SUMMARY Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions which were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably-associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes, and encompass both candidate disease genes and unnanotated proteins to inform on mechanism. Strikingly, whereas larger multi-protein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with 5 or fewer subunits are far more likely to be functionally un-annotated or restricted to vertebrates, suggesting more recent functional innovations.

Macromolecular assemblies involving membrane proteins (MPs) serve vital biological roles and are prime drug targets in a variety of diseases. Large-scale affinity purification studies of soluble-protein complexes have been accomplished for diverse model organisms, but no global characterization of MP-complex membership has been described so far. Here we report a complete survey of 1,590 putative integral, peripheral and lipid-anchored MPs from Saccharomyces cerevisiae, which were affinity purified in the presence of non-denaturing detergents. The identities of the co-purifying proteins were determined by tandem mass spectrometry and subsequently used to derive a high-confidence physical interaction map encompassing 1,726 membrane protein-protein interactions and 501 putative heteromeric complexes associated with the various cellular membrane systems. Our analysis reveals unexpected physical associations underlying the membrane biology of eukaryotes and delineates the global topological landscape of the membrane interactome.

Defective mobilization of Ca2؉ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca 2؉ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca

Cardiac-specific overexpression of a constitutively active form of calcineurin A (CNA) leads directly to cardiac hypertrophy in the CNA mouse model. Because cardiac hypertrophy is a prominent characteristic of many cardiomyopathies, we deduced that delineating the proteomic profile of ventricular tissue from this model might identify novel, widely applicable therapeutic targets. Proteomic analysis was carried out by subjecting fractionated cardiac samples from CNA mice and their WT littermates to gel-free liquid chromatography linked to shotgun tandem mass spectrometry. We identified 1,918 proteins with high confidence, of which 290 were differentially expressed. Microarray analysis of the same tissue provided us with alterations in the ventricular transcriptome. Because bioinformatic analyses of both the proteome and transcriptome demonstrated the up-regulation of endoplasmic reticulum stress, we validated its occurrence in adult CNA hearts through a series of immunoblots and RT-PCR analyses. Endoplasmic reticulum stress often leads to increased apoptosis, but apoptosis was minimal in CNA hearts, suggesting that activated calcineurin might protect against apoptosis. Indeed, the viability of cultured neonatal mouse cardiomyocytes (NCMs) from CNA mice was higher than WT after serum starvation, an apoptotic trigger. Proteomic data identified α-crystallin B (Cryab) as a potential mediator of this protective effect and we showed that silencing of Cryab via lentivector-mediated transduction of shRNAs in NCMs led to a significant reduction in NCM viability and loss of protection against apoptosis. The identification of Cryab as a downstream effector of calcineurin-induced protection against apoptosis will permit elucidation of its role in cardiac apoptosis and its potential as a therapeutic target.

High throughput methods are increasingly being used to examine the functions and interactions of gene products on a genome-scale. These include systematic large-scale proteomic studies of protein complexes and protein–protein interaction networks, functional genomic studies examining patterns of gene expression and comparative genomics studies examining patterns of conservation. Since these datasets offer different yet highly complementary perspectives on cell behavior it is expected that integration of these datasets will lead to conceptual advances in our understanding of the fundamental design and evolutionary principles that underlie the organization and function of proteins within biochemical pathways. Here we present Bacteriome.org, a resource that combines locally generated interaction and evolutionary datasets with a previously generated knowledgebase, to provide an integrated view of the Escherichia coli interactome. Tools are provided which allow the user to select and visualize functional, evolutionary and structural relationships between groups of interacting proteins and to focus on genes of interest. Currently the database contains three interaction datasets: a functional dataset consisting of 3989 interactions between 1927 proteins; a ‘core’ high quality experimental dataset of 4863 interactions between 1100 proteins and an ‘extended’ experimental dataset of 9860 interactions between 2131 proteins. Bacteriome.org is available online at http://www.bacteriome.org.

