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PubMed2026

Mapping the covalent cysteine interactome of Ebselen reveals high-sensitivity target engagement and redox proteome remodeling.

Ebselen is a covalent organoselenium compound with broad pharmacological activity, yet its cellular cysteine targets and downstream proteomic consequences remain incompletely defined. Here, we integrated competitive gel-based activity-based protein profiling, reactivity-dependent tandem orthogonal proteolysis-activity-based protein profiling, and TMT-based quantitative proteomics to map Ebselen-induced cysteine engagement and proteome remodeling in living cancer cells. Ebselen exhibited dose-dependent cytotoxicity and markedly perturbed intracellular thiol-redox balance, as reflected by glutathione depletion and altered reactive oxygen species-associated fluorescence readouts. Competitive gel-based profiling confirmed concentration-dependent engagement of protein cysteine residues in live cells. Quantitative rdTOP-ABPP further identified hundreds of dose-responsive cysteine sites in HeLa and HepG2 cells and revealed a preference for cysteine microenvironments enriched with basic residues. Cross-cell-line comparison highlighted CDK5 Cys53, SMU1 Cys298, and RPSA2 Cys163 as conserved covalent nodes, among which CDK5 Cys53 showed high sensitivity to Ebselen treatment, a finding validated by competitive labeling and MS-based site assignment. Global TMT proteomics revealed extensive remodeling of redox-related and cell-survival-associated pathways, including compensatory upregulation of selenoproteins such as TXNRD1 and GPX family members. Together, these results define a chemical proteomic atlas of Ebselen-cysteine interactions and provide a framework for understanding and optimizing covalent organoselenium therapeutics.

Humans↗
PubMedDate not supplied

Chemical proteomic tool for ligand mapping of CYP antitargets: an NMR-compatible 3D QSAR descriptor in the Heme-Based Coordinate System.

Chemical proteomic strategies strive to probe and understand protein-ligand interactions across gene families. One gene family of particular interest in drug and xenobiotic metabolism are the cytochromes P450 (CYPs), the topic of this article. Although numerous tools exist to probe affinity of CYP-ligand interactions, fewer exist for the rapid experimental characterization of the structural nature of these interactions. As a complement to recent advances in X-ray crystallography, NMR methods are being developed that allow for fairly high throughput characterization of protein-ligand interactions. One especially promising NMR approach involves the use of paramagnetic induced relaxation effects to measure distances of ligand atoms from the heme iron in CYP enzymes. Distances obtained from these T(1) relaxation measurements can be used as a direct source of 1-dimensional structural information or to restrain a ligand docking to generate a 3-dimensional data set. To facilitate such studies, we introduce the concept of the Heme-Based Coordinate System and present how it can be used in combination with NMR T(1) relaxation data to derive 3D QSAR descriptors directly or in combination with in silico docking. These descriptors should have application in defining the binding preferences of CYP binding sites using 3D QSAR models. They are especially well-suited for the biasing of fragment assembly and combinatorial chemistry drug design strategies, to avoid fragment or reagent combinations with enhanced affinity for CYP antitargets.

Computer Simulation↗
PubMed2004

Comparison of the proteome of Methylobacterium extorquens AM1 grown under methylotrophic and nonmethylotrophic conditions.

Methylobacterium extorquens AM1 is a facultative methylotrophic bacterium that is capable of growing in the presence of methanol as the sole carbon and energy source, but is also able to grow on a limited number of C(2), C(3), and C(4) compounds, for example succinate. This study provides a proteomic view of the cellular adaptation of M. extorquens AM1 to growth on methanol and succinate, respectively. Cytosolic proteins were separated by two-dimensional gel electrophoresis employing overlapping pH ranges and visualized by silver nitrate or fluorescence staining. A proteomic reference map containing 229 different proteins identified by peptide mass fingerprinting of tryptic fragments was established. Comparative proteome profiling of methanol- and succinate-grown cells led to the identification of 68 proteins that are induced under methylotrophic growth conditions in comparison to growth on succinate. This group includes most proteins known to be directly involved in methanol oxidation to CO(2) and in assimilation of one carbon units by the serine cycle as well as 18 proteins without any assigned function and two proteins with a predicted regulatory function. Furthermore, the proteome analysis revealed putative isoenzymes for formaldehyde-activating enzyme Fae, malyl-CoA lyase, malate-dehydrogenase, and fumarase, that need to be characterized functionally in future studies.

