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At least 775 records · Page 43Linked to original sources
PubMed2005

Complex proteome prefractionation using microscale solution isoelectrofocusing.

The proteomes of mammalian cells, tissues and biologic fluids are complex and consist of proteins present over a wide dynamic range. Current protein profiling technologies do not have the capacity to overcome the sample complexity for comprehensive analysis of complex proteomes. A common strategy to substantially expand protein profiling capacities is sample prefractionation. A prefractionation method developed in the authors' laboratory, microscale solution isoelectrofocusing, has resulted in a commercial product, the ZOOM IEF Fractionator, which provides a simple and convenient method for high-resolution separation of complex proteomes based upon their isoelectric points. Complex human samples such as cancer cells and biologic fluids can be fractionated into well-resolved fractions with minimal cross-contamination of proteins between adjacent fractions. This review focuses on the application of microscale solution isoelectrofocusing prefractionation and subsequent downstream strategies in expanding protein profiling capacities and mining low-abundance proteins of complex proteomes.

Animals↗
PubMed2006

Protein turnover on the scale of the proteome.

Protein turnover is a neglected dimension in postgenomic studies, defining the dynamics of changes in protein expression and forging a link between transcriptome, proteome and metabolome. Recent advances in postgenomic technologies have led to the development of new proteomic techniques to measure protein turnover on a proteome-wide scale. These methods are driven by stable isotope metabolic labeling of cells in culture or in intact animals. This review considers the merits and difficulties of different methods that allow access to proteome dynamics.

Animals↗
PubMed2025

Identifying potential biomarkers in the hippocampus of chronic fatigue syndrome rats treated with moxibustion at Zusanli (ST36): a proteomics study.

OBJECTIVE: To observe the effects of moxibustion at Zusanli (ST36) on rats with chronic fatigue syndrome (CFS) and to analyze the mechanisms of moxibustion through hippocampal Proteomics. METHODS: Male Sprague-Dawley (SD) rats were randomly divided into three groups: control group (CON), model group (MOD), and moxibustion group (MOX), with 12 rats in each group. The MOD and MOX groups underwent chronic multi-factor stress stimulation for 35 d to establish the CFS model. After modeling, the rats in the MOX group received mild moxibustion at Zusanli (ST36) (bilateral) for 10 minutes daily for 28 d. During the treatment period, rats in both the MOD and MOX groups continued modeling, while the CON group was kept under normal breeding conditions. The general condition of the rats was monitored, and behaviors were assessed using the Open Field Test (OFT), Exhaustion Treadmill Test, and Morris Water Maze (MWM). Hematoxylin and eosin (HE) staining and transmission electron microscopy (TEM) were employed to observe morphological changes in the hippocampus. Label-free Proteomics were utilized to identify differentially expressed proteins (DEPs) in the hippocampus, followed by bioinformatics analysis. The reliability of the Proteomics results was verified using Parallel Reaction Monitoring. RESULTS: A: Moxibustion at Zusanli (ST36) significantly reduced the general condition score of CFS rats, improved their behavioral performance in OFT, treadmill and MWM, and repaired the pathological and synaptic structural damage in the hippocampus.B: We identified DEPs by applying a fold change threshold of 1.2 and a significance level of P < 0.05. In the comparison between the CON and the MOD, we identified a total of 72 DEPs (31 up-regulated and 41 down-regulated) associated with the development of CFS. In the comparison between the MOX and the MOD group, we identified a total of 103 DEPs (40 up-regulated and 63 down-regulated) related to the therapeutic effects of moxibustion. Gene Ontology (GO) enrichment analysis showed that CFS and moxibustion treatment were related to multiple biological processes, molecular functions, and cellular components. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that CFS pathogenesis was linked to base excision repair, steroid biosynthesis, and systemic lupus erythematosus, Furthermore, the treatment of CFS with moxibustion was relevant to terpenoid skeleton biosynthesis.C: Compared with the two comparison groups, we identified 16 potential biomarkers, noting that moxibustion reversed the up-regulation of 14 DEPs and the down-regulation of 2 DEPs in CFS. These proteins are mainly associated with synaptic plasticity, ribosomal function, neurotransmitter secretion, glycine metabolism, and mitochondrial function. CONCLUSION: Moxibustion at Zusanli (ST36) is effective in treating CFS, the potential biomarkers identified by Proteomics confirm that the mechanisms of moxibustion involve multiple targets and pathways, which may be key to regulating the structural and functional damage in the hippocampus associated with CFS, highlighting their significant value for future research.

