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PubMedDate not supplied

Quantitation of molecular endpoints for the dose-response component of cancer risk assessment.

Cancer risk assessment involves the steps of hazard identification, dose-response assessment, exposure assessment, and risk characterization. The rapid advances in the use of molecular biology approaches has had an impact on all 4 components, but the greatest overall current and future impact will be on the dose-response assessment because this requires an understanding of the mechanisms of carcinogenesis, both background and induced by environmental agents. In this regard, hazard identification is a qualitative assessment and dose-response is a quantitative estimate. Thus, the latter will ultimately require a quantitative assessment of molecular endpoints that are used to describe the dose-response for cancer. It has been possible for many years to quantitate alterations at the level of the single gene. For example, analysis of mutation frequency by phenotypic selection, analysis of transcription (mRNA) by Northern blot, analysis of translation (proteins) by Western blot, and analysis of kinetics of metabolism from metabolite levels. However, it is becoming clear that it is necessary when considering risk for adverse health outcomes to develop quantitative approaches for whole cell phenotypes or organ effects. For example, cancer is a whole tissue phenotype, not a feature of single gene mutations, in spite of the multistep (multimutation) mode of formation of a tumor. Thus, there is the need to quantitate the circuitry of a cell: the metabolic/biochemical pathways, genetic regulation pathways, and signaling pathways in normal and stressed conditions. The hypothesis presented by Hanahan and Weinberg of the requirement for 6 acquired characteristics for tumor development, independent of tissue type and species or inducer, seems to provide a viable approach. This hypothesis can be addressed through whole cell molecular assessment using microarrays and quantitative PCR together with the emerging proteomic approaches. This is the world of the new computational cell biology.

Animals↗
PubMed2005

Efficient analysis and extraction of MS/MS result data from Mascot result files.

BACKGROUND: Mascot is a commonly used protein identification program for MS as well as for tandem MS data. When analyzing huge shotgun proteomics datasets with Mascot's native tools, limits of computing resources are easily reached. Up to now no application has been available as open source that is capable of converting the full content of Mascot result files from the original MIME format into a database-compatible tabular format, allowing direct import into database management systems and efficient handling of huge datasets analyzed by Mascot. RESULTS: A program called mres2x is presented, which reads Mascot result files, analyzes them and extracts either selected or all information in order to store it in a single file or multiple files in formats which are easier to handle downstream of Mascot. It generates different output formats. The output of mres2x in tab format is especially designed for direct high-performance import into relational database management systems using native tools of these systems. Having the data available in database management systems allows complex queries and extensive analysis. In addition, the original peak lists can be extracted in DTA format suitable for protein identification using the Sequest program, and the Mascot files can be split, preserving the original data format. During conversion, several consistency checks are performed. mres2x is designed to provide high throughput processing combined with the possibility to be driven by other computer programs. The source code including supplement material and precompiled binaries is available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/. CONCLUSION: The database upload allows regrouping of the MS/MS results using a database management system and complex analyzing queries using SQL without the need to run new Mascot searches when changing grouping parameters.

Databases, Factual↗
PubMed2005

The EH1 motif in metazoan transcription factors.

BACKGROUND: The Engrailed Homology 1 (EH1) motif is a small region, believed to have evolved convergently in homeobox and forkhead containing proteins, that interacts with the Drosophila protein groucho (C. elegans unc-37, Human Transducin-like Enhancers of Split). The small size of the motif makes its reliable identification by computational means difficult. I have systematically searched the predicted proteomes of Drosophila, C. elegans and human for further instances of the motif. RESULTS: Using motif identification methods and database searching techniques, I delimit which homeobox and forkhead domain containing proteins also have likely EH1 motifs. I show that despite low database search scores, there is a significant association of the motif with transcription factor function. I further show that likely EH1 motifs are found in combination with T-Box, Zinc Finger and Doublesex domains as well as discussing other plausible candidate associations. I identify strong candidate EH1 motifs in basal metazoan phyla. CONCLUSION: Candidate EH1 motifs exist in combination with a variety of transcription factor domains, suggesting that these proteins have repressor functions. The distribution of the EH1 motif is suggestive of convergent evolution, although in many cases, the motif has been conserved throughout bilaterian orthologs. Groucho mediated repression was established prior to the evolution of bilateria.