Bacterial Proteins↗
PubMed2006

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

Animals↗
PubMed2026

Proteome-wide Ubiquitinome Profiling Reveals Substrate-specific Dynamics Within the USP7 Network.

USP7 is a pleiotropic deubiquitylating enzyme that is involved in tumor suppression, (neuro) development, chromatin regulation and the DNA damage response. How USP7 regulates these diverse pathways is still unclear. Here, we report data-independent acquisition and label free quantitation mass spectrometry to profile the proteome-wide impact of USP7 on substrate de-ubiquitylation and overall protein abundance. First, we identified proteins associated with endogenous USP7 by immunopurification followed by data-independent acquisition and label free quantitation mass spectrometry. Integration of our new results with earlier interactomes of epitope-tagged USP7 yielded a consensus set of high-confidence protein targets. Domain mapping analysis revealed that, in addition to the TRAF domain, the ubiquitin-like domains of USP7 play a key role in substrate selection. Using specific enrichment of tryptic K-ε-GG peptides, we mapped proteome-wide changes in ubiquitinome dynamics following inhibition of USP7. Combining unbiased proteome-wide and targeted quantitative mass spectrometry revealed that deubiquitylation by USP7 can have different effects on the stability of distinct substrates, and suggests that USP7's activity profile is substrate-dependent rather than an intrinsic enzymatic property. Thus, in addition to providing a proteome-wide map of USP7 target sites, our multi-angle proteomics approach reveals that the effects of USP7-mediated deubiquitylation on its targets are remarkably variable and substrate-specific. Finally, based on these detailed molecular insights we show how USP7 connects various neurodevelopmental syndromes and tumor suppression pathways.

Ubiquitin-Specific Peptidase 7↗
PubMed2002

Complexities in ETS-domain transcription factor function and regulation: lessons from the TCF (ternary complex factor) subfamily. The Colworth Medal Lecture.

The ETS-domain transcription factor family can be divided into a series of subfamilies. Elk-1 represents the founding member of the ternary complex factor (TCF) subfamily. By focusing on the TCF subfamily, we can demonstrate the complexities that exist in the function and regulation of ETS-domain transcription factors. This article focuses on Elk-1 in detail and summarizes the functions of other TCFs. The key themes covered include the domain structure of the TCFs, the mechanisms of complex formation with serum response factor, regulation of TCFs by mitogen-activated protein kinase cascades, and transcriptional regulatory properties of the TCFs. Finally, the emerging role of the TCFs in vivo is discussed. A picture is developing indicating that, while these proteins exhibit significant sequence and functional conservation, key differences in their structure and regulation are being identified which may relate to unique functions of these proteins in vivo.

Amino Acid Sequence↗
PubMed2006

Role and challenges of proteomics in pharma and biotech: technical, scientific and commercial perspective.

Contemporary proteomics, currently in its exponential growth phase, is a bewildering array of tools. Proteomic methods are the result of a convergence of rapidly improving mass spectrometry technologies, protein chemistry and separation sciences, genomics and bioinformatics. Strides in improving proteomics technologies to map and measure proteomes and subproteomes are being made. However, no single proteomic platform appears ideally suited to address all research needs or accomplish ambitious goals satisfactorily. However, proteomics is in a unique position to contribute to protein discovery and to public health in terms of better biomarkers, diagnostics and treatment of disease. While the potential is great, many challenges and issues remain to be solved. Fundamental issues, such as biological variability, pre-analytic factors and analytical reproducibility, remain to be resolved. Neither an all-genetic approach nor an all-proteomic approach will solve biological complexity. Proteomics will be the foundation for constructing and extracting useful knowledge to pharma and biotech depicted in the following path: data --> structured data --> information --> information architecture --> knowledge --> useful knowledge.

Animals↗
PubMed2003

Functional genomics and proteomics: charting a multidimensional map of the yeast cell.