Animals↗
PubMed2005

On-line microdevice for stress proteomics.

The handling of the cells or tissues is essential for proteomics research or drug screening, where labor is not avoidable. The steps of cell wash, protein extraction, protein denaturing are complicated procedures in conventional method using centrifugation and pipetting in the laboratory. This is the bottle-neck for proteome research. To solve these problems, we propose to utilize the nanotechnology, which will improve the proteomics methodology. Utilizing the nanotechnology, we developed a novel microseparation system, where centrifugation and pipetting are needless. This system has a nanostructured microdevice, by which the cell handling, protein extraction, and antibody assay can be performed. Since cell transfer is needless, all cells are corrected without any loss during the cell-pretreatment procedures, which allowed high reproducibility and enabled the detection of low amount of protein expression. Utilizing the microdevice, we analyzed the stress induced proteins. We further succeeded the screening of food that was useful for immunity and found that an extraction from seaweed promoted the apoptosis of T-lymphoblastic cells. Here, we present an on-line microdevice for stress proteomics.

Nanotechnology↗
PubMed2026

Integrated multi-omics analysis of metabolomics and proteomics uncovers dysregulated amino acid metabolism in HCC metastasis.

BACKGROUND: Metastasis is the primary cause of treatment failure and adverse prognosis in hepatocellular carcinoma (HCC), and the molecular basis of HCC metastasis remains poorly defined. This work investigated the potential mechanisms underlying HCC metastasis through integrated multi-omics analysis of metabolomics and proteomics. METHOD: This retrospective study included 105 individuals with HCC, with comparative analysis between metastatic and non-metastatic cases. We further evaluated the effects of metastasis on serum metabolomics and proteomics in HCC patients. RESULT: Widespread disturbances in amino acid metabolism were identified via untargeted metabolomics in HCC patients with metastasis, closely governing inflammation-related metabolic remodeling and oxidative stress responses. Specifically, we identified 91 and 59 distinct differential metabolites capable of indicating HCC metastasis, with the screening criteria set as log2 fold change > 1.5, adjusted P value < 0.05, and VIP > 1.5 in positive and negative modes, respectively. The alanine, aspartate and glutamate metabolism pathway correlated with HCC-associated lung metastasis, while the gluconeogenesis pathway was linked to HCC-associated bone metastasis. Compared with HCC (non-metastatic hepatocellular carcinoma), the key molecular alterations in the multi-omics network of HCC_M (HCC with metastasis) are implicated in inflammatory metabolic reprogramming, oxidative stress response, gluconeogenesis, glycolysis, and the tricarboxylic acid (TCA) cycle. Twenty-five proteins, including PKM2, PERCK, ALDH2, CPS1, GLS1, GLUD1, GOT1, and SLC38A2, were identified as potential biomarkers for HCC metastasis. CONCLUSION: By integrating untargeted metabolomic and proteomic profiling, we identified distinct metabolic and proteomic changes linked to HCC metastasis. This work also characterized the pathological characteristics and core pathways underlying HCC metastasis, while identifying potential therapeutic candidates.

Humans↗
PubMed2026

Early Cardiomyopathy in Prediabetic NDPK-B-Deficient Mice Is Associated with Remodeling of the Mitochondrial O-GlcNAc Proteome.