Amino Acid Motifs↗
PubMed2001

Whole-cell simulation: a grand challenge of the 21st century.

Study of the cell will never be complete unless its dynamic behavior is understood. The complex behavior of the cell cannot be determined or predicted unless a computer model of the cell is constructed and computer simulation is undertaken. Rapid accumulation of biological data from genome, proteome, transcriptome and metabolome projects can bring us to the point where it is no longer purely speculative to discuss how to construct virtual cells in silico. This article describes attempts to construct whole cell models. The E-CELL project has completed a couple of virtual cell models, and computer simulations have revealed some biological surprises.

Anemia, Hemolytic, Congenital↗
PubMed2026

The Multi-Omics Landscape of Enzymatic Alterations in Systemic Lupus Erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune disease closely associated with enzyme dysfunction, yet its underlying molecular mechanisms remain incompletely understood. This study aims to characterize enzyme-network alterations associated with SLE status and disease activity and to identify candidate molecules with potential clinical relevance. METHODS: We integrated proteomic and phosphoproteomic data from peripheral blood mononuclear cells (PBMCs) of 130 SLE patients and 90 healthy controls (HC), along with transcriptomic data from 1461 SLE patients. Through systematic analysis of key enzyme phosphorylation sites, upstream transcription factors (TFs), and computationally prioritized candidate compounds, we sought to characterize enzyme-centered regulatory associations. RESULTS: Integrated proteomic and phosphoproteomic analyses revealed significant metabolic and signaling pathway disturbances, along with distinct phosphorylation patterns in SLE immune cells. Multiple SLE-associated and disease-activity-associated candidate molecules were identified. Regulatory network analysis uncovered an upstream transcription factor cluster centered around STAT1. Computational drug screening identified computationally prioritized candidate compounds with multi-gene DSigDB associations, which require further clinical safety evaluation and experimental validation. CONCLUSIONS: This study constructs a molecular map of SLE, highlighting associations between enzyme-network alterations, catalytic dysregulation, and SLE-related immune molecular signatures, and identifies candidate molecules for future clinical and functional evaluation.

Humans↗
PubMed2005

Geometrical distortions in two-dimensional gels: applicable correction methods.

Two-dimensional electrophoresis (2-DE) provides a rapid means for separating thousands of proteins from cell and tissue samples in one run. Although this powerful research tool has been enthusiastically applied in many fields of biomedical research, accurate analysis and interpretation of the data have provided many challenges. Several analysis steps are needed to convert the large amount of noisy data obtained with 2-DE into reliable and interpretable biological information. The goals of such analysis steps include accurate protein detection and quantification, as well as the identification of differentially expressed proteins between samples run on different gels. To achieve these goals, systematic errors such as geometric distortions between the gels must be corrected by using computer-assisted methods. A wide range of computer software has been developed, but no general consensus exists as standard for 2-DE data analysis protocol. The choice of analysis approach is an important element depending both on the data and on the goals of the experiment. Therefore, basic understanding of the algorithms behind the software is required for optimal results. This review highlights some of the common themes in 2-DE data analysis, including protein spot detection and geometric image warping using both spot- and pixel-based approaches. Several computational strategies are overviewed and their relative merits and potential pitfalls discussed. Finally, we offer our own personal view of future trends and developments in large-scale proteome research.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2005

Digging deeper into the plant cell wall proteome.

The proteome of the plant cell wall/apoplast is less well characterized than those of other subcellular compartments. This largely reflects the many technical challenges involved in extracting and identifying extracellular proteins, many of which resist isolation and identification, and in capturing a population that is both comprehensive and relatively uncontaminated with intracellular proteins. However, a range of disruptive techniques, involving tissue homogenization and subsequent sequential extraction and non-disruptive approaches has been developed. These approaches have been complemented more recently by other genome-scale screens, such as secretion traps that reveal the genes encoding proteins with N-terminal signal peptides that are targeted to the secretory pathway, many of which are subsequently localized in the wall. While the size and complexity of the wall proteome is still unresolved, the combination of experimental tools and computational prediction is rapidly expanding the catalog of known wall-localized proteins, suggesting the unexpected extracellular localization of other polypeptides and providing the basis for further exploration of plant wall structure and function.

