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PubMed2006

Rat plasma proteomics: effects of abundant protein depletion on proteomic analysis.

The proteomic analysis of plasma and serum samples represents a formidable challenge due to the presence of a few highly abundant proteins such as albumin and immunoglobulins. Detection of low abundance protein biomarkers requires therefore either the specific depletion of high abundance proteins with immunoaffinity columns and/or optimized protein fractionation methods based on charge, size or hydrophobicity. Here we describe the depletion of seven abundant rat plasma proteins with an immunoaffinity column with coupled antibodies directed against albumin, IgG, transferrin, IgM, haptoglobin, fibrinogen and alpha1-anti-trypsin. The IgY-R7-LC2 (Beckman Coulter) column showed high specificity for the targeted proteins and was able to efficiently remove most of the albumin, IgG and transferrin from rat plasma samples as judged by Western blot analysis. Depleted rat plasma protein samples were analyzed by SELDI-TOF MS, 2D SDS-PAGE and 2D-LC and compared to non-depleted plasma samples as well as to the abundant protein fraction that was eluted from the immunoaffinity column. Analysis of the depleted plasma protein fraction revealed improved signal to noise ratios, regardless of which proteomic method was applied. However, only a small number of new proteins were observed in the depleted protein fraction. Immunoaffinity depletion of abundant plasma proteins results in the significant dilution of the original sample which complicates subsequent analysis. Most proteomic approaches require specialized sample preparation procedures during which significant losses of less abundant proteins and potential biomarkers can occur. Even though abundant protein depletion reduces the dynamic range of the plasma proteome by about 2-3 orders of magnitude, the difference between medium-abundant and low abundant plasma proteins is still in the range of 7-8 orders of magnitude and beyond the dynamic range of current proteomic technologies. Thus, exploring the plasma proteome in greater detail remains a daunting task.

Animals↗
PubMed2003

Proteome analysis of Epstein-Barr virus-transformed B-lymphoblasts and the proteome database.

The proteome is the entire protein complement of the genome expressed in a particular cell, tissue, or organism at a given time under a specific set of environmental conditions. Proteomics is a combinatorial methodology to comprehensively analyze the proteome. The general protocol of the expression proteomics consists of advanced methods of high-resolution protein separation, high-quality image analysis and high-throughput protein identification. Although Epstein-Barr virus-transformed B-lymphoblastoid cell lines (LCLs) have long been believed to be immortalized, recent studies have provided ample evidence that a large proportion of LCLs have limited life spans due to shortening of telomeres, and that part of them are truly immortalized by developing strong telomerase activity to maintain telomeres. Differential proteome analysis of pre- and post-immortal LCLs would provide a powerful tool to analyze proteins participating in the process of immortalization. We focus in this review on cumulative data of proteomic information on pre- and post-immortal LCLs.

B-Lymphocytes↗
PubMed2006

Toward the complete yeast mitochondrial proteome: multidimensional separation techniques for mitochondrial proteomics.

Proteomic analyses of different subcellular compartments, so-called organellar proteomics, facilitate the understanding of cellular functions on a molecular level. In this work, various orthogonal multidimensional separation techniques both on the protein and on the peptide level are compared with regard to the number of identified proteins as well as the classes of proteins accessible by the respective methodology. The most complete overview was achieved by a combination of such orthogonal techniques as shown by the analysis of the yeast mitochondrial proteome. A total of 851 different proteins (PROMITO dataset) were identified by use of multidimensional LC-MS/MS, 1D-SDS-PAGE combined with nano-LC-MS/MS and 2D-PAGE with subsequent MALDI-mass fingerprinting. Our PROMITO approach identified the 749 proteins, which were found in the largest previous study on the yeast mitochondrial proteome, and additionally 102 proteins including 42 open reading frames with unknown function, providing the basis for a more detailed elucidation of mitochondrial processes. Comparison of the different approaches emphasizes a bias of 2D-PAGE against proteins with very high isoelectric points as well as large and hydrophobic proteins, which can be accessed more appropriately by the other methods. While 2D-PAGE has advantages in the possible separation of protein isoforms and quantitative differential profiling, 1D-SDS-PAGE with nano-LC-MS/MS and multidimensional LC-MS/MS are better suited for efficient protein identification as they are less biased against distinct classes of proteins. Thus, comprehensive proteome analyses can only be realized by a combination of such orthogonal approaches, leading to the largest dataset available for the mitochondrial proteome of yeast.

