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PubMedDate not supplied

Data input module for Birth Defects Systems Manager.

The need for a computational bioinformatics infrastructure to manage the vast digital information from functional genomics and proteomics motivated us to develop Birth Defects Systems Manager (BDSM) as an open resource to facilitate analysis and discovery in developmental biology and developmental toxicity. This report describes the design, development and implementation of the data loading module of BDSM, referred to as LoadBDSM. It includes a shared data directory resource that can be granted various levels of security for different research groups or investigators to manage experimental datasets individually or in groups. LoadBDSM allows the upload of data and experiment details using controlled semantics for developmental exposure (toxicant, dosing scenario, intervention), biological sample (species, tissue, stage) and disease outcome (time, risk, phenotype). It adheres to existing controlled vocabulary plus rules of inference (ontologies) for experiment, data and metadata annotations. LoadBDSM extends the capabilities of BDSM to support the emergence of "embryo-formatics" defined here as the data, information and knowledge from genomic sciences applied to, or derived from, an embryological context. This includes, but is not limited to, delineating pathways and biological regulatory networks for specific chemicals or classes of developmental toxicants, developing novel biomarkers indicative of exposure and/or predictive of adverse effects, and integrating modern computing and information technology with data from molecular biology.

Abnormalities, Drug-Induced↗
PubMedDate not supplied

Effect of immunoaffinity depletion of human serum during proteomic investigations.

Controversy exists regarding the proper mining of the human serum proteome. Because of the analytical challenges of accurately measuring samples containing a very large dynamic range of protein concentrations, current practices have employed depletion of the highly abundant housekeeping serum proteins, such as albumin and immunoglobins. There is question as to the selectivity of depletion, namely, is there loss of other non abundant serum proteins along with albumin, haptoglobin and other commonly depleted proteins. In this study, human serum was analyzed with and without immunoaffinity depletion of the six most abundant proteins by multidimensional liquid chromatography tandem mass spectrometry. Two replicates of each experiment were conducted and compared against one another. In both depleted and nondepleted replicates there was a 73% and 72% overlap of identified peptides and a 64% and 78% overlap of identified proteins, respectively. Of 262 unique proteins identified in the four experiments, 82 were found in common to all four experiments, 142 unique to the depleted serum, and 38 unique to the nondepleted serum. Although serum depletion of highly abundant proteins significantly increased the number of proteins identified, both the degree of sample complexity and this depletion method resulted in a nonselective loss of other proteins.

Albumins↗
PubMed2003

Analysis of protein induction in the CNS of SJL mice with experimental allergic encephalomyelitis by proteomic screening and immunohistochemistry.

Experimental allergic encephalomyelitis (EAE) is an autoimmune disease characterized by demyelination and inflammatory infiltrates in the CNS, and it is an animal model of multiple sclerosis. Piperonyl butoxide (PBO) suppresses disease in EAE mice, and it exhibits a dual effect on cytochrome P450s that manifests in a transient inhibitory phase followed by induction. In order to identify the expression of proteins associated with EAE, a proteomic screening was performed on hindbrain microsomes from control + vehicle, control + PBO, EAE + vehicle, and EAE + PBO female mice. Glucose regulated protein 94 (Grp94) and coagulation factor VIII were among the proteins identified in EAE + vehicle and EAE + PBO mice. Immunohistochemical staining of Grp94 was present in some neurons and oligodendrocytes in hindbrain sections from control animals, and in some cells within inflammatory infiltrates in EAE animals. Since Grp94 (also known as Gp96) can partake in antigen presentation and induction of proinflammatory cytokine expression, its presence in these cells suggests that it may play a role in the pathogenesis of EAE. Coagulation factor VIII is carried and protected by von Willebrand factor. Immunohistochemical staining of von Willebrand factor revealed its presence in some vessels within hindbrain sections from control animals. In EAE animals, the number of labeled vessels was significantly increased, and extracellular granular deposits were observed around labeled vessels indicating that the breakdown of the blood-brain barrier that occurs in EAE permitted its extravasation into the CNS. Additional proteins were identified in the different groups of mice by proteomic screening, but confirmation of their expression profile awaits investigations by independent measures.

Animals↗
PubMed2001

Microbial genes in the human genome: lateral transfer or gene loss?

