interest. In recent years, mass spectrometry (MS) has emerged as a powerful tool for identifying and quantifying histone modifications. This chapter describes strategies for investigating the reestablishment of histone PTMs during the mitotic cell cycle using quantitative MS approaches. By introducing these basic principles of experimental design and common protocols, we hope that this chapter will help readers to apply quantitative MS in their own research systems to study the biology of histone modifications.

MSQuant: a platform for stable isotope-based quantitative proteomics

Quantitative approaches in proteomics are emerging as a powerful tool to probe the dynamics of protein expression across biological conditions. Thereby, quantification helps to recognize proteins with potential biological relevance, which greatly aids in the design of follow-up experiments. Although multiple methods have been established that are based on stable-isotope labeling and label-free approaches, one of the remaining bottlenecks is the analysis and quantification of proteins in large datasets. MSQuant is a platform for protein quantification, capable of handling multiple labeling strategies and supporting several vendor data formats. Here, we report on the use and versatility of MSQuant.

Identification of new interacting partners for atypical Rho GTPases: a SILAC-based approach

In contrast to typical Rho GTPases the regulation of atypical Rho GTPases, such as the members of the RhoBTB subfamily, rarely depends on GEFs and/or GAPs. Instead, they are regulated at the level of their expression, by post-translational modifications, by their rate of degradation as well as through binding of diverse cell-specific interactors. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) is a powerful cutting-edge mass-spectrometry-based technology allowing for protein-interaction studies in vitro with removal of false-positive identifications. In this chapter, we describe how the SILAC technology can be applied to the identification of new interacting partners for atypical - constitutively active - Rho GTPases, i.e. RhoBTB3.

Identifying cellular targets of small-molecule probes and drugs with biochemical enrichment and SILAC

Sequencing of the human genome in the last decade has not yet led to a concomitant increase in the numbers of novel drug targets. While the pharmaceutical industry has invested heavily in improving drugs for existing protein targets, it has not tended toward a similar investment in experimental approaches to identify cellular targets of drugs. It is striking that the targets of numerous widely used FDA-approved drugs remain unknown. The development of robust, unbiased methods for target identification would greatly enhance our understanding the mechanisms-of-action of small molecules. Cell-based phenotypic screens followed by unbiased target identification have the potential to identify novel combinations of small molecules and their protein targets, shed light on drug polypharmacology, and enable unbiased screening approaches to drug discovery. Classical biochemical enrichment with immobilized small molecules has been used for over four decades but has been limited by issues concerning specificity and sensitivity. The application of mass spectrometry-based quantitative proteomics in combination with these affinity reagents has proven to be especially useful in addressing these common issues in affinity purification experiments. We describe the use of SILAC in identifying proteins that bind small-molecule probes and drugs in a cellular context.

A model for mitotic inheritance of histone lysine methylation

Histone lysine methylation has been implicated in epigenetic regulation of transcription. Using stable-isotope labelling and quantitative mass spectrometry, we analysed the dynamics of histone lysine methylation. Here we report that histone methylation levels are transiently reduced during S phase and are gradually re-established during subsequent cell cycle stages. However, despite the recovery of overall methylation levels before the next S phase, the methylation levels of parental and newly incorporated histones differ significantly. In addition, histone methylation levels are maintained at steady states by both restriction of methyltransferase activity and the active turnover of methyl groups in cells undergoing an extended G1/S phase arrest. Finally, we propose a 'buffer model' that unifies the imprecise inheritance of histone methylation and the faithful maintenance of underlying gene silencing.

Nanodiscs and SILAC-based mass spectrometry to identify a membrane protein interactome

Integral membrane proteins are challenging to work with biochemically given their insoluble nature; the nanodisc circumvents the difficulty by stabilizing them in small patches of lipid bilayer. Here, we show that nanodiscs combined with SILAC-based quantitative proteomics can be used to identify the soluble interacting partners of virtually any membrane protein. As a proof of principle, we applied the method to the bacterial SecYEG protein-conducting channel, the maltose transporter MalFGK(2) and the membrane integrase YidC. In contrast to the detergent micelles, which tend to destabilize interactions, the nanodisc was able to capture out of a complex whole cell extract the proteins SecA, Syd, and MalE with a high degree of confidence and specificity. The method was sensitive enough to isolate these interactors as a function of the lipid composition in the disc and the culture conditions. In agreement with a previous photo-cross linking analysis, YidC did not show any high-affinity interactions with cytosolic or periplasmic proteins. These three examples illustrate the utility of nanoscale lipid bilayers to identify the soluble peripheral partners of proteins intergrated in the lipid bilayer.