The challenge of large-scale functional genomics projects is to build a comprehensive map of the cell including genome sequence and gene expression data, information on protein localization, structure, function and expression, post-translational modifications, molecular and genetic interactions and phenotypic descriptions. Some of this broad set of functional genomics data has been already assembled for the budding yeast. Even though molecular cartography of the yeast cell is still far from comprehensive, functional genomics has begun to forge connections between disparate cellular events and to foster numerous hypotheses. Here we review several different genomics and proteomics technologies and describe bioinformatics methods for exploring these data to make new discoveries.

Chromosome Mapping↗
PubMed2005

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D.

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.

Cell Line, Transformed↗
PubMed2006

Toward a comprehensive quantitative proteome database: protein expression map of lymphoid neoplasms by 2-D DIGE and MS.

Using 2-D DIGE, we constructed a quantitative 2-D database including 309 proteins corresponding to 389 protein spots across 42 lymphoid neoplasm cell lines. The proteins separated by 2-D PAGE were identified by MS and assigned to the expression data obtained by 2-D DIGE. The cell lines were categorized into four groups: those from Hodgkin's lymphoma (HL) (4 cell lines), B cell malignancies (19 cell lines), T cell malignancies (16 cell lines), and natural killer (NK) cell malignancies (3 cell lines). We characterized the proteins in the database by classifying them according to their expression level. We found 28 proteins with more than a 2-fold difference between the cell line groups. We also noted the proteins that allowed multidimensional separation to be achieved (1) between HL cells and other cells, (2) between the cells derived from B cells, T cells and NK cells, and (3) between HL cells and anaplastic large cell lymphoma cells. Decision tree classification identified five proteins that could be used to classify the 42 cell lines according to differentiation. These results suggest that the quantitative 2-D database using 2-D DIGE will be a useful resource for studying the mechanisms underlying the differentiation phenotypes of lymphoid neoplasms.

Algorithms↗
PubMedDate not supplied

Technology development at the interface of proteome research and genomics: mapping nonpolymorphic proteins on the physical map of mouse chromosomes.

Data obtained from protein spots by peptide mass fingerprinting are used to identify the corresponding genes in sequence databases. The relevant cDNAs are obtained as clones from the Integrated Molecular Analysis of Genome Expression (I.M.A.G.E.) consortium. Mapping of I.M.A.G.E. clones is performed in two steps: first, cDNA clones are hybridized against a 10-hit genomic mouse bacterial artificial chromosome (BAC) library. Second, interspersed repetitive sequence polymerase chain reaction (IRS-PCR) using a single primer directed against the mouse B1 repeat element is performed on BACs. As each cDNA detects several BACs, and each individual BAC has a 50% chance to recover an IRS-PCR fragment, the majority of cDNAs produce at least a single IRS-PCR fragment. Individual IRS fragments are hybridized against high-density spotted filter grids containing the three-dimensional permutated pools of yeast artificial chromosome (YAC) library resources that are currently being used to construct a physical map of the mouse genome. IRS fragments that hybridize to YAC clones already placed into contigs immediately provide highly precise map positions. This technology therefore is able to draw links between proteins detected by 2-D gel electrophoresis and the corresponding gene loci in the mouse genome.

Animals↗
PubMed2001

Proteomic analysis of dendritic cell-derived exosomes: a secreted subcellular compartment distinct from apoptotic vesicles.

Dendritic cells constitutively secrete a population of small (50-90 nm diameter) Ag-presenting vesicles called exosomes. When sensitized with tumor antigenic peptides, dendritic cells produce exosomes, which stimulate anti-tumor immune responses and the rejection of established tumors in mice. Using a systematic proteomic approach, we establish the first extensive protein map of a particular exosome population; 21 new exosomal proteins were thus identified. Most proteins present in exosomes are related to endocytic compartments. New exosomal residents include cytosolic proteins most likely involved in exosome biogenesis and function, mainly cytoskeleton-related (cofilin, profilin I, and elongation factor 1alpha) and intracellular membrane transport and signaling factors (such as several annexins, rab 7 and 11, rap1B, and syntenin). Importantly, we also identified a novel category of exosomal proteins related to apoptosis: thioredoxin peroxidase II, Alix, 14-3-3, and galectin-3. These findings led us to analyze possible structural relationships between exosomes and microvesicles released by apoptotic cells. We show that although they both represent secreted populations of membrane vesicles relevant to immune responses, exosomes and apoptotic vesicles are biochemically and morphologically distinct. Therefore, in addition to cytokines, dendritic cells produce a specific population of membrane vesicles, exosomes, with unique molecular composition and strong immunostimulating properties.

