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[Results of proteomic-based study of the kidney, urine, plasma, and uremic ultrafiltrate. Potential applications of the results in nephrology].

Proteomics, a new branch of science studying proteins, only emerged in the postgenomic period. What makes so it important is that fact even the exciting recent insights into the genome have not furnished sufficient information about proteins, which are the main agents behind cellular, subcellular, and supracellular functions. The center of attention of proteomics is identification of proteins in complex protein mixtures with an emphasis on the identification of a large number of proteins at a time, search for interrelations between identified proteins, their more exact characterization, determination of quantity, and better understanding of their function. Proteomics in nephrology is still in its infancy. Although it makes use, like in other fields, of various methodological procedures, the principal techniques are two-dimensional gel electrophoresis and MALDI-TOF (matrix-assisted laser desorption/ionization-time of flight) mass spectrometry. Nephrology-related proteomic findings made to date inform about normal protein composition of renal parenchyma, urine and plasma, and on their alterations under the influence of physiological or pathological stimuli. Search is under way for uremic toxins in uremic infiltrate, and their elimination from the body of patients with renal failure using various dialysis membranes is being investigated. Findings have made it possible to formulate hypotheses regarding renal physiology and pathology. Current nephrology-related proteomics raises more questions than it answers. Its potential for improving the understanding of physiological processes, pathological states, non-invasive diagnosis, monitoring of therapy, development of drugs and therapeutic procedures is a major promise for future.

Animals↗

Multidimensional fractionation of the bovine skeletal muscle proteome.

The ultimate goal of proteomics is to understand complex biological systems. The first step toward this end is the discovery of protein differences by profiling a given proteome. One approach to proteome profiling is to fractionate it into intact proteins, with subsequent identification and quantitation. In this work, lysates of bovine skeletal muscle were prepared. Reproducible proteome profiles were generated by an automatic two-dimensional protein fractionation system. Proteins were separated by isoelectric point and then by hydrophobicity. The data collected from both separations were used to generate proteome profiles. A high protein content fraction with pl above 8.5 was digested with trypsin, and its main protein component was identified as lysozyme C by matrix assisted laser desorption/ionization-time of flight mass spectrometry.

Animals↗

Tale of two metal reducers: comparative proteome analysis of Geobacter sulferreducens PCA and Shewanella oneidensis MR-1.

Geobacter sulfurreducens and S. oneidensis are the subjects of intense research efforts due to their potential applications to bioremediation. The characterization of their proteomes, being done in parallel with the analysis of their genome sequences, transcriptomes, and metabolomes, is providing valuable insights to both their similarities and their differences. A primary target of interest in the proteomes of both of these metal-reducing microbes is the characterization of their c-type cytochromes. The discovery of their full compliment of c-type cytochromes and the description of what growth conditions trigger their expression is central to harnessing their bioremediation potential. Proteome analyses thus far show that both G. sulfurreducens and S. oneidensis share the common location of a majority of their c-type cytochromes in their outer membranes. The c-type cytochromes of G. sulfurreducens, however, appear to be less soluble and therefore more difficult to isolate from the membranes than those expressed by S. oneidensis. The majority of the G. sulfurreducens c-type cytochromes also differ from those of S. oneidensis in that they have higher isoelectric points, most higher than pH 8.0. These characteristics of solubility and isoelectric point could be related and could indicate an underlying functional difference in the strategy for metal reduction between these two microbes. The global proteome results available for G. sulfurreducens and S. oneidensis at the time of this writing are primarily the result of 2DE analysis coupled to protein identification by LC-MS/MS of tryptic peptides from in-gel digests and represent the most abundant proteins detected by Coomassie blue or silver nitrate staining. Currently, several complimentary efforts utilising the 2D-LC-MS/MS approaches are in progress, promising a more complete protein inventory for these microbes in the near future. As these data are added to those already available, the intricate network of metabolic processes, regulation of protein synthesis and protein function, transport of nutrients, and signal transduction will be elucidated. The existing tools of proteomics will be complimented with newer methods such as protein chips and phage display to further characterize these microbial systems. The end result, in the not too distant future, will be predictive models of G. sulfurreducens and S. oneidensis behavior in their natural habitats under a variety of environmental conditions.

Bacterial Proteins↗

Next-generation brain proteomics: Integrating single-cell, spatial, and multi-omics for clinical biomarker discovery.

