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Results for “quantitative proteomics”

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At least 487 records · Page 27Linked to original sources
PubMed2003

A novel approach to spot detection for two-dimensional gel electrophoresis images using pixel value collection.

Separation of complex mixtures of proteins by two-dimensional gel electrophoresis (2-DE) is a fundamental component of current proteomic technology. Quantitative analysis of the images generated by digitization of such gels is critical for the identification of alterations in protein expression within a given biological system. Despite the availability of several commercially available software packages designed for this purpose, image analysis is extremely resource intensive, subjective and remains a major bottleneck. In addition to reducing throughput, the requirement for manual intervention results in the introduction of operator subjectivity, which can limit the statistical significance of the numerical data generated. A key requirement of image analysis is the accurate definition of protein spot boundaries using a suitable method of image segmentation. We describe a method of spot detection applicable to 2-DE image files using a segmentation method involving pixel value collection via serial analysis of the image through its range of density levels. This algorithm is reproducible, sensitive, accurate and primarily designed to be automatic, removing operator subjectivity. Furthermore, it is believed that this method may offer the potential for improved spot detection over currently available software.

Algorithms↗
PubMed2001

Metabolic engineering of Saccharomyces cerevisiae for xylose utilization.

Metabolic engineering of Saccharomyces cerevisiae for ethanolic fermentation of xylose is summarized with emphasis on progress made during the last decade. Advances in xylose transport, initial xylose metabolism, selection of host strains, transformation and classical breeding techniques applied to industrial polyploid strains as well as modeling of xylose metabolism are discussed. The production and composition of the substrates--lignocellulosic hydrolysates--is briefly summarized. In a future outlook iterative strategies involving the techniques of classical breeding, quantitative physiology, proteomics, DNA micro arrays, and genetic engineering are proposed for the development of efficient xylose-fermenting recombinant strains of S. cerevisiae.

Biological Transport↗
PubMed2006

Proteometric study of ghrelin receptor function variations upon mutations using amino acid sequence autocorrelation vectors and genetic algorithm-based least square support vector machines.

Functional variations on the human ghrelin receptor upon mutations have been associated with a syndrome of short stature and obesity, of which the obesity appears to develop around puberty. In this work, we reported a proteometrics analysis of the constitutive and ghrelin-induced activities of wild-type and mutant ghrelin receptors using amino acid sequence autocorrelation (AASA) approach for protein structural information encoding. AASA vectors were calculated by measuring the autocorrelations at sequence lags ranging from 1 to 15 on the protein primary structure of 48 amino acid/residue properties selected from the AAindex database. Genetic algorithm-based multilinear regression analysis (GA-MRA) and genetic algorithm-based least square support vector machines (GA-LSSVM) were used for building linear and non-linear models of the receptor activity. A genetic optimized radial basis function (RBF) kernel yielded the optimum GA-LSSVM models describing 88% and 95% of the cross-validation variance for the constitutive and ghrelin-induced activities, respectively. AASA vectors in the optimum models mainly appeared weighted by hydrophobicity-related properties. However, differently to the constitutive activity, the ghrelin-induced activity was also highly dependent of the steric features of the receptor.

Algorithms↗
PubMed2004

Differential and quantitative molecular analysis of ischemia complexity reduction by isotopic labeling of proteins using a neural embryonic stem cell model.

The analysis of rapid changes of protein expression in living systems in response to insults requires rigorous methods of complexity reduction. To control dynamic pattern of hundreds or even thousands of protein isoforms, we applied a novel method of differential molecular analysis to a cellular model which is suited to study ischemia. Neural derivatives of murine embryonic stem cells were exposed to chemical ischemia. The model was used to obtain starting material for a quantitative differential proteomics analysis. Fractionation of phosphoproteins from these samples and subsequent identification by mass spectrometry of differential proteins provide proof of principle of how novel molecular analytical tools provide new insight into the network of neuroprotective molecular events during specific situations of neuronal stress and related pharmaceutical intervention. Our results indicate a particular role of an isoform of the acidic calcium-independent phospholipase A2 in this type of insult.

Alkylation↗
PubMedDate not supplied

Chemical proteomic tool for ligand mapping of CYP antitargets: an NMR-compatible 3D QSAR descriptor in the Heme-Based Coordinate System.

