SEARCH · Search PubMed

Results for “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.

SourceResearch connectionFrom yearThrough year

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

At least 739 records · Page 41Linked to original sources

PubMed2003

Proteome analysis at the level of subcellular structures.

The targeting of proteins to particular subcellular sites is an important principle of the functional organization of cells at the molecular level. In turn, knowledge about the subcellular localization of a protein is a characteristic that may provide a hint as to the function of the protein. The combination of classic biochemical fractionation techniques for the enrichment of particular subcellular structures with the large-scale identification of proteins by mass spectrometry and bioinformatics provides a powerful strategy that interfaces cell biology and proteomics, and thus is termed 'subcellular proteomics'. In addition to its exceptional power for the identification of previously unknown gene products, the analysis of proteins at the subcellular level is the basis for monitoring important aspects of dynamic changes in the proteome such as protein transloction. This review summarizes data from recent subcellular proteomics studies with an emphasis on the type of data that can retrieved from such studies depending on the design of the analytical strategy.

Animals↗

PubMedDate not supplied

Proteomics in cancer research.

With the human genome sequence now determined, the field of molecular medicine is moving beyond genomics to proteomics. In the field of cancer research, the key question is: how can oncologists best use techniques of proteomics in basic research and clinical application? In the postgenomic era, proteomics promises the discovery of biomarkers and tumor markers for early detection and diagnosis, novel protein-based drug targets for anticancer therapy, and new endpoints for the assessment of therapeutic efficacy and toxicity. This review paper will explore key themes in proteomics and their application in clinical cancer research.

Forecasting↗

PubMedDate not supplied

Proteomics: techniques and applications in cancer research.

Proteomics can be defined as functional analysis of the full set of proteins by high-throughput technologies in a given system. The workflow of proteomics is a multi-step process comprising sample preparation, separation, quantification and identification of proteins. Due to the high complexity of different protein species and the wide dynamic range of protein amount within a cell system it is necessary to apply appropriate analysis methods. One approach is to separate proteins first by two-dimensional gel electrophoresis (2-DE) according to charge and molecular weight. Proteins are then fragmented and analyzed using matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Identification of proteins can be achieved by comparing the mass/charge-ratios of these peptides to respective databases. Proteome analysis with respect to the identification of disease-associated patterns of molecules in different tissues is in the early stages, because standardisation of these techniques often remains to be established. However, proteome analyses is a promising tool to obtain holistic insights into the physiological status of a cell or cellular system. Compared to RNA-based studies some advantages are obvious: (1) post-translational modifications, e. g. phosphorylation, contributing to the activity status can be detected at the protein level only, (2) RNA-levels do not necessarily coincide with protein levels for a particular gene, (3) feedback-mechanisms within regulatory pathways can control protein activity without measurable changes in mRNA content.

Algorithms↗

PubMed2004

Analyzing the platelet proteome.

During the last 10 years, mass spectrometry (MS) has become a key tool for protein analysis and has underpinned the emerging field of proteomics. Using high-throughput tandem MS/MS following protein separation, it is potentially possible to analyze hundreds to thousands of proteins in a sample at a time. This technology can be used to analyze the protein content (i.e., the proteome) of any cell or tissue and complements the powerful field of genomics. The technology is particularly suitable for platelets because of the absence of a nucleus. Cellular proteins can be separated by either gel-based methods such as two-dimensional gel electrophoresis or one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis followed by liquid chromatography (LC) -MS/MS or by multidimensional LC-MS/MS. Prefractionation techniques, such as subcellular fractionations or immunoprecipitations, can be used to improve the analysis. Each method has particular advantages and disadvantages. Proteomics can be used to compare the proteome of basal and diseased platelets, helping to reveal information on the molecular basis of the disease.

Blood Platelets↗

PubMed2005

Characterization of mouse spleen cells by subtractive proteomics.