Cell Wall↗
PubMedDate not supplied

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↗
PubMed2004

Advances in two-dimensional gel matching technology.

For many years, two-dimensional gel electrophoresis has been the method of choice for the investigation of complex mixtures of proteins. Although there are a number of emerging technologies that can be applied to proteomics, none can yet yield routinely the breadth of information available from two-dimensional gels. To be able to obtain instant information regarding molecular mass and pI, as well as to highlight quickly the expression changes or unique proteins across a gel series requires sophisticated and powerful image analysis software. The range of software products offered by Nonlinear Dynamics covers all levels of user application and throughput, from the user-guided Phoretix two-dimensional approach, when working with a small number of gels, to the automatic processing of large numbers of gels with minimal user intervention with Progenesis. Integration of the analysis software with powerful database components allows advanced gel comparisons and data mining to be performed with statistical verification of the results. Spot pick lists can be quickly created and automatically linked to a number of commercially available spot picking robots further increasing the support for proteomics research. The importance of image analysis for accurate, reliable and meaningful results will be discussed. Recent advances in development, with particular attention placed on the impact of noise contamination within gels, are illustrated and how the Progenesis product from Nonlinear Dynamics can be utilized to get the most from two-dimensional gel electrophoresis is shown.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2006

MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics.

BACKGROUND: The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5-6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. DESCRIPTION: MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML) are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. CONCLUSION: The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion.

Computer Simulation↗
PubMed2006

Mapping and comprehensive analysis of the extracellular and cell surface proteome of the human pathogen Corynebacterium diphtheriae.

Secreted proteins of the human pathogen Corynebacterium diphtheriae might be involved in important pathogen-host cell interactions. Here, we present the first systematic reference map of the extracellular and cell surface proteome fractions of the type strain C. diphtheriae C7s(-)tox-. The analysis window of 2-DE covered the pI range from 3 to 10 along with a MW range from 8 to 150 kDa. Computational analysis of the 2-D gels detected almost 150 protein spots in the extracellular proteome fraction and about 80 protein spots of the cell surface proteome. MALDI-TOF-MS and PMF with trypsin unambiguously identified 107 extracellular protein spots and 53 protein spots of the cell surface, representing in total 85 different proteins of C. diphtheriae C7s(-)tox-. Several of the identified proteins are encoded by pathogenicity islands and might represent virulence factors of C. diphtheriae. Additionally, four solute-binding proteins (HmuT, Irp6A, CiuA, and FrgD) of different iron ABC transporters were identified, with the hitherto uncharacterized FrgD protein being the most abundant one of the cell surface proteome of C. diphtheriae C7s(-)tox-.

Amino Acid Sequence↗
PubMed2007

Virtual Expert Mass Spectrometrist v3.0: an integrated tool for proteome analysis.

The number of tools described in the literature for analysis of proteome data is growing fast. However, most tools are not able to communicate or exchange data with other tools. In Virtual Expert Mass Spectrometrist (VEMS) v3.0 an effort has been made to interface and export to already existing tools. In this chapter, an outline of how to use the VEMS program to search tandem mass spectrometry data against databases is described. Additionally, examples on how to extend the analysis with other external tools are given.

Calibration↗
PubMed2004

Self-consistent proteomic field theory of stochastic gene switches.

We present a self-consistent field approximation approach to the problem of the genetic switch composed of two mutually repressing/activating genes. The protein and DNA state dynamics are treated stochastically and on an equal footing. In this approach the mean influence of the proteomic cloud created by one gene on the action of another is self-consistently computed. Within this approximation a broad range of stochastic genetic switches may be solved exactly in terms of finding the probability distribution and its moments. A much larger class of problems, such as genetic networks and cascades, also remain exactly solvable with this approximation. We discuss, in depth, certain specific types of basic switches used by biological systems and compare their behavior to the expectation for a deterministic switch.