Diabetic cardiomyopathy (DCM) is characterized by myocardial remodeling that may already be evident during prediabetes, yet the molecular alterations accompanying these early changes remain poorly understood. The present study examined mouse models of Nucleoside diphosphate kinase B (NDPK-B)-deficient prediabetes and streptozotocin-induced diabetes using O-GlcNAc-associated proteomic profiling to define stage-specific molecular alterations during the progression from prediabetic to diabetic cardiomyopathy. Both models exhibited increased left ventricular extracellular matrix deposition and impaired diastolic function, together with activation of the hexosamine biosynthesis pathway. Profiling of O-GlcNAc-associated proteins uncovered extensive remodeling of the mitochondrial proteome already at the prediabetic stage, with respiratory complex I among the most prominently altered targets, alongside changes in substrate metabolism and inflammatory signaling. In overt DCM, the putative O-GlcNAc proteomic profile was associated with a shift toward wider lipid-dependent metabolic reprogramming and remodeling of mitochondrial proteins. These findings identify early remodeling of the mitochondrial O-GlcNAc-associated proteome as a molecular signature of prediabetic cardiomyopathy and highlight respiratory complex I proteins as candidate targets for future mechanistic investigations.

Animals↗
PubMed2026

Aptamer-Based Platforms for Human Aging Biomarkers: Multiplexed Proteomics, Biosensors and Translational Perspectives.

Aptamer-based multiplexed proteomic platforms, especially the SOMAmer-based SomaScan assay, are widely used for large-scale discovery of circulating biomarkers relevant to human aging. This review summarizes 42 original research articles published from 2020 through 2026 in which aptamers or aptamer-derived biosensors were used to characterize aging-related biomarkers in human samples or clinically relevant human-disease contexts. The eligible literature falls into several thematic areas: whole-plasma and organ-specific proteomic aging clocks; inflammaging and senescence-associated secretory phenotype (SASP) markers; cardiovascular, metabolic, renal, hepatic, musculoskeletal and neurodegenerative biomarker panels; and aptasensor platforms for detection of individual analytes. Only a small number of studies have compared aptamer- and antibody-based platforms in the same specimens; we tabulate these and show that median between-platform agreement is low to moderate, which constrains the pooling of findings across technologies. We also make explicit an interpretive point that is usually left implicit: because proteomic clocks are trained against chronological age, their correlation with chronological age measures fit to the training target rather than biological validity, and the informative quantity is the residual age gap. In the reviewed literature, SomaScan-based studies are concentrated in cardiovascular, neurodegenerative, frailty, and proteomic aging-clock research, whereas de novo SELEX campaigns targeting aging-specific epitopes and longitudinal human validation of wearable aptasensors were not identified. The main barriers to translation are cross-platform discordance, limited replication across ancestries, under-reported pre-analytical variability, cost, and the research-use-only status of most assays.

Humans↗
PubMed2006

Systematic proteome and transcriptome analysis of stem cell populations.

Methods for relative assessment of the transcriptional activity of the cell are now routinely employed and obtain large amounts of information regarding process such as transformation or development. These approaches have great impact and are of significant value. Nonetheless, mRNA is an intermediate in the process of protein synthesis and changes in mRNA expression do not reflect absolute or relative changes in protein levels. The mechanisms which translate mRNA to protein are highly regulated, and it remains unclear how the transcriptome reflects the functional state of the cell, as defined by its protein output. Large scale analyses of the proteome are now becoming a reality due to technical advances in protein arrays and mass spectrometry. Thus for the first time data on large numbers of mRNA transcripts and the levels of expression of their associated proteins is available in dynamic systems. Analysis of one such comparison, the transcriptome and proteome of primary haematopoietic stem cells, reveals post-translational regulation of the proteome in stem cell populations. The factors which must be considered when comparing two systematically acquired 'omics' datasets are reviewed and the relative merits of transcriptome and proteome approaches are discussed.

Animals↗
PubMed2002

Proteomic approaches to central nervous system disorders.