Accurate proteome-wide protein quantification from high-resolution 15N mass spectra

In quantitative mass spectrometry-based proteomics, the metabolic incorporation of a single source of ¹⁵N-labeled nitrogen has many advantages over using stable isotope-labeled amino acids. However, the lack of a robust computational framework for analyzing the resulting spectra has impeded wide use of this approach. We have addressed this challenge by introducing a new computational methodology for analyzing ¹⁵N spectra in which quantification is integrated with identification. Application of this method to an Escherichia coli growth transition reveals significant improvement in quantification accuracy over previous methods.

Identification and quantification of peptides and proteins secreted from prostate epithelial cells by unbiased liquid chromatography tandem mass spectrometry using goodness of fit and analysis of variance

The proteins secreted by prostate cancer cells (PC3(AR)6) were separated by strong anion exchange chromatography, digested with trypsin and analyzed by unbiased liquid chromatography tandem mass spectrometry with an ion trap. The spectra were matched to peptides within proteins using a goodness of fit algorithm that showed a low false positive rate. The parent ions for MS/MS were randomly and independently sampled from a log-normal population and therefore could be analyzed by ANOVA. Normal distribution analysis confirmed that the parent and fragment ion intensity distributions were sampled over 99.9% of their range that was above the background noise. Arranging the ion intensity data with the identified peptide and protein sequences in structured query language (SQL) permitted the quantification of ion intensity across treatments, proteins and peptides. The intensity of 101,905 fragment ions from 1421 peptide precursors of 583 peptides from 233 proteins separated over 11 sample treatments were computed together in one ANOVA model using the statistical analysis system (SAS) prior to Tukey-Kramer honestly significant difference (HSD) testing. Thus complex mixtures of proteins were identified and quantified with a high degree of confidence using an ion trap without isotopic labels, multivariate analysis or comparing chromatographic retention times.

Comparison of three quantitative phosphoproteomic strategies to study receptor tyrosine kinase signaling

There are three quantitative phosphoproteomic strategies most commonly used to study receptor tyrosine kinase (RTK) signaling. These strategies quantify changes in: (1) all three forms of phosphosites (phosphoserine, phosphothreonine and phosphotyrosine) following enrichment of phosphopeptides by titanium dioxide or immobilized metal affinity chromatography; (2) phosphotyrosine sites following anti- phosphotyrosine antibody enrichment of phosphotyrosine peptides; or (3) phosphotyrosine proteins and their binding partners following anti-phosphotyrosine protein immunoprecipitation. However, it is not clear from literature which strategy is more effective. In this study, we assessed the utility of these three phosphoproteomic strategies in RTK signaling studies by using EphB receptor signaling as an example. We used all three strategies with stable isotope labeling with amino acids in cell culture (SILAC) to compare changes in phosphoproteomes upon EphB receptor activation. We used bioinformatic analysis to compare results from the three analyses. Our results show that the three strategies provide complementary information about RTK pathways.

Quantitative phosphoproteomic strategies are most commonly used to study receptor tyrosine kinase (RTK) signaling by quantifying changes in: (1) phosphopeptides containing pS, pT, or pY; (2) phosphotyrosine-containing peptides; (3) phosphotyrosine-containing proteins. In this study, we assessed the utility of the three strategies for RTK signaling studies by using EphB receptor signaling as an example. Our results show that the three strategies are very complementary in providing information about RTK pathways.