Chemical proteomic strategies strive to probe and understand protein-ligand interactions across gene families. One gene family of particular interest in drug and xenobiotic metabolism are the cytochromes P450 (CYPs), the topic of this article. Although numerous tools exist to probe affinity of CYP-ligand interactions, fewer exist for the rapid experimental characterization of the structural nature of these interactions. As a complement to recent advances in X-ray crystallography, NMR methods are being developed that allow for fairly high throughput characterization of protein-ligand interactions. One especially promising NMR approach involves the use of paramagnetic induced relaxation effects to measure distances of ligand atoms from the heme iron in CYP enzymes. Distances obtained from these T(1) relaxation measurements can be used as a direct source of 1-dimensional structural information or to restrain a ligand docking to generate a 3-dimensional data set. To facilitate such studies, we introduce the concept of the Heme-Based Coordinate System and present how it can be used in combination with NMR T(1) relaxation data to derive 3D QSAR descriptors directly or in combination with in silico docking. These descriptors should have application in defining the binding preferences of CYP binding sites using 3D QSAR models. They are especially well-suited for the biasing of fragment assembly and combinatorial chemistry drug design strategies, to avoid fragment or reagent combinations with enhanced affinity for CYP antitargets.

Computer Simulation↗
PubMedDate not supplied

QTL analysis of proteome and transcriptome variations for dissecting the genetic architecture of complex traits in maize.

In this review, we present some studies on genetic analysis of proteome and transcriptome variations, which exemplify new strategies for a better understanding of the molecular and genetic bases of complex traits. A large genetic variability was revealed at the proteome expression level, which raised the possibility to predict phenotypical performance on the basis of gene product variability. This approach yielded limited results, but could be re-newed by extensive identification of proteins now allowed by mass spectrometry. The dissection of the genetic basis of the variation of individual protein amounts proves very powerful to select 'candidate' proteins, physiologically relevant for a given phenotypical trait, as shown by a study on the effect of water stress in maize. In order to investigate factors of grain quality in maize, we selected a regulatory locus known to control the expression of several storage protein genes, Opaque-2, and investigated the relationships between variability in zein amount and composition and the molecular polymorphism at this locus. Moreover, a QTL analysis revealed that the variability in Opaque-2 transcript abundance was controlled by several polymorphic trans-acting regulators unlinked to the Opaque-2 structural gene. Such genetic approaches should represent additional tools for physiological analysis of the huge amounts of data generated by transcritome and proteome projects.

DNA-Binding Proteins↗
PubMed2025

The farnesoid X receptor activates transcription independently of RXR at non-canonical response elements.

The farnesoid X receptor (FXR) is a nuclear receptor (NR) known to obligately heterodimerize with the retinoid X receptor (RXR). FXR is expressed as four isoforms (α1-α4) that drive transcription from IR-1 (inverted repeat-1) response elements (REs). Recently, we found that FXR isoforms α2/α4 also activate transcription from non-canonical ER-2 (everted repeat-2) REs, mediating most metabolic effects of general FXR activation. Here, we explored molecular determinants of regulation by FXRα2 from ER-2 REs through quantitative interaction proteomics, site-directed mutagenesis and transcriptomics. We discovered FXRα2 binds to and activates ER-2 elements in vitro and in reporter assays independently of RXR. Genome-wide binding analysis in mouse liver revealed higher ER-2 motif enrichment in FXR sites lacking RXR. Abrogation of FXRα2:RXR heterodimerization abolished IR-1, but preserved ER-2 transactivation. Transcriptome-wide, RXR overexpression inhibited 25% of FXRα2 targets in HepG2. These genes were specifically activated by the heterodimerization-deficient mutant FXRα2L434R, enriched for ER-2 motifs at their promoters, and involved in lipid metabolism and ammonia detoxification. In conclusion, RXR acts as a molecular switch, inhibiting FXRα2 activation from ER-2 while enhancing it from canonical IR-1 REs. Our results showcase FXR as the first NR with isoform-specific RXR-independent REs, highlighting a new layer of regulation and complexity for RXR-heterodimerizing NRs.

Humans↗
PubMed2005

Comparative study of apoptosis-related gene loci in human, mouse and rat genomes.

Many genes are involved in mammalian cell apoptosis pathway. These apoptosis genes often contain characteristic functional domains, and can be classified into at least 15 functional groups, according to previous reports. Using an integrated bioinformatics platform for motif or domain search from three public mammalian proteomes (International Protein Index database for human, mouse, and rat), we systematically cataloged all of the proteins involved in mammalian apoptosis pathway. By localizing those proteins onto the genomes, we obtained a gene locus centric apoptosis gene catalog for human, mouse and rat. Further phylogenetic analysis showed that most of the apoptosis related gene loci are conserved among these three mammals. Interestingly, about one-third of apoptosis gene loci form gene clusters on mammal chromosomes, and exist in the three species, which indicated that mammalian apoptosis gene orders are also conserved. In addition, some tandem duplicated gene loci were revealed by comparing gene loci clusters in the three species. All data produced in this work were stored in a relational database and may be viewed at http://pcas.cbi.pku.edu.cn/database/apd.php.

Animals↗
PubMed2004

Measures of diversity for populations and distances between individuals with highly reorganizable genomes.