Major analytical challenges encountered by shotgun proteome analysis include both the diversity and dynamic range of protein expression. Often new instrumentation can provide breakthroughs in areas where other analytical improvements have not been successful. In the current study, we utilized new instrumentation (LTQ FT) to characterize complex protein samples by shotgun proteomics. Proteomic analyses were performed on murine spleen tissue separated by magnetic beads into distinct CD45- and CD45+ cell populations. Using shotgun protein analysis we identified approximately 2,000 proteins per cell group by over 12,000 peptides with mass deviations of less than 4.5 ppm. Datasets obtained by LTQ FT analysis provided a significant increase in the number of proteins identified and greater confidence in those identifications and improved reproducibility in replicate analyses. Because CD45- and not CD45+ cells are able to regenerate functional pancreatic islet cells in a mouse model of type I diabetes, protein expression was further compared by a subtractive proteomic approach in search of an exclusive protein expression profile in CD45- cells. Characterization of the proteins exclusively identified in CD45- cells was performed using gene ontology terms via the Javascript GoMiner. The CD45- cell subset readily revealed proteins involved in development, suggesting the persistence of a fetal stem cell in an adult animal.

Animals↗

PubMed2006

Quantitative proteomics of the archaeon Methanococcus maripaludis validated by microarray analysis and real time PCR.

For the archaeon Methanococcus maripaludis, a fully sequenced and annotated model species of hydrogenotrophic methanogen, we report validation of quantitative protein level expression ratios on a proteome-wide basis. Using an approach based on quantitative multidimensional capillary HPLC and quadrupole ion trap mass spectrometry, coverage of gene expression approached that currently achievable with transcription microarrays. Comprehensive mass spectrometry-based proteomics and spotted cDNA arrays were used to compare global protein and mRNA levels in a wild-type (S2) and mutant strain (S40) of M. maripaludis. Using linear regression with 652 expression ratios generated by both the proteomic and microarray methods, a product moment correlation coefficient of 0.24 was observed. The correlation improved to 0.61 if only genes showing significant expression changes were included. A novel two-stage method of outlier detection was used for the protein measurements when Dixon's Q-test by itself failed to give satisfactory results. The log(2) transformations of the number of peptides or isotopic peptide pairs associated with each ORF, divided by the predicted molecular weight, were found to have moderately positive correlations with two bioinformatic predictors of gene expression based on codon bias. We detected peptides derived from 939 proteins or 55% of the genome coding capacity. Of these, 60 were overexpressed, and 34 were underexpressed in the mutant. Of the 1722 ORFs encoded in the genome, 1597 or 93% were probed by cDNA arrays. Of these, 50 were more highly expressed, and 45 showed lower expression levels in the mutant relative to the wild type. 15 ORFs were shown to be overexpressed by both methods, and two ORFs were shown to be overexpressed by proteomics and underexpressed by microarray.

Archaeal Proteins↗

PubMed2002

Biophysical characterization of proteins in the post-genomic era of proteomics.

Proteomics focuses on the high throughput study of the expression, structure, interactions, and, to some extent, function of large numbers of proteins. A true understanding of the functioning of a living cell also requires a quantitative description of the stoichiometry, kinetics, and energetics of each protein complex in a cellular pathway. Classical molecular biophysical studies contribute to understanding of these detailed properties of proteins on a smaller scale than does proteomics in that individual proteins are usually studied. This perspective article deals with the role of biophysical methods in the study of proteins in the proteomic era. Several important physical biochemical methods are discussed briefly and critiqued from the standpoint of information content and data acquisition. The focus is on conformational changes and macromolecular assembly, the utility of dynamic and static structural data, and the necessity to combine experimental approaches to obtain a full functional description. The conclusions are that biophysical information on proteins is a useful adjunct to "standard" proteomic methods, that data can be obtained by high throughput technology in some instances, but that hypothesis-driven experimentation may frequently be required.

Biophysical Phenomena↗

PubMed2002

Chemical strategies for functional proteomics.

With complete genome sequences now available for several prokaryotic and eukaryotic organisms, biological researchers are charged with the task of assigning molecular and cellular functions to thousands of predicted gene products. To address this problem, the field of proteomics seeks to develop and apply methods for the global analysis of protein expression and protein function. Here we review a promising new class of proteomic strategies that utilizes synthetic chemistry to create tools and assays for the characterization of protein samples of high complexity. These approaches include the development of chemical affinity tags to measure the relative expression level and post-translational modification state of proteins in cell and tissue proteomes. Additionally, we discuss the emerging field of activity-based protein profiling, which aims to synthesize and apply small molecule probes that monitor dynamics in protein function in complex proteomes.

