Mass spectrometry for the study of protein-protein interactions

Searching for EGF Fragments Recreating the Outer Sphere of the Growth Factor Involved in Receptor Interactions

The aims of this study were to determine whether it is possible to use peptide microarrays obtained using the SPOT technique (immobilized on cellulose) and specific polyclonal antibodies to select fragments that reconstruct the outer sphere of proteins and to ascertain whether the selected peptide fragments can be useful in the study of their protein-protein and/or peptide-protein interactions. Using this approach, epidermal growth factor (EGF) fragments responsible for the interaction with the EGF receptor were searched. A library of EGF fragments immobilized on cellulose was obtained using triazine condensing reagents. Experiments on the interactions with EGFR confirmed the high affinity of the selected peptide fragments. Biological tests on cells showed the lack of cytotoxicity of the EGF fragments. Selected EGF fragments can be used in various areas of medicine.

Identification of mitogen-activated protein kinase phosphatase-1 (MKP-1) protein partners using tandem affinity purification and mass spectrometry

BACKGROUND

According to the World Health Organization Report, depressive disorders affect about 10% of the population. The molecular mechanism of the pathogenesis of depression is still not well understood. The new findings point to phosphatases as potential targets for effective depression therapy. The aim of the present work was the development of a method that would enable the identification of mitogen-activated protein kinase phosphatase-1 (MKP-1) protein partners using a proteomic approach.

METHODS

The research was carried out using the PC12 cell line, often used as a model for neurobiological research. The use of the procedure for efficient purification of protein complexes-tandem affinity purification (TAP) will facilitate the identification of proteins interacting with MKP-1, a potential goal of effective antidepressant therapy.

RESULTS

Identified proteins belong to various groups: cytoskeletal, ribosomal, nucleic acid binding, chaperones, and enzymes and may potentially be involved in the molecular mechanism of depression.

CONCLUSIONS

The presented protocol for the purification of protein complexes is universal and can be successfully used in different mammalian cell lines. Proteins identified in the present work have been reported in the literature concerning studies on depressive disorders, which speaks in favour of their role in depression.

Proteomic characterization of a candidate polygenic driver of metabolism in non-small cell lung cancer

Proteome analysis revealed signatures of co-expressed upregulated metabolism proteins highly conserved between primary and non-small cell lung cancer (NSCLC) patient-derived xenograft tumors (Li et al. 2014, Nat. Communications 5:5469). The C10 signature is encoded by seven genes (ADSS, ATP2A2, CTPS1, IMPDH2, PKM2, PTGES3, SGPL1) and DNA alterations in C10-encoding genes are associated with longer survival in a subset of NSCLC. To explore the C10 signature as an oncogenic driver and address potential mechanisms of action, C10 protein expression and protein-protein interactions were determined. In independent NSCLC cohorts, the coordinated expression of C10 proteins was significant and mutations in C10 genes were associated with better outcome. Affinity purification-mass spectrometry and in vivo proximity-based biotin identification defined a C10 interactome involving 667 proteins including candidate drug targets and clusters associated with glycolysis, calcium homeostasis, and nucleotide and sphingolipid metabolism. DNA alterations in genes encoding C10 interactome components were also found to be associated with better survival. These data support the notion that the coordinated upregulation of the C10 signature impinges metabolic processes that collectively function as an oncogenic driver in NSCLC.

Cancer proteome and metabolite changes linked to SHMT2

Serine hydroxymethyltransferase 2 (SHMT2) converts serine plus tetrahydrofolate (THF) into glycine plus methylene-THF and is upregulated at the protein level in lung and other cancers. In order to better understand the role of SHMT2 in cancer a model system of HeLa cells engineered for inducible over-expression or knock-down of SHMT2 was characterized for cell proliferation and changes in metabolites and proteome as a function of SHMT2. Ectopic over-expression of SHMT2 increased cell proliferation in vitro and tumor growth in vivo. Knockdown of SHMT2 expression in vitro caused a state of glycine auxotrophy and accumulation of phosphoribosylaminoimidazolecarboxamide (AICAR), an intermediate of folate/1-carbon-pathway-dependent de novo purine nucleotide synthesis. Decreased glycine in the HeLa cell-based xenograft tumors with knocked down SHMT2 was potentiated by administration of the anti-hyperglycinemia agent benzoate. However, tumor growth was not affected by SHMT2 knockdown with or without benzoate treatment. Benzoate inhibited cell proliferation in vitro, but this was independent of SHMT2 modulation. The abundance of proteins of mitochondrial respiration complexes 1 and 3 was inversely correlated with SHMT2 levels. Proximity biotinylation in vivo (BioID) identified 48 mostly mitochondrial proteins associated with SHMT2 including the mitochondrial enzymes Acyl-CoA thioesterase (ACOT2) and glutamate dehydrogenase (GLUD1) along with more than 20 proteins from mitochondrial respiration complexes 1 and 3. These data provide insights into possible mechanisms through which elevated SHMT2 in cancers may be linked to changes in metabolism and mitochondrial function.

Hybrid CuCoO-GO enables ultrasensitive detection of antibiotics with enhanced laser desorption/ionization at nano-interfaces

The soaring concerns globally on antibiotic overuse have made calls for the development of rapid and sensitive detection methods urgent. Here we report that the hybrid CuCoO-GO matrix allows for sensitive detection of various antibiotics in combination with MALDI TOF MS. The new matrix is composed of few-layered GO nanosheets decorated with CuCoO nanoparticles with an average size of 10 nm, and exhibits excellent aqueous suspensibility. Accurate quantitation of the sulfonamide antibiotics in milk samples have been demonstrated using a CuCoO-GO matrix and a stable isotope (C¹³)-labeled analyte as the internal standard. Our experiments have achieved lower limits of detection (LOD) by several hundred fold for the detection of a panel of representative antibiotics, in comparison with the literature reports. Both intrabacterial and extrabacterial residual antibiotics can be sensitively detected with our method. We have further investigated the molecular mechanism of the enhanced desorption/ionization efficiency by the CuCoO-GO matrix with synchrotron radiation techniques for the first time. This work provides a sensitive matrix enabling MALDI-TOF MS to be applied in small molecular analysis, but also presents a distinct perspective on the mechanism behind the material functions.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