The human genome was analyzed for evidence that genes had been laterally transferred into the genome from prokaryotic organisms. Protein sequence comparisons of the proteomes of human, fruit fly, nematode worm, yeast, mustard weed, eukaryotic parasites, and all completed prokaryote genomes were performed, and all genes shared between human and each of the other groups of organisms were collected. About 40 genes were found to be exclusively shared by humans and bacteria and are candidate examples of horizontal transfer from bacteria to vertebrates. Gene loss combined with sample size effects and evolutionary rate variation provide an alternative, more biologically plausible explanation.

Animals↗
PubMed2004

Proteome analysis of hepatocellular carcinoma cell strains, MHCC97-H and MHCC97-L, with different metastasis potentials.

To better understand the mechanism underlying hepatocellular carcinoma (HCC) metastasis and to search for potential markers for HCC prognosis, differential proteome analysis on two HCC cell strains with high and low metastatic potentials, MHCC97-H and MHCC97-L, was conducted using two-dimensional (2-D) gel electrophoresis followed by matrix-assisted laser desorption/time of flight mass spectrometry and liquid chromatography ion trap mass spectrometry. Image analysis of silver-stained 2-D gels revealed that 56 protein spots showed significant differential expression in MHCC97-H and MHCC97-L cells (Student's t-test, P < 0.05) and 4 protein spots were only detected in MHCC97-H cells. Fourteen protein spots were further identified using in-gel tryptic digestion, peptide mass fingerprinting and tandem mass spectrometry. The expressions of pyruvate kinase M2, ubiquitin carboxy-terminal hydrolase L1, laminin receptor 67 kDa, S100 calcium-binding protein A4, thioredoxin and cytokeratin 19 were elevated in MHCC97-H cells. However, manganese superoxide dismutase, calreticulin precursor, cathepsin D, lactate dehydrogenase B, non-metastatic cell protein 1, cofilin 1 and calumenin precursor were down-regulated in MHCC97-H cells. Intriguingly, most of these identified proteins have been reported to be associated with tumor metastasis. The functional implications of alterations in the levels of these proteins are discussed.

Animals↗
PubMed2006

The pitfalls of proteomics experiments without the correct use of bioinformatics tools.

The elucidation of the entire genomic sequence of various organisms, from viruses to complex metazoans, most recently man, is undoubtedly the greatest triumph of molecular biology since the discovery of the DNA double helix. Over the past two decades, the focus of molecular biology has gradually moved from genomes to proteomes, the intention being to discover the functions of the genes themselves. The postgenomic era stimulated the development of new techniques (e.g. 2-DE and MS) and bioinformatics tools to identify the functions, reactions, interactions and location of the gene products in tissues and/or cells of living organisms. Both 2-DE and MS have been very successfully employed to identify proteins involved in biological phenomena (e.g. immunity, cancer, host-parasite interactions, etc.), although recently, several papers have emphasised the pitfalls of 2-DE experiments, especially in relation to experimental design, poor statistical treatment and the high rate of 'false positive' results with regard to protein identification. In the light of these perceived problems, we review the advantages and misuses of bioinformatics tools - from realisation of 2-DE gels to the identification of candidate protein spots - and suggest some useful avenues to improve the quality of 2-DE experiments. In addition, we present key steps which, in our view, need to be to taken into consideration during such analyses. Lastly, we present novel biological entities named 'interactomes', and the bioinformatics tools developed to analyse the large protein-protein interaction networks they form, along with several new perspectives of the field.

Amino Acid Sequence↗
PubMed2004

From ORFeome to biology: a functional genomics pipeline.

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.

Animals↗
PubMed2001

Archived polyacrylamide gels as a resource for proteome characterization by mass spectrometry.

Mass spectrometry was applied to identify protein spots excised from an archived two-dimensional polyacrylamide gel that had been dried and stored for eight years at room temperature. All proteins were successfully identified. Detailed characterization of protein digests by matrix-assisted laser desorption/ionization (MALDI) peptide mapping, nanoelectrospray tandem mass spectrometry and MALDI-quadrupole time-of-flight mass spectrometry revealed no evidence of protein degradation or modifications that could hamper identification of proteins in a sequence database. The experiment with a model protein demonstrated that the pattern of tryptic peptides and the yield of individual peptides were not noticeably changed in the in-gel digest of the archived protein spot compared to the digest of the spot excised from a fresh gel. Thus, the characterization of "archived proteomes" has the potential to advance proteomic research without repeating "wet" biochemistry experiments, that had been perfected in the laboratory years ago.