Affinity Labels↗

PubMed2003

Breast cancer: when proteomics challenges biological complexity.

Proteomics is now entering into the field of biomedicine with declared hopes for the identification of new pathological markers and therapeutic targets. Current proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of low-abundant proteins. However, the major limitation of proteomic investigations remains the complexity of biological structures and physiological processes, rendering the path of exploration of related pathologies paved with various difficulties and pitfalls. The case of breast cancer illustrates the major challenge facing modern proteomics and more generally post-genomics: to tackle the complexity of life.

Biomarkers, Tumor↗

PubMed2005

Proteomic mapping of brain plasma membrane proteins.

Proteomics is potentially a powerful technology for elucidating brain function and neurodegenerative diseases. So far, the brain proteome has generally been analyzed by two-dimensional gel electrophoresis, which usually leads to the complete absence of membrane proteins. We describe a proteomic approach for profiling of plasma membrane proteins from mouse brain. The procedure consists of a novel method for extraction and fractionation of membranes, on-membrane digestion, diagonal separation of peptides, and high-sensitivity analysis by advanced MS. Breaking with the classical plasma membrane fractionation approach, membranes are isolated without cell compartment isolation, by stepwise depletion of nonmembrane molecules from entire tissue homogenate by high-salt, carbonate, and urea washes followed by treatment of the membranes with sublytic concentrations of digitonin. Plasma membrane is further enriched by of density gradient fractionation and protein digested on-membrane by endoproteinase Lys-C. Released peptides are separated, fractions digested by trypsin, and analyzed by LC-MS/MS. In single experiments, the developed technology enabled identification of 862 proteins from 150 mg of mouse brain cortex. Further development and miniaturization allowed analysis of 15 mg of hippocampus, revealing 1,685 proteins. More that 60% of the identified proteins are membrane proteins, including several classes of ion channels and neurotransmitter receptors. Our work now allows in-depth study of brain membrane proteomes, such as of mouse models of neurological disease.

Animals↗

PubMed2025

Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE). METHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE. RESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively. CONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.

Humans↗

PubMed2026

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4 Hz and 30 Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0 Hz), low-frequency (4 Hz), or high-frequency (30 Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4 Hz and 29 at 30 Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals↗

PubMed2026

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗

PubMed2005

Proteomics approaches to biomarker detection.

The development of mass spectrometry (MS) technologies has brought the ability to gather massive amounts of data characterising the proteomes of complex mixtures. A major focus in proteomics is to leverage this data-gathering capability to conduct comparative analyses of biofluids from healthy and disease-affected patients for the identification of highly specific biomarkers and/or the development of MS-based diagnostic platforms. Much effort has gone into optimising the biofluid proteome coverage that can be obtained using these technologies, leaving proteomics poised to make an important impact in disease diagnostics in the future.

Biomarkers↗

PubMed2005

Recent advancements in differential proteomics based on stable isotope coding.

Stable isotope coding continues to be a powerful approach in comparative proteomics. This review focuses on recent developments in stable isotope coding-based strategies targeted towards protein expression, protein interactions with other biomolecules, post-translational modifications and absolute quantification. The focus of the bulk of proteomics studies is still on protein expression. An important recent application of isotope coding has been in organelle proteomics. The review ends with the conclusion that isotope coding remains an integral part of quantitative proteomics. There is, however, a need to develop coding strategies which can differentiate changes in protein expression and post-translational modification, address issues of protein dynamic range and facilitate real-time detection of proteins which show a statistically significant change after stimulus.

Amino Acids↗

PubMed2006

Shotgun proteomics of cyanobacteria--applications of experimental and data-mining techniques.

