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PubMed2005

Performance validation of an improved Xenon-arc lamp-based CCD camera system for multispectral imaging in proteomics.

Advances in gel-based nonradioactive protein expression and PTM detection using fluorophores has served as the impetus for developing analytical instrumentation with improved imaging capabilities. We describe a CCD camera-based imaging instrument, equipped with both a high-pressure Xenon arc lamp and a UV transilluminator, which provides broad-band wavelength coverage (380-700 nm and UV). With six-position filter wheels, both excitation and emission wavelengths may be selected, providing optimal measurement and quantitation of virtually any dye and allowing excellent spectral resolution among different fluorophores. While spatial resolution of conventional fixed CCD camera imaging systems is typically inferior to laser scanners, this problem is circumvented with the new instrument by mechanically scanning the CCD camera over the sample and collecting multiple images that are subsequently automatically reconstructed into a complete high-resolution image. By acquiring images in succession, as many as four different fluorophores may be evaluated from a gel. The imaging platform is suitable for analysis of the wide range of dyes and tags commonly encountered in proteomics investigations. The instrument is unique in its capabilities of scanning large areas at high resolution and providing accurate selectable illumination over the UV/visible spectral range, thus maximizing the efficiency of dye multiplexing protocols.

Arabidopsis Proteins↗
PubMed2006

Recent developments in proteomics: implications for the study of cardiac hypertrophy and failure.

The key components to the molecular understanding of the pathophysiology of various forms of heart failure involve global and/or large-scale identifications of proteins, their patterns of expression, posttranslational modifications, and functional characterization. Particularly, proteins involved in the induction of cardiac (mal)adaptive hypertrophic growth, interstitial fibrosis, and contractile dysfunction are of interest. In general, with the accumulation of vast amounts of DNA sequences in databases, researchers have become aware that merely having complete sequences of genomes and transcriptional changes for thousands of genes simultaneously will not be sufficient to elucidate, in molecular terms, the etiology and pathophysiology of cardiovascular disease. In the last decade, a new technology called proteomics has become available that allows biological and (patho)physiological questions to be approached exclusively from the protein perspective. Proteomics may enable us to map the entire complement of proteins expressed by the heart at any time and condition. This approach creates the unique possibility to identify, by differential analysis, protein alterations associated with the etiology of heart disease and its progression, outcome, and response to therapy. To illustrate the true power of proteomics, most of the currently available methodologies are first reviewed, including their limitations. This review also deals with the current status and the perspectives of proteomics applications in research on heart failure in general. Furthermore, examples of our recent data on global protein profiling of the pressure-overloaded rat right ventricle and of endothelin-1-stimulated cultures of neonatal rat cardiac myocytes are provided. The last section is devoted to the continuous advances in proteomic technologies, including protein separation methods, mass spectrometric instrumentation, computational analysis, and bioinformatic tools, together with integrative databases.

Cardiomegaly↗
PubMed2002

H. influenzae Consortium: integrative study of H. influenzae-human interactions.

Developments in high-throughput analysis tools coupled with integrative computational techniques have enabled biological studies to reach new levels. The ability to correlate large volumes of diverse data types into cohesive models of organism function has spawned a new systematic approach to biological investigation. The creation of a new consortium has been proposed to investigate a single organism utilizing these comprehensive approaches. The Haemophilus influenzae Consortium (HIC) would be comprised of five laboratories, each providing separate and complementary areas of expertise in the study of Haemophilus influenzae (HI). The 5-year study proposes to develop coherent models of HI, both as a stand-alone organism, and more importantly, as a human pathogen. Studies in growth condition specificity followed by genomic, metabolic, and proteomic experimentation will be combined and integrated through computational and experimental analyses to form dynamic and predictive models of HI and its responses. Data from the HIC will allow greater understanding of cellular behavior, pathogen-host interactions, bacterial infection, and provide future scientific endeavors with a template for studies of other pathogens.

Bacterial Adhesion↗
PubMedDate not supplied

Chaperone networks in bacteria: analysis of protein homeostasis in minimal cells.

The prevention of aberrant behavior of proteins is fundamental to cellular life. Protein homeostatic processes are present in cells to stabilize protein conformations, refold misfolded proteins, and degrade proteins that might be detrimental to the cell. Molecular chaperones and proteases perform a major role in these processes. In bacteria, the main cytoplasmic components involved in protein homeostasis include the chaperones trigger factor, DnaK/DnaJ/GrpE, GroEL/GroES, HtpG, as well as ClpB and the proteases ClpXP, ClpAP, HslUV, Lon, and FtsH. Based on recent genome sequencing efforts, it was surprising to find that the Mycoplasma, a genus proposed to include a minimal form of cellular life, do not contain certain major members of the protein homeostatic network, including GroEL/GroES. We propose that, in mycoplasmas, there has been a fundamental shift towards favoring processes that promote protein degradation rather than protein folding. The arguments are based on two different premises: (1) the regulation of stress response in Mycoplasma and (2) the unique characteristics of the Mycoplasma proteome.

