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PubMed2003

Popitam: towards new heuristic strategies to improve protein identification from tandem mass spectrometry data.

In recent years, proteomics research has gained importance due to increasingly powerful techniques in protein purification, mass spectrometry and identification, and due to the development of extensive protein and DNA databases from various organisms. Nevertheless, current identification methods from spectrometric data have difficulties in handling modifications or mutations in the source peptide. Moreover, they have low performance when run on large databases (such as genomic databases), or with low quality data, for example due to bad calibration or low fragmentation of the source peptide. We present a new algorithm dedicated to automated protein identification from tandem mass spectrometry (MS/MS) data by searching a peptide sequence database. Our identification approach shows promising properties for solving the specific difficulties enumerated above. It consists of matching theoretical peptide sequences issued from a database with a structured representation of the source MS/MS spectrum. The representation is similar to the spectrum graphs commonly used by de novo sequencing software. The identification process involves the parsing of the graph in order to emphasize relevant sections for each theoretical sequence, and leads to a list of peptides ranked by a correlation score. The parsing of the graph, which can be a highly combinatorial task, is performed by a bio-inspired algorithm called Ant Colony Optimization algorithm.

Algorithms↗
PubMed2006

Modeling the evolution of protein domain architectures using maximum parsimony.

Domains are basic evolutionary units of proteins and most proteins have more than one domain. Advances in domain modeling and collection are making it possible to annotate a large fraction of known protein sequences by a linear ordering of their domains, yielding their architecture. Protein domain architectures link evolutionarily related proteins and underscore their shared functions. Here, we attempt to better understand this association by identifying the evolutionary pathways by which extant architectures may have evolved. We propose a model of evolution in which architectures arise through rearrangements of inferred precursor architectures and acquisition of new domains. These pathways are ranked using a parsimony principle, whereby scenarios requiring the fewest number of independent recombination events, namely fission and fusion operations, are assumed to be more likely. Using a data set of domain architectures present in 159 proteomes that represent all three major branches of the tree of life allows us to estimate the history of over 85% of all architectures in the sequence database. We find that the distribution of rearrangement classes is robust with respect to alternative parsimony rules for inferring the presence of precursor architectures in ancestral species. Analyzing the most parsimonious pathways, we find 87% of architectures to gain complexity over time through simple changes, among which fusion events account for 5.6 times as many architectures as fission. Our results may be used to compute domain architecture similarities, for example, based on the number of historical recombination events separating them. Domain architecture "neighbors" identified in this way may lead to new insights about the evolution of protein function.

Cluster Analysis↗
PubMed2004

Comparative genomics for reliable protein-function prediction from genomic data.

Genomic data provide invaluable, yet unreliable information about protein function. However, if the overlap in information among various genomic datasets is taken into account, one observes an increase in the reliability of the protein-function predictions that can be made. Recently published approaches achieved this either by comparing the same type of data from multiple species (horizontal comparative genomics) or by using subtle, Bayesian methods to compare different types of genomic data from a single species (vertical comparative genomics). In this article, we discuss these methods, illustrating horizontal comparative genomics by comparing yeast two-hybrid (Y2H) data from Saccharomyces cerevisiae with Y2H data from Drosophila melanogaster, and illustrating vertical comparative genomics by comparing RNA expression data with proteomic data from Plasmodium falciparum.

Animals↗
PubMed2002

Use of deuterium-labeled lysine for efficient protein identification and peptide de novo sequencing.

Here, we describe a method for protein identification and de novo peptide sequencing. Through in vivo cell culturing, the deuterium-labeled lysine residue (Lys-d4) introduces a 4-Da mass tag at the carboxyl terminus of proteolytic peptides when cleaved by certain proteases. The 4-Da mass difference between the unlabeled and the deuterated lysine assigns a mass signature to all lysine-containing peptides in any pool of proteolytic peptides for protein identification directly through peptide mass mapping. Furthermore, it was used to distinguish between N- and C-terminal fragments for accurate assignments of daughter ions in tandem MS/MS spectra for sequence assignment. This technique simplifies the labeling scheme and the interpretation of the MS/MS spectra by assigning different series of fragment ions correctly and easily and is very useful in de novo peptide sequencing. We have also successfully implemented this approach to the analysis of protein mixtures derived from the human proteome.

