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Results for “Integrated proteomics”

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At least 145 records · Page 8Linked to original sources

PubMed2005

An integrated mass spectrometry-based proteomic approach: quantitative analysis of tandem affinity-purified in vivo cross-linked protein complexes (QTAX) to decipher the 26 S proteasome-interacting network.

We developed an integrated proteomic approach to decipher in vivo protein-protein interactions and applied this strategy to globally map the 26 S proteasome interaction network in yeast. We termed this approach QTAX for quantitative analysis of tandem affinity purified in vivo cross-linked (X) protein complexes. For this work, in vivo formaldehyde cross-linking was used to freeze both stable and transient interactions occurring in intact cells prior to lysis. To isolate cross-linked protein complexes with high purification efficiency under fully denaturing conditions, a new tandem affinity tag consisting of a hexahistidine sequence and an in vivo biotinylation signal was adopted for affinity-based purification. Tandem affinity purification after in vivo cross-linking was combined with tandem mass spectrometry coupled with a quantitative SILAC (stable isotope labeling of amino acids in cell culture) strategy to carry out unambiguous protein identification and quantification of specific protein interactions. Using this method, we captured and identified the full composition of yeast 26 S proteasome complex as well as the two known ubiquitin receptors, Rad23 and Dsk2. Quantitative mass spectrometry analysis allowed us to distinguish specific proteasome-interacting proteins (PIPs) from background proteins and led to the identification of a total of 64 potential PIPs of which 42 are novel interactions. Among the 64 putative specific PIPs, there are ubiquitin pathway components, ubiquitinated substrates, chaperones, and transcription and translation regulators, demonstrating the efficacy of the developed approach in capturing in vivo protein interactions. The method offers an advanced technical approach to elucidate the dynamic protein interaction networks of the proteasome and can find a wide range of applications in the studies of other macromolecular protein complex interaction networks.

Amino Acid Sequence↗

PubMed2026

Beyond ion channel dysfunction: Integration of the transcriptome and proteome from patient-specific re-engineered cardiac cells, and population-level QT genome-wide association study reveals broad cellular dysfunction.

BACKGROUND: Congenital long QT syndrome (LQTS) is a cardiac channelopathy with increased risk of cardiac-triggered syncope/seizures, sudden cardiac arrest, and sudden cardiac death. OBJECTIVE: This study aimed to describe the transcriptomic and proteomic profiles in patient-derived inducible pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of the 3 canonical genotypes of congenital LQTS: LQT1, LQT2, and LQT3 and integrate these omics-level findings with each other and with population/clinical level QT-genome-wide association study (GWAS) data. METHODS: LQT1, LQT2, LQT3 and respective isogenic control iPSC-CMs were cultured, and RNA and protein samples were collected. RNA sequencing and mass spectrometry-enabled proteomic analysis was performed. PrediXcan analysis was performed using QT GWAS summary statistics and transcriptome expression data. Differential gene and protein expression and ingenuity pathway analysis (IPA) was performed comparing each LQT genotype with its respective isogenic control. RESULTS: 1645 differentially expressed genes (DEGs) were identified; 13 were altered in all 3 LQTS genotypes. IPA analysis of DEGs revealed 301 altered pathways; 47 were altered in all LQTS genotypes. Proteomic analysis identified 2561 differentially expressed proteins (DEPs); 30 were altered in all 3 genotypes. IPA analysis of DEPs identified 646 altered pathways. 306 genes/proteins were identified as significantly altered in both the transcriptome and proteome; pathway analysis of these 301 genes identified 201 altered pathways. 7 pathways were altered in all 3 LQTS genotypes in both the transcriptome and proteome. Integration of the population-level PrediXcan results and the cardiomyocyte-derived omics results identified multiple shared pathways. CONCLUSION: Multi-omics analysis of LQTS and integration of omics results with QT GWAS data reveals that primary LQTS-causative ion channel defects precipitate secondary alterations in a wide range of cellular pathways. Our findings suggest more broad molecular level changes throughout the cell. This study lays the foundation for further exploration of broad cellular changes resulting from ion channel disturbances and how they contribute to disease mechanism.