Acrylic Resins↗
PubMed2004

Cy5 maleimide labelling for sensitive detection of free thiols in native protein extracts: identification of seed proteins targeted by barley thioredoxin h isoforms.

Barley thioredoxin h isoforms HvTrxh1 and HvTrxh2 differ in temporal and spatial distribution and in kinetic properties. Target proteins of HvTrxh1 and HvTrxh2 were identified in mature seeds and in seeds after 72 h of germination. Improvement of the established method for identification of thioredoxin-targeted proteins based on two-dimensional electrophoresis and fluorescence labelling of thiol groups was achieved by application of a highly sensitive Cy5 maleimide dye and large-format two-dimensional gels, resulting in a 10-fold increase in the observed number of labelled protein spots. The technique also provided information about accessible thiol groups in the proteins identified in the barley seed proteome. In total, 16 different putative target proteins were identified from 26 spots using tryptic in-gel digestion, matrix-assisted laser-desorption ionization-time-of-flight MS and database search. HvTrxh1 and HvTrxh2 were shown to have similar target specificity. Barley alpha-amylase/subtilisin inhibitor, previously demonstrated to be reduced by both HvTrxh1 and HvTrxh2, was among the identified target proteins, confirming the suitability of the method. Several alpha-amylase/trypsin inhibitors, some of which are already known as target proteins of thioredoxin h, and cyclophilin known as a target protein of m-type thioredoxin were also identified. Lipid transfer protein, embryospecific protein, three chitinase isoenzymes, a single-domain glyoxalase-like protein and superoxide dismutase were novel identifications of putative target proteins, suggesting new physiological roles of thioredoxin h in barley seeds.

Bridged Bicyclo Compounds↗
PubMed1996

Rapid protein identification using N-terminal "sequence tag" and amino acid analysis.

Proteins can be identified by amino acid analysis and database matching, but it is often desirable to increase the confidence in identity through the use of other techniques. Here we describe a rapid protein identification method that uses Edman degradation to create a 3 or 4 amino acid N-terminal "sequence tag," following which proteins are subjected to amino acid analysis protein identification procedures. Edman degradation methods have been modified to take only 23 min per cycle, and rapid amino acid analysis techniques are used. The Edman degradation and amino acid analysis is done on a single PVDF membrane-bound protein sample. A computer database matching program is also presented which uses both amino acid composition and "sequence tag" data for protein identification. This method represents the most inexpensive, accurate, and rapid means of protein identification, which is ideal for the screening of proteomes separated by 2-D gel electrophoresis. The creation of N-terminal Edman degradation "sequence-tags" prior to peptide mass fingerprinting of samples should also be useful.

Amino Acid Sequence↗
PubMed2001

Arrays for protein expression profiling: towards a viable alternative to two-dimensional gel electrophoresis?

Two-dimensional gel electrophoresis (2-DE) is used as a platform method for the measurement of protein expression patterns within cells, tissues or organisms. This approach can support expression profiling of several thousand proteins in multiple samples and as such it is currently unrivaled as a tool for the analysis of protein expression, which is a key component of the rapidly expanding field of proteomics. However, 2-DE has a number of significant limitations and as a consequence, alternative approaches for the measurement of expression of proteins within complex samples are actively being explored. Here we review some existing and emerging methods for protein expression analysis. In particular, we review a range of technologies that might be integrated to support the development of 'arrays' or 'chips' for rapid, high-throughput analysis of protein expression in a manner analogous to the current use of DNA arrays for mRNA expression analysis. We conclude that such separation-independent platforms may ultimately supersede two-dimensional (2-D) gel-based analyses for global protein expression analysis but that before this the technologies might provide important new platforms for diagnostic and prognostic monitoring of diseases.

Databases, Protein↗
PubMedDate not supplied

Feature based fuzzy matching of 2D gel electrophoresis images.

Automatic alignment (matching) of two-dimensional gel electrophoresis images is of primary interest in the evolving field of proteomics. In the present study, feature-based matching techniques, in their classical and robust versions, are described, and an automatic method of fuzzy alignment (FA) is introduced. This method allows automatic matching of two gel images with different numbers of features with unknown correspondence. Performance of FA is tested on simulated and real data sets.

