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At least 19 recordsLinked to original sources

Establishment of a near-standard two-dimensional human urine proteomic map.

A proteomic map for human urine on two-dimensional (2-D) gels has been developed. Initial studies demonstrated that the urine proteins prepared by conventional methods showed interference and poor reproducibility in 2-D electrophoresis (2-DE). To address this issue, urine samples were dialyzed to remove any interfering molecules. The dialysis of urine proteins and the concentration by lyophilization without fractionation significantly improved the reproducibility and resolution and likely represents the total urine proteins on a 2-D gel. In addition, removing albumin from urine using Affi-Gel Blue helped to identify the low-abundant proteins. Using the developed method, we prepared proteins from urine collected from healthy females and males. The large inter- and intra-subject variation in protein profiles on 2-D gels made it difficult to establish a normal human urine proteomic 2-D map. To resolve this problem, urinary proteins were prepared from the pooled urine collected from 20 healthy females and males, respectively. The established male and female urine proteomes separated on 2-D gels were almost identical except for some potential sex-dependent protein spots. We have annotated 113 different proteins on the 2-D gel by peptide mass fingerprinting (PMF). We propose that the established total urine proteome can be used for 2-DE analysis, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and identification of novel disease-specific biomarkers.

Albumins↗

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↗

Novel map descriptors for characterization of toxic effects in proteomics maps.

We consider a novel numerical characterization of proteomics maps based on the construction of a graph obtained by connecting all protein spots in a proteomics map that are at distance equal to, or smaller than, a critical distance D(c). We refer to the so constructed graph as a cluster graph and we calculate four associated characteristic matrices, previously considered in the literature: (1) the Euclidean-distance matrix ED; (2) the neighborhood-distance matrix ND; (3) the path-distance matrix based on the shortest paths between connected spots PD; and (4) the quotient matrix Q, the elements of which are given as the quotient of the corresponding elements of ED and ND matrices. Numerical descriptors for proteomics maps include in particular the leading eigenvalue of the Q matrix and the family of associated "higher order" matrices defined as powers of Q. These map descriptors show considerable sensitivity to perturbations of proteomics maps by toxicants.

Animals↗

[Construction of a proteomic map database].

The first proteomic map database of China will be published by Bioinformation Center and Research Center of Proteomics, Shanghai Institutes for Biological Sciences, the Chinese Academy of Sciences.The database consists of physical layer, link layer and interfacial layer. As Java technique was introduced to construct the database system, the database does not depend on special working platform. With the search instruments users can easily look through the proteomic map and get concrete information of proteins they are interested in.

China↗

LMPD: LIPID MAPS proteome database.

The LIPID MAPS Proteome Database (LMPD) is an object-relational database of lipid-associated protein sequences and annotations. The initial release contains 2959 records, representing human and mouse proteins involved in lipid metabolism. UniProt IDs were obtained based on keyword search of KEGG and GO databases, and this LMPD protein list was then enhanced with annotations from UniProt, EntrezGene, ENZYME, GO, KEGG and other public resources. We also assigned associations with general lipid categories, based on GO and KEGG annotations. Users may search LMPD by database ID or keyword, and filter by species and/or lipid class associations; from the search results, one can then access a compilation of data relevant to each protein of interest, cross-linked to external databases. The LIPID MAPS Proteome Database (LMPD) is publicly available from the LIPID MAPS Consortium website (http://www.lipidmaps.org/). The direct URL is http://www.lipidmaps.org/data/proteome/index.cgi.

Animals↗

Towards a two-dimensional proteome map of Mycoplasma pneumoniae.

A Proteome map of the bacterium Mycoplasma pneumoniae was constructed using two-dimensional (2-D) gel electrophoresis in combination with mass spectrometry (MS). M. pneumoniae is a human pathogen with a known genome sequence of 816 kbp coding for only 688 open reading frames, and is therefore an ideal model system to explore the scope and limits of the current technology. The soluble protein content of this bacterium grown under standard laboratory conditions was separated by 1-D or 2-D gel electrophoresis applying various pH gradients, different acrylamide concentrations and buffer systems. Proteins were identified using liquid chromatography-electrospray ionization ion trap and matrix-assisted laser desorption/ionization-MS. Mass spectrometric protein identification was supported and controlled using N-terminal sequencing and immunological methods. So far, proteins from about 350 spots were characterized with MS by determining the molecular weights and partial sequences of their tryptic peptides. Comparing these experimental data with the DNA sequence-derived predictions it was possible to assign these 350 proteins to 224 genes. The importance of proteomics for genome analysis was shown by the identification of four proteins, not annotated in the original publication. Although the proteome map is still incomplete, it is already a useful reference for comparative analyses of M. pneumoniae cells grown under modified conditions.

Acrylic Resins↗

Canonical labeling of proteome maps.