Humans↗

PubMed2026

Exogenous ABA enhances cold tolerance of Rhododendron yedoense var. poukhanense under subzero temperature: integrating physiology, transcriptome, and proteome.

Low temperature limits the growth and ornamental value of evergreen shrubs. Rhododendron yedoense var. poukhanense, an important ornamental shrub from Northeast China, frequently suffers freezing damage during winter. While exogenous abscisic acid (ABA) enhances cold tolerance in many plants, its molecular mechanisms at subzero temperatures remain poorly understood in non-model species lacking chromosome-level reference genomes. This study investigated the effects of exogenous ABA on freezing tolerance in R. yedoense var. poukhanense at -4 °C using an integrated physiological, transcriptomic, and proteomic approach. Cutting seedlings were subjected to four treatments: CK (22°C control), A (22°C + ABA), LT (-4°C), and ALT (-4°C + ABA). Photosynthetic pigments, osmotic regulation substances, antioxidant enzyme activities, and malondialdehyde (MDA) content were measured. Transcriptome sequencing and quantitative proteomics were performed, and transcriptome data were validated by quantitative real-time PCR (qRT-PCR) of 15 selected genes. ABA pretreatment reduced visible cold injury severity, partially preserved photosynthetic pigments, decreased MDA content by 28.7%, and promoted recovery of catalase (+43.6%), superoxide dismutase (+31.1%), and peroxidase (+20.0%) activities under freezing stress. Transcriptome analysis revealed 8, 444 differentially expressed genes (DEGs) in LT versus CK and 6, 481 DEGs in ALT versus CK, representing a 23% reduction in transcriptional reprogramming scope attributable to ABA priming. The ALT versus LT comparison identified only 1, 690 additional DEGs, indicating that most cold-responsive genes were pre-activated during the ABA priming phase. Proteome analysis identified 1, 461 differentially expressed proteins (DEPs) in ALT versus CK. Integrated analysis revealed extensive post-transcriptional regulation, with transcript-protein concordance of only 1.0-4.1%, and co-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in both omics layers. qRT-PCR validation confirmed high reliability of the transcriptome data (R2 = 0.8500). These findings demonstrate that exogenous ABA enhances freezing tolerance through multi-layered molecular regulation encompassing transcriptional buffering, translational reprogramming, and functional reallocation from photosynthesis to stress protection. This study provides the first integrated physiology-transcriptome-proteome framework for ABA-mediated freezing tolerance in an evergreen ornamental shrub and offers theoretical support for ABA-based winter protection strategies.

Rhododendron yedoense var. Poukhanense↗

PubMed2005

Toward the complete membrane proteome: high coverage of integral membrane proteins through transmembrane peptide detection.

To attain a comprehensive membrane proteome of two strains of Corynebacterium glutamicum (l-lysine-producing and the characterized model strains), both sample pretreatment and analysis methods were optimized. Isolated bacterial membranes were digested with trypsin/cyanogen bromide or trypsin/chymotrypsin, and a complementary protein set was identified using the multidimensional protein identification technology (MudPIT). Besides a distinct number of cytosolic or membrane-associated proteins, the combined data analysis from both digests yielded 326 integral membrane proteins ( approximately 50% of all predicted) covering membrane proteins both with small and large numbers of transmembrane helices. Also membrane proteins with a high GRAVY score were identified, and basic and acidic membrane proteins were evenly represented. A significant increase in hydrophobic peptides with distinctly higher sequence coverage of transmembrane regions was achieved by trypsin/chymotrypsin digestion in an organic solvent. The percentage of identified membrane proteins increased with protein size, yielding 80% of all membrane proteins above 60 kDa. Most prominently, almost all constituents of the respiratory chain and a high number of ATP-binding cassette transport systems were identified. This newly developed protocol is suitable for the quantitative comparison of membrane proteomes and will be especially useful for applications such as monitoring protein expression under different growth and fermentation conditions in bacteria such as C. glutamicum. Moreover with more than 50% coverage of all predicted membrane proteins (including the non-expressed species) this improved method has the potential for a close-to-complete coverage of membrane proteomes in general.

Bacterial Proteins↗

PubMed2004

Integrated system for rapid proteomics analyses using microfluidic devices coupled to nanoelectrospray mass spectrometry.