Animals↗
PubMed2006

Alterations in the rat serum proteome during liver injury from acetaminophen exposure.

Changes in the serum proteome were identified during early, fulminant, and recovery phases of liver injury from acetaminophen in the rat. Male F344 rats received a single, noninjury dose or a high, injury-producing dose of acetaminophen for evaluation at 6 to 120 h. Two-dimensional gel electrophoresis of immunodepleted serum separated approximately 800 stained proteins per sample from which differentially expressed proteins were identified by mass spectrometry. Serum alanine aminotransferase/aspartate aminotransferase levels and histopathology revealed the greatest liver damage at 24 and 48 h after high-dose acetaminophen corresponding to the time of greatest serum protein alterations. After 24 h, 68 serum proteins were significantly altered of which 23 proteins were increased by >5-fold and 20 proteins were newly present compared with controls. Only minimal changes in serum proteins were noted at the low dose without any histopathology. Of the 54 total protein isoforms identified by mass spectrometry, gene ontology processes for 38 unique serum proteins revealed involvement of acute phase response, coagulation, protein degradation, intermediary metabolism, and various carrier proteins. Elevated serum tumor necrosis factor-alpha from 24 to 48 h suggested a mild inflammatory response accompanied by increased antioxidant capability demonstrated by increased serum catalase activity. Antibody array and enzyme-linked immunosorbent assay analyses also showed elevation in the chemokine monocyte chemoattractant protein-1 and the metalloprotease inhibitor tissue inhibitor of metalloproteinases-1 during this same period of liver injury. This study demonstrates that serum proteome alterations probably reflect both liver damage and a concerted, complex response of the body for organ repair and recovery during acute hepatic injury.

Acetaminophen↗
PubMed2006

SPINE high-throughput crystallization, crystal imaging and recognition techniques: current state, performance analysis, new technologies and future aspects.

This paper reviews the developments in high-throughput and nanolitre-scale protein crystallography technologies within the remit of workpackage 4 of the Structural Proteomics In Europe (SPINE) project since the project's inception in October 2002. By surveying the uptake, use and experience of new technologies by SPINE partners across Europe, a picture emerges of highly successful adoption of novel working methods revolutionizing this area of structural biology. Finally, a forward view is taken of how crystallization methodologies may develop in the future.

Crystallography↗
PubMed2003

Differences in the spatial and quantitative reproducibility between two second-dimensional gel electrophoresis systems.

Two-dimensional polyacrylamide gel electrophoresis (PAGE), together with 2-D gel electrophoresis (GE) analysis software, is a common technique to analyze a complex proteome. In order to accurately locate the differentially expressed proteins in human pituitary macroadenoma tissues in our long-term research program to clarify the molecular mechanisms of macroadenoma formation, a reproducible separation system is needed. An immobilized pH-gradient dry gel-strip (IPG strip) has been extensively used for first-dimensional isoelectric focusing (IEF), and has achieved a high degree of reproducibility in the IEF direction. For the second dimension (SDS-PAGE), different types of gel systems are available, including horizontal vs. vertical gel systems, and gradient vs. constant-percentage gels. A typical horizontal system is the Multiphor II system that analyzes one gel at a time, using a precast gradient gel (180 x 245 x 0.5 mm), and a typical vertical system is the Dodeca system, which analyzes up to 12 gels at a time, using usually a single-concentration gel (190 x 205 x 1 mm). The present study evaluated the spatial and quantitative reproducibility of the two systems for the separation of the complex human pituitary proteome. PDQuest software was used to analyze the digitized gel-image data, and SPSS statistical software was used to analyze the data. The results demonstrated a high percentage (>99%) of protein-spot matches within each electrophoretic system. The Dodeca gel system demonstrated better between-gel reproducibility for spot position, higher resolution in the Sodium dodecyl sulfate (SDS)-PAGE direction, lower gel background, better spot quality, and higher reproducibility of the spot volume.

Electrophoresis, Gel, Two-Dimensional↗