Identification of two arginine kinase forms of endoparasitoid Leptomastix dactylopii venom by bottom up-sequence tag approach

Leptomastix dactylopii (Howard) is an endoparasitoid wasp, natural enemy of mealybug Planococcus citri (Risso). Despite the acquired knowledge regarding this host-parasitoid interaction, only little information is available on the factors of parasitoid origin able to modulate the mealybug physiology. The major alteration observed in P. citri is a strong reduction in fecundity, which is evident soon after parasitization by L. dactylopii or venom injection in unparasitized hosts indicating that this proteinaceus secretion injected at the oviposition plays a key-role in host regulation. Protein identification of L. dactilopii venom has been limited by the lack of literature sources and public protein databases. Here, we identified two venom proteins by an integrated trascriptomic and proteomic approach. A custom-made transcriptomic database from the L. dactylopii venom glands was created by applying the high-throughput RNA sequencing approach. Two-dimensional gel electrophoresis (2DE) trypsinized protein spots were analyzed by high-resolution mass spectrometry (FTICRMS-12 T). The most abundant peptide ions were fragmented by collision induced dissociation and the obtained sequence tags were subjected to custom-made protein database searching. Two putative arginine kinases (full-length and truncated form) were identified. This is the first case in which both, truncated and full length arginine kinases, are identified in an endoparasitoid non-paralyzing venom.

Proteomic analyses reveal distinct chromatin-associated and soluble transcription factor complexes

The current knowledge on how transcription factors (TFs), the ultimate targets and executors of cellular signalling pathways, are regulated by protein–protein interactions remains limited. Here, we performed proteomics analyses of soluble and chromatin-associated complexes of 56 TFs, including the targets of many signalling pathways involved in development and cancer, and 37 members of the Forkhead box (FOX) TF family. Using tandem affinity purification followed by mass spectrometry (TAP/MS), we performed 214 purifications and identified 2,156 high-confident protein–protein interactions. We found that most TFs form very distinct protein complexes on and off chromatin. Using this data set, we categorized the transcription-related or unrelated regulators for general or specific TFs. Our study offers a valuable resource of protein–protein interaction networks for a large number of TFs and underscores the general principle that TFs form distinct location-specific protein complexes that are associated with the different regulation and diverse functions of these TFs.

From pathways to networks: connecting dots by establishing protein-protein interaction networks in signaling pathways using affinity purification and mass spectrometry

Signal transductions are the basis of biological activities in all living organisms. Studying the signaling pathways, especially under physiological conditions, has become one of the most important facets of modern biological research. During the last decade, MS has been used extensively in biological research and is proven to be effective in addressing important biological questions. Here, we review the current progress in the understanding of signaling networks using MS approaches. We will focus on studies of protein-protein interactions that use affinity purification followed by MS approach. We discuss obstacles to affinity purification, data processing, functional validation, and identification of transient interactions and provide potential solutions for pathway-specific proteomics analysis, which we hope one day will lead to a comprehensive understanding of signaling networks in humans.

ROCS: a reproducibility index and confidence score for interaction proteomics studies

Background

Affinity-Purification Mass-Spectrometry (AP-MS) provides a powerful means of identifying protein complexes and interactions. Several important challenges exist in interpreting the results of AP-MS experiments. First, the reproducibility of AP-MS experimental replicates can be low, due both to technical variability and the dynamic nature of protein interactions in the cell. Second, the identification of true protein-protein interactions in AP-MS experiments is subject to inaccuracy due to high false negative and false positive rates. Several experimental approaches can be used to mitigate these drawbacks, including the use of replicated and control experiments and relative quantification to sensitively distinguish true interacting proteins from false ones.

Methods

To address the issues of reproducibility and accuracy of protein-protein interactions, we introduce a two-step method, called ROCS, which makes use of Indicator Prey Proteins to select reproducible AP-MS experiments, and of Confidence Scores to select specific protein-protein interactions. The Indicator Prey Proteins account for measures of protein identifiability as well as protein reproducibility, effectively allowing removal of outlier experiments that contribute noise and affect downstream inferences. The filtered set of experiments is then used in the Protein-Protein Interaction (PPI) scoring step. Prey protein scoring is done by computing a Confidence Score, which accounts for the probability of occurrence of prey proteins in the bait experiments relative to the control experiment, where the significance cutoff parameter is estimated by simultaneously controlling false positives and false negatives against metrics of false discovery rate and biological coherence respectively. In summary, the ROCS method relies on automatic objective criterions for parameter estimation and error-controlled procedures.

Results

We illustrate the performance of our method by applying it to five previously published AP-MS experiments, each containing well characterized protein interactions, allowing for systematic benchmarking of ROCS. We show that our method may be used on its own to make accurate identification of specific, biologically relevant protein-protein interactions, or in combination with other AP-MS scoring methods to significantly improve inferences.

Conclusions

Our method addresses important issues encountered in AP-MS datasets, making ROCS a very promising tool for this purpose, either on its own or in conjunction with other methods. We anticipate that our methodology may be used more generally in proteomics studies and databases, where experimental reproducibility issues arise. The method is implemented in the R language, and is available as an R package called “ROCS”, freely available from the CRAN repository http://cran.r-project.org/.

