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Results for “targeted proteomic analysis”

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PubMed2002

Application of NMR in structural proteomics: screening for proteins amenable to structural analysis.

In the time of structural proteomics when protein structures are targeted on a genome-wide scale, the detection of "well-behaved" proteins that would yield good quality NMR spectra or X-ray images is the key to high-throughput structure determination. Already, simple one-dimensional proton NMR spectra provide enough information for assessing the folding properties of proteins. Heteronuclear two-dimensional spectra are routinely used for screenings that reveal structural, as well as binding, properties of proteins. NMR can thus provide important information for optimizing conditions for protein constructs that are amenable to structural studies.

Nuclear Magnetic Resonance, Biomolecular↗

PubMed2002

Genomics and plant cells: application of genomics strategies to Arabidopsis cell biology.

In this review I seek to describe how the complete catalogue of plant genes and proteins, revealed by genome sequencing, can provide novel insights into cell biology. Many new analytical methods have been developed to digest the flood of genome sequence data, including analysis of the transcriptome, proteome and metabolites. High-throughput analysis of protein targeting and other methods will ascribe new information to proteins and create important links with other large datasets. To fulfil the potential revealed by this genomic information, many challenges have to be met. Among these are organizational changes needed to create common datasets accessible to all scientists, and bioinformatics solutions to capture and integrate diverse datasets. Once harnessed, these new strategies will irrevocably change the way we conduct plant science.

Arabidopsis↗

PubMed2003

[Advances in the applications of DNA chips and proteomics approaches for neurosciences].

DNA chips and proteomics are two of the recently developed high-throughput technologies that allow us to simultaneously analyze the expression levels of multiple genes and the interactions of their products in the brain. Their applications in neuroscience provide us with the unprecedented opportunities for understanding of the brain. A typical gene chip experiment contains a series of steps, including preparations (or purchase) of DNA chips, target DNA and probes, hybridization of chips with target DNA, chip scanning, and imaging analysis. The technologies in proteomics are more complicated, which comprise of three main aspects of technologies: protein isolation, identification and bioinformatic analysis of data. If protein isolation is based on 2-D, it includes the preparation of protein sample, 2-D, staining gels, spot excision, proteolysis, mass spectrometry of purified protein and finally undergoing bioinformatic analysis. Here we review the two technologies with emphasis on their applications in neurosciences. The challenges, advantages and disadvantages of the two techniques, and perspectives for their developments are discussed.

Animals↗

PubMed2026

Integrated multi-omics strategies for identifying novel therapies in psoriasis.

MOTIVATION: Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression (DGE) from bulk and single-cell RNA sequencing (scRNA-seq), colocalization, pathway enrichment, and protein-protein interaction analyses. RESULTS: Proteome-wide MR identified 29 candidate protein targets (Bonferroni-corrected), all replicated in independent datasets. Fifteen targets showed significant expression associations in blood or skin. Eleven proteins-UBLCP1, IL23A, ASF1A, RARRES2, ICAM1, PRSS53, ICAM5, GCA, IL2RA, DBI, and NFKB1-exhibited consistent directional effects with their genes. Genetic susceptibility analysis confirmed 20 target-specific polygenic scores for psoriasis and five for psoriatic arthritis. DGE analysis identified 13 targets in bulk and 13 in scRNA-seq-primarily in keratinocytes and immune cells-with IL2RA, COMP, and A2ML1 dysregulated across both. Colocalization analysis implicated shared causal variants for psoriasis in ASF1A, CD8A, CTF1, IL7R, MMP12, RARRES2, XCL2, DBI, IL23A, IL2RA, SGSH, and TIMD4. Enrichment analyses highlighted involvement in cytotoxicity, immune regulation, and JAK-STAT signaling. Eighteen targets interacted with approved anti-psoriasis drugs. Notably, drugs targeting IL2RA, IL7R, CTF1, ICAM1, MMP12, NFKB1, CD8A, DDX58, IL12A, SGSH, and FAP are approved or in trials for other diseases, suggesting repurposing potential. Our integrative multi-omics approach prioritized 29 high-confidence targets, including 13 novel candidates (RARRES2, ASF1A, CTF1, DBI, B3GNT2, CD8A, TIMD4, CRTAM, SGSH, XCL2, DAPK2, A2ML1, and FAP). Several high-priority targets-such as IL2RA, IL23, MMP12, RARRES2, IL7R, and ICAM1-were supported across analytical layers. These findings provide a robust foundation for psoriasis drug development. AVAILABILITY AND IMPLEMENTATION: The code used for the analyses in this manuscript has been archived in Zenodo at [DOI: 10.5281/zenodo.19692128].