This chapter presents an integrated and modular microsystem providing rapid analyses of low femtomole of in-gel digests for proteomics applications. Enhancement of sample throughput is facilitated using an autosampler, a microfabricated device comprising a large (2.4-microL total volume) separation channel together with a low-dead-volume interface to nES mass spectrometry. Sample preconcentration is achieved by packing C18 reverse phase or immobilized metal affinity chromatography (IMAC) beads into the large channel of this microfluidic device to adsorb peptides or enrich the sample in phosphopeptides prior to capillary electrophoresis separation and MS detection. This integrated microfluidic systems enables a sample throughput of up to 12 samples/h with a detection limit of approx 5 nM (25 fmol inj.). Replicate injections of peptide standards indicated that reproducibility of migration time was typically 1.2-1.8%, whereas relative standard deviation (RSD) values of 9.2-11.8% were obtained on peak heights. The application of this device is demonstrated for 2D gel spots obtained from protein extracts of human astrocyte cells and for excised bands of membrane proteins from Neisseria meningitidis. A stepped acetonitrile gradient can be incorporated with the present microfluidic system to enhance selectivity during sample analysis.

Astrocytes↗

PubMed2006

Integrating forward and reverse proteomics to unravel protein function.

To date, proteomics approaches have aimed to either identify novel proteins or change in protein expression/modification in various organisms under normal or disease conditions. One major aspect of functional proteomics is to identify protein biological properties in a given context, however, forward proteomics approaches alone cannot complete this goal. Indeed, with the increasing successes of such proteomics-based research strategies and the subsequent increasing amounts of proteins identified with unknown molecular functions, approaches allowing for systematic analyses of protein functions are desired. In this review, we propose to depict the complementarities of forward and reverse proteomics approaches in the definite understanding of protein functions. This dual strategy requires a data integration loop which allows for systematic characterization of protein function(s). The details of the integrative process combining both in silico and experimental resources and tools are presented. Altogether, we believe that the integration of forward and reverse proteomics approaches supported by bioinformatics will provide an efficient path towards systems biology.

Animals↗

PubMed2002

Integrating cancer genomics and proteomics in the post-genome era.

The dawn of the post-genome era is leading to extraordinary opportunities in biomedicine. Our group has embarked on a major effort to integrate genomics, transcriptomics and proteomics for the profiling of tumor tissues, an approach we refer to as operomics. Our major goals are the molecular classification of tumors and the identification of markers for the early detection of cancer. Molecular analyses of tumors rely on microdissected tissues, which are simultaneously investigated for genomic, transcriptomic and proteomic changes. Genomic alterations in tumor cells being investigated include deletions, amplifications and methylation changes across the entire genome as well as point mutations in specific genes. Expression analysis at the RNA level is being undertaken using oligonucleotide and cDNA based microarrays. An important aspect of our approach is the large-scale identification and quantitative analysis of tumor proteins in whole cell lysates as well as in protein compartments. Protein separation strategies include two-dimensional polyacrylamide gel electrophoresis and liquid chromatography. Specific protein subsets, of interest include membrane proteins, secreted proteins and antigenic proteins as sources of biomarkers for early detection of cancer. Our current approach is illustrated with findings stemming from our studies of human gliomas.

Brain Neoplasms↗

PubMedDate not supplied

Enrichment of integral membrane proteins for proteomic analysis using liquid chromatography-tandem mass spectrometry.

An increasing number of proteomic strategies rely on liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect and identify constituent peptides of enzymatically digested proteins obtained from various organisms and cell types. However, sample preparation methods for isolating membrane proteins typically involve the use of detergents and chaotropes that often interfere with chromatographic separation and/or electrospray ionization. To address this problem, a sample preparation method combining carbonate extraction, surfactant-free organic solvent-assisted solubilization, and proteolysis was developed and demonstrated to target the membrane subproteome of Deinococcus radiodurans. Out of 503 proteins identified, 135 were recognized as hydrophobic on the basis of their calculated hydropathy values (GRAVY index), corresponding to coverage of 15% of the predicted hydrophobic proteome. Using the PSORT algorithm, 53 of the proteins identified were classified as integral outer membrane proteins and 215 were classified as integral cytoplasmic membrane proteins. All identified integral cytoplasmic membrane proteins had from 1 to 16 mapped transmembrane domains (TMDs), and 65% of those containing four or more mapped TMDs were identified by at least one hydrophobic membrane spanning peptide. The extensive coverage of the membrane subproteome (24%) by identification of highly hydrophobic proteins containing multiple TMDs validates the efficacy of the described sample preparation technique to isolate and solubilize hydrophobic integral membrane proteins from complex protein mixtures.