Psb27, a transiently associated protein, binds to the chlorophyll binding protein CP43 in photosystem II assembly intermediates

Photosystem II (PSII), a large multisubunit pigment-protein complex localized in the thylakoid membrane of cyanobacteria and chloroplasts, mediates light-driven evolution of oxygen from water. Recently, a high-resolution X-ray structure of the mature PSII complex has become available. Two PSII polypeptides, D1 and CP43, provide many of the ligands to an inorganic Mn(4)Ca center that is essential for water oxidation. Because of its unusual redox chemistry, PSII often undergoes degradation followed by stepwise assembly. Psb27, a small luminal polypeptide, functions as an important accessory factor in this elaborate assembly pathway. However, the structural location of Psb27 within PSII assembly intermediates has remained elusive. Here we report that Psb27 binds to CP43 in such assembly intermediates. We treated purified genetically tagged PSII assembly intermediate complexes from the cyanobacterium Synechocystis 6803 with chemical cross-linkers to examine intermolecular interactions between Psb27 and various PSII proteins. First, the water-soluble 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) was used to cross-link proteins with complementary charged groups in close association to one another. In the His27△ctpAPSII preparation, a 58-kDa cross-linked species containing Psb27 and CP43 was identified. This species was not formed in the HT3△ctpA△psb27PSII complex in which Psb27 was absent. Second, the homobifunctional thiol-cleavable cross-linker 3,3'-dithiobis(sulfosuccinimidylpropionate) (DTSSP) was used to reversibly cross-link Psb27 to CP43 in His27△ctpAPSII preparations, which allowed the use of liquid chromatography/tandem MS to map the cross-linking sites as Psb27K(63)↔CP43D(321) (trypsin) and CP43K(215)↔Psb27D(58)AGGLK(63)↔CP43D(321) (chymotrypsin), respectively. Our data suggest that Psb27 acts as an important regulatory protein during PSII assembly through specific interactions with the luminal domain of CP43.

Metabolic priming by a secreted fungal effector

Maize smut caused by the fungus Ustilago maydis is a widespread disease characterized by the development of large plant tumours. U. maydis is a biotrophic pathogen that requires living plant tissue for its development and establishes an intimate interaction zone between fungal hyphae and the plant plasma membrane. U. maydis actively suppresses plant defence responses by secreted protein effectors. Its effector repertoire comprises at least 386 genes mostly encoding proteins of unknown function and expressed exclusively during the biotrophic stage. The U. maydis secretome also contains about 150 proteins with probable roles in fungal nutrition, fungal cell wall modification and host penetration as well as proteins unlikely to act in the fungal-host interface like a chorismate mutase. Chorismate mutases are key enzymes of the shikimate pathway and catalyse the conversion of chorismate to prephenate, the precursor for tyrosine and phenylalanine synthesis. Root-knot nematodes inject a secreted chorismate mutase into plant cells likely to affect development. Here we show that the chorismate mutase Cmu1 secreted by U. maydis is a virulence factor. The enzyme is taken up by plant cells, can spread to neighbouring cells and changes the metabolic status of these cells through metabolic priming. Secreted chorismate mutases are found in many plant-associated microbes and might serve as general tools for host manipulation.

Quantitative proteomics of complex mixtures

Measurement of biologically important effector protein molecules has been a long-standing essential component of biological research. Advances in biotechnology, in the form of high-resolution mass spectrometers, and in bioinformatics, now allow the simultaneous quantitative analysis of thousands of proteins. While these techniques still do not allow definitive identification of the entire proteome of complex mixtures, such as cells, quantitative analyses of hundreds to thousands of proteins in such complex mixtures provides a means to elucidate molecular alterations that occur during perturbation of cellular systems. This article will outline considerations of reducing sample complexity, by strategies such as multidimensional separations (gel-based and chromatography-based, including multidimensional protein identification technology). In addition, some of the most common methods used to quantitatively measure proteins in complex mixtures (2D difference in-gel electrophoresis, isotope-coded affinity tags, isotope-coded protein labeling, tandem mass tags, isobaric tags for relative and absolute quantitation, stable isotope labeling of amino acids in cell culture and label-free), as well as recent examples of each strategy, are described.