Psoriasis↗

PubMed2005

[Methods of experimental validation of potential target proteins for creation of new drugs].

Review is devoted to the description of the main existing and developing technologies for experimental validation of potential targets predicted in silico by comparative genomics and bioinformatics methods. Since this problem has not been solved yet, the description of a wide set of methods, suitable for the validation of potential targets, is given. The following questions have been considered: (1) applications of proteomic technologies (control of potential targets expression and their variability, analysis of protein-protein interactions); (2) use of genomics technologies in experimental validation of targets (inactivation of the target genes, suppression of transcription, inactivation of the target mRNA, suppression of translation); (3) methods of direct inactivation of target proteins (monoclonal antibodies, light-inactivation, one-chain antibodies, intrabodies, aptamers); (4) high-throughput technologies; (5) targets validations in vivo.

Animals↗

PubMed2005

Effects of increased cellular zinc levels on gene and protein expression in HT-29 cells.

High cellular zinc concentrations lead to impairments in ATP synthesis and cell cycle control particularly in neurons and epithelial cells. The molecular basis for these dysfunctions is still not fully elucidated. Here we analyzed the effects of a high zinc exposure (10 ppm) on gene and protein expression in the human epithelial cell line HT-29. Of the 1176 genes analyzed with cDNA arrays, nine differentially expressed genes were identified. Proteome analysis based on 1310 detected proteins identified 11 molecular targets. Most of the identified genes/proteins have not been linked to cellular zinc status before (e.g. PEC-60, R-ras3). More than half of the targets participate in ATP production or stress response. Therefore, it appears that higher zinc concentrations mediate their effects mainly via impairments in cellular energy metabolism and stress response.

Gene Expression Profiling↗

PubMed2003

The proteome: anno Domini 2002.

We present some current definitions related to functional and structural proteomics and the human proteome, and we review the following aspects of proteome analysis: Classical 2-D map analysis (isoelectric focusing (IEF) followed by SDS-PAGE); Quantitative proteomics (isotope-coded affinity tag (ICAT), fluorescent stains) and their use in e.g., tumor analysis and identification of new target proteins for drug development; Electrophoretic pre-fractionation (how to see the hidden proteome!); Multidimensional separations, such as: (a) coupled size-exclusion and reverse-phase (RP)-HPLC; (b) coupled ion-exchange and RP-HPLC; (c) coupled RP-HPLC and RP-HPLC at 25/60 degrees C; (d) coupled RP-HPLC and capillary electrophoresis (CE); (e) metal affinity chromatography coupled with CE; Protein chips. Some general conclusions are drawn on proteome analysis and we end this review by trying to decode the glass ball of the aruspex and answer the question: "Quo vadis, proteome"?

Animals↗

PubMed2007

Comparative proteomic analysis of chronic myelogenous leukemia cells: inside the mechanism of imatinib resistance.

Imatinib is the first molecular targeted therapy that has shown clinical success, but imatinib acquired resistance, although a rare event, is critical during the therapy of chronic myelogenous leukaemia (CML). With the aim of better understanding the molecular mechanisms accompanying acquisition of resistance to this drug, a comparative proteomic approach was undertaken on CML cell lines LAMA 84 S (imatinib sensitive) and LAMA 84 R (imatinib resistant). Forty-four differentially expressed proteins were identified and categorized into five main functional classes: (I) heat shock proteins and chaperones; (II) nucleic acid interacting proteins (binding/synthesis/stability); (III) structural proteins, (IV) cell signaling, and (V) metabolic enzymes. Several heat shock proteins known to complex Bcr-Abl were overexpressed in imatinib resistant cells, showing a possible involvement of these proteins in the mechanism of resistance. HnRNPs also resulted in being up-regulated in imatinib resistant cells. These proteins have been shown to be strongly and directly related to Bcr-Abl activity. To our knowledge, this is the first direct proteomic comparison of imatinib sensitive/resistant CML cell lines.

Antineoplastic Agents↗

PubMed2025

Integrative proteomic analysis provides novel therapeutic insights for etiological subtypes of diabetes.