We propose a canonical labeling of proteome maps, which enables one to sort and catalog the maps in a simple way. The canonical label of a proteome map is based on the canonical labeling of vertexes of Hasse diagram embedded in the map resulting in the adjacency matrix, the rows of which when viewed as binary numbers are the smallest possible such numbers. The use of the approach in documentation is illustrated with the proteome maps of liver cells of healthy male Fisher F344 rats and the rats treated with different peroxisome proliferators.

Algorithms↗

Novel matrix invariants for characterization of changes of proteomics maps.

Previous studies on mathematical characterization of proteomics maps by sets of map invariants were based on the construction of a set of distance-related matrices obtained by matrix multiplication of a single matrix by itself. Here we consider an alternative characterization of proteomics maps based on a set of matrices characterizing local features of an embedded zigzag curve over the map. It is shown that novel invariants can well characterize proteomics maps. Advantages of the novel approach are discussed.

Models, Theoretical↗

On 3-D graphical representation of proteomics maps and their numerical characterization.

We consider numerical characterization of proteomics maps by representing a map as a three-dimensional graphical object based on x, y coordinates of the spots and using their relative abundance as the z coordinate. In our representation the protein spots are first ordered based on their relative abundance and labeled accordingly. In the next step a 3-D path is constructed connecting spots having adjacent labels. Finally a matrix is constructed by assigning to each pairs of labels (i, j) matrix element, the numerical value of which is based on the quotients of the Euclidean distance and the distance along the 3-D zigzag between the two points. The approach has been illustrated on a fragment of a proteomics map and compared with 2-D graphical representation of proteomics maps.

Computer Graphics↗

On characterization of dose variations of 2-D proteomics maps by matrix invariants.

We explore the characterization of 2-D electrophoresis proteomics maps by certain structural invariants derived from matrixes constructed by considering for all pairs of spots in a proteomics maps the shortest (Euclidean) distances and distances measured along zigzag lines connecting protein spots of the neighboring abundance. This paper is a sequel to previous papers in which we outlined the idea of characterizing 2-D proteomics maps by graph-theoretical descriptors. To illustrate the approach, we selected data of Anderson et al. (Anderson, N. L.; Esquer-Blasco, R.; Richardson, F.; Foxworthy, P.; Eacho, P. The effects of peroxisome proliferators on protein abundances in mouse liver. Toxicol. Appl. Pharmacol. 1996, 137, 75-89) on protein abundance in mouse liver under a series of dose of peroxisome proliferator LY1711883. We found strong linear correlation between the experimentally applied doses and the leading eigenvalue of a D/D-type matrix (Randić, M.; Kleiner, A. F.; DeAlba, L. M. Distance/ distance matrices. J. Chem. lnf. Comput. Sci. 1994, 34, 277-286) constructed for the experimental proteomics maps.

Acetophenones↗

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↗

Proteomic mapping provides powerful insights into functional myelin biology.

Myelin is a dynamic, functionally active membrane necessary for rapid action potential conduction, axon survival, and cytoarchitecture. The number of debilitating neurological disorders that occur when myelin is disrupted emphasizes its importance. Using high-resolution 2D gel electrophoresis, mass spectrometry, and immunoblotting, we have developed an extensive proteomic map of proteins present in myelin, identifying 98 proteins corresponding to at least 130 of the approximately 200 spots on the map. This proteomic map has been applied to analyses of the localization and function of selected proteins, providing a powerful tool to investigate the diverse functions of myelin.

Animals↗

Novel characterization of proteomics maps by sequential neighborhoods of protein spots.

We consider a characterization of proteomics maps based on an alternative kind of neighborhood graphs for the protein spots on 2-D gel. The novel approach considers for every protein spot only the nearest neighborhood consisting of protein spots of higher abundance. The approach has the simplicity and advantages of the recently introduced characterization of proteome maps based on considering the nearest neighborhoods of protein spots, but it also has important additional desirable computational features. The characterization of the nearest neighborhood graphs of 2-D gel proteomics maps is sensitive to the number of spots considered and may lead to changes in the degree of similarity of different maps when the number of points has been changed, thus imposing restrictions on the protocol used for comparison of maps. The novel approach presented in this work is less sensitive to the number of points used in the analysis because graphs are constructed in a stepwise process in which the role of more distant neighbors has been diminished by linking a new spot to the nearest spot that has been already part of the neighborhood graph. In this way a graph with N + 1 spots is obtained from the graph on N spots by adding a single new link, while in the case of the nearest neighborhood graphs adding a new spot introduces novel neighborhoods and generally results in a graph that may differ significantly from the neighborhood graph on N points.

Animals↗

The human platelet proteome mapped by peptide-centric proteomics: a functional protein profile.