Bacterial Proteins↗
PubMed2006

Proteomic analyses of murine macrophages treated with Bacillus anthracis lethal toxin.

Bacillus anthracis is the etiological agent of anthrax and the bacterium produces a tripartite anthrax toxin composed of protective antigen (PA), lethal factor (LF) and edema factor (EF). PA represents the binding domain of the toxin and acts in concert with either LF, a metalloprotease, or EF, an adenylate cyclase, to form lethal toxin (LeTx) or edema toxin (EdTx), respectively. We analyzed the proteomics response of two murine macrophage cell lines (J774.1A and RAW264.7) following B. anthracis LeTx treatment to detect unique host proteins involved in anthrax infection using difference in-gel electrophoresis (DIGE) followed by nanoLC-MS for identification of the proteins. The comparative proteomics approach identified a set of proteins in each cell line that was consistently upregulated when the two macrophage cell lines were treated with LeTx. The upregulated proteins include those involved in energy metabolism, cytoskeleton structure and stress response. A subset of five proteins (ATP synthase beta subunit, beta-actin, Hsp70, vimentin, and Hsp60 homolog) was identified that were commonly upregulated in both cell lines. The proteomic data suggest the involvement of reactive oxygen species (ROS) in cell lysis as seen by the upregulation of proteins that lead to the production of ROS in both the cell lines used in our study. However, proteins that afford protection against ROS may play an important role in the survival of the macrophage to LeTx infection as shown by the differences in proteomic responses of the two cell lines to the action of LeTx. These identified proteins may have the potential to be used as biomarkers for diagnostics and therapeutics.

Animals↗
PubMed2006

GOlorize: a Cytoscape plug-in for network visualization with Gene Ontology-based layout and coloring.

UNLABELLED: We have implemented a graph layout algorithm that exposes Gene Ontology (GO) class structure on the network nodes. It can be used in conjunction with BiNGO plug-in to Cytoscape, which finds the GO categories over-represented in a given network. Our plug-in, named GOlorize, first highlights the class members with category-specific color-coding and then constructs an enhanced visualization of the network using a class-directed layout algorithm. AVAILABILITY: http://www.cytoscape.org/plugins2.php. SUPPLEMENTARY INFORMATION: Installation instructions and tutorial at http://www.cytoscape.org/plugins/GOlorize/GOlorizeUserGuide.pdf.

Algorithms↗
PubMed2006

Exploration of biological network centralities with CentiBiN.

BACKGROUND: The elucidation of whole-cell regulatory, metabolic, interaction and other biological networks generates the need for a meaningful ranking of network elements. Centrality analysis ranks network elements according to their importance within the network structure and different centrality measures focus on different importance concepts. Central elements of biological networks have been found to be, for example, essential for viability. RESULTS: CentiBiN (Centralities in Biological Networks) is a tool for the computation and exploration of centralities in biological networks such as protein-protein interaction networks. It computes 17 different centralities for directed or undirected networks, ranging from local measures, that is, measures that only consider the direct neighbourhood of a network element, to global measures. CentiBiN supports the exploration of the centrality distribution by visualising central elements within the network and provides several layout mechanisms for the automatic generation of graphical representations of a network. It supports different input formats, especially for biological networks, and the export of the computed centralities to other tools. CONCLUSION: CentiBiN helps systems biology researchers to identify crucial elements of biological networks. CentiBiN including a user guide and example data sets is available free of charge at http://centibin.ipk-gatersleben.de/. CentiBiN is available in two different versions: a Java Web Start application and an installable Windows application.

Computer Graphics↗
PubMed2004

GoSurfer: a graphical interactive tool for comparative analysis of large gene sets in Gene Ontology space.

UNLABELLED: The analysis of complex patterns of gene regulation is central to understanding the biology of cells, tissues and organisms. Patterns of gene regulation pertaining to specific biological processes can be revealed by a variety of experimental strategies, particularly microarrays and other highly parallel methods, which generate large datasets linking many genes. Although methods for detecting gene expression have improved substantially in recent years, understanding the physiological implications of complex patterns in gene expression data is a major challenge. This article presents GoSurfer, an easy-to-use graphical exploration tool with built-in statistical features that allow a rapid assessment of the biological functions represented in large gene sets. GoSurfer takes one or two list(s) of gene identifiers (Affymetrix probe set ID) as input and retrieves all the Gene Ontology (GO) terms associated with the input genes. GoSurfer visualises these GO terms in a hierarchical tree format. With GoSurfer, users can perform statistical tests to search for the GO terms that are enriched in the annotations of the input genes. These GO terms can be highlighted on the GO tree. Users can manipulate the GO tree in various ways and interactively query the genes associated with any GO term. The user-generated graphics can be saved as graphics files, and all the GO information related to the input genes can be exported as text files. AVAILABILITY: GoSurfer is a Windows-based program freely available for noncommercial use and can be downloaded at http://www.gosurfer.org. Datasets used to construct the trees shown in the figures in this article are available at http://www.gosurfer.org/download/GoSurfer.zip.