AIMS: Type 2 diabetes (T2D) is a highly heterogeneous disease characterised by subtypes with variations in aetiology, disease progression, and risk of complications. However, potential drug targets for these subtypes have not been explored. This study aims to investigate potential drug targets by integrating proteomics. MATERIALS AND METHODS: Summary-level data of circulating proteins were extracted from the UK Biobank and the deCODE Health Study. Genetic associations with five diabetes subtypes were obtained from Swedish All New Diabetics in Scania and Malmö Diet and Cancer cohort, including severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). The associations between circulating proteins and diabetes subtypes were assessed through Mendelian randomisation, followed by multiple sensitivity and colocalization analyses. Additionally, tissue-specific, pathway and functional enrichment analysis, assessment of protein druggability, and the protein-protein interaction (PPI) networks were used to further explore biological mechanisms and therapeutic potential. RESULTS: Genetically predicted levels of 2, 2, 9, 3, and 5 circulating proteins were associated with SIRD, SIDD, MARD, MOD, and SAID, respectively. Colocalization analyses further revealed links between GRN with MARD/SIRD, LILRB5 with SIDD/MARD, CR1 with MARD, TNFSF12 with MOD, and DAPK2 with SAID. Enrichment analysis suggested that these proteins were mainly enriched in blood and adipose tissues and involved in immune and inflammatory related pathways. PPI analysis revealed GRN, TNFSF12, and DAPK2 are associated with known T2D targets. CONCLUSIONS: Our study identified several potential drug targets for different subtypes of diabetes using an integrated genetic approach, yielding new insights for precision medicine of diabetes.

Humans↗

PubMed2004

Proteomic analysis of integral plasma membrane proteins.

Efficient methods for profiling proteins integral to the plasma membrane are highly desirable for the identification of overexpressed proteins in disease cells. Such methods will aid in both understanding basic biological processes and discovering protein targets for the design of therapeutic monoclonal antibodies. Avoiding contamination by subcellular organelles and cytosolic proteins is crucial to the successful proteomic analysis of integral plasma membrane proteins. Here we report a biotin-directed affinity purification (BDAP) method for the preparation of integral plasma membrane proteins, which involves (1) biotinylation of cell surface membrane proteins in viable cells, (2) affinity enrichment using streptavidin beads, and (3) depletion of plasma membrane-associated cytosolic proteins by harsh washes with high-salt and high-pH buffers. The integral plasma membrane proteins are then extracted and subjected to SDS-PAGE separation and HPLC/MS/MS for protein identification. We used the BDAP method to prepare integral plasma membrane proteins from a human lung cancer cell line. Western blotting analysis showed that the preparation was almost completely devoid of actin, a major cytosolic protein. Nano-HPLC/MS/MS analysis of only 30 microg of protein extracted from the affinity-enriched integral plasma membrane preparation led to the identification of 898 unique proteins, of which 781 were annotated with regard to their plasma membrane localization. Among the annotated proteins, at least 526 (67.3%) were integral plasma membrane proteins. Notable among them were 62 prenylated proteins and 45 Ras family proteins. To our knowledge, this is the most comprehensive proteomic analysis of integral plasma membrane proteins in mammalian cells to date. Given the importance of integral membrane proteins for drug design, the described approach will expedite the characterization of plasma membrane subproteomes and the discovery of plasma membrane protein drug targets.

Cell Line, Tumor↗

PubMed2004

Proteomic characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery.

Clinical cancer proteomics aims at the identification of markers for early detection and predictive purposes, as well as to provide novel targets for drug discovery and therapeutic intervention. Proteomics-based analysis of traditional sources of biomarkers, such as serum, plasma, or tissue lyzates, has resulted in a wealth of information and the finding of several potential tumor biomarkers. However, many of these markers have shown limited usefulness in a clinical setting, underscoring the need for new clinically relevant sources. Here we present a novel and highly promising source of biomarkers, the tumor interstitial fluid (TIF) that perfuses the breast tumor microenvironment. We collected TIFs from small pieces of freshly dissected invasive breast carcinomas and analyzed them by two-dimensional polyacrylamide gel electrophoresis in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Western immunoblotting, as well as by cytokine-specific antibody arrays. This approach provided for the first time a snapshot of the protein components of the TIF, which we show consists of more than one thousand proteins--either secreted, shed by membrane vesicles, or externalized due to cell death--produced by the complex network of cell types that make up the tumor microenvironment. So far, we have identified 267 primary translation products including, but not limited to, proteins involved in cell proliferation, invasion, angiogenesis, metastasis, inflammation, protein synthesis, energy metabolism, oxidative stress, the actin cytoskeleton assembly, protein folding, and transport. As expected, the TIF contained several classical serum proteins. Considering that the protein composition of the TIF reflects the physiological and pathological state of the tissue, it should provide a new and potentially rich resource for diagnostic biomarker discovery and for identifying more selective targets for therapeutic intervention.

