Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “quantitative proteomics”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59Linked to original sources
PubMed2005

Subcellular proteomic analysis of host-pathogen interactions using human monocytes exposed to Yersinia pestis and Yersinia pseudotuberculosis.

Yersinia pestis, the etiological agent of plague, is of concern to human health both from an infectious disease and a biodefense perspective. While Y. pestis and Yersinia pseudotuberculosis share more than 90% DNA homology, they have significantly different clinical manifestations. Plague is often fatal if untreated, yet Y. pseudotuberculosis causes severe intestinal distress but is rarely fatal. A better understanding of host response to these closely related pathogens may help explain the different mechanisms of virulence and pathogenesis that result in such different clinical outcomes. The aim of this study was to characterize host protein expression changes in human monocyte U937 cells after exposure to Y. pestis and Y. pseudotuberculosis. In order to gain global proteomic coverage of host response, proteins from cytoplasmic, nuclear and membrane fractions of host cells were studied by two-dimensional differential gel electrophoresis and relative protein expression differences were quantitated. Differentially expressed proteins, with at least 1.5-fold expression changes and p values of 0.01 or less, were identified by mass spectrometry including matrix-assisted laser desorption/ionization-MS or liquid chromatography tandem mass spectrometry. With these criteria, differential expression was detected in 16 human proteins after Y. pestis exposure and 13 human proteins after Y. pseudotuberculosis exposure, of which only two of the differentially expressed proteins identified were shared between the two exposures. Proteins identified in this study are reported to be involved in a wide spectrum of cellular functions and host defense mechanisms including apoptosis, cytoskeletal rearrangement, protein synthesis and degradation, DNA replication and transcription, metabolism, protein folding, and cell signaling. Notably, the differential expression patterns observed can distinguish the two pathogen exposures from each other and from unexposed host cells. The functions of the differentially expressed proteins identified provide insight on the different virulence and pathogenic mechanisms of Y. pestis and Y. pseudotuberculosis.

Electrophoresis, Gel, Two-Dimensional↗
PubMedDate not supplied

In vivo dual-tagging proteomic approach in studying signaling pathways in immune response.

Up to date, few successes have been achieved to identify the signaling molecules directly from immune cells due to their low-abundance and dynamic nature. Here, we designed an in vivo dual-tagging quantitative approach that integrated epitope-tagging which allows single affinity purification of the natural complexes formed at real-time, and amino acid-coded mass tagging (AACT) that assists mass spectrometry-based quantitative measurement, to identify the specific components of a signaling complex formed in macrophage cells upon lipopolysaccharide (LPS) stimulation. The sensitivity and accuracy of this quantitative method are significantly higher than those of tandem affinity purification, because the multiple step of purifications are avoided to preserve weakly interacting molecules. We identified a number of proteins that interact with MyD88, a critical adaptor protein in innate immune response, in macrophages upon stimulation. Among those newly identified MyD88-interacting partners, FLAP-1 was found to be an activator of NF-kappaB, the key transcription factor in immune response. This integrated approach provides global information on the functional link between MyD88 and other proteins in transducing the TLR-mediated signal and is generally applicable to in vivo analyses of other signaling pathways.

5-Lipoxygenase-Activating Proteins↗
PubMed2005

Towards quantitative biology: integration of biological information to elucidate disease pathways and to guide drug discovery.

Developing a new drug is a tedious and expensive undertaking. The recently developed high-throughput experimental technologies, summarised by the terms genomics, transcriptomics, proteomics and metabolomics provide for the first time ever the means to comprehensively monitor the molecular level of disease processes. The "-omics" technologies facilitate the systematic characterisation of a drug target's physiology, thereby helping to reduce the typically high attrition rates in discovery projects, and improving the overall efficiency of pharmaceutical research processes. Currently, the bottleneck for taking full advantage of the new experimental technologies are the rapidly growing volumes of automatically produced biological data. A lack of scalable database systems and computational tools for target discovery has been recognised as a major hurdle. In this review, an overview will be given on recent progress in computational biology that has an impact on drug discovery applications. The focus will be on novel in silico methods to reconstruct regulatory networks, signalling cascades, and metabolic pathways, with an emphasis on comparative genomics and microarray-based approaches. Promising methods, such as the mathematical simulation of pathway dynamics are discussed in the context of applications in discovery projects. The review concludes by exemplifying concrete data-driven studies in pharmaceutical research that demonstrate the value of integrated computational systems for drug target identification and validation, screening assay development, as well as drug candidate efficacy and toxicity evaluations.