Algorithms↗
PubMed2000

JESAM: CORBA software components to create and publish EST alignments and clusters.

MOTIVATION: Expressed Sequence Tags (ESTs) are cheap, easy and quick to obtain relative to full genomic sequencing and currently sample more eukaryotic genes than any other data source. They are particularly useful for developing Sequence Tag Sites (STSs for mapping), polymorphism discovery, disease gene hunting, mass spectrometer proteomics, and most ironically for finding genes and predicting gene structure after the great effort of genomic sequencing. However, ESTs have many problems and the public EST databases contain all the errors and high redundancy intrinsic to the submitted data so it is often found that derived database views, which reduce both errors and redundancy, are more effective starting points for research than the original raw submissions. Existing derived views such as EST cluster databases and consensus databases have never published supporting evidence or intermediary results leading to difficulties trusting, correcting, and customizing the final published database. These difficulties have lead many groups to wastefully repeat the complex intermediary work of others in order to offer slightly different final views. A better approach might be to discover the most expensive common calculations used by all the approaches and then publish all intermediary results. Given a globally accessible database with a suitable component interface, like the JESAM software described in this paper, the creation of customized EST-derived databases could be achieved with minimum effort. RESULTS: Databases of EST and full-length mRNA sequences for four model organisms have been self-compared by searching for overlaps consistent with contiguity. The sequence comparisons are performed in parallel using a PVM process farm and previous results are stored to allow incremental updates with minimal effort. The overlap databases have been published with CORBA interfaces to enable flexible global access as demonstrated by example Java applet browsers. Simple cDNA supercluster databases built as alignment database clients are themselves published via CORBA interfaces browsable with prototypical applets. A comparison with UniGene Mouse and Rat databases revealed undesirable features in both and the advantages of contrasting perspectives on complex data. AVAILABILITY: The software is packaged as two Jar files available from: URL: http://corba.ebi.ac.uk/EST/jesam/jesam. html. One jar contains all the Java source code, and the other contains all the C, C++ and IDL code. Links to working examples of the alignment and cluster viewers (if remote firewall permits) can be found at http://corba.ebi.ac.uk/EST. All the Washington University mouse EST traces are available for browsing at the same URL.

Animals↗
PubMed2002

Analysis of signaling pathways using functional proteomics.

Advances in analytical methods for protein analysis by mass spectrometry provide new tools for global analysis of the expressed protein profile of cells (referred to as proteomics). Currently, available methodology samples only part of the proteome. This is sufficient for analysis of signal transduction, because signaling pathways contain enzymes, which modify high-abundance proteins other than those of the pathway. Thus, modulation of the signaling through a pathway will produce a "footprint" in the proteome that is characteristic of a specific cell phenotype. Comparison of different samples to identify these differences in posttranslational modification or protein expression is referred to as functional proteomics. This review surveys the methods in widest use in functional proteomics, as well as a few promising new ones. Although proteomic analyses were first conducted 26 years ago, a renewed interest is fueled by several recent advances. Most important are the availability of public genome and protein databases and the development of high-sensitivity, easy-to-use mass spectrometers and database search engines capable of exploiting these databases. Other important advances include improved two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), computer programs for analysis of the 2D-PAGE gel images, protocols for proteolytic digestion of proteins in excised gel pieces, and low-flow chromatography methods. Despite the limitations of these methods, they can distinguish subtle changes in the phenotype of cells, providing the basis for future studies in regulation of the phenotype.

Animals↗
PubMed2005

IMGT, the international ImMunoGeneTics information system: a standardized approach for immunogenetics and immunoinformatics.