Adult↗

PubMed2002

Peptide sequence motif analysis of tandem MS data with the SALSA algorithm.

We have developed a pattern recognition algorithm called SALSA (scoring algorithm for spectral analysis) for the detection of specific features in tandem MS (MS-MS) spectra. Application of the SALSA algorithm to the detection of peptide MS-MS ion series enables identification of MS-MS spectra displaying characteristics of specific peptide sequences. SALSA analysis scores MS-MS spectra based on correspondence between theoretical ion series for peptide sequence motifs and actual MS-MS product ion series, regardless of their absolute positions on the m/z axis. Analyses of tryptic digests of bovine serum albumin (BSA) by LC-MS-MS followed by SALSA analysis detected MS-MS spectra for both unmodified and multiple modified forms of several BSA tryptic peptides. SALSA analysis of MS-MS data from mixtures of BSA and human serum albumin (HSA) tryptic digests indicated that ion series searches with BSA peptide sequence motifs identified MS-MS spectra for both BSA and closely related HSA peptides. Optimal discrimination between MS-MS spectra of variant peptide forms is achieved when the SALSA search criteria are optimized to the target peptide. Application of SALSA to LC-MS-MS proteome analysis will facilitate the characterization of modified and sequence variant proteins.

Algorithms↗

PubMedDate not supplied

Reversed-phase high-performance liquid chromatographic prefractionation of immunodepleted human serum proteins to enhance mass spectrometry identification of lower-abundant proteins.

Serum analysis represents an extreme challenge due to the dynamic range of the proteins of interest, and the high structural complexity of the constituent proteins. In serum, the quantities of proteins and peptides of interest range from those considered "high abundance", present at 2-70% by mass of total protein, to those considered "low abundance", present at 10(-12) M or less. This range of analytical target molecules is outside the realm of available technologies for proteomic analysis. Therefore, in this study, we have developed a workflow toward addressing the complexity of these samples through the application of multidimensional separation techniques. The use of reversed-phase methods for the separation and fractionation of protein samples has been investigated, with the goal of developing an optimized serum separation for application to proteomic analysis. Samples of human serum were depleted of the six most abundant proteins, using an immunoaffinity LC method, then were separated under a variety of reversed-phase (RP) conditions using a macroporous silica C18 surface modified column material. To compare the qualities of the RP separations of this complex protein sample, absorbance chromatograms were compared, and fractions were collected for off-line SDS-PAGE and 2D-LC-MS/MS analysis. The column fractions were further investigated by determination of protein identities using either whole selected fractions, or gel bands excised from SDS-PAGE gels of the fractions. In either case samples underwent tryptic fragmentation and peptide analysis using MALDI-MS or LC-MS/MS. The preferred conditions for RP protein separation exhibited reproducibly high resolution and high protein recoveries (>98%, as determined by protein assay). Using the preferred conditions also permitted high column mass load, with up to 500 microg of protein well tolerated using a 4.6 mm ID x 50 mm column, or up to 1.5 mg on a 9.4 mm ID x 50 mm column. Elevated column temperature (80 degrees C) was observed to be a critical operational parameter, with poorer results observed at lower temperatures. The combination of sample simplification by immunoaffinity depletion combined with a robust and high recovery RP-HPLC fractionation yields samples permitting higher quality protein identifications by coupled LC-MS methods.

Amino Acid Sequence↗

PubMed2006

Proteomic analysis of plasma membrane from hypoxia-adapted malignant melanoma.

Hypoxic conditions often persist within poorly vascularized tumors. At the cellular level constitutive activation of transcriptional regulators of the hypoxic response leads to the emergence of clones with aggressive phenotypes. The primary interface between the cell and the hypoxic environment is the plasma membrane. A detailed investigation of this organelle is expected to yield further targets for therapeutic perturbation of the response to hypoxia. In the present study, quantitative proteomic analysis of plasma membrane from hypoxia-adapted murine B16F10 melanoma was performed using differential 16O/18O stable isotopic labeling and multidimensional liquid chromatography-tandem mass spectrometry. The analysis resulted in the identification of 24,853 tryptic peptides, providing quantitative information for 2,433 proteins. For a subset of plasma membrane and secreted proteins, quantitative RT-PCR was used to gain further insight into the genomic regulatory events underlying the response to hypoxia. Consistent increases at the proteomic and transcriptomic levels were observed for aminopeptidase N (CD13), carbonic anhydrase IX, potassium-transporting ATPase, matrix metalloproteinase 9, and stromal cell derived factor I (SDF-1). Antibody-based analysis of a panel of human melanoma cell lines confirmed that CD13 and SDF-1 were consistently upregulated during hypoxia. This study provides the basis for the discovery of novel hypoxia-induced membrane proteins.