Proteomics moves from expression to turnover: update and future perspective

Proteomics is a rapidly developing discipline that seeks to understand the role of proteins in the wider biological context. In order to take a holistic view of a biological system, it is vital that we can elucidate the dynamics of the proteome. In this article, we have outlined the recent advances in experimental strategies for measuring protein synthesis and degradation on a proteome-wide scale. The application of mass spectrometry and non-mass spectrometric-based approaches in this field of research has been discussed. The article also explores the challenges associated with these types of analyses and the development of appropriate bioinformatic resources for interrogating the complex datasets that are generated.

Characterization of ubiquitination dependent dynamics in growth factor receptor signaling by quantitative proteomics

Protein ubiquitination is a dynamic reversible post-translational modification that plays a key role in the regulation of numerous cellular processes including signal transduction, endocytosis, cell cycle control, DNA repair and gene transcription. The conjugation of the small protein ubiquitin or chains of ubiquitin molecules of various types and lengths to targeted proteins is known to alter proteins' lifespan, localization and function and to modulate protein interactions. Despite its central importance in various aspects of cellular life and function there are only a limited number of reports investigating ubiquitination on a proteomic scale, mainly due to the inherited complexity and heterogeneity of ubiquitination. We describe here a quantitative proteomics strategy based on the specificity of ubiquitin binding domains (UBDs) and Stable Isotope Labeling by Amino acids in Cell culture (SILAC) for selectively decoding ubiquitination-driven processes involved in the regulation of cellular signaling networks. We applied this approach to characterize the temporal dynamics of ubiquitination events accompanying epidermal growth factor receptor (EGFR) signal transduction. We used recombinant UBDs derived from endocytic adaptor proteins for specific enrichment of ubiquitinated complexes from the EGFR network and subsequent quantitative analyses by high accuracy mass spectrometry. We show that the strategy is suitable for profiling the dynamics of ubiquitination occurring on individual proteins as well as ubiquitination-dependent events in signaling pathways. In addition to a detailed seven time-point profile of EGFR ubiquitination over 30 minutes of ligand stimulation, our data determined prominent involvement of Lysine-63 ubiquitin branching in EGF signaling. Furthermore, we found two centrosomal proteins, PCM1 and Azi1, to form a multi-protein complex with the ubiquitin E3 ligases MIB1 and WWP2 downstream of the EGFR, thereby revealing possible ubiquitination cross-talk between EGF signaling and centrosomal-dependent rearrangements of the microtubules. This is a general strategy that can be utilized to study the dynamics of other cellular systems and post-translational modifications.

Improvement of the quantification accuracy and throughput for phosphoproteome analysis by a pseudo triplex stable isotope dimethyl labeling approach

Accurately quantifying the changes of phosphorylation level on specific sites is crucial to understand the role of protein phosphorylation in physiological and pathological processes. Here, a pseudo triplex stable isotope dimethyl labeling approach was developed to improve the accuracy and the throughput of comprehensive quantitative phosphoproteome analyses. In this strategy, two identical samples are labeled with light and heavy isotopes, respectively, while another comparative sample is labeled with an intermediate isotope. Two replicated quantification results were achieved in just one experiment, and the relative standard deviation (RSD) criterion was used to control the quantification accuracy. Compared with the conventional duplex labeling approach, the number of quantified phosphopeptides increased nearly 50% and the experimental time was reduced by 50% under the same quantification accuracy. Combined with the automated online reversed phase-strong cation exchange-reversed phase (RP-SCX-RP) multidimensional separation system, a comparative phosphoproteome analysis of hepatocellular carcinoma (HCC) and normal human liver tissues was performed. Over 1800 phosphopeptides corresponding to ~2000 phosphorylation sites were quantified reliably in a 42 h multidimensional analysis. The pro-directed motifs, which were mainly associated with the extracellular signal-regulated kinases (ERKs), were observed as being overrepresented in the regulated phosphorylation sites, and some quantification results of phosphorylation sites were validated by the other studies. Therefore, this pseudo triplex labeling approach was demonstrated as a promising alternative for the comprehensive quantitative phosphoproteome analysis.