The discovery, design and evaluation of new medicines is critically dependent on the elucidation of protein mechanisms involved in human diseases. Since the proteome of a cell or tissue is not a simple reflection of its transcriptome, direct protein-based analysis is needed. Advances in proteomic technologies are improving the analysis of membrane proteins and signaling complexes with increased speed and molecular detail. Changes in protein isoforms due to post-translational modifications, such as phosphorylation induced by cell signaling events and alternative splice forms of receptors, may be mapped to an altered protein expression pattern in clinically relevant cell populations with a causative or diagnostic disease link. A CNS proteome database derived from primary human tissues may avoid ambiguities of experimental models. It will also accelerate the development of more specific diagnostic and prognostic disease markers as well as new selective therapeutics. Proteomics is also being applied to resolve in silico gene prediction uncertainties by direct open reading frame verification. These advances hold great promise for improvements in the understanding, diagnosis and therapy of central nervous system disorders.

Biomarkers↗
PubMed2005

[Proteomics and its role in medicine].

Proteomics is a new methodological and conceptual approach to the study of live systems, which aims to map the whole proteom - the protein complement of genome. It aspires to describe quantitatively and qualitatively all proteins present at the given moment in the cell, tissue or the organism. The principal tools of proteomics are separation techniques based on electrophoresis and chromatography, which are used to fractionate complex protein mixtures and namely the mass spectrometry used for the identification of individual proteins. Proteomics represents very young and rapid developing specialization, which has already proved its valuable potential for the study of various physiological and pathlogical molecular mechanisms and for the direct use in the diagnostics of serious diseases.

Chromatography↗
PubMedDate not supplied

Proteomics in the diagnosis of hepatocellular carcinoma: focus on high risk hepatitis B and C patients.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. The high morbidity rate associated with this cancer is mainly linked to the late diagnosis, when therapy is no longer effective and this is particularly true for high risk patients, such as hepatitis B and C infected individuals. A biomarker can be defined as a substance, found in an increased amount in the body fluids, such as blood, which can indicate the presence of liver cancer. Current screening methodologies for liver cancer in at-risk patients rely on measuring the serum level of alpha-fetoprotein (AFP), a biomarker, as well as ultrasound imaging. AFP's sensitivity is very limited since many other liver diseases can result in a very high blood level of AFP similar to that observed in HCC. In addition, AFP is not always elevated in the early stages of cancer development, when therapy is mostly effective. Imaging, on the other hand, depends to a large extent on the operator. Therefore, better diagnostic methods are needed to increase the survival rate in liver cancer patients. Proteomics can be simply defined as the protein expression of the genome; and protein expression can vary depending on the biological state. Antibody microarrays can scan for multiple targets (antigens) within the tissue or in the circulation. This technology is still in its infancy and has great potential as a diagnostic tool for hepatitis liver cancer patients. Another proteomic approach is mass spectrometry, which can detect proteins and present them as charged species (ions). The mass spectrometric technique termed SELDI (surface enhanced laser desorption ionization), releases proteins in a sample from a capturing surface that can specifically bind groups of proteins which share common features (hydrophobic, negatively charged, etc.) and the expression of thousands of proteins can be monitored simultaneously. Proteomic profiles of hepatitis patients, liver cancer patients and healthy individuals can be established and evaluated for diagnosis. Elevated proteins can further be isolated and identified using the well-established mass spectrometric protein identification methods. In this article, the technological SELDI mass spectrometry and antibody microarrays are presented at the basic level. In addition, the current state of the novel liver cancer diagnostic methods (and biomarkers) that have been evaluated with focus on high risk hepatitis B and C patients using proteomic approaches are reviewed and highlighted.

Biomarkers, Tumor↗
PubMed2026

Unlocking the Circulating Proteome: Toward Clinical Translation.

Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Humans↗
PubMed2000

The dynamic range of protein expression: a challenge for proteomic research.