IMGT, the international ImMunoGeneTics information system http://imgt.cines.fr, was created in 1989 by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM) (Université Montpellier II and CNRS) at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) of any species which belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT consists of five databases, ten on-line tools and more than 8,000 HTML pages of Web resources. IMGT provides a common access to standardized data from genome, genetics, proteome and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY comprises six main concepts: IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, ORIENTATION and OBTENTION. Based on these concepts, the controlled vocabulary and the annotation rules necessary for the immunogenetics data identification, classification, description and numbering and for the management of IMGT knowledge are defined in the IMGT Scientific chart. IMGT is the international reference in immunogenetics and immunoinformatics for medical research (repertoire analysis of the IG antibody sites and of the TR recognition sites in autoimmune and infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires in farm and wild life species), genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (detection and follow up of residual diseases) and therapeutical approaches (grafts, immunotherapy, vaccinology). IMGT is freely available at http://imgt.cines.fr.

Journal Article↗
PubMed2006

A mass spectrometry-based proteomic approach to study Marek's Disease Virus gene expression.

Marek's Disease Virus (MDV) is an avian herpesvirus that causes a lymphoproliferative disorder in chickens. MDV transitions between a lytic phase in which new viruses are produced and a latent phase in which the virus lays dormant. The mechanism controlling this lytic-to-latent switch remains unclear. To better understand the lytic phase of MDV infection, a mass spectrometry-based strategy was developed to identify viral proteins and to qualitatively examine their abundance in lytically infected chicken embryo fibroblast (CEF) cells. A combination of strong cation exchange chromatography (SCXC) and microcapillary reversed-phase liquid chromatography-tandem mass spectrometry (murpLC/MS/MS) was used to resolve peptides from tryptic digests of MDV-infected CEF cell lysates. Peptides were identified by searching the tandem mass spectra against a protein database containing both MDV proteins and all currently available Gallus gallus proteins using the SEQUEST algorithm. A total of 427 MDV peptides, corresponding to 82 unique proteins, were identified, with 56 of them detected with at least two unique peptides. Overall, nearly 80% of all putative MDV proteins expressed in infected CEF cells were identified. We anticipate that this approach will be a viable method for determining how viral and host proteome changes occurring in Marek's Disease pathogenesis regulate the switch between the lytic and latent phases of the MDV life cycle.

Animals↗
PubMed2003

Proteomic analysis of acrylamide gel separated proteins immobilized on polyvinylidene difluoride membranes following proteolytic digestion in the presence of 80% acetonitrile.

Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) combined with mass spectrometry (MS) is a highly accurate and sensitive means of identifying proteins. We have developed a novel method for digesting proteins on polyvinylidene difluoride (PVDF) membranes for subsequent matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS analysis. After Tricine sodium dodecyl sulfate (SDS)-PAGE, separated proteins were electroblotted onto PVDF membranes in a semidry discontinuous buffer system, visualized by staining with Coomassie Blue, excised, digested with trypsin or lysC in 80% acetonitrile, and then analyzed by MALDI-TOF MS. This method has several advantages over in-gel digestion in terms of sample handling, sensitivity, and time. We identified 105 fmol of Bacillus subtilis SecA and 100 approximately 500 fmol of standard proteins. We also analyzed the submembrane protein fraction solubilized by 1% n-dodecyl-beta-D-maltoside from B. subtilis membranes after separation by 2-D PAGE, and identified 116 protein spots. This method can detect proteins at the 10 approximately 50 fmol level by pooling more than ten identical electroblotted protein spots.

Acetonitriles↗
PubMedDate not supplied

Proteomic analysis of differential protein expression in atherosclerosis.