Amino Acid Sequence↗

PubMed2004

High-throughput proteomics using antibody microarrays.

Antibody-based microarrays are a novel technology that hold great promise in proteomics. Microarrays can be printed with thousands of recombinant antibodies carrying the desired specificities, the biologic sample (e.g., an entire proteome) and any specifically bound analytes detected. The microarray patterns that are generated can then be converted into proteomic maps, or molecular fingerprints, revealing the composition of the proteome. Using this tool, global proteome analysis and protein expression profiling will thus provide new opportunities for biomarker discovery, drug target identification and disease diagnostics, as well as providing insights into disease biology. Intense work is currently underway to develop this novel technology platform into the high-throughput proteomic tool required by the research community.

Antibodies↗

PubMed2005

Emerging issues of the expression profiling technologies for the study of gynecologic cancer.

Evaluation of the prognostic parameters of gynecologic cancer has shown their failure for classification according to the clinical behavior or the prediction of its outcome. This weakness has important implications on prognosis and treatment. The increasing understanding of the complexity of the human genome, coupled with the development of high throughput analysis techniques and bioinformatics tools, has changed our concepts on cancer biology, by shifting our targets to a global analysis of the transcriptome and the proteome, linking genes and their products into functional pathways. These approaches permit the documentation of expression patterns of thousands of genes within a cell. With the use of DNA microarray technology, it is feasible to identify signature patterns of expression in tumor samples that faithfully correlate with its biology, providing accurate prognosis for each cancer patient and thus a rational customized treatment. At this stage, there is a need for systematic studies for the validation of these novel approaches. In this review, we provide a basic background of the concept of the technology, highlight several emerging issues from their applications on gynecologic cancer, discuss a series of important themes and problems regarding their interpretation and relevance for the clinicians, and comment on future areas of research.

Computational Biology↗

PubMed2003

Rediscovering the sweet spot in drug discovery.

Advances over the past decade in drug discovery technologies have not yet led to an increase in productivity. We analyzed the reasons that have led to this juncture and identify the selection of the right target and the right lead as crucial. New approaches are required to take full advantage of the genomics revolution. For targets, methods are becoming available for high-throughput proteome analysis and pathway characterization that synergize with studies of disease association and differential expression. For leads, methods are being developed that 'reverse' the high-throughput screening paradigm by mapping drugs and drug-like compounds back onto the proteome. The synergy between pathway mapping and compound mapping could allow the pharmaceutical and biotechnology industries to rediscover the sweet spot of research productivity.

Biotechnology↗

PubMed2005

Transcriptome and proteome analysis identifies the pathways that increase hepatic lipid accumulation in zinc-deficient rats.

For identification of the underlying molecular changes in hepatic lipid metabolism in zinc deficiency, rats were force-fed a zinc-deficient diet. Subsequently DNA-microarray and proteome profiling was performed in combination with hepatic lipid analysis. Of 6200 target sequences analyzed, 268 transcripts showed altered expression levels in livers of zinc-deficient rats, with 43 genes thereof related to hepatic lipid metabolism. Northern blot analysis and quantitative real-time RT-PCR were employed to confirm changes in mRNA levels. Proteins involved in lipid metabolism were identified by proteome analysis. Functional gene clusters with uniform changes in transcript levels suggested that the pathways required for lipolysis and mitochondrial as well as peroxisomal fatty acid degradation were downregulated, whereas those needed for de novo fatty acid synthesis and triglyceride assembly were increased. Subsequent enzymatic analysis of liver tissues confirmed an almost 40% greater triacylglycerol concentration in zinc-depleted rats, as well as an altered fatty acid composition of the lipid fraction as determined by gas chromatography. Liver lipids of zinc-deficient rats had significantly greater proportions of cis-9-oleic acid, cis-11-vaccenic acid, caprylic acid, myristic acid, alpha-linolenic acid, and eicosapentaenoic acid, and significantly less stearic and arachidonic acids. These alterations in hepatic metabolism are discussed in the context of changes in mRNA and protein levels of enzymes and transporters responsible for fatty acid metabolism, sequestration, and their transcriptional control.

Animals↗