The mammalian brain's functional complexity arises from the sophisticated architecture of neurons and glia. This network is essentially defined by its dynamic proteome, which reveals the functional execution underlying neural computation and disease. This review integrates the technological leap in neuroproteomics. It has moved beyond bulk tissue proteome cataloguing to high-sensitivity single-cell and spatial resolution. We detail how next-generation platforms, such as TIMS-PASEF and Orbitrap-Astral, have enabled deeper and faster phenotypic profiling of limited brain samples. However, the proteome coverage remains constrained by dynamic range, sample loss, ionisation bias and incomplete detection of low-abundance regulatory proteins. We further examine how such studies have revealed the proteomic remodelling that drives lineage specification and synaptic plasticity by linking temporal protein expression waves to biological function. Crucially, we delineate the clinical translational trajectory, illustrating how aberrant signatures are verified in cerebrospinal fluid (CSF) and validated in plasma to support precision medicine. Finally, we argue for the necessity of "fused" multi-omics integration and Artificial Intelligence (AI) to decode the non-linear molecular logic of brain pathology.

Humans↗

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗

Systemic Proteomic Alterations and Predictive Biomarkers of Paroxetine Response in Refractory Rosacea: A Secondary Analysis of a Randomized Clinical Trial.

IMPORTANCE: Rosacea is a chronic inflammatory cutaneous disorder characterized by persistent erythema and vascular dysregulation. While paroxetine has shown clinical efficacy in reducing these symptoms, the systemic molecular mechanisms underlying its therapeutic response remain poorly characterized. OBJECTIVE: To investigate systemic proteomic alterations and identify potential predictive biomarkers in patients with refractory erythematous rosacea following paroxetine treatment. DESIGN, SETTING, AND PARTICIPANTS: This prospective plasma proteomic analysis was nested within a multicenter, randomized, double-blind, placebo-controlled clinical trial (Prospective Rosacea Refractory Erythema Randomized Clinical Trial [PRRERCT]). Participants included patients aged 18 to 65 years with refractory rosacea (Clinician's Erythema Assessment [CEA] score &#x2265;3). Plasma samples were collected at baseline and after 12 weeks of treatment. The data for this study were analyzed between September 2025 and November 2025. INTERVENTIONS: Participants received oral paroxetine, 25 mg per day, for a 12-week treatment period. MAIN OUTCOMES AND MEASURES: Systemic protein expression profiles were analyzed using data-independent acquisition liquid chromatography-tandem mass spectrometry. Clinical response was evaluated using CEA and the Flushing Assessment Tool. Correlations between proteomic changes and clinical improvements were assessed, and predictive biomarkers were identified using receiver operating characteristic curve analysis. RESULTS: Among 24 participants (mean [SD] age, 35 [11] years; 24 [100%] female), paroxetine treatment significantly reduced mean (SD) CEA scores from 3.1 (0.3) to 2.3 (0.7) and Flushing Assessment Tool scores from 3.1 (0.6) to 2.0 (0.9) (P&#x2009;<&#x2009;.001). Exploratory proteomic analysis revealed 497 candidate differentially expressed proteins after treatment. Downregulated proteins showed preliminary enrichment in pathways related to immune response activation, insulin receptor signaling, and neuronal remodeling. A subset of 98 reversed-response proteins was observed, primarily linked to synaptic vesicle cycles and vascular smooth muscle contraction. Proteomic alterations were associated with clinical improvement (65 proteins for erythema; 73 for flushing). Candidate biomarkers, notably OLFML3 (area under the receiver operating characteristic curve [AUC], 0.87 [95% CI, 0.70-1.00]) and IGFBP2 (AUC, 0.80 [95% CI 0.55-1.00]), demonstrated high predictive value for clinical response. CONCLUSIONS AND RELEVANCE: In this secondary analysis of a randomized clinical trial, paroxetine treatment was associated with modulation of systemic neuro-vascular-immune networks in patients with rosacea. These exploratory findings provide preliminary mechanistic clues regarding the possible disease-modifying potential of paroxetine and point to circulating protein signatures that may facilitate personalized therapeutic strategies for rosacea management. TRIAL REGISTRATION: Chinese Clinical Trial Registry Identifier: ChiCTR2000031479.

Humans↗

Better approaches to finding the needle in a haystack: optimizing proteome analysis through automation.

Recent evidence has demonstrated a lack of correlation between transcriptional profiles and actual protein levels in cells. Proteome analysis has therefore become indispensable and complementary to genomic analysis for an accurate picture of cellular metabolism. Although proteomics is a relatively young discipline, technology for increasing throughput in proteomic projects is rapidly being developed. The operating paradigm in proteome analysis today is a combination of two-dimensional (2-D) gel electrophoresis (for protein resolution) with mass spectrometry (for protein identification). All the intermediary steps in the procedure including gel staining, image analysis, protein spot excision, digestion and mass spectrometry can be automated to increase efficiency and save time. This report reviews the current state of the proteomics technology and discusses approaches to enhance the sensitivity of 2-D gels with fractionation techniques.