Animals↗
PubMed2004

Current two-dimensional electrophoresis technology for proteomics.

Two-dimensional gel electrophoresis (2-DE) with immobilized pH gradients (IPGs) combined with protein identification by mass spectrometry (MS) is currently the workhorse for proteomics. In spite of promising alternative or complementary technologies (e.g. multidimensional protein identification technology, stable isotope labelling, protein or antibody arrays) that have emerged recently, 2-DE is currently the only technique that can be routinely applied for parallel quantitative expression profiling of large sets of complex protein mixtures such as whole cell lysates. 2-DE enables the separation of complex mixtures of proteins according to isoelectric point (pI), molecular mass (Mr), solubility, and relative abundance. Furthermore, it delivers a map of intact proteins, which reflects changes in protein expression level, isoforms or post-translational modifications. This is in contrast to liquid chromatography-tandem mass spectrometry based methods, which perform analysis on peptides, where Mr and pI information is lost, and where stable isotope labelling is required for quantitative analysis. Today's 2-DE technology with IPGs (Görg et al., Electrophoresis 2000, 21, 1037-1053), has overcome the former limitations of carrier ampholyte based 2-DE (O'Farrell, J. Biol. Chem. 1975, 250, 4007-4021) with respect to reproducibility, handling, resolution, and separation of very acidic and/or basic proteins. The development of IPGs between pH 2.5-12 has enabled the analysis of very alkaline proteins and the construction of the corresponding databases. Narrow-overlapping IPGs provide increased resolution (delta pI = 0.001) and, in combination with prefractionation methods, the detection of low abundance proteins. Depending on the gel size and pH gradient used, 2-DE can resolve more than 5000 proteins simultaneously (approximately 2000 proteins routinely), and detect and quantify < 1 ng of protein per spot. In this article we describe the current 2-DE/MS workflow including the following topics: sample preparation, protein solubilization, and prefractionation; protein separation by 2-DE with IPGs; protein detection and quantitation; computer assisted analysis of 2-DE patterns; protein identification and characterization by MS; two-dimensional protein databases.

Animals↗
PubMed2005

Quantitative analysis of both protein expression and serine / threonine post-translational modifications through stable isotope labeling with dithiothreitol.

While phosphorylation and O-GlcNAc (cytoplasmic and nuclear glycosylation) are linked to normal and pathological changes in cell states, these post-translational modifications have been difficult to analyze in proteomic studies. We describe advances in beta-elimination / Michael addition-based approaches which allow for mass spectrometry-based identification and comparative quantification of O-phosphate or O-GlcNAc-modified peptides, as well as cysteine-containing peptides for expression analysis. The method (BEMAD) involves differential isotopic labeling through Michael addition with normal dithiothreitol (DTT) (d0) or deuterated DTT (d6), and enrichment of these peptides by thiol chromatography. BEMAD was comparable to isotope-coded affinity tags (ICAT; a commercially available differential isotopic quantification technique) in protein expression analysis, but also provided the identity and relative amounts of both O-phosphorylation and O-GlcNAc modification sites. Specificity of O-phosphate vs. O-GlcNAc mapping is achieved through coupling enzymatic dephosphorylation or O-GlcNAc hydrolysis with differential isotopic labeling. Blocking of cysteine labeling by prior oxidation of a cytosolic lysate from mouse brain allowed specific targeting of serine / threonine post-translational modifications as demonstrated through identification of 21 phosphorylation sites (5 previously reported) in a single mass spectrometry analysis. These results demonstate BEMAD is suitable for large-scale quantitative analysis of both protein expression and serine / threonine post-translational modifications.

Animals↗
PubMed2004

Proteomic analysis of proteins altered by dibenzoylmethane in human prostatic cancer LNCaP cells.