Mitochondrial Proteins↗
PubMed2006

Arabidopsis thaliana proteomics: from proteome to genome.

Proteomics has become an important approach for investigating cellular processes and network functions. Significant improvements have been made during the last few years in technologies for high-throughput proteomics, both at the level of data analysis software and mass spectrometry hardware. As proteomics technologies advance and become more widely accessible, efforts of cataloguing and quantifying full proteomes are underway to complement other genomics approaches, such as RNA and metabolite profiling. Of particular interest is the application of proteome data to improve genome annotation and to include information on post-translational protein modifications with the annotation of the corresponding gene. This type of analysis requires a paradigm shift because amino acid sequences must be assigned to peptides without relying on existing protein databases. In this review, advances and current limitations of full proteome analysis are briefly highlighted using the model plant Arabidopsis thaliana as an example. Strategies to identify peptides are also discussed on the basis of MS/MS data in a protein database-independent approach.

Arabidopsis↗
PubMed2003

The Proteome Analysis database: a tool for the in silico analysis of whole proteomes.

The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Animals↗
PubMed2003

Comprehensive proteomic profiling identifies serum proteomic signatures for detection of hepatocellular carcinoma and its subtypes.

BACKGROUND: Detection of hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD) is difficult. We investigated the use of comprehensive proteomic profiling of sera to differentiate HCC from CLD. METHODS: Proteomes in sera from 20 CLD patients with alpha-fetoprotein (AFP) <500 microg/L (control group) and 38 HCC patients (disease group) were profiled by anion-exchange fractionation (first dimension), two types (IMAC3 copper and WCX2) of ProteinChip Arrays (second dimension), and time-of-flight mass spectrometry (third dimension). Bioinformatic tests were used to identify tumor-specific proteomic features and to estimate the values of the tumor-specific proteomic features in the diagnosis of HCC. Cross-validation was performed, and we also validated the models with pooled sera from the control and disease groups, serum from a CLD patient with AFP >500 microg/L, and postoperative sera from two HCC patients. RESULTS: Among 2384 common serum proteomic features, 250 were significantly different between the HCC and CLD cases. Two-way hierarchical clustering differentiated HCC and CLD cases. Most HCC cases with advanced disease were clustered together and formed two subgroups that contained significantly more cases with lymph node invasion or distant metastasis. For differentiation of HCC and CLD by an artificial network (ANN), the area under the ROC curve was 0.91 (95% confidence interval, 0.82-1.01; P <0.0005) for all cases and 0.954 (95% confidence interval, 0.881-1.027; P <0.0005) for cases with nondiagnostic serum AFP (<500 microg/L). At a specificity of 90%, the sensitivity was 92%. Both cluster analysis and ANN correctly classified the pooled serum samples, the CLD serum sample with increased AFP, and the HCC patient in complete remission. CONCLUSION: Tumor-specific proteomic signatures may be useful for detection and classification of hepatocellular cancers.

Carcinoma, Hepatocellular↗
PubMed2003

In silico proteome analysis to facilitate proteomics experiments using mass spectrometry.

Proteomics experiments typically involve protein or peptide separation steps coupled to the identification of many hundreds to thousands of peptides by mass spectrometry. Development of methodology and instrumentation in this field is proceeding rapidly, and effective software is needed to link the different stages of proteomic analysis. We have developed an application, proteogest, written in Perl that generates descriptive and statistical analyses of the biophysical properties of multiple (e.g. thousands) protein sequences submitted by the user, for instance protein sequences inferred from the complete genome sequence of a model organism. The application also carries out in silico proteolytic digestion of the submitted proteomes, or subsets thereof, and the distribution of biophysical properties of the resulting peptides is presented. proteogest is customizable, the user being able to select many options, for instance the cleavage pattern of the digestion treatment or the presence of modifications to specific amino acid residues. We show how proteogest can be used to compare the proteomes and digested proteome products of model organisms, to examine the added complexity generated by modification of residues, and to facilitate the design of proteomics experiments for optimal representation of component proteins.