Amino Acid Sequence↗

PubMedDate not supplied

Platelet proteomics: identification of potential therapeutic targets.

The integration of proteomics into biochemical and biological investigation has proved a powerful tool in understanding the anucleate platelet. Over the past few years, various approaches have been used to document platelet proteins and here, we describe our efforts to analyse specific platelet subproteomes so as to capture biologically relevant proteins of low abundance. These include characterisation of the phosphotyrosine proteome, the platelet releasate and more recently, the proteome of membrane lipid rafts. These approaches have revealed a wealth of relevant platelet proteins, which may in the future prove suitable as therapeutic targets in atherothrombosis.

Animals↗

PubMedDate not supplied

Affinity labeling of highly hydrophobic integral membrane proteins for proteome-wide analysis.

The ability to identify and quantitate integral membrane proteins is an analytical challenge for mass spectrometry-based proteomics. The use of surfactants to solubilize and facilitate derivatization of these proteins can suppress peptide ionization and interfere with chromatographic separations during microcapillary reversed-phase liquid chromatography-electrospray-tandem mass spectrometry. To circumvent the use of surfactants and increase proteome coverage, an affinity labeling method has been developed to target highly hydrophobic integral membrane proteins using organic-assisted extraction and solubilization followed by cysteinyl-specific labeling using biotinylation reagents. As demonstrated on the membrane subproteome of Deinococcus radiodurans, specific and quantitative labeling of integral membrane proteins was achieved using a 60% methanol-aqueous buffer system and (+)-biotinyl-iodoacetamidyl-3,6-dioxaoctanediamine as the cysteinyl-alkylating reagent. From a total of 220 unique Cys-labeled peptides, 89 proteins were identified, of which 40 were integral membrane proteins containing from one to nine mapped transmembrane domains with a maximum positive GRAVY of 1.08. The protocol described can be used with other stable isotope labeling reagents (e.g., ICAT) to enable comparative measurements to be made on differentially expressed hydrophobic membrane proteins from various organisms (e.g., pathogenic bacteria) and cell types and provide a viable method for comparative proteome-wide analyses.

Affinity Labels↗

PubMed2005

Integrative genomic, transcriptional, and proteomic diversity in natural isolates of the human pathogen Burkholderia pseudomallei.

Natural isolates of pathogenic bacteria can exhibit a broad range of phenotypic traits. To investigate the molecular mechanisms contributing to such phenotypic variability, we compared the genomes, transcriptomes, and proteomes of two natural isolates of the gram-negative bacterium Burkholderia pseudomallei, the causative agent of the human disease melioidosis. Significant intrinsic genomic, transcriptional, and proteomic variations were observed between the two strains involving genes of diverse functions. We identified 16 strain-specific regions in the B. pseudomallei K96243 reference genome, and for eight regions their differential presence could be ascribed to either DNA acquisition or loss. A remarkable 43% of the transcriptional differences between the strains could be attributed to genes that were differentially present between K96243 and Bp15682, demonstrating the importance of lateral gene transfer or gene loss events in contributing to pathogen diversity at the gene expression level. Proteins expressed in a strain-specific manner were similarly correlated at the gene expression level, but up to 38% of the global proteomic variation between strains comprised proteins expressed in both strains but associated with strain-specific protein isoforms. Collectively, >65 hypothetical genes were transcriptionally or proteomically expressed, supporting their bona fide biological presence. Our results provide, for the first time, an integrated framework for classifying the repertoire of natural variations existing at distinct molecular levels for an important human pathogen.

Bacterial Proteins↗

PubMed2006

Integration of gel-based proteome data with pProRep.