Animals↗
PubMed2006

Mitochondrial proteomic characterization of human normal articular chondrocytes.

OBJECTIVE: Mitochondrial dysfunctions have been associated with apoptosis, aging and osteoarthritis (OA). Chondrocyte mitochondrial proteins are attractive targets for the study of the metabolism of cartilage degradation. The copurification of "contaminating" proteins has been the major problem in all phases of mitochondrial proteome research. Therefore, we set up a procedure for the proteomic analysis of human chondrocyte mitochondrial proteins. METHOD: Four types of protein extracts were obtained from primary cultured chondrocytes isolated from healthy donors: (1) initial total chondrocyte extract (CE), (2) cytosol-enriched supernatant fraction (CY), (3) crude mitochondria fraction (CM), and (4) pure mitochondria fraction (PM). Mitochondria were purified by density gradient ultracentrifugation. Mitochondrial proteins were separated by means of two-dimensional gel electrophoresis (2-DE) and silver stained. Protein spots were then identified by mass spectrometry using MALDI-TOF/TOF technology. RESULTS: The best 2-DE reference map of mitochondrial proteome was constructed employing PM fraction. Thirty-nine percent of the identified proteins were functionally distributed in the mitochondria, 14% in the endoplasmic reticulum and 36% in the cytoplasm. Examining their biological function, 22% are involved in protein targeting, 12% in signaling, 12% in glycolysis, 10% in RNA, DNA or protein synthesis, 10% in oxidative phosphorylation and 4% in redox. The analysis of mitochondrial Mn-superoxide dismutase (SODM) revealed an age-dependent decrease of this protein. CONCLUSION: PM fraction allowed the obtention of a high quality proteomic map for the study of mitochondrial proteins in human articular chondrocytes. This proteomic approach may be also efficient to analyze both quantitative and qualitative modulations of the mitochondrial proteome in human chondrocytes during aging and pathological conditions such as OA.

Adolescent↗
PubMed2026

Hex-MASP for mapping the whole-tissue spatial proteome and the intrabrain distribution of monoclonal antibodies.

Whole-tissue level spatial proteomics provides critical insights into region-specific biological regulations but remains challenging. Previously, we introduced the micro-scaffold assisted spatial proteomics (MASP) concept for whole-tissue mapping. However, this prototype required substantial development in spatial resolution, practicality, and throughput for practical application. Here we present a next-generation MASP technique (hex-MASP) featuring i) a new design of hexagonal-micro-wells fabricated with optimized projection micro-stereolithography 3D-printing, achieving high spatial resolution, sampling robustness, and mechanical strength for reproducibly compartmentalizing even tough tissues; ii) enhanced throughput/effectiveness in sample preparation and LC-MS analysis with high quantitative quality. Applied to mouse brain, hex-MASP achieved in-depth, whole-tissue mapping for >6,000 proteins in mouse brains, with high spatial accuracy and excellent data quality. The substantially improved resolution revealed critical regional details across the entire brain, that were not previously captured, enabling precise depiction of protein distribution heterogeneity. This technique enabled the identification of many unreported regionally enriched proteins across brain structures. We further applied hex-MASP to investigate the intrabrain distribution of intracerebroventricularly dosed antibody therapeutics and related proteins, which enabled whole-tissue mapping of protein drugs revealed insights into antibody brain penetration and distribution. Hex-MASP represents a robust, scalable platform for whole-tissue spatial proteomics.

Animals↗
PubMed2007

Proteomics analysis of the interactome of N-myc downstream regulated gene 1 and its interactions with the androgen response program in prostate cancer cells.