Drosophila poly suggests a novel role for the Elongator complex in insulin receptor-target of rapamycin signalling

Multi-cellular organisms need to successfully link cell growth and metabolism to environmental cues during development. Insulin receptor-target of rapamycin (InR-TOR) signalling is a highly conserved pathway that mediates this link. Herein, we describe poly, an essential gene in Drosophila that mediates InR-TOR signalling. Loss of poly results in lethality at the third instar larval stage, but only after a stage of extreme larval longevity. Analysis in Drosophila demonstrates that Poly and InR interact and that poly mutants show an overall decrease in InR-TOR signalling, as evidenced by decreased phosphorylation of Akt, S6K and 4E-BP. Metabolism is altered in poly mutants, as revealed by microarray expression analysis and a decreased triglyceride : protein ratio in mutant animals. Intriguingly, the cellular distribution of Poly is dependent on insulin stimulation in both Drosophila and human cells, moving to the nucleus with insulin treatment, consistent with a role in InR-TOR signalling. Together, these data reveal that Poly is a novel, conserved (from flies to humans) mediator of InR signalling that promotes an increase in cell growth and metabolism. Furthermore, homology to small subunits of Elongator demonstrates a novel, unexpected role for this complex in insulin signalling.

The integration and annotation of the human interactome in the UniHI Database

In recent years, remarkable progress has been made toward the systematic charting of human protein interactions. The utilization of the generated interaction data remained however challenging for biomedical researchers due to lack of integration of currently available resources. To facilitate the direct access and analysis of the human interactome, we have developed the Unified Human Interactome (UniHI) database. It provides researchers with a user-friendly Web-interface and integrates interaction data from 12 major resources in its latest version, establishing one of the largest catalogs for human PPIs worldwide. At present, UniHI houses over 250,000 distinct interactions between 22,300 unique proteins and is publically available at http://www.unihi.org.

Bio::Homology::InterologWalk--a Perl module to build putative protein-protein interaction networks through interolog mapping

BACKGROUND

Protein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction.

RESULTS

We introduce Bio::Homology::InterologWalk, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, Drosophila melanogaster. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation.

CONCLUSIONS

Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy to customise the results by post-processing, allowing the putative PPI datasets to be easily integrated into existing analysis workflows. The Bio::Homology::InterologWalk module, sample scripts and full documentation are freely available from the Comprehensive Perl Archive Network (CPAN) under the GNU Public license.

Proteomic tools for the analysis of transient interactions between metalloproteins

Metalloproteins play major roles in cell metabolism and signalling pathways. In many cases, they show moonlighting behaviour, acting in different processes, depending on the physiological state of the cell. To understand these multitasking proteins, we need to discover the partners with which they carry out such novel functions. Although many technological and methodological tools have recently been reported for the detection of protein interactions, specific approaches to studying the interactions involving metalloproteins are not yet well developed. The task is even more challenging for metalloproteins, because they often form short-lived complexes that are difficult to detect. In this review, we gather the different proteomic techniques and biointeractomic tools reported in the literature. All of them have shown their applicability to the study of transient and weak protein-protein interactions, and are therefore suitable for metalloprotein interactions.

Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

Background

Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming) experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible.

Methods

Here we report the development of a simple open source program module (OpenPPI_predictor) that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism.

Results

Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans.

Availability

The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/.

MEASUREMENT of Protein 53 Diffusion Coefficient in Live HeLa Cells Using Raster Image Correlation Spectroscopy (RICS)

We have applied Raster Image Correlation Spectroscopy (RICS) technique to characterize the dynamics of protein 53 (p53) in living cells before and after the treatment with DNA damaging agents. HeLa cells expressing Green Fluorescent Protein (GFP) tagged p53 were incubated with and without DNA damaging agents, cisplatin or eptoposide, which are widely used as chemotherapeutic drugs. Then, the diffusion coefficient of GFP-p53 was determined by RICS and it was significantly reduced after the drug treatment while that of the one without drug treatment was not. It is suggested that the drugs induced the interaction of p53 with either other proteins or DNA. Together, our results demonstrated that RICS is able to detect the protein dynamics which may be associated with protein-protein or protein-DNA interactions in living cells and it may be useful for the drug screening.

A strategy for enrichment of claudins based on their affinity to Clostridium perfringens enterotoxin

BACKGROUND

Claudins, a family of protein localized in tight junctions, are essential for the control of paracellular permeation in epithelia and endothelia. The interaction of several claudins with Clostridium perfringens enterotoxin (CPE) has been exploited for an affinity-based enrichment of CPE-binding claudins from lysates of normal rat cholangiocytes.

RESULTS

Immunoblotting and mass spectrometry (MS) experiments demonstrate strong enrichment of the CPE-binding claudins -3, -4 and -7, indicating specific association with glutathione-S-transferase (GST)-CPE(116-319) fusion protein. In parallel, the co-elution of (non-CPE-binding) claudin-1 and claudin-5 was observed. The complete set of co-enriched proteins was identified by MS after electrophoretic separation. Relative mass spectrometric protein quantification with stable isotope labeling with amino acids in cell culture (SILAC) made it possible to discriminate specific binding from non-specific association to GST and/or matrix material.

CONCLUSION

CPE(116-319) provides an efficient tool for single step enrichment of different claudins from cell lysates. Numerous proteins were shown to be co-enriched with the CPE-binding claudins, but there are no indications (except for claudins -1 and -5) for an association with tight junctions.

Discrete dynamic modeling with asynchronous update, or how to model complex systems in the absence of quantitative information

A major aim of systems biology is the study of the inter-relationships found within and between large biological data sets. Here we describe one systems biology method, in which the tools of network analysis and discrete dynamic (Boolean) modeling are used to develop predictive models of cellular signaling in cases where detailed temporal and kinetic information regarding the propagation of the signal through the system is lacking. This approach is also applicable to data sets derived from some other types of biological systems, such as transcription factor-mediated regulation of gene expression during the control of developmental fate, or host defense responses following pathogen attack, and is equally applicable to plant and non-plant systems. The method also allows prediction of how elimination of one or more individual signaling components will affect the ultimate outcome, thus allowing the researcher to model the effects of genetic knockout or pharmacological block. The method also serves as a starting point from which more quantitative models can be developed as additional information becomes available.