UNLABELLED: pProRep is a web application integrating electrophoretic and mass spectral data from proteome analyses into a relational database. The graphical web-interface allows users to upload, analyse and share experimental proteome data. It offers researchers the possibility to query all previously analysed datasets and can visualize selected features, such as the presence of a certain set of ions in a peptide mass spectrum, on the level of the two-dimensional gel. AVAILABILITY: The pProRep package and instructions for its use can be downloaded from http://www.ptools.ua.ac.be/pProRep. The application requires a web server that runs PHP 5 (http://www.php.net) and MySQL. Some (non-essential) extensions need additional freely available libraries: details are described in the installation instructions.

Computational Biology↗

PubMed2004

Functional proteomics mapping of a human signaling pathway.

Access to the human genome facilitates extensive functional proteomics studies. Here, we present an integrated approach combining large-scale protein interaction mapping, exploration of the interaction network, and cellular functional assays performed on newly identified proteins involved in a human signaling pathway. As a proof of principle, we studied the Smad signaling system, which is regulated by members of the transforming growth factor beta (TGFbeta) superfamily. We used two-hybrid screening to map Smad signaling protein-protein interactions and to establish a network of 755 interactions, involving 591 proteins, 179 of which were poorly or not annotated. The exploration of such complex interaction databases is improved by the use of PIMRider, a dedicated navigation tool accessible through the Web. The biological meaning of this network is illustrated by the presence of 18 known Smad-associated proteins. Functional assays performed in mammalian cells including siRNA knock-down experiments identified eight novel proteins involved in Smad signaling, thus validating this integrated functional proteomics approach.

Adaptor Proteins, Signal Transducing↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

PubMed2006

Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: zero-inflated Poisson regression models to predict abundance of undetected proteins.

MOTIVATION: Integrated analysis of global scale transcriptomic and proteomic data can provide important insights into the metabolic mechanisms underlying complex biological systems. However, because the relationship between protein abundance and mRNA expression level is complicated by many cellular and physical processes, sophisticated statistical models need to be developed to capture their relationship. RESULTS: In this study, we describe a novel data-driven statistical model to integrate whole-genome microarray and proteomic data collected from Desulfovibrio vulgaris grown under three different conditions. Based on the Poisson distribution pattern of proteomic data and the fact that a large number of proteins were undetected (excess zeros), zero-inflated Poisson (ZIP)-based models were proposed to define the correlation pattern between mRNA and protein abundance. In addition, by assuming that there is a probability mass at zero representing unexpressed genes and expressed proteins that were undetected owing to technical limitations, a Potential ZIP model was established. Two significant improvements introduced by this approach are (1) the predicted protein abundance level values for experimentally detected proteins are corrected by considering their mRNA levels and (2) protein abundance values can be predicted for undetected proteins (in the case of this study, approximately 83% of the proteins in the D.vulgaris genome) for better biological interpretation. We demonstrated the use of these statistical models by comparatively analyzing proteomic and microarray results from D.vulgaris grown on lactate-based versus formate-based media. These models correctly predicted increased expression of Ech hydrogenase and decreased expression of Coo hydrogenase for D.vulgaris grown on formate.

Adenosine Triphosphate↗

PubMed2024

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-Treated Pancreatic Beta Cells.

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse posttranslational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated β-cells. We observed a swift response in the global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-κB signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple colocalized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

Proteomics↗

PubMed2004

A proteomic analysis of lysosomal integral membrane proteins reveals the diverse composition of the organelle.

Lysosomes are endocytic subcellular compartments that contribute to the degradation and recycling of cellular material. Using highly purified rat liver tritosomes (Triton WR1339-filled lysosomes) and an ion exchange chromatography/LC-tandem MS-based protein/peptide separation and identification procedure, we characterized the major integral membrane protein complement of this organelle. While many of the 215 proteins we identified have been previously associated with lysosomes and endosomes, others have been associated with the endoplasmic reticulum, Golgi, cytosol, plasma membrane, and lipid rafts. At least 20 proteins were identified as unknown cDNAs that have no orthologues of known function, and 35 proteins were identified that function in protein and vesicle trafficking. This latter group includes multiple Rab and SNARE proteins as well as ubiquitin. Defining the roles of these proteins in the lysosomal membrane will assist in elucidating novel lysosomal functions involved in cellular homeostasis and pathways that are affected in various disease processes.

Animals↗

PubMed2026

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis↗