Several studies have been published in which holistic approaches were used to characterise the proteome and transcriptome of human platelets. The key intent being that a deeper understanding of the normal and aberrant physiological functions of platelets can only be achieved if most biomolecular building blocks are mapped. Here we present the application of recently developed novel technologies that overcome some of the shortcomings of gel-based proteomics. Central in our approach is the so-called combined fractional diagonal chromatography (COFRADIC)-technology in which sets of representative peptides are sorted in a diagonal RP chromatographic system through a specific modification of their side chain. In this study we combined three different COFRADIC sorting techniques to analyse the proteome of human platelets. Methionyl, cysteinyl and amino terminal peptides were isolated and analysed by MS/MS. Merging the peptide identifications obtained after database searching resulted in a core set of 641 platelet proteins, which comprises the largest set identified today. In comparison to previously published platelet proteomes, we identified 404 novel platelet proteins containing a high number of hydrophobic membrane proteins and hypothetical proteins. Furthermore we discuss the observed characteristics and potential benefits of each of the different COFRADIC technologies for proteome analysis and highlight important issues that need to be considered when searching sequence databases using data obtained in peptide-centric, non-gel proteomics studies.

Animals↗

A comparative study of proteomics maps using graph theoretical biodescriptors.

This paper reports the development of new methods for mathematical characterization of effects of different toxic agents on the cellular proteome. We describe numerical characterization of proteomics maps based on mathematical invariants. A graph is first associated with a proteomics map by considering partial ordering of spots on 2-D gels by ordering proteins with respect to the mass and the charge, the two properties by which proteins are separated. The graph is then embedded over the map, and several graph theoretical invariants have been constructed. In particular we consider invariants that can be extracted from the Euclidean distance-adjacency matrix of the embedded graph, in which only Euclidean distances between adjacent vertices of a graph are considered. The approach is illustrated using proteomics patterns of normal liver cells of rats and those derived from liver cells of animals exposed to four peroxisome proliferators. In contrast to direct comparison of spot abundance our approach incorporates information on spots locations. The difference between the two approaches is that in the first case only changes in abundances are considered as a measure of perturbation of the proteome map, but in the second case not only the charge but also the mass of proteins are used for ordering protein spots.

Animals↗

Establishment of a 2-D human urinary proteomic map in IgA nephropathy.

Immunoglobulin A nephropathy (IgAN) is the most common form of immune complex-mediated glomerulonephritis worldwide. Although chronic renal failure develops in considerable numbers of IgAN patients, the exact etiology has not yet been clearly elucidated. To establish the urinary protein map of IgAN, we performed a urinary proteomic analysis. Thirteen patients with IgAN and 12 normal controls were recruited. Morning midstream spot urine samples were used with Centriprep ultrafiltration for concentration and desalting. 2-DE was performed and compared between IgAN and normal control, and urinary proteins were identified by MALDI-TOF MS. A large number of protein spots were identified in IgAN and normal control samples, with means of 311 spots and 174 spots, respectively. Approximately 216 protein spots were detected as differentially expressed in IgAN. Among these, 82 spots were over-expressed, and 134 spots were under-expressed compared to normal controls. A total of 84 differentially expressed spots, representing 59 different proteins, were finally identified in IgAN. We have established a urinary proteomic map of IgAN and this result helps in the identification. Further study is needed to determine the potential pathogenic role of these proteins.

Adolescent↗

A novel subfractionation approach for mitochondrial proteins: a three-dimensional mitochondrial proteome map.

As mitochondria play critical roles in both cell life and cell death, there is great interest in obtaining a human mitochondrial proteome map. Such a map could potentially be useful in diagnosing diseases, identifying targets for drug therapy, and in screening for unwanted drug side effects. In this paper, we present a novel approach to obtaining a human mitochondrial proteome map that combines sucrose gradient centrifugation with standard two-dimensional gel electrophoresis. The resulting three-dimensional separation of proteins allows us to address some of the problems encountered during previous attempts to obtain mitochondrial proteome maps such as resolution of proteins and solubility of hydrophobic proteins during isoelectric focusing. In addition, we show that this new approach provides functional information about protein complexes within the organelle that is not obtained with two-dimensional gel electrophoresis of whole mitochondria.

Adenosine Triphosphate↗

On invariants of a 2-D proteome map derived from neighborhood graphs.

We consider the problem of the construction of invariants for characterization of 2-D maps, such as 2-D proteome maps, 2-D NMR spectral maps, etc., that in addition to facilitating cataloguing such maps, can be used for comparison of maps and numerical evaluation of their degree of similarity. A novel approach, based on the concept that the nearest neighborhood of points (spots) on a map are sufficiently flexible to allow one not only to vary the number of points used for characterization of the map but also the density of information on their relative positions, is put forward. The method is illustrated with the Coomassie brilliant blue stained 2-D gel electrophoresis patterns of the proteomes from liver cells of healthy male Fisher F344 rats and the rats treated with four peroxisome proliferators.

Animals↗