Discrete dynamic modeling of cellular signaling networks

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Advanced technologies for studies on protein interactomes

One of the key challenges of biology in the post-genomic era is to assign function to the many genes revealed by large-scale sequencing programmes, since only a small fraction of gene function can be directly inferred from the coding sequence. Identifying interactions between proteins is a substantial part in understanding their function. The main technologies for investigating protein-protein interactions and assigning functions to proteins include direct detection intermolecular interactions through protein microarray, yeast two-hybrid system, mass spectrometry fluorescent techniques to visualize protein complexes or pull-down assays, as well as technologies detecting functional interactions between genes, such as RNAi knock down or functional screening of cDNA libraries. Over recent years, considerable advances have been made in the above techniques. In this review, we discuss some recent developments and their impact on the gene function annotation.

The tumour suppressor PTEN mediates a negative regulation of the E3 ubiquitin-protein ligase Nedd4

The tumour suppressor PTEN (phosphatase and tensin homologue deleted on chromosome 10; a phosphatidylinositol 3-phosphatase) is a multifunctional protein deregulated in many types of cancer. It is suggested that a number of proteins that relate with PTEN functionally or physically have not yet been found. In order to search for PTEN-interacting proteins that might be crucial in the regulation of PTEN, we exploited a proteomics-based approach. PTEN-expressing NIH 3T3 cell lysates were used in affinity chromatography and then analysed by LC–ESI–MS/MS (liquid chromatography–electrospray ionization–tandem MS). A total of 93 proteins were identified. Among the proteins identified, we concentrated on the E3 ubiquitin-protein ligase Nedd4 (neural-precursor-cell-expressed, developmentally down-regulated gene 4), and performed subsequent validation experiments using HeLa cells. Nedd4 inhibited PTEN-induced apoptotic cell death and, conversely, the Nedd4 level was down-regulated by PTEN. The down-regulation effect was diminished by a mutation (C124S) in the catalytic site of PTEN. Nedd4 expression was also decreased by a PI3K (phosphoinositide 3-kinase) inhibitor, LY294002, suggesting that the regulation is dependent on the phosphatase-kinase activity of the PTEN-PI3K/Akt pathway. Semi-quantitative real-time PCR analysis revealed that Nedd4 was transcriptionally regulated by PTEN. Thus our results have important implications regarding the roles of PTEN upon the E3 ubquitin ligase Nedd4 as a negative feedback regulator as well as a substrate.

Mammalian two-hybrid assay for detecting protein-protein interactions in vivo

The mammalian two-hybrid system is a very powerful tool to investigate protein-protein interactions in terms of functional domains and identify potential binding ligands and partners of a protein. Compared with the yeast two-hybrid system, the mammalian two-hybrid system provides the milieu for the bona fide posttranslational modifications and localizations of most eukaryotic proteins and, therefore, should be a better choice to study proteins of mammalian origin. This chapter depicts the detailed experimental procedures adapted by various laboratories. Researchers with experience in molecular biology could modify the procedures according to their own needs, that is, the choice of restriction sites in the cloning process. The reference list could be of use to researchers who wish to understand more of the system and explore its wider applications.

Ocular effects of exposure to industrial chemicals: clinical management and proteomic approaches to damage assessment

Industrial chemicals in a variety of applications are often found in highly populated areas and their presence carries risks. The threat of serious consequences from inadvertent or intentional events involving hazardous chemicals is a possibility. Extremism and/or other illicit activities pose environmental threats from chemical exposures. We present here a review of the threat of ocular injury in small-and large-scale chemical releases and discuss mechanisms of damage and repair to the eyes. The emerging field of proteomics has been described in relation to its potential role in the assessment of ocular changes following chemical exposures and management of ocular trauma.

Use of multidimensional separation protocols for the purification of trace components in complex biological samples for proteomics analysis

The routine detection of low abundance components in complex samples for detailed proteomics analysis continues to be a challenge. Whilst the potential of multidimensional chromatographic fractionation for this purpose has been proposed for some years, and was used effectively for the purification to homogeneity of trace components in bulk biological samples for N-terminal sequence analysis, its practical application in the proteomics arena is still limited. This article reviews some of the recent data using these approaches, including the use of microaffinity purification as part of multidimensional protocols for downstream proteomics analysis.

Co-immunoprecipitations revisited: an update on experimental concepts and their implementation for sensitive interactome investigations of endogenous proteins

The study of protein-protein interactions involving endogenous proteins frequently relies on the immunoaffinity capture of a protein of interest followed by mass spectrometry-based identification of co-purifying interactors. A notorious problem with this approach is the difficulty of distinguishing physiological interactors from unspecific binders. Additional challenges pose the need to employ a strategy that is compatible with downstream mass spectrometry and minimizes sample losses during handling steps. Finally, the complexity of data sets demands solutions for data filtering. Here we present an update on co-immunoprecipitation procedures for sensitive interactome mapping applications. We define the relevant terminology, review methodological advances that reduce sample losses, and discuss experimental strategies that facilitate recognition of candidate interactors through a combination of informative controls and data filtering. Finally, we provide starting points for initial validation experiments and propose conventions for manuscripts which report on co-immunoprecipitation work.

Advances in fungal proteomics

Proteomics, the global analysis of proteins, will contribute greatly to our understanding of gene function in the post-genomic era. This review summarizes recent developments in fungal proteomics and also generalizes protocols for sample preparation from plant pathogenic fungi. Challenges and future perspectives of proteomics are discussed as well.

