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PubMed2002

Detection technologies in proteome analysis.

Common strategies employed for general protein detection include organic dye, silver stain, radiolabeling, reverse stain, fluorescent stain, chemiluminescent stain and mass spectrometry-based approaches. Fluorescence-based protein detection methods have recently surpassed conventional technologies such as colloidal Coomassie blue and silver staining in terms of quantitative accuracy, detection sensitivity, and compatibility with modern downstream protein identification and characterization procedures, such as mass spectrometry. Additionally, specific detection methods suitable for revealing protein post-translational modifications have been devised over the years. These include methods for the detection of glycoproteins, phosphoproteins, proteolytic modifications, S-nitrosylation, arginine methylation and ADP-ribosylation. Methods for the detection of a range of reporter enzymes and epitope tags are now available as well, including those for visualizing beta-glucuronidase, beta-galactosidase, oligohistidine tags and green fluorescent protein. Fluorescence-based and mass spectrometry-based methodologies are just beginning to offer unparalleled new capabilities in the field of proteomics through the performance of multiplexed quantitative analysis. The primary objective of differential display proteomics is to increase the information content and throughput of proteomics studies through multiplexed analysis. Currently, three principal approaches to differential display proteomics are being actively pursued, difference gel electrophoresis (DIGE), multiplexed proteomics (MP) and isotope-coded affinity tagging (ICAT). New multiplexing capabilities should greatly enhance the applicability of the two-dimensional gel electrophoresis technique with respect to addressing fundamental questions related to proteome-wide changes in protein expression and post-translational modification.

Genes, Reporter↗

PubMed2025

Proteomic signatures and predictive modeling of cadmium-associated anxiety in middle-aged and elderly populations: an environmental exposure association study.

BACKGROUND: Emerging evidence implicates environmental contaminants such as cadmium (Cd) as modifiable risk factors for anxiety. Despite growing recognition of heavy metal toxicity in neuropsychiatric disorders, the molecular mechanisms linking environmental exposure to anxiety pathogenesis remain poorly understood. METHODS: Based on the established cohort of individuals with cognitive impairment in cadmium-contaminated areas, this cross-sectional association study enrolled 50 middle-aged and elderly hospitalized patients from these regions, adhering to the STROBE guidelines. Blood concentrations of cadmium (Cd), lead (Pb), and mercury (Hg) were analyzed in relation to anxiety severity assessed via the Hamilton Anxiety Rating Scale (HAMA). Plasma proteomic profiling was performed using data-independent acquisition (DIA) quantitative technology with an LC-MS/MS platform (timsTOF Pro, Bruker Daltonics), systematically characterizing 2,531 proteins across all samples. Machine learning techniques, specifically XGBoost and LASSO, were employed to identify biomarkers that were subsequently validated through mediation analysis and animal experiments, allowing for the screening of key protein signatures. Finally, clinical variables were integrated to construct a comprehensive model, which was then thoroughly evaluated. RESULTS: Anxious individuals exhibited significantly higher blood Cd levels than controls (β = 0.50, 95% CI: 0.07-0.93, p < 0.01), with anxiety positively correlating with depression (r = 0.62, p = 0.003) and inversely with ApoE3 genotype prevalence. Proteomics identified 120 differentially expressed proteins in anxious patients, enriched in oxidative phosphorylation and neurodegenerative pathways. CCDC126 emerged as a cadmium-associated biomarker, validated in rat models exposed to Cd. Combining CCDC126, blood Cd, Pb, and hypertension, a clinical prediction model achieved robust discrimination (AUC = 0.80, validation cohort). CONCLUSIONS: This first integrative environmental-proteomic study highlights cadmium's synergistic role in anxiety pathophysiology and psychiatric comorbidity. The predictive model offers translatable potential for early risk stratification, while CCDC126 provides mechanistic insights for targeted interventions in populations exposed to environmental pollutants.

Cadmium↗

PubMed2004

Prediction of liver fibrosis and cirrhosis in chronic hepatitis B infection by serum proteomic fingerprinting: a pilot study.