Journal Article↗
PubMed2004

Vascular proteomics: linking proteomic and metabolomic changes.

Cardiovascular diseases constitute the largest of death in the Western world. Various stressors, including elevated blood pressure, smoking, diabetes, and hypercholesterolemia directly or indirectly damage the vessel wall, eventually inducing arterial stiffness (arteriosclerosis) and lipid accumulation (atherosclerosis). However, the molecular mechanisms of atheroma formation are not yet fully clarified. While many investigators have used proteomic techniques to study cardiac diseases, vascular proteomics is still in its infancy. The present review highlights studies, in which proteomics has been successfully applied to study protein alterations in the vasculature. Furthermore, we will summarize our recent progress in combining proteomic and metabolomic techniques to reveal protein and metabolite alterations in the cardiovascular system: two-dimensional (2-D) gel electrophoresis proved to be highly complementary to nuclear magnetic resonance (NMR) spectroscopy, in that post-translational modifications of the most abundant enzymes were displayed on 2-D gels while NMR spectroscopy revealed changes in the corresponding metabolites. Importantly, the simultaneous assessment of protein and metabolite changes translated purely descriptive proteomic and metabolomic profiles into a functional context and provided important insights into pathophysiological mechanisms that would not have been obtained by other techniques.

Animals↗
PubMed2005

SPS' Digest: the Swiss Proteomics Society selection of proteomics articles.

Despite the consolidation of the specialized proteomics literature around a few established journals, such as Proteomics, Molecular and Cellular Proteomics, and the Journal of Proteome Research, a lot of information is still spread in many different publications from different fields, such as analytical sciences, MS, bioinformatics, etc. The purpose of SPS' Digest is to gather a selection of proteomics articles, to categorize them, and to make the list available on a periodic basis through a web page and email alerts.

Animals↗
PubMed2006

Gel-free mass spectrometry-based high throughput proteomics: tools for studying biological response of proteins and proteomes.

Revolutionary advances in biological mass spectrometry (MS) have provided a basic tool to make possible comprehensive proteomic analysis. Traditionally, two-dimensional gel electrophoresis has been used as a separation method coupled with MS to facilitate analysis of complex protein mixtures. Despite the utility of this method, the many challenges of comprehensive proteomic analysis has motivated the development of gel-free MS-based strategies to obtain information not accessible using two-dimensional gel separations. These advanced strategies have enabled researchers to dig deeper into complex proteomes, gaining insights into the composition, quantitative response, covalent modifications and macromolecular interactions of proteins that collectively drive cellular function. This review describes the current state of gel-free, high throughput proteomic strategies using MS, including (i) the separation approaches commonly used for complex mixture analysis; (ii) strategies for large-scale quantitative analysis; (iii) analysis of post-translational modifications; and (iv) recent advances and future directions. The use of these strategies to make new discoveries at the proteome level into the effects of disease or other cellular perturbations is discussed in a variety of contexts, providing information on the potential of these tools in electromagnetic field research.

Animals↗
PubMed2005

System, trends and perspectives of proteomics in dicot plants Part II: Proteomes of the complex developmental stages.

This review is devoted to the proteomes of the complex developmental stages of dicotyledoneous (dicot) plant materials. The two core technologies, two-dimensional gel electrophoresis (2-DGE) and mass spectrometry (MS), independently or in combination with each other, are propelling dicot plant proteomics to new discoveries and functions, with the establishment of tissue-specific and organelle proteomes, mostly in Arabidopsis thaliana and Medicago truncatula, revealing their complexity and specificity. These experimental proteomes have provided a good start towards the establishment of high-density 2-DGE reference maps and peptide mass fingerprint databases, for not only the model dicot plants, A. thaliana and M. truncatula, but also other important dicot plants, which will serve as a basis for proteomes of many other dicot plants and plant materials.

Arabidopsis↗
PubMed2006

Complex graph matrix representations and characterizations of proteomic maps and chemically induced changes to proteomes.