Nutritional Proteomics: Methods and Concepts for Research in Nutritional Science

Nutritional proteomics or nutriproteomics is the application of proteomics methodology to nutrition-related research but also represents the interaction of bioactive food ingredients with proteins, whereby the interaction with proteins occurs in two basically specific ways. Firstly, the effect of nutrients on protein expression, which can be monitored by protein mapping, and secondly, the interaction of nutrients with proteins by post-translational modifications or small-molecule protein interactions. These interactions result in changes to the three-dimensional structure of such effected proteins. As a consequence, their original functions are modulated, resulting for example in reduced activity in the case of enzymes or changes in ability of recognition between molecules such as protein-protein interactions and ligand-receptor interactions. The characterization of such modifications together with functional data from established biochemical and physiological methods will result in a better understanding of the interplay between bioactive dietary components and diet-related diseases such as cancer, diabetes or neurodegenerative diseases. The occurrence of such modifications can possibly be additionally used as biomarkers in the diagnosis and therapy of these diseases as well as biomarkers for the efficacy or safety of selected nutrients.

Large-scale mapping of human protein-protein interactions by mass spectrometry

Mapping protein–protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein–protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24 540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein–protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

Mass spectrometry-based proteomic analysis of the epitope-tag affinity purified protein complexes in eukaryotes

In recent years, MS has been widely used to study protein complex in eukaryotes. The identification of interacting proteins of a particular target protein may help defining protein-protein interaction and proteins of unknown functions. To isolate protein complexes, high-speed ultracentrifugation, sucrose density-gradient centrifugation, and coimmunoprecipitation have been widely used. However, the probability of getting nonspecific binding is comparatively high. Alternatively, by use of one- or two-step (tandem affinity purification) epitope-tag affinity purification, protein complexes can be isolated by affinity or immunoaffinity columns. These epitope-tags include protein A, hexahistidine (His), c-Myc, hemaglutinin (HA), calmodulin-binding protein, FLAG, maltose-binding protein, Strep, etc. The isolated protein complex can then be subjected to protease (i.e., trypsin) digestion followed by an MS analysis for protein identification. An example, the epitope-tag purification of the Arabidopsis cytosolic ribosomes, is addressed in this article to show the success of the application. Several representative protein complexes in eukaryotes been isolated and characterized by use of this approach are listed. In this review, the comparison among different tag systems, validation of interacting relationship, and choices of MS analysis method are addressed. The successful rate, advantages, limitations, and challenges of the epitope-tag purification are also discussed.

N-cadherin is an in vivo substrate for protein tyrosine phosphatase sigma (PTPsigma) and participates in PTPsigma-mediated inhibition of axon growth

Protein tyrosine phosphatase sigma (PTPsigma) belongs to the LAR family of receptor tyrosine phosphatases and was previously shown to negatively regulate axon growth. The substrate for PTPsigma and the effector(s) mediating this inhibitory effect were unknown. Here we report the identification of N-cadherin as an in vivo substrate for PTPsigma. Using brain lysates from PTPsigma knockout mice, in combination with substrate trapping, we identified a hyper-tyrosine-phosphorylated protein of approximately 120 kDa in the knockout animals (relative to sibling controls), which was identified by mass spectrometry and immunoblotting as N-cadherin. beta-Catenin also precipitated in the complex and was also a substrate for PTPsigma. Dorsal root ganglion (DRG) neurons, which highly express endogenous N-cadherin and PTPsigma, exhibited a faster growth rate in the knockout mice than in the sibling controls when grown on laminin or N-cadherin substrata. However, when N-cadherin function was disrupted by an inhibitory peptide or lowering calcium concentrations, the differential growth rate between the knockout and sibling control mice was greatly diminished. These results suggest that the elevated tyrosine phosphorylation of N-cadherin in the PTPsigma(-/-) mice likely disrupted N-cadherin function, resulting in accelerated DRG nerve growth. We conclude that N-cadherin is a physiological substrate for PTPsigma and that N-cadherin (and likely beta-catenin) participates in PTPsigma-mediated inhibition of axon growth.

Cataloging the relationships between proteins: a review of interaction databases

By organizing and making widely accessible the increasing amounts of data from high-throughput analyses, protein interaction databases have become an integral resource for the biological community in relating sequence data with higher-order function. To provide a sense of the use and applicability of these databases, we describe each of the major comprehensive interaction databases as well as some of the more specialized ones. Content description, search/browse functionalities, and data presentation are discussed. A succinct explanation of database contents helps the user quickly identify whether the database contains applicable information to their research interest. Broad levels of search/browse functions as well as descriptions/examples allow users to quickly find and access pertinent data. At this point, clear presentation of search results as well as the primary content is necessary. Many databases display information graphically or divided into smaller digestible parts over a number of tabbed/linked pages. In addition, cross-linking between the databases promotes interconnectivity of the data and is an added layer of relational data for the user. Overall, although these protein interaction databases are under continual improvement, their current state shows that much time and effort has gone into organizing and presenting these large sets of data-describing protein interactions.

Protein kinase C delta activates topoisomerase IIalpha to induce apoptotic cell death in response to DNA damage

DNA topoisomerase II is an essential nuclear enzyme that modulates DNA processes by altering the topological state of double-stranded DNA. This enzyme is required for chromosome condensation and segregation; however, the regulatory mechanism of its activation is largely unknown. Here we demonstrate that topoisomerase IIalpha is activated in response to genotoxic stress. Concomitant with the activation, the expression of topoisomerase IIalpha is increased following DNA damage. The results also demonstrate that the proapoptotic kinase protein kinase C delta (PKCdelta) interacts with topoisomerase IIalpha. This association is in an S-phase-specific manner and is required for stabilization and catalytic activation of topoisomerase IIalpha in response to DNA damage. Conversely, inhibition of PKCdelta activity attenuates DNA damage-induced activation of topoisomerase IIalpha. Finally, aberrant activation of topoisomerase IIalpha by PKCdelta is associated with induction of apoptosis upon exposure to genotoxic agents. These findings indicate that PKCdelta regulates topoisomerase IIalpha and thereby cell fate in the genotoxic stress response.