Animals↗

Proteomics: a new approach to the study of disease.

The global analysis of cellular proteins has recently been termed proteomics and is a key area of research that is developing in the post-genome era. Proteomics uses a combination of sophisticated techniques including two-dimensional (2D) gel electrophoresis, image analysis, mass spectrometry, amino acid sequencing, and bio-informatics to resolve comprehensively, to quantify, and to characterize proteins. The application of proteomics provides major opportunities to elucidate disease mechanisms and to identify new diagnostic markers and therapeutic targets. This review aims to explain briefly the background to proteomics and then to outline proteomic techniques. Applications to the study of human disease conditions ranging from cancer to infectious diseases are reviewed. Finally, possible future advances are briefly considered, especially those which may lead to faster sample throughput and increased sensitivity for the detection of individual proteins.

Biomarkers↗

High-throughput profiling of the mitochondrial proteome using affinity fractionation and automation.

Recent studies have demonstrated the need for complementing cellular genomic information with specific information on expressed proteins, or proteomics, since the correlation between the two is poor. Typically, proteomic information is gathered by analyzing samples on two-dimensional gels with the subsequent identification of specific proteins of interest by using trypsin digestion and mass spectrometry in a process termed peptide mass fingerprinting. These procedures have, as a rule, been labor-intensive and manual, and therefore of low throughput. The development of automated proteomic technology for processing large numbers of samples simultaneously has made the concept of profiling entire proteomes feasible at last. In this study, we report the initiation of the (eventual) complete profile of the rat mitochondrial proteome by using high-throughput automated equipment in combination with a novel fractionation technique using minispin affinity columns. Using these technologies, approximately one hundred proteins could be identified in several days. In addition, separate profiles of calcium binding proteins, glycoproteins, and hydrophobic or membrane proteins could be generated. Because mitochondrial dysfunction has been implicated in numerous diseases, such as cancer, Alzheimer's disease and diabetes, it is probable that the identification of the majority of mitochondrial proteins will be a beneficial tool for developing drug and diagnostic targets for associated diseases.

Animals↗

Proteomics on a chip: promising developments.

The field of proteomics is expanding rapidly due to the completion of the human genome and the realization that genomic information is often insufficient to comprehend cellular mechanisms. This considerable expansion of proteomics towards high-throughput platforms is stressing its current technical capabilities. In recent years, technologies in microfluidic and array technologies have appeared for proteomics. These novel approaches might help solve current technical challenges in proteomics. This review presents a general survey of the recent development in microfluidic and array technologies from a proteomics perspective.

Amino Acid Sequence↗

Towards global analysis of mammalian proteomes using sample prefractionation prior to narrow pH range two-dimensional gels and using one-dimensional gels for insoluble and large proteins.

The number of unique protein species in proteomes from a single mammalian cell type is not well defined but is likely to be at least 10000-20000. Since standard-size two-dimensional gels typically resolve only about 1500 to 3000 spots, they merely analyze a small portion of these proteomes. In addition, all insoluble proteins and typically proteins > 100 kDa are seldom resolved on two-dimensional (2-D) gels. The current study demonstrates the feasibility of an overall strategy for more comprehensive quantitative comparisons of complex proteomes derived from physiological fluids or mammalian cell extracts. A key feature of this approach is to prefractionate samples into a few well-resolved fractions based on the proteins' isoelectric points (pIs) using microscale solution isoelectric focusing. These fractions are then separated on narrow pH range two-dimensional gels approximately +/- 0.1 pH unit wider than the prefractionated pool. When this prefractionation approach is applied to complex mammalian proteomes, it improves resolution and spot recovery at high protein loads compared with use of parallel narrow pH range gels without prefractionation. The minimal cross-contamination between fractions allows quantitative comparisons in contrast to most alternative prefractionation methods. In addition, complementary data can be obtained by parallel analysis of the solubilized fraction on high-resolution large-pore-gradient one-dimensional gels followed by mass spectrometric identification to analyze proteins between 100 and approximately 500 kDa. Similarly, insoluble proteins can be analyzed using large-pore gels for large proteins and 10-12% one-dimensional sodium dodecyl sulfate (SDS) gels for smaller proteins. Together, these strategies should permit more reliable quantitative comparisons of complex mammalian proteomes where detection of at least 10000 protein spots is needed in order to analyze the majority of the unique protein species.

Animals↗

Rapid quantitative measurements of proteomes by Fourier transform ion cyclotron resonance mass spectrometry.