Although recent studies have shown that several pro-inflammatory proteins can be used as biomarkers for atherosclerosis, the mechanism of atherogenesis is unclear and little information is available regarding proteins involved in development of the disease. Atherosclerotic tissue samples were collected from patients in order to identify the proteins involved in atherogenesis. The protein expression profile of atherosclerosis patients was analysed using two-dimensional electrophoresis-based proteomics. Thirty-nine proteins were detected that were differentially expressed in the atherosclerotic aorta compared with the normal aorta. Twenty-seven of these proteins were identified in the MS-FIT database. They are involved in a number of biological processes, including calcium-mediated processes, migration of vascular smooth muscle cells, matrix metalloproteinase activation and regulation of pro-inflammatory cytokines. Confirmation of differential protein expression was performed by Western blot analysis. Potential applications of the results include the identification and characterization of signalling pathways involved in atherogenesis, and further exploration of the role of selected identified proteins in atherosclerosis.

Aortic Diseases↗
PubMed2000

Membrane proteomics: use of additive main effects with multiplicative interaction model to classify plasma membrane proteins according to their solubility and electrophoretic properties.

Recent efforts at the proteomic level were employed to describe the protein equipment of the plasma membrane of the model plant Arabidopsis thaliana. These studies had revealed that the plasma membrane is rich in extrinsic proteins but came up against two major problems: (i) few hydrophobic proteins were recovered in two-dimensional electrophoresis gels, and (ii) many plasma membrane proteins had no known function or were unknown in the database despite extensive sequencing of the Arabidopsis genome. In this paper, several methods expected to enrich a membrane sample in hydrophobic proteins were compared. The optimization of solubilization procedures revealed that the detergent to be used depends on the lipid content of the sample. The corresponding proteomes were compared with the statistical model AMMI (additive main effects with multiplicative interaction) that aimed at regrouping proteins according to their solubility and electrophoretic properties. Distinct groups emerged from this analysis and the identification of proteins in each group allowed us to assign specific features to several of them. For instance, two of these groups regrouped very hydrophobic proteins, one group contained V-ATPase subunits, another group contained proteins with one transmembrane domain as well as proteins known to interact with membrane proteins. This study provides methodological tools to study particular classes of plasma membrane proteins and should be applicable to other cellular membranes.

Amino Acid Sequence↗
PubMed2005

Proteomic analysis of parkin knockout mice: alterations in energy metabolism, protein handling and synaptic function.

Parkin knockout (KO) mice show behavioural and biochemical changes that reproduce some of the presymptomatic aspects of Parkinson's disease, in the absence of neuronal degeneration. To provide insight into the pathogenic mechanisms underlying the preclinical stages of parkin-related parkinsonism, we searched for possible changes in the brain proteome of parkin KO mice by means of fluorescence two-dimensional difference gel electrophoresis and mass spectrometry. We identified 87 proteins that differed in abundance between wild-type and parkin KO mice by at least 45%. A high proportion of these proteins were related to energy metabolism. The levels of several proteins involved in detoxification, stress-related chaperones and components of the ubiquitin-proteasome pathway were also altered. These differences might reflect adaptive mechanisms aimed at compensating for the presence of reactive oxygen species and the accumulation of damaged proteins in parkin KO mice. Furthermore, the up-regulation of several members of the membrane-associated guanylate kinase family of synaptic scaffold proteins and several septins, including the Parkin substrate cell division control related protein 1 (CDCRel-1), may contribute to the abnormalities in neurotransmitter release previously observed in parkin KO mice. This study provides clues into possible compensatory mechanisms that protect dopaminergic neurones from death in parkin KO mice and may help us understand the preclinical deficits observed in parkin-related parkinsonism.

Animals↗
PubMed2005

Assessing the precision of high-throughput computational and laboratory approaches for the genome-wide identification of protein subcellular localization in bacteria.