Identification of Trichloroethanol Visualized Proteins from Two-Dimensional Polyacrylamide Gels by Mass Spectrometry

Proteins visualized by 2,2,2-trichloroethanol (TCE) on two-dimensional electrophoresis gels are efficiently identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and MS/MS. In a previous study, a method was developed that placed TCE in the polyacrylamide gel so that protein bands can be visualized without staining in less than 5 min. A visible fluorophore is generated by reaction of TCE with tryptophan that allows for protein visualization. In this study, MALDI-TOF MS and LC-MS/MS are used to identify randomly selected Escherichia coli proteins. The identification of TCE visualized proteins is compared to the identification of Coomassie brilliant blue (CBB) stained proteins from two-dimensional gel electrophoresis of E. coli proteins. This study demonstrated that TCE visualized proteins are compatible with protein identification by MALDI-TOF peptide mass fingerprinting. For 10 randomly selected spots, TCE visualization lead to statistically significant identification of 5 proteins and CBB visualization lead to identification of 6 proteins. TCE visualized proteins are also shown to be well suited for protein identification using LC-MS/MS. In 16 spots selected for MS/MS analysis, TCE samples lead to the identification of 79 peptides; while CBB samples lead to the identification of 65 peptides. TCE samples also supported the identification of more proteins. The low stoichiometry of labeling of tryptophan residues does not require inclusion of this modification for database searches. In addition to being a rapid visualization technique compatible with MS, TCE visualization utilizes rapid washing conditions for sample preparation of proteins spots excised from polyacrylamide gels.

Immune control of Babesia bovis infection

Babesia bovis causes an acute and often fatal infection in adult cattle, which if resolved, leads to a state of persistent infection in otherwise clinically healthy cattle. Persistently infected cattle are generally resistant to reinfection with related parasite strains, and this resistance in the face of infection is termed concomitant immunity. Young animals are generally more resistant than adults to B. bovis infection, which is dependent on the spleen. Despite the discovery of B. bovis over a century ago, there are still no safe and effective vaccines that protect cattle against this most virulent of babesial pathogens. Immunodominant antigens identified by serological reactivity and dominant T-cell antigens have failed to protect cattle against challenge. This review describes the innate and acquired immune mechanisms that define resistance in young calves and correlate with the development of concomitant immunity in older cattle following recovery from clinical disease. The first sections will discuss the innate immune responses by peripheral blood- and spleen-derived macrophages in cattle induced by B. bovis merozoites and their products that limit parasite replication, and comparison of natural killer cell responses in the spleens of young (resistant) and adult (susceptible) cattle. Later sections will describe a proteomic approach to discover novel antigens, especially those recognized by immune CD4+ T lymphocytes. Because immunodominant antigens have failed to stimulate protective immunity, identification of subdominant antigens may prove to be important for effective vaccines. Identification of CD4+ T-cell immunogenic proteins and their epitopes, together with the MHC class II restricting elements, now makes possible the development of MHC class II tetramers and application of this technology to both quantify antigen-specific lymphocytes during infection and discover novel antigenic epitopes. Finally, with the imminent completion of the B. bovis genome-sequencing project, strategies using combined genomic and proteomic approaches to identify novel vaccine candidates will be reviewed. The availability of an annotated B. bovis genome will, for the first time, enable identification of non-immunodominant proteins that may stimulate protective immunity.

Emerging tools for real-time label-free detection of interactions on functional protein microarrays

The availability of extensive genomic information and content has spawned an era of high-throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions--yeast two-hybrid and immunoprecipitation with mass spectrometric detection--have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high-throughput technologies for displaying proteins on functional protein microarrays and the real-time label-free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large-scale study of protein interactions with proteins as well as with other biomolecules.

Analysis of phosphatase and tensin homolog tumor suppressor interacting proteins by in vitro and in silico proteomics

The phosphatase and tensin homolog (PTEN) tumor suppressor is a multifunctional protein deregulated in many types of cancer. To date, a comprehensive documentation of PTEN interacting proteins has not been performed. The goal of our study was to characterize the PTEN interactome using affinity pull-down and tandem mass spectrometry (MS/MS). Wild-type PTEN cDNA was inserted into pTRC-His2 vector to create a 6-His tagged protein, which was expressed in Escherichia coli. Lysate from a human lymphoma cell line was used in pull-down assays, utilizing affinity for nickel-agarose beads. Bound proteins were eluted with imidazole, digested and analyzed on an LCQ DecaXP ion trap mass spectrometer. The nickel affinity pull-down efficiency was evaluated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western blot analysis. Acquired data were searched against the NCBI nr.fasta nonredundant protein database using the SEQUEST algorithm and screened using INTERACT and ProteinProphet. All experiments were performed in duplicate with 6-His-lacZ serving as control. A total of 79 proteins were identified in the wild-type 6-His-PTEN pull-down by MS/MS. We further validated a subset of the proteins present in the PTEN interactome by performing immunoprecipitation using an anti-PTEN antibody and establishing the presence of the proteins in the immunocomplex by Western blot analysis. A search of published PTEN interactions was also performed using Online Mendelian Inheritance in Man, Human Protein Reference Database, the IntAct Project database, and PubMed. This in silico analysis confirmed 42 out of 79 (53%) of the proteins identified by MS/MS. The remaining 37 proteins represent probable PTEN interactions not previously documented in public databases or reported in the literature. These results highlight the value of combining both in vitro biochemical approaches with in silico analyses for a comprehensive study of protein-protein interactions.

CLPM: a cross-linked peptide mapping algorithm for mass spectrometric analysis

Background

Protein-protein, protein-DNA and protein-RNA interactions are of central importance in biological systems. Quadrapole Time-of-flight (Q-TOF) mass spectrometry is a sensitive, promising tool for studying these interactions. Combining this technique with chemical crosslinking, it is possible to identify the sites of interactions within these complexes. Due to the complexities of the mass spectrometric data of crosslinked proteins, new software is required to analyze the resulting products of these studies.