Automation↗
PubMed2004

Free flow electrophoresis coupled with liquid chromatography-mass spectrometry for a proteomic study of the human cell line (K562/CR3).

The requirement for prefractionation in proteomic analysis is linked to the challenge of performing such an analysis on complex biological samples and identifying low level components in the presence of numerous abundant housekeeping and structural proteins. The employment of a preliminary fractionation step results in a reduction of complexity in an individual fraction and permits more complete liquid chromatography/mass spectrometry (LC/MS) analysis. Free flow electrophoresis (FFE), a solution-based preparative isoelectric focusing technique, fractionates and enriches protein fractions according to their charge differences and is orthogonal in selectivity to the popular reversed phase high performance liquid chromatography (HPLC) fractionation step. In this paper, we explored the advantages of a combination of FFE and liquid chromatography/mass spectrometry to extend the dynamic range of a proteomic analysis of a complex cell lysate. In this study, the whole cell lysate of a chronic myelogeneous leukemia cell line, K562/CR3, was prefractionated by FFE into 96 fractions spanning pH 3-12. Of these, 35 fractions were digested with trypsin and then analyzed by LC/MS. Depending on the algorithm used for peptide assignment from MS/MS data, at least 319 proteins were identified through database searches. The results also suggested that pI could serve as an additional criterion besides peptide fragmentation pattern for protein identification, although in some cases, a pI shift might indicate post-translational modification. In summary, this study demonstrated that free flow electrophoresis provided a useful prefractionation step for proteomic analysis and when combined with LC/MS allowed the identification of significant number of low level proteins in complex samples.

Chromatography, High Pressure Liquid↗
PubMed2006

Proteomic analysis of the cerebrospinal fluid of patients with lumbar disk herniation.

To better understand the pathophysiologic mechanisms underlying spinal nerve root injury induced by lumbar disk herniation (LDH), comparative proteomic analysis of cerebrospinal fluid (CSF) between patients with LDH (the experiment group) and the otherwise healthy patients who had had implants removed from healed fractures in the lower limbs (the control group) was carried out using 2-DE followed by LC-IT-MS and database searching. Image analysis of silver-stained 2-DE gels revealed that 15 protein spots showed significant differential expression between the two groups of CSF samples (p < 0.05). After searching the database we found that in CSF of LDH patients, the expression of cystatin C, apolipoprotein A-IV, vitamin D-binding protein, neurofilament triplet L protein, IgG, tetranectin, and hemoglobin were elevated. However, ProSAAS, prostagladin D2 synthase, creatine kinase B, superoxide dismutase 1 and peroxiredoxin 2 were decreased. The subsequent ELISA measured the concentration of tetranectin, vitamin D-binding protein and cystatin C and confirmed the results of proteomic analysis. These identified proteins are involved in the pathophysiological process of spinal nerve root injury caused by herniated lumbar disk. The functional implications of the alterations in the levels of these proteins are discussed in this paper.

Adult↗
PubMed2005

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

BACKGROUND: Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. RESULTS: Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. CONCLUSION: HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Algorithms↗
PubMed2004

Identification of chromosomally encoded membranal polypeptides of Bacillus anthracis by a proteomic analysis: prevalence of proteins containing S-layer homology domains.

Bacillus anthracis is the causative agent of anthrax disease. Improvement of existing anthrax vaccines, which are currently based on the administration of Protective Antigen (the highly immunogenic nontoxic subunit of the bacterial toxin) may entail other bacterial immunogenic elements, part of which are predicted to reside on the surface of bacterial cells. In the present study, membranal proteins extracted from a stationary-phase culture of a nonvirulent B. anthracis strain, devoid of the native virulence plasmids pXO1 and pXO2, were separated by two-dimensional electrophoresis (2-DE) and a characteristic protein map was defined. The proteomic analysis allowed matrix-assisted laser desorption/ionization-time of flight mass spectrometry-assisted identification of 86 protein spots which represent the product of 30 individual open reading frames (ORF). Among these, a prevalent class of proteins was the S-layer proteins (which were found to represent more than 75% of the B. anthracis membranal fraction) and proteins containing S-layer homology (SLH)-membranal localization domains. Five novel SLH proteins, previously inferred only from bioinformatic ORF analysis (draft genome sequence), were identified and one was shown to be a highly abundant membranal protein. Western blots of the 2-DE gels were probed with sera from convalescent rabbits and guinea pigs infected with virulent B. anthracis (Vollum strain). This analysis revealed that B. anthracis immune animals exhibit antibodies against at least 14 distinct membranal proteins present in the 2-DE map, establishing that these proteins are expressed in vivo and are able to elicit an immune response. The identification of the protein components of the B. anthracis membranal fraction, as well as the establishment of their potential immunogenicity, underscore the strength of the proteomic approach for identifying molecules which may serve for further analysis of immune and protective abilities.