BACKGROUND: Identification of a bacterial protein's subcellular localization (SCL) is important for genome annotation, function prediction and drug or vaccine target identification. Subcellular fractionation techniques combined with recent proteomics technology permits the identification of large numbers of proteins from distinct bacterial compartments. However, the fractionation of a complex structure like the cell into several subcellular compartments is not a trivial task. Contamination from other compartments may occur, and some proteins may reside in multiple localizations. New computational methods have been reported over the past few years that now permit much more accurate, genome-wide analysis of the SCL of protein sequences deduced from genomes. There is a need to compare such computational methods with laboratory proteomics approaches to identify the most effective current approach for genome-wide localization characterization and annotation. RESULTS: In this study, ten subcellular proteome analyses of bacterial compartments were reviewed. PSORTb version 2.0 was used to computationally predict the localization of proteins reported in these publications, and these computational predictions were then compared to the localizations determined by the proteomics study. By using a combined approach, we were able to identify a number of contaminants and proteins with dual localizations, and were able to more accurately identify membrane subproteomes. Our results allowed us to estimate the precision level of laboratory subproteome studies and we show here that, on average, recent high-precision computational methods such as PSORTb now have a lower error rate than laboratory methods. CONCLUSION: We have performed the first focused comparison of genome-wide proteomic and computational methods for subcellular localization identification, and show that computational methods have now attained a level of precision that is exceeding that of high-throughput laboratory approaches. We note that analysis of all cellular fractions collectively is required to effectively provide localization information from laboratory studies, and we propose an overall approach to genome-wide subcellular localization characterization that capitalizes on the complementary nature of current laboratory and computational methods.

Bacterial Proteins↗
PubMed2005

Differential proteomic analysis of bronchoalveolar lavage fluid in asthmatics following segmental antigen challenge.

Allergic asthma is characterized by persistent airway inflammation and remodeling. Bronchoalveolar lavage conducted with fiberoptic bronchoscopy has been widely used for investigating the pathogenesis of asthma and other lung disorders. Identification of proteins in the bronchoalveolar lavage fluid (BALF) and their expression changes at different stages of asthma could provide further insights into the complex molecular mechanisms involved in this disease. In this report, we describe the first comprehensive differential proteomic analysis of BALF from both asthmatic patients and healthy subjects before and 24 h after segmental allergen challenge. Our proteomic analysis involves affinity depletion of six abundant BALF proteins, SDS-PAGE fractionation, protein in-gel digestion, and subsequent nano-LC-MS/MS analysis in conjunction with database searching for protein identification and semiquantitation. More than 1,500 distinct proteins were identified of which about 10% displayed significant up-regulation specific to the asthmatic patients after segmental allergen challenge. The differentially expressed proteins represent a wide spectrum of functional classes such as chemokines, cytokines, proteases, complement factors, acute phase proteins, monocyte-specific granule proteins, and local matrix proteins, etc. The majority of these protein expression changes are closely associated with many aspects of the pathophysiology of asthma, including inflammation, eosinophilia, airway remodeling, tissue damage and repair, mucus production, and plasma infiltration. Importantly a large portion of these proteins and their expression changes were identified for the first time from BALF, thus providing new insights for finding novel pathological mediators and biomarkers of asthma.

Adult↗
PubMedDate not supplied

Is there a rational method to purify proteins? From expert systems to proteomics.

The purification of recombinant proteins for therapeutic or analytical applications requires the use of several chromatographic steps in order to achieve a high level of purity. A range of techniques is available such as anion and cation exchange chromatography, which can be carried out at different pHs, and hence used at different steps, hydrophobic interaction chromatography, gel filtration and affinity chromatography. Evidently when confronted with a complex mixture of partially unknown proteins or a clarified cell extract there are many different routes one can take in order to choose the minimum and most efficient number of purification steps to achieve a desired level of purity (e.g. 98, 99.5 or 99.9%). In this review we will show how an initial "proteomic" characterization of the complex initial mixture of target protein and protein contaminants can be used to select the most efficient chromatographic separation steps in order to achieve a maximum level of purity with a minimum number of steps. The chosen methodology was implemented in a computer based expert system. The first algorithm developed was used to select the most efficient purification method to separate a protein from its contaminants based on the physicochemical properties of the protein product and the protein contaminants. The second algorithm developed was used to predict the number and concentration of contaminants after each separation as well as protein product purity. The successful application of the expert system approach, based on an initial proteomic characterization, to the practical cases of protein mixtures and clarified fermentation supernatant is presented and discussed. The purification strategy proposed was experimentally tested and validated with a mixture of four proteins and the experimental validation was also carried out with an "unknown" supernatant of Bacillus subtilis producing a recombinant beta-1,3-glucanase. The system was robust to errors <10% which is the range that can be found in the experimental determination of the properties in the database of product and contaminants. On the other hand, the system was sensitive both to larger variations (>20%) in the properties of the contaminant database and the protein product and to variations in one protein property (e.g. hydrophobicity).