Proteomic research, for its part, is benefiting enormously from the last decade of genomic research as we now have archived, annotated and audited sequence databases to correlate and query experimental data. While the two-dimensional electrophoresis (2-DE) gels are still a central part of proteomics, we reflect on the possibilities and realities of the current 2-DE technology with regard to displaying and analysing proteomes. Limitations of analysing whole cell/tissue lysates by 2-DE alone are discussed, and we investigate whether extremely narrow p/ranges (1 pH unit/25 cm) provide a solution to display comprehensive protein expression profiles. We are confronted with a challenging task: the dynamic range of protein expression. We believe that most of the existing technology is capable of displaying many more proteins than is currently achievable by integrating existing and new techniques to prefractionate samples prior to 2-DE display or analysis. The availability of a "proteomics toolbox", consisting of defined reagents, methods, and equipment, would assist a comprehensive analysis of defined biological systems.

Chemical Fractionation↗
PubMed2002

Analysis of the human lumbar cerebrospinal fluid proteome.

Idiopathic low back pain has no known cause, and the molecular basis is unknown. Neuropeptidergic systems have been previously studied, and proteomics methods have been applied in this present study. Proteomics combines high-resolution two-dimensional (2-D) gel electrophoresis, high-sensitivity mass spectrometry, and continuously expanding protein databases. Proteomics offers a comprehensive, bird's-eye view to analyze, at a systems level, all of the proteins in cerebrospinal fluid (CSF) that might contribute to idiopathic low back pain. CSF contains a high salt concentration and low protein concentration. In order to obtain a high-quality 2-D pattern, several sample preparation methods were tested to remove salts - protein precipitation with either acetone or trichloroacetic acid/acetone, or sample treatment with a Bio-Spin column. More spots were visualized on the 2-D gel of human CSF, and a relatively high protein recovery was obtained when a Bio-Spin column was used to process a human CSF sample. Sixty-one protein spots, obtained from 2-D gels with a pH range of either 3-10 or 4-7, were identified by matrix assisted laser desorption/ionization-mass spectrometry (MALDI-MS) and MALDI-post-source decay (PSD)-MS. These 61 protein spots represent 22 proteins; six of those proteins were not annotated in any previously published 2-D maps. Those six proteins are PRO2619, pigment epithelium-derived factor, albumin homolog, kallikrein-6 precursor, DJ717I23.1, and AMBP protein precursor. These protein-mapping data will contribute to the database that will be used in the future to compare the proteomes obtained from the CSF of controls and low back pain patients, to characterize differentially expressed proteins, and to elucidate the biological markers for idiopathic low back pain.

Amino Acid Sequence↗
PubMed2001

ToothPrint, a proteomic database for dental tissues.

Increasing demand exists to disseminate and integrate proteomic data as proteome analysis assumes a commanding role in the postgenome era. Databases on the World Wide Web are an effective means to share information obtained from two-dimensional gels and allied proteomic approaches. Here we report the establishment of ToothPrint, a proteomic database for dental tissues accessed at http://toothprint.otago.ac.nz. Using developing rat enamel as a prototype, ToothPrint provides a variety of functionally relevant data (ligand binding, subcellular localisation, developmental regulation) in addition to protein identification maps. Features designed to enhance usability of the website and simplify its computing requirements are also outlined. Customized for mineralizing tissues, ToothPrint should prove to be an effective bioinformatic resource for investigations of dental biology.

Animals↗
PubMed2001

Continuous free-flow electrophoresis separation of cytosolic proteins from the human colon carcinoma cell line LIM 1215: a non two-dimensional gel electrophoresis-based proteome analysis strategy.