BACKGROUND: Most noninvasive predictive models of liver fibrosis are complicated and have suboptimal sensitivity. This study was designed to identify serum proteomic signatures associated with liver fibrosis and to develop a proteome-based fingerprinting model for prediction of liver fibrosis. METHODS: Serum proteins from 46 patients with chronic hepatitis B (CHB) were profiled quantitatively on surface-enhanced laser desorption/ionization (SELDI) ProteinChip arrays. The identified liver fibrosis-associated proteomic fingerprint was used to construct an artificial neural network (ANN) model that produced a fibrosis index with a range of 0-6. The clinical value of this index was evaluated by leave-one-out cross-validation. RESULTS: Thirty SELDI proteomic features were significantly associated with the degree of fibrosis. Cross-validation showed that the ANN fibrosis indices derived from the proteomic fingerprint strongly correlated with Ishak scores (r = 0.831) and were significantly different among stages of fibrosis. ROC curve areas in predicting significant fibrosis (Ishak score >or=3) and cirrhosis (Ishak score >or=5) were 0.906 and 0.921, respectively. At 89% specificity, the sensitivity of the ANN fibrosis index in predicting fibrosis was 89%. The sensitivity for prediction increased with degree of fibrosis, achieving 100% for patients with Ishak scores >4. The accuracy for prediction of cirrhosis was also 89%. Inclusion of International Normalized Ratio, total protein, bilirubin, alanine transaminase, and hemoglobin in the ANN model improved the predictive power, giving accuracies >90% for the prediction of fibrosis and cirrhosis. CONCLUSIONS: A unique serum proteomic fingerprint is present in the sera of patients with fibrosis. An ANN fibrosis index derived from this fingerprint could differentiate between different stages of fibrosis and predict fibrosis and cirrhosis in CHB infection.

Blood Proteins↗

PubMed2005

PROTICdb: a web-based application to store, track, query, and compare plant proteome data.

PROTICdb is a web-based application, mainly designed to store and analyze plant proteome data obtained by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spectrometry (MS). The purposes of PROTICdb are (i) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements, and (ii) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of post-translational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs of image analysis and MS identification software, or by filling web forms. 2-D PAGE annotated maps can be displayed, queried, and compared through a graphical interface. Links to external databases are also available. Quantitative data can be easily exported in a tabulated format for statistical analyses. PROTICdb is based on the Oracle or the PostgreSQL Database Management System and is freely available upon request at the following URL: http://moulon.inra.fr/ bioinfo/PROTICdb.

Computer Graphics↗

PubMed2006

Mass spectrometric quantitation of C-reactive protein using labeled tryptic peptides.

Given the extensive efforts applied toward proteomics and research in biomarkers, methods for the simultaneous measurement of proteins, peptides, metabolic intermediates, hormones, etc. in a complex sample may be required in the foreseeable future. Assays based on mass spectrometric detection may be suitable for meeting the demands of such complex samples with sensitivity and specificity. An analytical method for the quantitation of C-reactive protein (CRP), a well-known marker of inflammation, is described. Exact quantities of two synthetic (13)C-labeled CRP tryptic peptides were added as internal standards directly to the sample prior to chemical treatment, trypsinization, and liquid chromatography/mass spectrometry quantitation. C-reactive protein levels based on isotopic response ratios were measured. Intact C-reactive protein was spiked into blank rat urine for chemical and enzymatic treatment, producing linear response ratios of labeled to unlabeled peptides. For rigorous quantitation, standard curves, and quality control samples were prepared in rat urine with highly purified labeled and unlabeled peptides over the 50 pg-5 ng/muL concentration range. Using the same chemical and enzymatic treatment used for digestion of intact CRP, data from these samples demonstrated excellent analytical performance. The method was successfully applied toward the quantitation of urinary C-reactive protein from a study of drug-induced nephrotoxicity.

Amino Acid Sequence↗

PubMed2004

Identification by proteomic analysis of calreticulin as a marker for bladder cancer and evaluation of the diagnostic accuracy of its detection in urine.