A case study on the comparison of different software tools for automated quantification of peptides

MS-driven proteomics has evolved over the past two decades to a high tech and high impact research field. Two distinct factors clearly influenced its expansion: the rapid growth of an arsenal of instrument and proteomic techniques that led to an explosion of high quality data and the development of software tools to analyze and interpret these data which boosted the number of scientific discoveries. In analogy with the benchmarking of new instruments and proteomic techniques, such software tools must be thoroughly tested and analyzed. Recently, new tools were developed for automatic peptide quantification in quantitative proteomic experiments. Here we present a case study where the most recent and frequently used tools are analyzed and compared.

Bacterial proteins with cleaved or uncleaved signal peptides of the general secretory pathway

Correct protein compartmentalization is a key step for molecular function and cell viability, and this is especially true for membrane and externalized proteins of bacteria. Recent proteomic reports of Bacillus subtilis have shown that many proteins with Sec-like signal peptides and absence of a transmembrane helix domain are still observed in membrane-enriched fractions, but further evidence about signal peptide cleavage or soluble protein contamination is still needed. Here we report a proteomic screening of identified peptides in culture filtrate, membrane fraction and whole cell lysate of Mycobacterium tuberculosis. We were able to detect peptide sequencing evidence that shows that the predicted signal peptide was kept uncleaved for several types of proteins such as mammalian cell entry (Mce) proteins and PE or PE-PGRS proteins. Label-free quantitation of all proteins identified in each fraction showed that the majority of these proteins with uncleaved signal peptides are, indeed, enriched in the Triton X-114 lipid phase. Some of these proteins are likely to be located in the inner membrane while others may be outer membrane proteins.

Investigating the role of FGF-2 in stem cell maintenance by global phosphoproteomics profiling

Human embryonic stem cells (hESCs) are of immense interest for regenerative medicine as a source of tissue replacement. Expansion of hESCs as a pluripotent population requires a balance between survival, proliferation and self-renewal signals. One of the key growth factors that maintains this balance is fibroblast growth factor-2 (FGF-2). However, the underlying molecular mechanisms are poorly understood. We recently profiled specifically tyrosine phosphorylation events that occur during FGF-2 stimulation of hESCs (Ding et al., J. Cell. Physiol. 2010, 225, 417-428). Here, we complement this phosphoproteome profiling by analyzing temporal dynamics of mostly serine and threonine protein phosphorylation events. Our multi-dimensional strategy combines strong cation exchange chromatography to reduce the sample complexity followed by titanium dioxide off-line for the enrichment of phosphopeptides and dimethylation-based stable isotope labeling for quantification. This approach allowed us to identify and quantify 3261 unique proteins from which 1064 proteins were found to be phosphorylated in one or more residues (representing 1653 unique phosphopeptides). Approximately 40% of the proteins (553 unique phosphopeptides) showed differential phosphorylation upon FGF-2 treatment. Among those are several members of the canonical pathways involved in pluripotency and self-renewal (e.g. Wnt and PI3K/AKT), hESC-associated proteins such as SOX2, RIF1, SALL4, DPPA4, DNMT3B and 53 proteins that are target genes of the pluripotency transcription factors SOX2, OCT4 and NANOG. These findings complement existing pluripotency analyses and provide new insights into how FGF-2 assists in maintaining the undifferentiated state of hESCs.

Quantitative nucleolar proteomics reveals nuclear re-organization during stress- induced senescence in mouse fibroblast

Background

Nucleolus is the most prominent mammalian organelle within the nucleus which is also the site for ribosomal biogenesis. There have been many reports indicating the involvement of nucleolus in the process of aging. Several proteins related to aging have been shown to localize in the nucleolus, which suggests the role of this organelle in senescence.