The patterns of gene expression, post-translational modifications, protein/biomolecular interactions, and how these may be affected by changes in the environment, cannot be accurately predicted from DNA sequences. Approaches for proteome characterization are generally based upon mass spectrometric analysis of in-gel digested two dimensional polyacrylamide gel electrophoresis (2-D PAGE) separated proteins, allowing relatively rapid protein identification compared to conventional approaches. This technique, however, is constrained by the speed of the 2-D PAGE separations, the sensitivity limits intrinsic to staining necessary for protein visualization, the speed and sensitivity of subsequent mass spectrometric analyses for identification, and the limited ability for accurate quantitative measurements based on differences in spot intensity. We are presently developing alternative approaches for proteomics based upon the combination of fast capillary electrophoresis, or other suitable chromatographic separations, and the high mass accuracy and sensitivity obtainable with unique Fourier transform ion cyclotron resonance (FTICR) mass spectrometers available at our laboratory. Several approaches are presently being pursued; one based upon the analysis of intact proteins and the second upon approaches for global protein digestion and accurate peptide mass analysis. Quantitation of protein/peptide levels are based on using two or more stable-isotope labeled versions of proteomes which are combined to obtain precise quantitation of relative protein abundances. We describe the status of our efforts towards the development of a high-throughput proteomics capability and present initial results for application to several microorganisms and discuss our efforts for extending the developed capability to mammalian proteomes.

Bacterial Proteins↗

Integrating molecular medicine with functional proteomics: realities and expectations.

We analyze key proteomic issues and cutting-edge technologies that will spearhead inroads into functional interpretations of human diseases and their therapeutic rectification, following the availability of the predicted human proteome. We contrast the distinctions between high quality data that are low throughput, (e.g., 3-D proteomic reconstructions in embryogenic and nervous system contexts, and multigenerational transgenic studies), versus automated data harvesting that is more distant from human disease phenotypes and currently fulfills a diagnostic role, (e.g., molecular portraits of human diseases via transcriptomic analyses). We examine the extent to which these approaches impinge upon a realistic understanding of human diseases, namely how close they come to revealing the causal events involved in the initiation of disease. While tissue sources from human embryogenesis, foetal development and the brain remain the absolute priority, the pragmatic approaches utilize judicious data integration from selected proteomic studies of model organisms. The role of genome-wide disease-related screens, "humanized" transgenic analyses, multigenerational gene interference methods, and analyses of post-translational modifications in epigenetic contexts from Drosophila will be crucial, since these avenues are far too slow and transgenically cumbersome in mammals. Finally, the implementation of multi compartment electrolyzers (MCE) and multi photon detection (MPD) systems will be pivotal for the proteomic profiling of human tissue samples.

Animals↗

Hepatocellular carcinoma: from bedside to proteomics.

Hepatocellular carcinoma (HCC or hepatoma) is the most common primary cancer of the liver. It is responsible for approximately one million deaths each year, mainly in underdeveloped and developing countries. The aetiological factors identified in the development of HCC included persistent infection by hepatitis B and hepatitis C viruses, and exposure to aflatoxins. Although immunization can protect individuals from being infected by the hepatitis B virus, the early detection of HCC in those who have been infected by the virus remains a challenge. Thus most HCCs present late and are not suitable for curative treatment. Hence there is a tremendous interest and urgency to identify novel HCC diagnostic marker(s) for early detection, and tumour specific disease associated proteins as potential therapeutic targets in the treatment of HCC. Screening for these HCC proteins has been facilitated by proteomics, a key technology in the global analysis of protein expression and understanding gene function. Present and earlier proteome analyses of HCC have used predominantly experimental in vitro systems. The protein expression profiles of several hepatoma cell lines such as HepG2, Huh7, SK-Hep1, and Hep3B have been compared with normal liver, and nontransformed cell lines (Chang and WRL-68), while a comprehensive proteome analysis to create a protein database was carried out for the cell line HCC-M. In the future, proteome analyses utilizing tumour tissues, which reflect the pathological state of HCC more closely, will be undertaken. This work will complement the gene expression studies of HCC which are already underway. Efforts have also been directed at the proteome analysis of hepatic stellate cells, as these cells play an important role in liver fibrosis. Since liver fibrosis is reversible but not cirrhosis, it is of considerable importance to identify therapeutic targets that can slow its progression.

Amino Acid Sequence↗

Adapting arrays and lab-on-a-chip technology for proteomics.