BACKGROUND: New methods for detection of bladder cancer are needed because cystoscopy is both invasive and expensive and urine cytology has low sensitivity. We screened proteins as tumor markers for bladder cancer by proteomic analysis of cancerous and healthy tissues and investigated the diagnostic accuracy of one such marker in urine. METHODS: Three specimens of bladder cancer and healthy urothelium, respectively, were used for proteome differential display using narrow-pH-range two-dimensional electrophoresis. To evaluate the presence of calreticulin (CRT) as detected by Western blotting, we obtained 22 cancerous and 10 noncancerous surgical specimens from transurethral resection or radical cystectomy. To evaluate urinary CRT, we collected 70 and 181 urine samples from patients with and without bladder cancer, respectively. Anti-CRT COOH-terminus antibody was used to detect CRT in tissue and urine. RESULTS: Proteomic analysis revealed increased CRT (55 kDa; pI 4.3) in cancer tissue. Quantitative Western blot analysis showed that CRT was increased in cancer tissue (P = 0.0003). Urinary CRT had a sensitivity of 73% (95% confidence interval, 62-83%) at a specificity of 86% (80-91%) for bladder cancer in the samples tested. CONCLUSIONS: Proteomic analysis is useful in searching for candidate proteins as biomarkers and led to the identification of urinary CRT. The diagnostic accuracy of urinary CRT for bladder cancer appears comparable to that of Food and Drug Administration-cleared urinary markers, but further studies are needed to determine its diagnostic role.

Aged↗

PubMed2002

Two-dimensional gel electrophoresis in proteomics: old, old fashioned, but it still climbs up the mountains.

Proteomics has traditionally used the separating power of two-dimensional electrophoresis for the quantitative analysis of protein amounts in complex extracts. However, the limitations of this approach in terms of throughput and analyzable protein range have elicited the development of other proteomics approaches, based either on peptide separations instead of protein separations, or based on direct protein recognition and selection on dedicated arrays (protein chips). These recent methods seem very promising, and probably look more promising than they will ultimately be, just because their weaknesses are not fully characterized yet. The purpose of this paper is thus to highlight the strengths and weaknesses of all the proteomics approaches proposed to date and to try to deduce the respective niches in proteomics that these approaches will have in the future.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2006

Quantitative phosphoproteomic analysis of the tumor necrosis factor pathway.

Protein phosphorylation has become a focus of many proteomic studies due to the central role that it plays in biology. We combine peptide-based gel-free isoelectric focusing and immobilized metal affinity chromatography to enhance the detection of phosphorylation events within complex protein samples using LC-MS. This method is then used to carry out a quantitative phosphoproteomic analysis of the tumor necrosis factor (TNF) pathway using HeLa cells metabolically labeled with 15N-containing amino acids, where 145 phosphorylation sites were found to be up-regulated upon the activation of the TNF pathway.

Chromatography, Affinity↗

PubMedDate not supplied

Shotgun lipidomics: electrospray ionization mass spectrometric analysis and quantitation of cellular lipidomes directly from crude extracts of biological samples.

Lipidomics, after genomics and proteomics, is a newly and rapidly expanding research field that studies cellular lipidomes and the organizational hierarchy of lipid and protein constituents mediating life processes. Lipidomics is greatly facilitated by recent advances in, and novel applications of, electrospray ionization mass spectrometry (ESI/MS). In this review, we will focus on the advances in ESI/MS, which have facilitated the development of shotgun lipidomics and the utility of intrasource separation as an enabling strategy for utilization of 2D mass spectrometry in shotgun lipidomics of biological samples. The principles and experimental details of the intrasource separation approach will be extensively discussed. Other ESI/MS approaches towards the quantitative analyses of global cellular lipidomes directly from crude lipid extracts of biological samples will also be reviewed and compared. Multiple examples of lipidomic analyses from crude lipid extracts employing these approaches will be given to show the power of ESI/MS techniques in lipidomics. Currently, modern society is plagued by the sequelae of lipid-related diseases. It is our hope that the integration of these advances in multiple disciplines will catalyze the development of lipidomics, and such development will lead to improvements in diagnostics and therapeutics, which will ultimately result in the extended longevity and an improved quality of life for humankind.

Animals↗

PubMed2005

Cytokine profile and proteome analysis in bronchoalveolar lavage of patients with sarcoidosis, pulmonary fibrosis associated with systemic sclerosis and idiopathic pulmonary fibrosis.