We have presented a complex graph matrix representation to characterize proteomics maps obtained from 2D-gel electrophoresis. In this method, each bubble in a 2D-gel proteomics map is represented by a complex number with components which are charge and mass. Then, a graph with complex weights is constructed by connecting the vertices in the relative order of abundance. This yields adjacency matrices and distance matrices of the proteomics graph with complex weights. We have computed the spectra, eigenvectors, and other properties of complex graphs and the Euclidian/graph distance obtained from the complex graphs. The leading eigenvalues and eigenvectors and, likewise, the smallest eigenvalues and eigenvectors, and the entire graph spectral patterns of the complex matrices derived from them yield novel weighted biodescriptors that characterize proteomics maps with information of charge and masses of proteins. We have also applied these eigenvector and eigenvalue maps to contrast the normal cells and cells exposed to four peroxisome proliferators, namely, clofibrate, diethylhexyl phthalate (DEHP), perfluorodecanoic acid (PFDA), and perfluoroctanoic acid (PFOA). Our complex eigenspectra show that the proteomic response induced by DEHP differs from the corresponding responses of other three chemicals consistent with their chemical structures and properties.

Algorithms↗
PubMed2026

Quantitative proteomics reveals coordinated changes in the proteome during replicative senescence.

Cellular senescence is a state of irreversible cell cycle arrest triggered by telomere erosion, persistent DNA damage or chronic stress. The accumulation of senescent cells disrupts tissue function and contributes to aging and disease. Here, we employ mass spectrometry-based proteomics to systematically interrogate dynamic proteome changes at multiple levels during the progression of replicative cellular senescence. We demonstrate that proteome changes during senescence occur in a coordinated manner, characterized by widespread protein depletion on chromatin. Moreover, components of the cytoplasmic translation machinery are depleted, while mitochondrial proteins display increased insolubility. Autophagic and proteasome activity is compromised in senescent cells along with remodeling of ubiquitin linkages and depletion of ubiquitin E3 ligases. Comparison of the senescent proteome with different pathophysiological cellular states reveals a distinctive senescent signature shaped by changes in the proteostasis network. Collectively, we provide a resource for the exploration of temporally resolved changes in the senescent proteome.

Cellular Senescence↗
PubMed2006

A proteome reference map and proteomic analysis of Bifidobacterium longum NCC2705.

A comprehensive proteomic study was carried out to identify and characterize proteins expressed by Bifidobacterium longum NCC2705. A total of 708 spots representing 369 protein entries were identified by MALDI-TOF-MS and/or ESI-MS/MS. Isoelectric point values estimated by gel electrophoresis matched closely with their predicted ones, although some discrepancies exist suggesting that post-translational protein modifications might be common in B. longum. The identified proteins represent 21.4% of the predicted 1727 ORFs in the genome and correspond to 30% of the predicted proteome. Moreover 95 hypothetical proteins were experimentally identified. This is the first compilation of a proteomic reference map for the important probiotic organism B. longum NCC2705. The study aimed to define a number of cellular pathways related to important physiological processes at the proteomic level. Proteomic comparison of glucose- and fructose-grown cells revealed that fructose and glucose are catabolized via the same degradation pathway. Interestingly the sugar-binding protein specific to fructose (BL0033) and Frk showed higher levels of expression in cells grown on fructose than on glucose as determined by semiquantitative RT-PCR. BL0033 time course and concentration experiments showed that the induction time and fructose concentration correlates to increased expression of BL0033. At the same time, an ABC (ATP-binding cassette) transporter ATP-binding protein (BL0034) was slightly up-regulated in cells grown on fructose compared with glucose. All of the above results suggest that the uptake of fructose into the cell may be conducted by a specific transport system in which BL0033 might play an important role.

ATP-Binding Cassette Transporters↗
PubMed2005

DynaProt 2D: an advanced proteomic database for dynamic online access to proteomes and two-dimensional electrophoresis gels.