This paper explores the use of proteomics as a tool for identifying protein species whose expression has been altered by dibenzoylmethane (DBM) in LNCaP cells. Although DBM, a constituent of licorice, has been shown to induce cell cycle arrest and regulate androgen receptor (AR) expression, the mechanism by which these events occur is unknown. To develop a better understanding of the effect of DBM on cancer cells, we analyzed changes in protein expression induced by DBM in LNCaP cells using two-dimensional (2-D) gel electrophoresis. The proteomic approach used to study LNCaP cells has lead to the analysis and identification of a number of protein species that increase or decrease as a result of exposure to DBM. In particular, twenty features were found to be differentially expressed in this study based on the quantitation of two separate 2-D-fluorescence difference gel electrophoresis analyses. Thirteen of these features were identified through mass spectrometric analysis. The intensity of 10 out of the 13 spots identified increased 2- to 3-fold in response to 25 micro M and 50 micro M DBM and the remaining three spots decreased 2-fold in response to the same DBM treatment. This study investigates proteomic changes induced by treatment of cells with DBM in order to develop a model for the mechanism by which DBM induces cell cycle arrest and represses AR expression.

Cell Line, Tumor↗
PubMed2006

Retention prediction of peptides based on uninformative variable elimination by partial least squares.

A quantitative structure-retention relationship analysis was performed on the chromatographic retention data of 90 peptides, measured by gradient elution reversed-phase liquid chromatography, and a large set of molecular descriptors computed for each peptide. Such approach may be useful in proteomics research in order to improve the correct identification of peptides. A principal component analysis on the set of 1726 molecular descriptors reveals a high information overlap in the descriptor space. Since variable selection is advisable, the retention of the peptides is modeled with uninformative variable elimination partial least squares, besides classic partial least squares regression. The Kennard and Stone algorithm was used to select a calibration set (63 peptides) from the available samples. This set was used to build the quantitative structure-retention relationship models. The remaining 27 peptides were used as independent external test set to evaluate the predictive power of the constructed models. The UVE-PLS model consists of 5 components only (compared to 7 components in the best PLS model), and has the best predictive properties, i.e., the average error on the retention time is less than 30 s. When compared also to stepwise regression and an empirical model, the obtained UVE-PLS model leads to better and much better predictions, respectively.

Algorithms↗
PubMed2001

A proteomic approach to the identification of lung cancer markers.

We have developed a comprehensive approach to the identification of protein markers in lung cancer that includes profiling of tumor tissue and cell lines as well as the analysis of serum for autoantibodies to lung tumor antigens. A large number of proteins that are differentially expressed in the major subtypes of lung cancer have been identified by mass spectrometry. A database of protein expression in lung cancer and other types of cancer has been constructed that integrates two-dimensional gel profiles, mass spectrometry data, quantitative protein data and gene expression data at the RNA level, that serves as a resource for biomarker identification. Analysis of the serological response in lung cancer has led to the identification of novel markers detectable in serum of lung cancer patients at the time of diagnosis. The proteomic approach is likely to yield novel classification schemes and novel markers for early diagnosis of lung cancer.

Biomarkers, Tumor↗
PubMed2006

Quantitative structure-activity relationship based quantification of the impacts of enzyme-substrate binding on rates of peroxidase-mediated reactions of estrogenic phenolic chemicals.

The initial rates of horseradish peroxidase (HRP)-mediated enzymatic reactions of 15 assorted aqueous phase phenolic chemicals were studied. The associated reaction rate constants were found to correlate quantitatively with two independent variables: the highest-occupied molecular orbital energy (E(HOMO)) defining the intrinsic redox reactivities of the phenolic substrates and the distance between a substrate and the deltaN of HIS42's imidazole ring in an HRP/substrate binding complex, obtained through molecular simulations. Highly correlated quantitative structure-activity relationship (QSAR) equations were thus developed. This work provides insights into the impacts that HRP/substrate binding may have on HRP-mediated reactions. Additionally, the QSAR equations developed in the work may serve as a basis to further explore the potential use of HRP-mediated reactions in the treatment of estrogenic contaminants, and they constitute an important tool for redesign and screening of potential proteomic modifications to the wild-type HRP structure intended to enhance reactivity toward selected substrates.