NDRG1 is known to play important roles in both androgen-induced cell differentiation and inhibition of prostate cancer metastasis. However, the proteins associated with NDRG1 function are not fully enumerated. Using coimmunoprecipitation and mass spectrometry analysis, we identified 58 proteins that interact with NDRG1 in prostate cancer cells. These proteins include nuclear proteins, adhesion molecules, endoplasmic reticulum (ER) chaperons, proteasome subunits, and signaling proteins. Integration of our data with protein-protein interaction data from the Human Proteome Reference Database allowed us to build a comprehensive interactome map of NDRG1. This interactome map consists of several modules such as a nuclear module and a cell membrane module; these modules explain the reported versatile functions of NDRG1. We also determined that serine 330 and threonine 366 of NDRG1 were phosphorylated and demonstrated that the phosphorylation of NDRG1 was prominently mediated by protein kinase A (PKA). Further, we showed that NDRG1 directly binds to beta-catenin and E-cadherin. However, the phosphorylation of NDRG1 did not interrupt the binding of NDRG1 to E-cadherin and beta-catenin. Finally, we showed that the inhibition of NDRG1 expression by RNA interference decreased the ER inducible chaperon GRP94 expression, directly proving that NDRG1 is involved in the ER stress response. Intriguingly, we observed that many members of the NDRG1 interactome are androgen-regulated and that the NDRG1 interactome links to the androgen response network through common interactions with beta-catenin and heat shock protein 90. Therefore we overlaid the transcriptomic expression changes in the NDRG1 interactome in response to androgen treatment and built a dual dynamic picture of the NDRG1 interactome in response to androgen. This interactome map provides the first road map for understanding the functions of NDRG1 in cells and its roles in human diseases, such as prostate cancer, which can progress from androgen-dependent curable stages to androgen-independent incurable stages.

Androgens↗
PubMed2001

Towards the Toxoplasma gondii proteome: position of 13 parasite excretory antigens on a standardized map of two-dimensionally separated tachyzoite proteins.

High resolution two-dimensional separation of Toxoplasma gondii tachyzoite lysate revealed up to 224 distinct protein spots in Coomassie-stained gel. Computional matching of 14 digitized gels yielded a standard two-dimensional proteome map. The excretory T. gondii dense granule proteins GRA1-GRA8, S16/acid phosphatase, nucleoside triphosphate hydrolase, and H4 were identified by Western blotting of both total gel and isolated protein spots. In addition, two excretory antigens defined by parasite-specific monoclonal T cells, p36 and p40, were mapped by a novel T-cell blotting technique based on electroeluting single protein spots and testing the eluates for antigenic activity against the T-cell clones. In summary, these results represent a first step in Toxoplasma proteome analysis.

Animals↗
PubMed2004

Complexity analysis of yeast proteome network.

Topological and compositional complexity of protein-protein networks is assessed in a variety of ways making use of graph theory and information theory. The methodology used is borrowed from mathematical chemistry and includes complexity descriptors such as substructure count, overall connectivity, walk count, and information on various vertex distributions. The approach is applied to the (incomplete) proteome of Saccharomyces cerevisiae containing 232 protein complexes of a total of 1,440 proteins. The proteome network and each of its nine functional subsets of protein complexes are disconnected graphs, containing a number of noninteracting species and a major component. A weighted edge between two vertices in these graphs stands for the number of shared proteins between the respective complexes. The major component is a highly connected, 'small-world' network, in which the average vertex distance between protein complexes does not exceed 2.2 (2.4 for the entire proteome), whereas the maximum distance does not exceed 4 (or 5 for the proteome). The vertex degree distribution in the major proteome component with 199 complexes follows the power law P(k) approximately k(-gamma), with gamma approximately = 1.7. The analysis of the functional organization of the yeast proteome has shown that, for any pair of biological functions, there always exist many proteins that can perform both functions. The potential application of the quantitative proteome descriptors discussed includes quantitative relationships between the structure and biological action of dynamic protein complexes in changing environment, identification of targets for markers/drugs, as well as system analysis and comparative studies of proteomes.

Fungal Proteins↗