Results

In this study, we used quantitative mass spectrometry to map the flux of proteins into and out of the nucleolus during the induction of senescence in cultured mammalian cells. Changes in the abundance of 344 nucleolar proteins in sodium butyrate-induced senescence in NIH3T3 cells were studied by SILAC (stable isotope labeling by amino acids in cell culture)-based mass spectrometry. Biochemically, we have validated the proteomic results and confirmed that B23 (nucleophosmin) protein was down-regulated, while poly (ADP-ribose) polymerase (PARP) and nuclear DNA helicase II (NDH II/DHX9/RHA) were up-regulated in the nucleolus upon treatment with sodium butyrate. Accumulation of chromatin in the nucleolus was also observed, by both proteomics and microscopy, in sodium butyrate-treated cells. Similar observations were found in other models of senescence, namely, in mitoxantrone- (MTX) treated cells and primary fibroblasts from the Lamin A knockout mice.

Conclusion

Our data indicate an extensive nuclear organization during senescence and suggest that the redistribution of B23 protein and chromatin can be used as an important marker for senescence.

MassChroQ: a versatile tool for mass spectrometry quantification

Recently, many software tools have been developed to perform quantification in LC-MS analyses. However, most of them are specific to either a quantification strategy (e.g. label-free or isotopic labelling) or a mass-spectrometry system (e.g. high or low resolution). In this context, we have developed MassChroQ (Mass Chromatogram Quantification), a versatile software that performs LC-MS data alignment and peptide quantification by peak area integration on extracted ion chromatograms. MassChroQ is suitable for quantification with or without labelling and is not limited to high-resolution systems. Peptides of interest (for example all the identified peptides) can be determined automatically, or manually by providing targeted m/z and retention time values. It can handle large experiments that include protein or peptide fractionation (as SDS-PAGE, 2-D LC). It is fully configurable. Every processing step is traceable, the produced data are in open standard formats and its modularity allows easy integration into proteomic pipelines. The output results are ready for use in statistical analyses. Evaluation of MassChroQ on complex label-free data obtained from low and high-resolution mass spectrometers showed low CVs for technical reproducibility (1.4%) and high coefficients of correlation to protein quantity (0.98). MassChroQ is freely available under the GNU General Public Licence v3.0 at http://pappso.inra.fr/bioinfo/masschroq/.

Protein phosphatase 2A (B55α) prevents premature activation of forkhead transcription factor FoxM1 by antagonizing cyclin A/cyclin-dependent kinase-mediated phosphorylation

The forkhead transcription factor FoxM1 controls expression of a large number of genes that are specifically expressed during the G(2) phase of the cell cycle. Throughout most of the cell cycle, FoxM1 activity is restrained by an autoinhibitory mechanism, involving a repressor domain present in the N-terminal part of the protein. Activation of FoxM1 in G(2) is achieved by Cyclin A/Cyclin-dependent kinase (Cdk)-mediated phosphorylation, which alleviates autoinhibition by the N-terminal repressor domain. Here, we show that FoxM1 interacts with B55α, a regulatory subunit of protein phosphatase 2A (PP2A). B55α binds the catalytic subunit of PP2A, and this promotes dephosphorylation and inactivation of FoxM1. Indeed, we find that overexpression of B55α results in decreased FoxM1 activity. Inversely, depletion of B55α results in premature activation of FoxM1. The activation of FoxM1 that is observed upon depletion of B55α is fully dependent on Cyclin A/Cdk-mediated phosphorylation of FoxM1. Taken together, these data demonstrate that B55α acts to antagonize Cyclin A/Cdk-dependent activation of FoxM1, to ensure that FoxM1 activity is restricted to the G(2) phase of the cell cycle.

Software lock mass by two-dimensional minimization of peptide mass errors

Mass accuracy is a key parameter in proteomic experiments, improving specificity, and success rates of peptide identification. Advances in instrumentation now make it possible to routinely obtain high resolution data in proteomic experiments. To compensate for drifts in instrument calibration, a compound of known mass is often employed. This 'lock mass' provides an internal mass standard in every spectrum. Here we take advantage of the complexity of typical peptide mixtures in proteomics to eliminate the requirement for a physical lock mass. We find that mass scale drift is primarily a function of the m/z and the elution time dimensions. Using a subset of high confidence peptide identifications from a first pass database search, which effectively substitute for the lock mass, we set up a global mathematical minimization problem. We perform a simultaneous fit in two dimensions using a function whose parameterization is automatically adjusted to the complexity of the analyzed peptide mixture. Mass deviation of the high confidence peptides from their calculated values is then minimized globally as a function of both m/z value and elution time. The resulting recalibration function performs equal or better than adding a lock mass from laboratory air to LTQ-Orbitrap spectra. This 'software lock mass' drastically improves mass accuracy compared with mass measurement without lock mass (up to 10-fold), with none of the experimental cost of a physical lock mass, and it integrated into the freely available MaxQuant analysis pipeline ( www.maxquant.org ).

Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes

Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

Quantitative shotgun proteomics using a uniform ¹⁵N-labeled standard to monitor proteome dynamics in time course experiments reveals new insights into the heat stress response of Chlamydomonas reinhardtii

Crop-plant-yield safety is jeopardized by temperature stress caused by the global climate change. To take countermeasures by breeding and/or transgenic approaches it is essential to understand the mechanisms underlying plant acclimation to heat stress. To this end proteomics approaches are most promising, as acclimation is largely mediated by proteins. Accordingly, several proteomics studies, mainly based on two-dimensional gel-tandem MS approaches, were conducted in the past. However, results often were inconsistent, presumably attributable to artifacts inherent to the display of complex proteomes via two-dimensional-gels. We describe here a new approach to monitor proteome dynamics in time course experiments. This approach involves full ¹⁵N metabolic labeling and mass spectrometry based quantitative shotgun proteomics using a uniform ¹⁵N standard over all time points. It comprises a software framework, IOMIQS, that features batch job mediated automated peptide identification by four parallelized search engines, peptide quantification and data assembly for the processing of large numbers of samples. We have applied this approach to monitor proteome dynamics in a heat stress time course using the unicellular green alga Chlamydomonas reinhardtii as model system. We were able to identify 3433 Chlamydomonas proteins, of which 1116 were quantified in at least three of five time points of the time course. Statistical analyses revealed that levels of 38 proteins significantly increased, whereas levels of 206 proteins significantly decreased during heat stress. The increasing proteins comprise 25 (co-)chaperones and 13 proteins involved in chromatin remodeling, signal transduction, apoptosis, photosynthetic light reactions, and yet unknown functions. Proteins decreasing during heat stress were significantly enriched in functional categories that mediate carbon flux from CO₂ and external acetate into protein biosynthesis, which also correlated with a rapid, but fully reversible cell cycle arrest after onset of stress. Our approach opens up new perspectives for plant systems biology and provides novel insights into plant stress acclimation.

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

Collagen stimulation of platelets induces a rapid spatial response of cAMP and cGMP signaling scaffolds

Intracellular communication is tightly regulated in both space and time. Spatiotemporal control is important to achieve a high level of specificity in both dimensions. For instance, cAMP-dependent kinase (PKA) attains spatial resolution by interacting with distinct members of the family of A-kinase anchoring proteins (AKAPs) that position PKA at specific loci within the cell. To control the cAMP induced signal in time, distinct signal terminators such as phosphodiesterases and phosphatases are often co-localized at the AKAP scaffold. In platelets, high levels of cAMP/cGMP maintain the resting state to allow free circulation. Exposure to collagen, for instance when the vessel is damaged, triggers platelet activation through initiation of the GPVI (glycoprotein VI)/FcRγ-chain forming the onset of a plethora of signaling pathways. Consequently overall intra-platelet cAMP and cGMP levels drop, however detail on how PKA, but also cGMP-dependent protein kinase (PKG) respond in relation to their localized signaling scaffolds is currently missing. To investigate this, we employed a quantitative chemical proteomics approach in activated human platelets enabling the specific enrichment of cAMP/cGMP signaling nodes. Our data reveal that within a few minutes several specific PKA and PKG signaling nodes respond significantly to the activating signal, whereas others do not, suggesting a rapid adaption of specific localized cAMP and cGMP pools to the stimulus. Using protein phosphorylation data gathered we touch upon the potential cross-talk between protein phosphorylation and signaling scaffold function as a general theme in platelet spatiotemporal control.