The conventional approach for analyzing the protein complement of a genome involves the combination of two-dimensional gel electrophoresis (2-DE) and mass spectrometric based protein identification technologies. While 2-DE is a powerful separation technique, it is severely limited by the insolubility of certain classes of proteins (e.g. hydrophobic membrane proteins), as well as the amount of protein that can be processed. Here, we describe a simple procedure for resolving complex mixtures of proteins that involves a combination of free flow electrophoresis (FFE), a liquid-based isoelectric focussing (IEF) method, and sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Resolved proteins were identified by peptide fragment sequencing using capillary column reversed-phase high performance liquid chromatography (RP-HPLC)/mass spectrometry (MS). An initial demonstration of the method was performed using digitonin/ethylenediaminetetraacetic acid EDTA extracted cytosolic proteins from the human colon carcinoma cell line, LIM 1215. Cytosolic proteins were separated by liquid-based IEF (pH range 3-10) into 96 fractions, and each FFE fraction was further fractionated by SDS-PAGE. Selected protein bands were excised from the SDS-PAGE gel, digested in situ with trypsin, and subsequently identified by on-line RP-HPLC/electrospray-ionization ion trap MS. Our results indicate that FFE is: (i) an extremely powerful liquid-based IEF method for resolving proteins; (ii) not limited by the amount of sample that can be loaded onto the instrument; and (iii) capable of fractionating intact protein complexes (a potentially powerful tool for cell-mapping proteomics). An up-to-date list of cytosolic proteins from the human colorectal carcinoma cell line LIM 1215 can be found in the Joint Protein Structure Laboratory (JPSL) proteome database. This information will provide an invaluable resource for future proteomics-based biological studies of colon cancer. The JPSL proteome database can be accessed through the World Wide Web (WWW) network (http://www.ludwig.edu.au/jpsl/jpslhome.html).

Chromatography, High Pressure Liquid↗
PubMed2001

Proteomics of breast cancer for marker discovery and signal pathway profiling.

Breast cancer is the most common form of cancer among women and the identification of markers to discriminate tumorigenic from normal cells, as well as the different stages of this pathology, is of critical importance. Two-dimensional electrophoresis has been used before for studying breast cancer, but the progressive completion of human genomic sequencing and the introduction of mass spectrometry, combined with advanced bioinformatics for protein identification, have considerably increased the possibilities for characterizing new markers and therapeutic targets. Breast cancer proteomics has already identified markers of potential clinical interest (such as the molecular chaperone 14-3-3 sigma) and technological innovations such as large scale and high throughput analysis are now driving the field. Methods in functional proteomics have also been developed to study the intracellular signaling pathways that underlie the development of breast cancer. As illustrated with fibroblast growth factor-2, a mitogen and motogen factor for breast cancer cells, proteomics is a powerful approach to identify signaling proteins and to decipher the complex signaling circuitry involved in tumor growth. Together with genomics, proteomics is well on the way to molecularly characterizing the different types of breast tumor, and thus defining new therapeutic targets for future treatment.

14-3-3 Proteins↗
PubMed2001

Contribution of proteomics to tumor immunology.

In the postgenome era, the global analysis of gene and protein expression is allowed at RNA and protein level by microarrays and proteomics. The application of these complementary approaches provides new opportunities for tumor immunology investigation. Indeed, applied to the study at the molecular level of the differentiation and maturation of dendritic cells which are the most potent antigen presenting cells, microarray analysis has identified important changes in a large number of genes, whereas the proteomic analysis provided information that could not be obtained at the RNA level, such as the separation of different isoforms and the characterization of post-translational modifications. On the other hand, proteomics allows serological screening of tumor antigens. Indeed, two-dimensional (2-D) polyacrylamide gel electrophoresis allows simultaneously separation several thousand individual proteins from tumor tissue or tumor cell lines. Proteins eliciting humoral response in cancer are identified by 2-D Western blot using cancer patient sera, followed by mass spectrometry analysis and database search. Applied to different types of cancer, the proteome based approach has allowed us to define several tumor antigens. The common occurrence of autoantibodies to certain of these proteins in different cancers may be useful in cancer screening and diagnosis as well as for immunotherapy.

Amino Acid Sequence↗