Result

We designed a Cross-Linked Peptide Mapping (CLPM) algorithm which takes advantage of all of the information available in the experiment including the amino acid sequence from each protein, the identity of the crosslinker, the identity of the digesting enzyme, the level of missed cleavage, and possible chemical modifications. The algorithm does in silico digestion and crosslinking, calculates all possible mass values and matches the theoretical data to the actual experimental data provided by the mass spectrometry analysis to identify the crosslinked peptides.

Conclusion

Identifying peptides by their masses can be an efficient starting point for direct sequence confirmation. The CLPM algorithm provides a powerful tool in identifying these potential interaction sites in combination with chemical crosslinking and mass spectrometry. Through this cost-effective approach, subsequent efforts can quickly focus attention on investigating these specific interaction sites.

Prefractionation techniques in proteome analysis: the mining tools of the third millennium

The present review deals with prefractionation protocols used in proteomic investigation in preparation for mass spectrometry (MS) or two-dimensional electrophoresis (2-DE) map analysis. Briefly, reported methods focus on cell organelle differential centrifugation and on chromatographic approaches, to continue in extenso with a panoply of electrophoretic methods. In the case of chromatography, procedures useful as a prefractionation step, including affinity, ion-exchange, and reversed-phase resins, revealed several hundreds of new species, previously undetected in unfractionated samples. Novel chromatographic prefractionation methods are also discussed such as a multistaged fractionation column, consisting in a set of immobilized chemistries, serially connected in a stack format (an assembly of seven blocks), each capable of harvesting a given protein population. Such a method significantly simplifies the complexity of treated samples while concentrating species, all resulting in a larger number of visible proteins by MS or 2-DE. Electrophoretic prefractionation protocols include all those electrokinetic methodologies which are performed in free solution, essentially all relying on isoelectric focusing steps (although some approaches based on gels and granulated media are also discussed). Devices associated with electrophoretic separation are multichamber apparatus, such as the multicompartment electrolyzers equipped with either isoelectric membranes or with isoelectric beads. Multicup device electrophoresis and several others, exploiting the conventional technique of carrier ampholyte focusing, are reviewed. This review also reports approaches for sample treatments in order to detect low-abundance species. Among others, a special emphasis is made on the reduction of concentration difference between proteins constituting a sample. This latter consists in a library of combinatorial ligands coupled to small beads. Such a library comprises hexameric ligands composed of 20 amino acids, resulting in millions of different structures. When these beads are impregnated with complex proteomes (e.g., human sera) of widely differing protein compositions, they are able to significantly reduce the concentration differences, thus greatly enhancing the possibility to evidence low-abundance species. It is felt that this panoply of methods could offer a strong step forward in "mining below the tip of the iceberg" for detecting the "unseen proteome".

Interaction of the Saccharomyces cerevisiae cortical actin patch protein Rvs167p with proteins involved in ER to Golgi vesicle trafficking

We have used affinity chromatography to identify two proteins that bind to the SH3 domain of the actin cytoskeleton protein Rvs167p: Gyp5p and Gyl1p. Gyp5p has been shown to be a GTPase activating protein (GAP) for Ypt1p, a Rab GTPase involved in ER to Golgi trafficking; Gyl1p is a protein that resembles Gyp5p and has recently been shown to colocalize with and belong to the same protein complex as Gyp5p. We show that Gyl1p and Gyp5p interact directly with each other, likely through their carboxy-terminal coiled-coil regions. In assays of GAP activity, Gyp5p had GAP activity toward Ypt1p and we found that this activity was stimulated by the addition of Gyl1p. Gyl1p had no GAP activity toward Ypt1p. Genetic experiments suggest a role for Gyp5p and Gyl1p in ER to Golgi trafficking, consistent with their biochemical role. Since Rvs167p has a previously characterized role in endocytosis and we have shown here that it interacts with proteins involved in Golgi vesicle trafficking, we suggest that Rvs167p may have a general role in vesicle trafficking.

Myxoma virus M11L prevents apoptosis through constitutive interaction with Bak

M11L, a 166-amino-acid antiapoptotic protein of myxoma virus, was previously shown to bind to the peripheral benzodiazepine receptor by hydrophobic interactions at the outer mitochondrial membrane. Here we demonstrate that an additional property of M11L is the ability to constitutively form inhibitory complexes with the proapoptotic Bcl-2 family member Bak in human cells. This binding interaction was identified by both FLAG-tagged pull-down assays and tandem affinity purification from transfected and virus-infected human cells. M11L binds constitutively to human Bak and, under some inducible conditions, to human Bax as well, but not to the other Bcl-2 family members (Bad, Bid, Bcl-2). When stably expressed in human embryonic kidney (HEK293) cells, M11L effectively protects these cells from Fas ligand-induced apoptosis, thereby blocking release of cytochrome c, activation of caspase 9, and cleavage of poly(ADP-ribose) polymerase. We also demonstrate in coexpression studies that M11L can interact with Bak independently of any involvement with Bax. Furthermore, cells stably expressing M11L function to prevent apoptosis that is induced by overexpression of Bak. We conclude that M11L inhibits, in a species-independent fashion, apoptotic signals mediated by activation of Bak.

Chip-based analysis of protein-protein interactions by fluorescence detection and on-chip immunoprecipitation combined with microLC-MS/MS analysis

A new chip-based method to identify protein-protein interactions was developed using the guanine nucleotide exchange factor GRF2 and two interacting proteins, Ras and calmodulin, as model proteins. A generic immobilization strategy for FLAG-tagged bait proteins on a protein-repellent streptavidin chip surface was implemented by presentation of an oriented anti-FLAG antibody. A flow cell device, integrating different chip surfaces, was developed, and the interaction of immobilized GRF2 with the two analytes was verified by fluorescence assays. On-chip tryptic digest assays were then performed on the capture surface and analyzed by microLC-MS/MS. The interaction of GRF2 with calmodulin and Ras was demonstrated, and the lower limit of detection was determined. We also implemented an on-chip immunoprecipitation assay to identify GRF2-binding partners from complex protein mixtures. Cells overexpressing FLAG-GRF2 were lysed and then incubated with the anti-FLAG chip. In addition to detecting GRF2, we also identified calmodulin, demonstrating that this technique can successfully identify endogenous levels of proteins, bound to recombinant bait proteins. This chip-based method has the advantage that no subsequent gel separations of protein complexes prior to LC-MS analysis are required and is therefore amenable to miniaturized high-throughput determination of protein-protein interactions.