The impact of proteomics as a discovery engine in life science and in drug discovery has increased tremendously over the last seven years. At the same time, proteomics has expanded from the initial trust as a two-dimensional gel based approach to cover more functional and structural properties of proteins. The development of lab-on-a-chip and protein arrays for proteomics will have to evolve with the changes in proteomics to stay relevant. Here, we review the changes in the field of proteomics and their impact on the development in protein arrays and lab-on-a-chip.

Antibodies↗

Stabilization of cell wall proteins in Bacillus subtilis: a proteomic approach.

Even though cell wall proteins of Bacillus subtilis are characterized by specific cell wall retention signals, some of these are also components of the extracellular proteome. In contrast to the majority of extracellular proteins, wall binding proteins disappeared from the extracellular proteome during the stationary phase and are subjected to proteolysis. Thus, the extracellular proteome of the multiple protease-deficient strain WB700 was analyzed which showed an increased stability of secreted WapA processing products during the stationary phase. In addition, stabilization of the WapA processing products was observed also in a sigD mutant strain which is impaired in motility and cell wall turnover. Next, we analyzed if proteins that can be extracted from B. subtilis cell walls are stabilized in the WB700 strain as well as in the sigD mutant. Thus, the cell wall proteome of B. subtilis wild type was defined showing most abundantly cell wall binding proteins (CWBPs) resulting from the WapA and WprA precursor processing. The inactivation of extracellular proteases as well as SigmaD caused an increase of CWBP105 and a decrease of CWBP62 in the cell wall proteome. We conclude that WapA processing products are substrates for the extracellular proteases which are stabilized in the absence of sigD due to an impaired cell wall turnover.

Amino Acid Sequence↗

Functional proteomics: The goalposts are moving.

Holistic understanding of protein function is a primary goal of the post-genome sequencing era. Functional genomic approaches are powerful and relatively straightforward but produce an incomplete picture at the protein level. Proteomics offers physiologically enriched insights to protein function, and ongoing advances are enabling proteome analyses to proceed with increased depth and efficiency. Exciting discoveries have emerged recently amidst growing awareness of the power of proteomics. However, while proven as a potent discovery tool, proteomics is under pressure to provide improved functional value particularly in concert with other investigative approaches. As reviewed here for ERp29, a recently discovered endoplasmic reticulum protein, the role of novel proteins can remain elusive even after substantial information has accrued. Thousands more proteins of uncertain function will be unveiled in the near future. Consequently, the goalposts are moving for proteomics both through increasing demand for high-value functional information and improving capacity to deliver.

Animals↗

Proteomic Profiling of the Large-Vessel Vasculitis Spectrum Identifying Shared Signatures of Innate Immune Activation and Stromal Remodeling.

OBJECTIVE: Takayasu arteritis (TAK) and giant cell arteritis (GCA), the most common forms of large-vessel vasculitis (LVV), can result in serious morbidity. Understanding the molecular basis of LVV should aid in developing better biomarkers and treatments. METHODS: Plasma proteomic profiling of 184 proteins was performed in two cohorts. Cohort 1 included patients with established TAK (n = 96) and large-vessel GCA (LV-GCA) (n = 35) in addition to healthy control participants (HCs) (n = 35). Cohort 2 comprised patients presenting acutely with possible cranial GCA (C-GCA) in whom the diagnosis was subsequently confirmed (C-GCA, n = 150) or excluded (Not C-GCA, n = 89). Proteomic findings were compared to published transcriptomic data from LVV-affected arteries. RESULTS: In cohort 1, comparison to HCs revealed 52 differentially abundant proteins (DAPs) in TAK and 72 DAPs in LV-GCA. Within-case analyses identified 16 and 18 disease activity-associated proteins in TAK and LV-GCA, respectively. In cohort 2, comparing C-GCA versus not C-GCA revealed 31 DAPs. Analysis within C-GCA cases suggested the presence of distinct endotypes, with more pronounced proteomic changes in the biopsy-proven subgroup. Cross-comparison of TAK, LV-GCA, and biopsy-proven C-GCA revealed highly similar plasma proteomic profiles, with 26 shared DAPs including interleukin 6 (IL-6), monocyte/macrophage-related proteins (CCL7, CSF1), tissue remodeling proteins (TIMP1, TNC), and novel associations (TNFSF14, IL-7R). Plasma proteomic findings reflected LVV arterial phenotype; for 42% of DAPs, the corresponding gene was differentially expressed in tissue. CONCLUSION: These findings suggest shared pathobiology across the LVV spectrum involving innate immunity, lymphocyte homeostasis, and tissue remodeling. Network-based analyses highlighted immune-stromal cross-talk and identified novel therapeutic targets (eg, TNFSF14).

Humans↗