In this paper we address the problem of defining a measure of diversity for a population of individuals whose genome can be subjected to major reorganizations during the evolutionary process. To this end, we introduce a measure of diversity for populations of strings of variable length defined on a finite alphabet, and from this measure we derive a semi-metric distance between pairs of strings. The definitions are based on counting the number of substrings of the strings, considered first separately and then collectively. This approach is related to the concept of linguistic complexity, whose definition we generalize from single strings to populations. Using the substring count approach we also define a new kind of Tanimoto distance between strings. We show how to extend the approach to representations that are not based on strings and, in particular, to the tree-based representations used in the field of genetic programming. We describe how suffix trees can allow these measures and distances to be implemented with a computational cost that is linear in both space and time relative to the length of the strings and the size of the population. The definitions were devised to assess the diversity of populations having genomes of variable length and variable structure during evolutionary computation runs, but applications in quantitative genomics, proteomics, and pattern recognition can be also envisaged.

Computational Biology↗
PubMed2005

The mysterious pulmonary brush cell: a cell in search of a function.

Brush cells, also termed tuft, caveolated, multivesicular, and fibrillovesicular cells, are part of the epithelial layer in the gastrointestinal and respiratory tracts. The cells are characterized by the presence of a tuft of blunt, squat microvilli (approximately 120-140/cell) on the cell surface. The microvilli contain filaments that stretch into the underlying cytoplasm. They have a distinctive pear shape with a wide base and a narrow microvillous apex. The function of the pulmonary brush cell is obscure. For this reason, a working group convened on August 23, 2004, in Bethesda, Maryland, to review the physiologic role of the brush (microvillous) cell in normal airways and alveoli and in respiratory diseases involving the alveolar region (e.g., emphysema and fibrosis) and airway disease characterized by either excessive or insufficient amounts of airway fluid (e.g., cystic fibrosis, chronic bronchitis, and exercise-induced asthma). The group formulated several suggestions for future investigation. For example, it would be useful to have a panel of specific markers for the brush cell and in this way separate these cells for culture and more direct examination of their function (e.g., microarray analysis and proteomics). Using quantitative analysis, it was suggested to examine the number and location of the cells in disease models. Understanding the function of these cells in alveoli and airways may provide clues to the pathogenesis of several disease states (e.g., cystic fibrosis and fibrosis) as well as a key for new therapeutic modalities.

Animals↗
PubMed2002

Identification and characterization of subfamily-specific signatures in a large protein superfamily by a hidden Markov model approach.

BACKGROUND: Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. The next step of such database studies should include the development of classification systems capable of distinguishing between subfamilies within a structurally and functionally diverse superfamily. This would be helpful in elucidating sequence-structure-function relationships of proteins. RESULTS: Here, we present a method to diagnose sequences into subfamilies by employing hidden Markov models (HMMs) to find windows of residues that are distinct among subfamilies (called signatures). The method starts with a multiple sequence alignment (MSA) of the subfamily. Then, we build a HMM database representing all sliding windows of the MSA of a fixed size. Finally, we construct a HMM histogram of the matches of each sliding window in the entire superfamily. To illustrate the efficacy of the method, we have applied the analysis to find subfamily signatures in two well-studied superfamilies: the cadherin and the EF-hand protein superfamilies. As a corollary, the HMM histograms of the analyzed subfamilies revealed information about their Ca2+ binding sites and loops. CONCLUSIONS: The method is used to create HMM databases to diagnose subfamilies of protein superfamilies that complement broad profile and motif databases such as BLOCKS, PROSITE, Pfam, SMART, PRINTS and InterPro.

Binding Sites↗
PubMed2006

Dissecting the genetic basis of rheumatoid arthritis in mouse models.

Rheumatoid Arthritis, RA, is a common polygenic multi-factorial chronic inflammatory disorder that involves complex interactions between genetic and environmental factors. Despite major advances, the aetiology of the disease is still not completely understood. In this post-genome era, the sequencing of the human and some murine genomes as well as advances in global screening technologies offer an opportunity to accelerate the search for new pathological pathways and to identify new therapeutic targets. Animal models of RA offer an opportunity to dissect the genetic basis of disease in a simplified genome and controlled environment with the aim of identifying new pathological pathways and thus new therapeutic targets. Linkage analysis in the mouse model has identified more than 60 Loci, controlling disease phenotypes, immune response and cytokines. This indicates that gene variations among inbred mice strains affect the disease and that those polymorphic genes could be potential therapeutic targets. However, progress in identification of susceptibility genes in mouse models is slow. The progress is hampered by the complexity of disease as well as the traditional genetic dissection strategies. In this post-genome era, the sequencing of the human and some murine genomes as well as advances in global screening technologies offer an opportunity to accelerate the progress.

Animals↗