The aim of this study was to analyze the type of immune response (Th1, Th2) and protein composition of bronchoalveolar lavage (BAL) of patients with sarcoidosis, pulmonary fibrosis associated with systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF). Flow cytometry analysis of intracellular cytokines revealed different patterns: in IPF and SSc Th2 profiles were predominant, whereas in sarcoidosis Th1 prevailed. The proteomic analysis of BAL fluid (BALF) showed that there were quantitative differences between the three diseases. These were more evident between sarcoidosis and IPF, confirming our previous observations, whereas SSc had an intermediate profile between the two, however with some peculiarities. Comparison of BALF protein maps, constructed with the same quantity of total proteins, enabled us to identify the main profiles of the three diseases: an increase in plasma protein prevalent in sarcoidosis and also present in SSc, though for fewer proteins with respect to IPF and a greater abundance of low molecular weight proteins, mainly locally produced, in IPF. These findings are in line with the different pathogenesis of these diseases: IPF is considered a prevalently fibrotic disorder limited to the lung, with intense local production of functionally different proteins, whereas sarcoidosis and SSc are systemic immunoinflammatory diseases.

Adult↗

PubMed2005

The application of proteomics to diabetes.

Poteomics is the investigation of all the proteins and their various modifications making up a system, be that a cell, tissue or organism. The techniques involved in proteomics allow the global screening of complex samples of proteins and provide qualitative and quantitative evidence of altered protein expression. This lends itself to the investigation of the molecular mechanisms underpinning disease processes and the effects of treatment. This review describes the main techniques of proteomics and how they have begun to be applied to diabetes research.

Adipose Tissue↗

PubMed2026

Quantitative interactome mapping of skeletal muscle insulin resistance.

Protein-protein interactions (PPIs) are dynamic and critical to adaptive homeostasis. While there have been massive efforts to catalogue proteome-wide PPIs, global quantification of changes remains a challenge. Here, we integrate dynamic protein correlation profiling - mass spectrometry (PCP-MS) and quantitative cross linking-mass spectrometry (qXL-MS) using multiplexed stable isotope labelling to characterise global PPI remodelling following the development of chronic skeletal muscle insulin resistance (IR) with or without acute insulin stimulation. We quantify >7,000 unique PPIs amongst 5,346 proteins and show changes in the interactome network dominate the proteome response. Our data show the dysregulation of protein processing in the endoplasmic/sarcoplasmic reticulum involving changes in PPIs with protein chaperones and disulfide isomerases is a major hallmark of skeletal muscle IR. Mechanistically, we show the dysregulation of PPIs with Protein-Disulfide Isomerase 6 (PDIA6) regulates cysteine oxidation and insulin sensitivity. Taken together, we show in vivo quantitative interactome mapping is a powerful approach to understand disease mechanisms and provide new insights into protein network re-organisations with IR.

Insulin Resistance↗

PubMed2002

New tools for quantitative phosphoproteome analysis.

Recent advances in analytical methods, particularly in the area of mass spectrometry, have brought the field of proteomics to the forefront in biological science. The ultimate goal of proteomics--to characterize proteins expressed within a cell under a specific set of conditions--is daunting due to the complexity and dynamic nature the of protein population within the cell. While much of the effort has focused on developing methods to identify expressed proteins, the identification of posttranslational modifications is equally important for comprehensive proteome characterization. Of all the known posttranslational modifications, phosphorylation arguably plays the largest role in the context of cellular homeostasis. This review discusses some of the recent progress made in the development of techniques not only to identify, but also to quantitatively determine sites of phosphorylation.

Animals↗

PubMed2024

Proteome analysis provides insights into sex differences in Holothuria Scabra.