Multiple sclerosis is a chronic demyelinating disorder characterized by the infiltration of auto-reactive immune cells from the periphery into the central nervous system resulting in axonal injury and neuronal cell death. Experimental autoimmune encephalomyelitis represents the best characterized animal model as common clinical, histological, and immunological features are recapitulated. A label-free mass spectrometric proteomics approach was used to detect differences in protein abundance within specific fractions of disease-affected tissues including the soluble lysate derived from the spinal cord and membrane protein-enriched peripheral blood mononuclear cells. Tissues were harvested from actively induced experimental autoimmune encephalomyelitis mice and sham-induced ("vehicle" control) counterparts at the disease peak followed by subsequent analysis by nanoflow liquid chromatography tandem mass spectrometry. Relative protein quantitation was performed using both intensity-and fragmentation-based approaches. After statistical evaluation of the data, over 500 and 250 differentially abundant proteins were identified in the spinal cord and peripheral blood mononuclear cell data sets, respectively. More than half of these observations have not previously been linked to the disease. The biological significance of all candidate disease markers has been elucidated through rigorous literature searches, pathway analysis, and validation studies. Results from comprehensive targeted mass spectrometry analyses have confirmed the differential abundance of ϳ200 candidate markers (>twofold dysregulated expression) at a 70% success rate. This study is, to our knowledge, the first to examine the cell-surface proteome of peripheral blood mononuclear cells in experimental autoimmune encephalomyelitis. These data provide a unique mechanistic insight into the dynamics of peripheral immune cell infiltration into CNS-privileged sites at a molecular level and has identified several candidate markers, which represent promising targets for future multiple sclerosis therapies. The mass spectrometry proteomics data associated with this

Tandem mass spectrometry is the prevailing approach for large-scale peptide sequencing in high-throughput proteomic profiling studies. Effective database search engines have been developed to identify peptide sequences from MS/MS fragmentation spectra. Since proteins are polymorphic and subject to post-translational modifications (PTM), however, computational methods for detecting unanticipated variants are also needed to achieve true proteome-wide coverage. Different from existing "unrestrictive" search tools, we present a novel algorithm, termed SIMS (for Sequential Motif Interval Search), that interprets pairs of product ion peaks, representing potential amino acid residues or "intervals", as a means of mapping PTMs or substitutions in a blind database search mode. An effective heuristic software program was likewise developed to evaluate, rank, and filter optimal combinations of relevant intervals to identify candidate sequences, and any associated PTM or polymorphism, from large collections of MS/MS spectra. The prediction performance of SIMS was benchmarked extensively against annotated reference spectral data sets and compared favorably with, and was complementary to, current state-of-the-art methods. An exhaustive discovery screen using SIMS also revealed thousands of previously overlooked putative PTMs in a compendium of yeast protein complexes and in a proteome-wide map of adult mouse cardiomyocytes. We demonstrate that SIMS, freely accessible for academic research use, addresses gaps in current proteomic data interpretation pipelines, improving overall detection coverage, and facilitating comprehensive investigations of the fundamental multiplicity of the expressed proteome.

BackgroundThe full length Rad51 promoter is highly active in cancer cells but not in normal cells. We therefore set out to assess whether we could confer this tumor-selectivity to an adenovirus vector.Methodology/Principal FindingsExpression of an adenovirally-vectored luciferase reporter gene from the Rad51 promoter was up to 50 fold higher in cancer cells than in normal cells. Further evaluations of a panel of truncated promoter mutants identified a 447 bp minimal core promoter element that retained the full tumor selectivity and transcriptional activity of the original promoter, in the context of an adenovirus vector. This core Rad51 promoter was highly active in cancer cells that lack functional p53, but less active in normal cells and in cancer cell lines with intact p53 function. Exogenous expression of p53 in a p53 null cell line strongly suppressed activity of the Rad51 core promoter, underscoring the selectivity of this promoter for p53-deficient cells. Follow-up experiments showed that the p53-dependent suppression of the Rad51 core promoter was mediated via an indirect, p300 coactivator dependent mechanism. Finally, transduction of target cells with an adenovirus vector encoding the thymidine kinase gene under transcriptional control of the Rad51 core promoter resulted in efficient killing of p53 defective cancer cells, but not of normal cells, upon addition of ganciclovir.Conclusions/SignificanceOverall, these experiments demonstrated that a small core domain of the Rad51 promoter can be used to target selective transgene expression from adenoviral vectors to tumor cells lacking functional p53.