Amino Acid Sequence↗
PubMed2005

AVID: an integrative framework for discovering functional relationships among proteins.

BACKGROUND: Determining the functions of uncharacterized proteins is one of the most pressing problems in the post-genomic era. Large scale protein-protein interaction assays, global mRNA expression analyses and systematic protein localization studies provide experimental information that can be used for this purpose. The data from such experiments contain many false positives and false negatives, but can be processed using computational methods to provide reliable information about protein-protein relationships and protein function. An outstanding and important goal is to predict detailed functional annotation for all uncharacterized proteins that is reliable enough to effectively guide experiments. RESULTS: We present AVID, a computational method that uses a multi-stage learning framework to integrate experimental results with sequence information, generating networks reflecting functional similarities among proteins. We illustrate use of the networks by making predictions of detailed Gene Ontology (GO) annotations in three categories: molecular function, biological process, and cellular component. Applied to the yeast Saccharomyces cerevisiae, AVID provides 37,451 pair-wise functional linkages between 4,191 proteins. These relationships are approximately 65-78% accurate, as assessed by cross-validation testing. Assignments of highly detailed functional descriptors to proteins, based on the networks, are estimated to be approximately 67% accurate for GO categories describing molecular function and cellular component and approximately 52% accurate for terms describing biological process. The predictions cover 1,490 proteins with no previous annotation in GO and also assign more detailed functions to many proteins annotated only with less descriptive terms. Predictions made by AVID are largely distinct from those made by other methods. Out of 37,451 predicted pair-wise relationships, the greatest number shared in common with another method is 3,413. CONCLUSION: AVID provides three networks reflecting functional associations among proteins. We use these networks to generate new, highly detailed functional predictions for roughly half of the yeast proteome that are reliable enough to drive targeted experimental investigations. The predictions suggest many specific, testable hypotheses. All of the data are available as downloadable files as well as through an interactive website at http://web.mit.edu/biology/keating/AVID. Thus, AVID will be a valuable resource for experimental biologists.

Algorithms↗
PubMed2026

Proteomic insights into Helicobacter pylori infection in stomach cells, revealing host response and host-targeted therapeutics repurposing.

BACKGROUND: Helicobacter pylori (H. pylori) is a globally prevalent gastric pathogen strongly associated with chronic gastritis, peptic ulcers, and gastric cancer. While bacterial factors have been extensively studied, host proteomic responses and their therapeutic potential remain largely underexplored. RESEARCH DESIGN AND METHODS: Current analyses employed a systematic proteomics-based data integration and harmonization approach (retrospective qualitative cohort study) to identify important differentially regulated host proteins. Proteomic datasets were curated from in vitro studies and analyzed for functional enrichment, protein-protein interaction networks, and hub protein identification. To explore therapeutic repurposing, drug repositioning was performed using the DrugBank database. RESULTS: Data summation describing protein differential regulation in human gastric cells as a result of the infection revealed 1672 perturbed host proteins. Bioinformatics analysis revealed 11 proteins including CSK, MET, RELA, MARK2, GRB2, FTO, PLCG1, CRKL, RPS5, RPS9, and RPS27A to be ideal host targets for therapeutic repurposing. Clinically approved drugs such as Dasatinib (targeting CSK) and Crizotinib (targeting MET) emerged as promising candidates due to favorable pharmacokinetics and known bioactivity. CONCLUSIONS: Host-directed therapeutics could offer alternative strategies to conventional antibiotic therapy, addressing challenges such as resistance and infection recurrence, providing a foundation for future experimental validation and development of host-targeted interventions for infection control.

Humans↗

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