Sex-determining mechanism is still ambiguous for sea cucumber Holothuria scabra which only manifests gonochorism in gonad. In this study, proteomic analysis was employed to delineate sex-related proteins and genes in gonads of H. scabra, subsequently validated through Quantitative real-time polymerase chain reaction (qRT-PCR). A total of 5,313 proteins were identified via proteome sequencing. Among these, 817 proteins exhibited expression in both the ovary and testis, with 445 proteins displaying up-regulation and 372 proteins showing down-regulation (ovary vs testis). Furthermore, 136 and 69 proteins were identified as ovary-specific and testis-specific Differentially Abundant Proteins (DAPs), respectively. And 9 DAP coding genes which play crucial role in ovary and testis were verified by qRT-PCR. Notably, 24 ovary-bias proteins enriched in ribosome pathway strongly indicated the crucial role of ribosome in ovary. This study serves to furnish novel evidence pertaining to sex differences in H. scabra.

Animals↗

PubMed1999

Biosequence exegesis.

Annotation of large-scale gene sequence data will benefit from comprehensive and consistent application of well-documented, standard analysis methods and from progressive and vigilant efforts to ensure quality and utility and to keep the annotation up to date. However, it is imperative to learn how to apply information derived from functional genomics and proteomics technologies to conceptualize and explain the behaviors of biological systems. Quantitative and dynamical models of systems behaviors will supersede the limited and static forms of single-gene annotation that are now the norm. Molecular biological epistemology will increasingly encompass both teleological and causal explanations.

Animals↗

PubMedDate not supplied

Investigation of the mouse serum proteome.

With the rapid assimilation of genomic information and the equally impressive developments in the field of proteomics, there is an unprecedented interest in biomarker discovery. Although human biofluids represent increasingly attractive samples from which new and more accurate disease biomarkers may be found, the intrinsic person-to-person variability in these samples complicates their discovery. One of the most extensively used animal models for studying human disease is mouse because, unlike humans, they represent a highly controllable experimental model system. Unfortunately, very little is known about the proteomic composition of mouse serum. In this study, a multidimensional fractionation approach on both the protein and the peptide level that does not require depletion of highly abundant serum proteins was combined with tandem mass spectrometry to characterize proteins within mouse serum. Over 12 300 unique peptides that originate from 4567 unique proteins-approximately 16% of all known mouse proteins-were identified. The results presented here represent the broadest proteome coverage in mouse serum and provide a foundation from which quantitative comparisons can be made in this important animal model.

Amino Acid Sequence↗

PubMedDate not supplied

On the dependence of a characterization of proteomics maps on the number of protein spots considered.

We have reexamined the numerical characterization of proteomics maps based on the construction of novel distance matrices associated with the nearest neighbor graph for the protein spots. In particular we consider dependence of a characterization of proteomics map on the number of proteins considered in the analysis. We examined a collection of proteomics maps in which we approximately doubled the number of spots to be used for quantitative analysis, considering cases of maps having 30, 50, 100, 250, 500, and 1054 protein spots. For each case we have compared the similarity-dissimilarity results for five proteomics maps of rat liver cells associated with the control group and four proliferators administrated by intraperitoneal injection. We found that proteins maps based on a set of about the 250 most abundant proteins spots suffice for a satisfactory numerical characterization of such maps.

Animals↗

PubMed2007

Surface-plasmon-resonance-based chemical proteomics: efficient specific extraction and semiquantitative identification of cyclic nucleotide-binding proteins from cellular lysates by using a combination of surface plasmon resonance, sequential elution and liquid chromatography-tandem mass spectrometry.

Chemical proteomics is a powerful methodology for identifying the cellular targets of small molecules, however, it is biased towards abundant proteins. Therefore, quantitative strategies are needed to distinguish between specific and nonspecific interactions. Here, we explore the potential of the combination of surface plasmon resonance (SPR) coupled to liquid chromatography-tandem mass spectrometry (LC-MS/MS) as an alternative approach in chemical proteomics. We coupled cGMP molecules to the SPR chip, and monitored the binding and dissociation of proteins from a human lysate by using sequential elution steps and SPR. The eluted proteins were subsequently identified by LC-MS/MS. Our approach enabled the efficient and selective extraction of low-abundant cyclic-nucleotide-binding proteins such as cGMP-dependent protein kinase, and a quantitative assessment of the less- and nonspecific competitive binding proteins. The data show that SPR-based chemical proteomics is a promising alternative for the efficient specific extraction and quantitative identification of small-molecule-binding proteins from complex mixtures.

Cell Line↗