Estrogens↗
PubMed2006

Proteomic analysis of primary esophageal squamous cell carcinoma reveals downregulation of a cell adhesion protein, periplakin.

Recent advances in two-dimensional electrophoresis (2-DE) such as fluorescent 2-D differential gel electrophoresis (2-D DIGE) has made it possible to detect and quantitate the critical changes involved in disease pathogenesis. We have previously identified novel proteins with altered expression in primary colorectal cancer using agarose 2-DE that has a higher loading capacity than immobilized pH gradient gel. The aim of this study is to identify novel proteins with altered expression in primary esophageal cancer using the powerful method of agarose 2-DE and agarose 2-D DIGE. Excised tissues from 12 patients of primary esophageal cancer were obtained. Proteins with altered expression between cancer and adjacent non-cancer tissues were analyzed by agarose 2-D DIGE and identified by mass spectrometry. Thirty-three proteins out of 74 spots with altered expression in tumors were identified. Among them, a 195-kDa protein, periplakin, was significantly downregulated in esophageal cancer, which was confirmed by immunoblotting. Immunohistochemistry showed that periplakin was mainly localized at cell-cell boundaries in normal epithelium and dysplastic lesions, while it disappeared from cell boundaries, shifted to cytoplasm, in early cancers and scarcely expressed in advanced cancers. These results suggest that periplakin could be a useful marker for detection of early esophageal cancer and evaluation of tumor progression.

Aged↗
PubMed2006

Dissecting the ubiquitin pathway by mass spectrometry.

Protein modification by ubiquitin is a central regulatory mechanism in eukaryotic cells. Recent proteomics developments in mass spectrometry enable systematic analysis of cellular components in the ubiquitin pathway. Here, we review the advances in analyzing ubiquitinated substrates, determining modified lysine residues, quantifying polyubiquitin chain topologies, as well as profiling deubiquitinating enzymes based on the activity. Moreover, proteomic approaches have been developed for probing the interactome of proteasome and for identifying proteins with ubiquitin-binding domains. Similar strategies have been applied on the studies of the modification by ubiquitin-like proteins as well. These strategies are discussed with respect to their advantages, limitations and potential improvements. While the utilization of current methodologies has rapidly expanded the scope of protein modification by the ubiquitin family, a more active role is anticipated in the functional studies with the emergence of quantitative mass spectrometry.

Animals↗
PubMed2006

Glycation of interferon-beta-1b and human serum albumin in a lyophilized glucose formulation. Part III: application of proteomic analysis to the manufacture of biological drugs.

Glycation of interferon-beta-1b and human serum albumin was identified in a lyophilized glucose formulation by a sensitive LC-MS approach. The extent of glycation was measured by a label-free quantitation strategy. The glycation sites were determined by the accurate mass (FTICR MS) with MS/MS measurements on the corresponding tryptic peptides. The extent of glycation was measured by the ratio of the peak intensity between the glycated and the average value for three non-glycated peptides in the same run. Residues lysine 18 of interferon-beta-1b, and lysine 51, lysine 233, and lysine 545 of human serum albumin were more prone to be glycated than other sites in this lyophilized glucose formulation. Residues of lysine 51 and lysine 233 but not lysine 545 of human serum albumin are highly accessible to solvent as found in a solution storage study by Lapolla et al. The extent of glycation of both proteins and the number of glycation sites of human serum albumin were increased with the storage time at 25 degrees C. In total, two glycation sites of interferon beta-1b and 17 glycation sites of human serum albumin were identified in the lyophilized glucose formulation with a storage time at 25 degrees C of 35 days. Among the 17 glycation sites, only lysine 525 of human serum albumin has been found in vivo in diabetic patients by Shaklai et al. As expected, there was no glycation found on both interferon-beta-1b and human serum albumin in the control samples (similar lyophilized formulation but using mannitol instead of glucose).

Amino Acid Sequence↗
PubMed2002

Analytical reproducibility in (1)H NMR-based metabonomic urinalysis.