Cyanobacteria are photosynthetic bacteria notable for their ability to produce hydrogen and a variety of interesting secondary metabolites. As a result of the growing number of completed cyanobacterial genome projects, the development of post-genomics analysis for this important group has been accelerating. DNA microarrays and classical two-dimensional gel electrophoresis (2DE) were the first technologies applied in such analyses. In many other systems, 'shotgun' proteomics employing multi-dimensional liquid chromatography and tandem mass spectrometry has proven to be a powerful tool. However, this approach has been relatively under-utilized in cyanobacteria. This study assesses progress in cyanobacterial shotgun proteomics to date, and adds a new perspective by developing a protocol for the shotgun proteomic analysis of the filamentous cyanobacterium Anabaena variabilis ATCC 29413, a model for N(2) fixation. Using approaches for enhanced protein extraction, 646 proteins were identified, which is more than double the previous results obtained using 2DE. Notably, the improved extraction method and shotgun approach resulted in a significantly higher representation of basic and hydrophobic proteins. The use of protein bioinformatics tools to further mine these shotgun data is illustrated through the application of PSORTb for localization, the grand average hydropathy (GRAVY) index for hydrophobicity, LipoP for lipoproteins and the exponentially modified protein abundance index (emPAI) for abundance. The results are compared with the most well-studied cyanobacterium, Synechocystis sp. PCC 6803. Some general issues in shotgun proteome identification and quantification are then addressed.

Computational Biology↗

PubMed2006

HPLC techniques for proteomics analysis--a short overview of latest developments.

Due to the complex nature of the proteome, instrumentation and methods development for sample cleanup, fractionation, preconcentration, chromatographic separation and detection becomes urgent for the identification of peptides and proteins. Newly developed techniques and equipment for separation and detection, such as nano-HPLC and multidimensional HPLC for protein and peptide separation, enabled proteomics to experience dynamic growth during the past few years. In any proteomic analysis the most important and sometimes most difficult task is the separation of the complex mixture of proteins or peptides. This review describes some aspects and limitations of HPLC, both multidimensional and one-dimensional, in proteomics research without attempting to discuss all available HPLC methods, which would need far more space than available here.

Animals↗

PubMed2026

The association of cardiovascular health with new-onset pulmonary hypertension and the mediating role of proteomic signatures.

BACKGROUND: The cardiovascular health (CVH) metrics have been reported to play an important role in the development of noncommunicable chronic diseases, yet its link to pulmonary hypertension (PH) risk and the underlying biological mechanisms remain unclear. This study aimed to investigate the association of CVH with PH risk and elucidate the mediating role of plasma proteomic signatures. METHODS: A total of 279 220 participants without PH at enrollment of the UK Biobank were included. Cox regression was used to quantify the association between CVH and incident PH. Proteome-wide association analysis, mediation analysis, and functional enrichment analysis were conducted to identify protein mediators. Key hub proteins were further validated at the transcriptional level through quantitative polymerase chain reaction (qPCR) in an animal model of PH, as well as at the protein level, and by macrophage-specific knockdown of interleukin (IL)-6 and CCL4 to evaluate its impact on rat pulmonary artery smooth muscle cell (PASMC) migration and proliferation. RESULTS: Over a median 13.2-year follow-up, 1325 PH cases occurred. Compared to the lowest CVH, participants with moderate and high CVH had 59% [hazard ratio (HR): 0.41; 95% confidence interval (CI): 0.33-0.49] and 82% (HR: 0.18; 95% CI: 0.14-0.23) lower risk, respectively. Proteomic analyses revealed that this association was significantly mediated by a distinct plasma protein signature. Pathway enrichment analysis indicates that proteins are significantly enriched in inflammatory/immune pathways, and key hub proteins were identified as participating in the central mechanism pathway. In the lung tissue of PH rat models, the mRNA and protein expression levels of IL-6 and C-C motif chemokine ligand 4 (CCL4) were significantly elevated. Furthermore, functional assays demonstrated that knockdown of IL-6 or CCL4 in macrophages significantly attenuated the migration and proliferation of rat PASMCs in vitro. CONCLUSION: High CVH level, defined by Life's Essential 8 (LE8), is significantly linked to a reduced risk of developing PH. This protective effect is primarily mediated by a proteomic signature, revealing the role of signaling pathways such as cytokine-cytokine receptor interaction in the prevention of PH.

Hypertension, Pulmonary↗