Animals↗
PubMed2004

A targeted proteomics approach to the rapid identification of bacterial cell mixtures by matrix-assisted laser desorption/ionization mass spectrometry.

A proteomic approach to the rapid identification of bacteria is presented, which relies on the solubilization of a limited number of proteins from intact cells combined with on-probe tryptic digestion. Within 20 min, complete cleavage products of a limited set of bacterial proteins with molecular masses of about 4-125 kDa were obtained by on-probe digestion with immobilized trypsin. Bacterial peptides suitable for unimolecular decomposition analysis were generated within 5 min, and the sequence information obtained allowed identification of abundant proteins, and accordingly, their bacterial sources via searches in the NCBI database. Analysis of fragmentation products was also shown to allow for identification of bacterial peptides identical in mass but differing slightly in amino acid sequence by manual data analysis. In this work, Bacillus subtilis 168, B. globigii, B. sphaericus 14577, B. cereus T, and B. anthracis Sterne were examined, and various cold shock proteins were identified in all species. In addition, DNA-binding, 60 kDa-heat shock, surface-related and other stress-protective proteins were identified in the bacterial cell digests, and species-specific tryptic peptides could be generated from each of the Bacillus species studied. Bacterial peptides could be analyzed with greater sensitivity and mass accuracy than the parent proteins. The applicability of this targeted proteomics approach to the rapid identification of Bacillus species was further established by analyzing binary cell mixtures.

Amino Acid Sequence↗
PubMed2002

Comparative bioinformatic analysis of complete proteomes and protein parameters for cross-species identification in proteomics.

Peptide mass fingerprinting (PMF) remains the most amenable technique for protein identification in proteomics, using mass spectrometry as the primary analytical technique coupled with bioinformatics. This relies on the presence of the amino acid sequence of the protein in the current databanks. Despite this, it is desirable to be able to use the technique for organisms whose genomes are not yet fully sequenced and apply cross-species protein identification. In this study, we have re-examined the feasibility of such approaches by considering the extent of protein similarity between genome sequences using a data set of 29 complete bacterial and two eukaryotic genomes. A range of protein and peptide features are considered, including protein isoelectric focussing point, protein mass, and amino acid conservation. The effectiveness of PMF approaches has then been tested with a series of computer simulations with varying peptide number and mass accuracy for several cross-species tests. The results show that PMF alone is unsuitable in general for divergent species jumps, or when protein similarity is less than 70% identity. Despite this, there exists a considerable enrichment above random of tryptic peptide conservation and PMF promises to remain useful when combined with other data than just peptide masses for cross-species protein identification.

Algorithms↗
PubMedDate not supplied

Two-dimensional liquid chromatography study of the human whole saliva proteome.

The human whole saliva proteome was investigated using two-dimensional liquid chromatography (2-DLC). The 2-DLC study was able to identify, with high confidence, 102 proteins including most known salivary proteins (35), and a large number of common serum proteins (67). Peptides from proline-rich proteins, abundant in saliva, had unusual cleavage sites and were frequently only partially tryptic. Three proteins not previously observed in human saliva were also detected. Significantly greater numbers of identified proteins, including high molecular weight, low molecular weight, and proline-rich proteins, were found with 2-DLC compared to previously reported two-dimensional gel electrophoresis studies.

Amino Acid Sequence↗