Metabonomic analysis of biofluids and tissues utilizing high-resolution NMR spectroscopy and chemometric techniques has proven valuable in characterizing the biochemical response to toxicity for many xenobiotics. To assess the analytical reproducibility of metabonomic protocols, sample preparation and NMR data acquisition were performed at two sites (one using a 500 MHz and the other using a 600 MHz system) using two identical (split) sets of urine samples from an 8-day acute study of hydrazine toxicity in the rat. Despite the difference in spectrometer operating frequency, both datasets were extremely similar when analyzed using principal components analysis (PCA) and gave near-identical descriptions of the metabolic responses to hydrazine treatment. The main consistent difference between the datasets was related to the efficiency of water resonance suppression in the spectra. In a 4-PC model of both datasets combined, describing all systematic dose- and time-related variation (88% of the total variation), differences between the two datasets accounted for only 3% of the total modeled variance compared to ca. 15% for normal physiological (pre-dose) variation. Furthermore, <3% of spectra displayed distinct inter-site differences, and these were clearly identified as outliers in their respective dose-group PCA models. No samples produced clear outliers in both datasets, suggesting that the outliers observed did not reflect an unusual sample composition, but rather sporadic differences in sample preparation leading to, for example, very dilute samples. Estimations of the relative concentrations of citrate, hippurate, and taurine were in >95% correlation (r(2)) between sites, with an analytical error comparable to normal physiological variation in concentration (4-8%). The excellent analytical reproducibility and robustness of metabonomic techniques demonstrated here are highly competitive compared to the best proteomic analyses and are in significant contrast to genomic microarray platforms, both of which are complementary techniques for predictive and mechanistic toxicology. These results have implications for the quantitative interpretation of metabonomic data, and the establishment of quality control criteria for both regulatory agencies and for integrating data obtained at different sites.

Animals↗
PubMed2026

Monocytes Defined by Platelet Interactions and Oxidative Stress Signaling Underlie HIV-Associated Atherosclerosis.

BACKGROUND: Monocytes contribute to atherosclerosis by migrating into inflamed endothelium and differentiating into lipid-laden macrophages. In people living with HIV, chronic inflammation increases atherosclerosis risk, yet the role of specific monocyte subsets remains unclear. We investigated how distinct monocyte populations contribute to vascular pathology in early HIV-associated atherosclerosis. METHODS: We profiled 123&#x2009;965 circulating monocytes using single-cell RNA sequencing and integrated plasma microparticle proteomics in 32 individuals stratified by HIV and atherosclerosis status. Supervised learning identified cluster- and disease-specific signatures, validated by platelet-monocyte cocultures, reverse transcription-quantitative polymerase chain reaction, bulk RNA sequencing, flow cytometry, and ELISA. RESULTS: Seven monocyte clusters were identified, including a subset characterized by platelet-monocyte complexes. Bulk RNA sequencing of platelet-monocyte cocultures revealed platelet-driven upregulation of genes involved in inflammation, lipid metabolism, oxidative stress, and endothelial adhesion. Platelet-monocyte complex-derived macrophages secreted higher levels of TGF-&#x3b2; (transforming growth factor-&#x3b2;)&#xa0;and IL-10 (interleukin-10), displayed decreased CD14 and increased CD80/CD86 while retaining CD36, and promoted endothelial-to-mesenchymal transition (decreased expression of CDH5 and PECAM1; increased expression of S100A4 and markers of&#xa0;vascular inflammation (ICAM1), VCAM), and IL-6 (interleukin-6), and CCL2&#xa0;(C-C motif chemokine ligand 2) secretion). Additionally, CD14+ monocytes from HIV+ atherosclerosis-negative and HIV+ atherosclerosis-positive groups showed enhanced ROS-NRF2 (reactive oxygen species-nuclear factor erythroid 2-related factor 2)&#xa0;pathway activities, supported by increased basal and H2O2-induced p90RSK phosphorylation, indicating oxidative stress priming. CONCLUSIONS: Two monocyte clusters contribute independently to vascular immune dysregulation in people living with HIV. Platelet-monocyte complex-derived macrophages promote endothelial dysfunction while adopting a profibrotic cytokine profile. CD14+ monocytes show heightened oxidative signaling and stress responses, consistent with vascular activation. Together, these mechanisms may accelerate atherosclerosis development in HIV, even in the absence of traditional cardiovascular risk factors.