DynaProt 2D presents an advanced online database for dynamic access to proteomes and two-dimensional (2D) gels. The database was designed to administer complete in silico proteomes and links them with experimental proteomic data in the manner of 2D electrophoresis gels (IPG-Dalt). The 2D gels serve as reference maps in 2D gel analysis as well as tools for navigation of the database to switch between experimental and predicted data. Therefore, all identified spots in the gels are clickable and linked with summarized protein information. The protein information tables contain calculated characteristics, which are often used in proteomics, such as the molecular weight, isoelectric point, codon adaptation index, grand average of hydropathicity, etc. The design of the database permits online extension of gel data and protein attributes without knowledge of any software language. Besides navigation via 2D gels, the clear graphical user interface permits quick and intuitive searching throughout complete proteomes and supports, e.g. the search for proteins with isoelectric points within pH ranges of interest or protein classes (e.g. ribosomal proteins or transporters). The first organism implemented in the database is Lactococcus lactis. The database is available at www.wzw.tum.de/proteomik/lactis.

Bacterial Proteins↗
PubMed2005

[Project on disease-related proteomics and a proteome factory for drug innovation].

The proteome is expected to be thoroughly researched in Post Genome Projects following the completion of the Human Genome Sequencing Project. Many research projects to investigate disease-related proteins are being undertaken worldwide. Analysis of the proteome, which has an intimate involvement in biogenics, should provide a breakthrough in vital activity and provide substantial clues for new treatments, diagnoses and new target of drugs. In the 2003 fiscal year, The Ministry of Health, Labour and Welfare (MHLW) started the Health, Labour and Welfare Scientific Research Founding Program "Disease Related Proteomics". At the time, the Japan Health Sciences Foundation was delegated the project from MHLW, along with the Japan Pharmaceutical Manufactures Association, and established a consortium with 22 pharmaceutical companies for this project, collaborating with the National Institute of Health Science to start the Project on Disease Related Proteomics and a Proteome Factory for Drug Innovation. In this report, the project overview and its facilities will be introduced.

Databases, Protein↗
PubMed2026

Spatial Proteomics of the Human Atherosclerotic Microenvironment Reveals Heterogeneity in Intraplaque Proteomes and Extracellular Matrix Remodeling.

Plaque heterogeneity underlies the propensity of atherosclerotic lesions to rupture and trigger cardiovascular events. Most proteomic studies examine bulk changes, obscuring key spatial differences in protein abundance. We report a high-resolution spatial proteomics workflow exploring the molecular landscape of human plaques and a murine myocardium. By combining laser capture microdissection with high-sensitivity ion-mobility mass spectrometry, spatial profiling of cellular and extracellular matrix (ECM) proteomes was achieved. Over 2700 proteins were detected from 50,000 &#x3bc;m2 areas, revealing substantial intraplaque heterogeneity across distinct regions (lipid-rich, media, shoulder, necrotic core, intima) and distance from the artery lumen. Inverse correlations between proteases (cathepsin B) and core structural ECM proteins (perlecan, HSPG2) indicated active ECM remodeling. Analysis of media layers indicated distinct protein signatures associated with smooth muscle contraction and cell-cell communication. Blood coagulation signatures, including platelet degranulation and fibrin formation, were enriched at the intima. Inflammatory (clusters of differentiation 4/68, CD4/CD68; vascular cell adhesion molecule 1, VCAM1) and vascular damage markers (tenascin-C, TNC) were enriched in shoulder regions. The necrotic core was dominated by blood proteins, consistent with intraplaque hemorrhage. This workflow resolves proteomic changes over &#x223c;200 &#x3bc;m distances, providing unprecedented insights into plaque morphology and offers a powerful tool for elucidating plaque biology.

Humans↗
PubMed2000

Proteomics meets cell biology: the establishment of subcellular proteomes.

Proteome research aims to unravel the biological complexity encoded by the genome. Due to the complexity of higher eukaryotic cells, single-step characterization of a proteome is likely to be difficult to achieve. However, advantage can be taken of the macromolecular architecture of a cell, e.g., subcellular compartments, organelles, macromolecular structures and multiprotein complexes, to establish subcellular proteomes. This review highlights recent developments in this area of proteomics, namely the establishment of two-dimensional electrophoresis (2-DE) reference maps of subcellular compartments and organelles as well as the characterization of macromolecular structures and multiprotein complexes using a proteomics approach.

Proteome↗