Host Evasion by Emerging Paramyxoviruses: Hendra Virus and Nipah Virus V Proteins Inhibit Interferon Signaling

Interferon (IFN) can activate Signal Transducer and Activator of Transcription (STAT) proteins to establish a cellular antiviral response and inhibit virus replication. Many viruses have evolved strategies to inhibit this antiviral mechanism, but paramyxoviruses are unique in their abilities to directly target the IFN-responsive STAT proteins. Hendra virus and Nipah virus (Henipaviruses) are recently emerged paramyxoviruses that are the causative agents of fatal disease outbreaks in Australia and peninsular Malaysia. Similar to other paramyxoviruses, Henipaviruses inhibit IFN signal transduction through a virus-encoded protein called V. Recent studies have shown that Henipavirus V proteins target STAT proteins by inducing the formation of cytoplasmically localized high molecular weight STAT-containing complexes. This sequestration of STAT1 and STAT2 prevents STAT activation and blocks antiviral IFN signaling. As the V proteins are important factors for host evasion, they represent logical targets for therapeutics directed against Henipavirus epidemics.

Quantification in Proteomics through Stable Isotope Coding: A Review

This review focuses on techniques for quantification and identification in proteomics by stable isotope coding. Methods are examined for analyzing expression, post-translational modifications, protein:protein interactions, single amino acid polymorphism, and absolute quantification. The bulk of the quantification literature in proteomics focuses on expression analysis, where a wide variety of methods targeting different features of proteins are described. Methods for the analysis of post-translational modification (PTM) focus primarily on phosphorylation and glycosylation, where quantification is achieved in two ways, either by substitution or tagging of the PTM with an isotopically coded derivatizing agent in a single process or by coding and selecting PTM modified peptides in separate operations. Absolute quantification has been achieved by age-old internal standard methods, in which an isotopically labeled isoform of an analyte is synthesized and added to a mixture at a known concentration. One of the surprises is that isotope coding can be a valuable aid in the examination of intermolecular association of proteins through stimulus:response studies. Preliminary efforts to recognize single amino acid polymorphism are also described. The review ends with the conclusion that (1) isotope ratio analysis of protein concentration between samples does not necessarily relate directly to protein expression and rate of PTM and (2) that multiple new methods must be developed and applied simultaneously to make existing stable isotope quantification methods more meaningful. Although stable isotope coding is a powerful, wonderful new technique, multiple analytical issues must be solved for the technique to reach its full potential as a tool to study biological systems.

Identification of NPM-ALK interacting proteins by tandem mass spectrometry

Constitutive overexpression of nucleophosmin-anaplastic lymphoma kinase (NPM-ALK) is a key oncogenic event in anaplastic large-cell lymphomas with the characteristic chromosomal aberration t(2;5)(p23;q35). Proteins that interact with ALK tyrosine kinase play important roles in mediating downstream cellular signals, and are potential targets for novel therapies. Using a functional proteomic approach, we determined the identity of proteins that interact with the ALK tyrosine kinase by co-immunoprecipitation with anti-ALK antibody, followed by electrospray ionization and tandem mass spectrometry (MS/MS). A total of 46 proteins were identified as unique to the ALK immunocomplex using monoclonal and polyclonal antibodies, while 11 proteins were identified in the NPM immunocomplex. Previously reported proteins in the ALK signal pathway were identified including PI3-K, Jak2, Jak3, Stat3, Grb2, IRS, and PLCgamma1. More importantly, many proteins previously not recognized to be associated with NPM-ALK, but with potential NPM-ALK interacting protein domains, were identified. These include adaptor molecules (SOCS, Rho-GTPase activating protein, RAB35), kinases (MEK kinase 1 and 4, PKC, MLCK, cyclin G-associated kinase, EphA1, JNK kinase, MAP kinase 1), phosphatases (meprin, PTPK, protein phosphatase 2 subunit), and heat shock proteins (Hsp60 precursor). Proteins identified by MS were confirmed by Western blotting and reciprocal immunoprecipitation. This study demonstrates the utility of antibody immunoprecipitation and subsequent peptide identification by tandem mass spectrometry for the elucidation of ALK-binding proteins, and its potential signal transduction pathways.

In line desalting mass spectrometry for the study of noncovalent biological complexes

Electrospray ionization-mass spectrometry is becoming widely used as a high-throughput method for the study of biomolecular interactions. It allows for the analysis of complexes from heterogeneous mixtures with high sensitivity and selectivity. In many cases, biomolecules and their complexes must be stored in nonvolatile salt buffers and other solubilizing agents, such as organics or detergents, to maintain stability and integrity. To ensure an efficient electrospray process, desalting and exchanging the biomolecular solutions into a volatile buffer is imperative. Current off-line or on-line methods to accomplish this are time-consuming, frequently disrupt noncovalent interactions, and can result in considerable sample loss. Here we describe a simple, general, and highly efficient, rapid in-line desalting approach using a small gel cartridge to assist in the mass spectrometric analysis of biomolecules and their complexes. Though the method has broad applicability, we focus our analysis on proteins and demonstrate its usefulness by examining protein-metal, protein-protein, protein-DNA, and protein-RNA interactions. The method is shown to provide rapid direct analysis of analyte solutions containing salts, glycerol, organics, and involatile buffers without deleterious effects.