Humans↗
PubMed2002

A proteomic approach for the identification of cell-surface proteins shed by metalloproteases.

Proteolytic cleavage (shedding) of extracellular domains of many membrane proteins by metalloproteases is an important regulatory mechanism used by mammalian cells in response to environmental and physiological changes. Here we describe a proteomic system for analyzing cell surface shedding. The method utilized short-term culture supernatants from induced cells as starting material, followed by lectin-affinity purification, deglycosylation, and polyacrylamide gel electrophoresis separation. Relative quantitation of proteins was achieved via isotope dilution. In this study, a number of proteins already known to be shed were identified from activated monocytes and endothelial cells, thereby validating the method. In addition, a group of proteins were newly identified as being shed. The method provides an unbiased means to screen for shed proteins.

Adult↗
PubMed2002

Genomic and proteomic analysis of the myeloid differentiation program: global analysis of gene expression during induced differentiation in the MPRO cell line.

We have used an approach using 2-dimensional gel electrophoresis with mass spectrometry analysis combined with oligonucleotide chip hybridization for a comprehensive and quantitative study of the temporal patterns of protein and mRNA expression during myeloid development in the MPRO murine cell line. This global analysis detected 123 known proteins and 29 "new" proteins out of 220 protein spots identified by tandem mass spectroscopy, including proteins in 12 functional categories such as transcription factors and cytokines. Bioinformatic analysis of these proteins revealed clusters with functional importance to myeloid differentiation. Previous analyses have found that for a substantial number of genes the absolute amount of protein in the cell is not strongly correlated to the amount of mRNA. These conclusions were based on simultaneous measurement of mRNA and protein at just a single time point. Here, however, we are able to investigate the relationship between mRNA and protein in terms of simultaneous changes in their levels over multiple time points. This is the first time such a relationship has been studied, and we find that it gives a much stronger correlation, consistent with the hypothesis that a substantial proportion of protein change is a consequence of changed mRNA levels, rather than posttranscriptional effects. Cycloheximide inhibition also showed that most of the proteins detected by gel electrophoresis were relatively stable. Specific investigation of transcription factor mRNA representation showed considerable similarity to those of mature human neutrophils and highlighted several transcription factors and other functional nuclear proteins whose mRNA levels change prominently during MPRO differentiation but which have not been investigated previously in the context of myeloid development. Data are available online at http://bioinfo.mbb.yale.edu/expression/myelopoiesis.

Animals↗
PubMed2001

Recent developments in computational proteomics.

The mapping of the human genome was completed earlier this year and efforts are underway to understand the role of gene products (i.e. proteins) in biological pathways and human disease and to exploit their functional roles to derive protein therapeutics and protein-based drugs. A key component to the next revolution in the 'post-genomic' era will be the increasingly widespread use of protein structure in rational experimental design. Improvements in quality, availability and utility of large-scale 3D and 4D protein structural information are enabling a revolution in rational design, having particular impact on drug discovery and optimization. New computational methodologies now yield modeled structures that are, in many cases, quantitatively comparable with crystal structures, at a fraction of the cost.

Animals↗
PubMed2005

Chlamydomonas reinhardtii proteomics.

Proteomics, based on the expanding genomic resources, has begun to reveal new details of Chlamydomonas reinhardtii biology. In particular, analyses focusing on subproteomes have already provided new insight into the dynamics and composition of the photosynthetic apparatus, the chloroplast ribosome, the oxidative phosphorylation machinery of the mitochondria, and the flagellum. It assisted to discovered putative new components of the circadian clockwork as well as shed a light on thioredoxin protein-protein interactions. In the future, quantitative techniques may allow large scale comparison of protein expression levels. Advances in software algorithms will likely improve the use of genomic databases for mass spectrometry (MS) based protein identification and validation of gene models that have been predicted from the genomic DNA sequences. Although proteomics has only been recently applied for exploring C. reinhardtii biology, it will likely be utilized extensively in the near future due to the already existing genetic, genomic, and biochemical tools.

Animals↗