Computer Graphics↗
PubMed2004

Computational prediction of protein-protein interactions.

Eukaryotic proteins typically contain one or more modular domains such as kinases, phosphatases, and phoshopeptide-binding domains, as well as characteristic sequence motifs that direct post-translational modifications such as phosphorylation, or mediate binding to specific modular domains. A computational approach to predict protein interactions on a proteome-wide basis would therefore consist of identifying modular domains and sequence motifs from protein primary sequence data, creating sequence specificity-based algorithms to connect a domain in one protein with a motif in another in "interaction space," and then graphically constructing possible interaction networks. Computational methods for predicting modular domains in proteins have been quite successful, but identifying the short sequence motifs these domains recognize has been more difficult. We are developing improved methods to identify these motifs by combining experimental and computational techniques with databases of sequences and binding information. Scansite is a web-accessible program that predicts interactions between proteins using experimental binding data from peptide library and phage display experiments. This program focuses on domains important in cell signaling, but it can, in principle, be used for other interactions if the domains and binding motifs are known. This chapter describes in detail how to use Scansite to predict the binding partners of an input protein, and how to find all proteins that contain a given sequence motif.

Amino Acid Motifs↗
PubMed2026

NExON-Bayes: a Bayesian approach to network estimation informed by ordinal covariates.

MOTIVATION: In heterogeneous disease settings, accounting for intrinsic sample variability is crucial for obtaining reliable and interpretable omic network estimates. However, most graphical model analyses of biomedical data assume homogeneous conditional dependence structures, potentially leading to misleading conclusions. To address this, we propose a joint Gaussian graphical model that leverages sample-level ordinal covariates (e.g. disease stage) to account for heterogeneity and improve the estimation of partial correlation structures. RESULTS: Our modelling framework, called NExON-Bayes, extends the graphical spike-and-slab framework to account for ordinal covariates, jointly estimating their relevance to the graph structure and leveraging them to improve the accuracy of network estimation. To scale to high-dimensional omic settings, we develop an efficient variational inference algorithm tailored to our model. Through simulations, we demonstrate that our method outperforms the vanilla graphical spike-and-slab (with no covariate information), as well as other state-of-the-art network approaches which exploit covariate information. Applying our method to reverse phase protein array data from patients diagnosed with stage I, II or III breast carcinoma, we estimate the behaviour of proteomic networks as cancer progresses. Our model provides insights not only through inspection of the estimated proteomic networks, but also of the estimated ordinal covariate dependencies of key groups of proteins within those networks, offering a comprehensive understanding of how biological pathways shift across disease stages. AVAILABILITY AND IMPLEMENTATION: A user-friendly R package for NExON-Bayes with tutorials is available on Github at github.com/jf687/NExON, and archived at https://doi.org/10.5281/zenodo.20312938. The source of the dataset used is cited in the relevant section.

Bayes Theorem↗
PubMedDate not supplied

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

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

Animals↗
PubMed2001

Analysis of the plant proteome.

For many years the analysis of plant proteomes has been restricted to the construction of descriptive catalogues or the search for markers. The analysis of plant proteomes is now gaining a functional dimension, however, because the focus has shifted onto well-defined plant-specific tissues and organelles, the simultaneous mining of proteomic and physiological data and specific methodological efforts.

Biotechnology↗
PubMed2003

Protein informatics towards function identification.

The study of structural genomics and structural proteomics has determined the tertiary structures of many hypothetical proteins, whose molecular functions could not be understood using conventional methods. In order to infer the geometrical location of the functional site, the biochemical function and the biological function of the hypothetical protein, much effort has been made in protein informatics. The importance of heterogeneous databases and various descriptors of amino acid sequences, tertiary structures and pathways on the proteome scale has been emphasised.

Binding Sites↗
PubMed2004

Protein expression clone repositories for functional proteomics.

The information generated from the sequence of the human genome has inspired efforts to systematically develop organized collections of human cDNA clones for use in expression screens in mammalian cells. These high-throughput cloning initiatives offer significant advantages over the cDNA libraries that have been used in the past, including greater experimental flexibility, immediate identification of hits, information regarding all tested proteins (even for those giving no response) and eventually more comprehensive coverage. Some of the lessons learned and the considerations that underlie the creation of genome-wide cDNA repositories are discussed here. Although still inchoate, these resources are already impacting the manner in which high-throughput functional screens are performed.

Animals↗
PubMed2004

Proteomic analysis of salt-sensitive outer membrane proteins of Vibrio parahaemolyticus.

Vibrio parahaemolyticus, a universal marine pathogen with available genome sequences, could be used as a bacterial model to clarify the various physiological phenomena of its native and host environments. In the present study, proteomic methodologies were applied to investigate the expression pattern of outer membrane proteins (OMPs) of V. parahaemolyticus at different NaCl concentrations. OmpW, OmpV, elongation factor TU and polar flagellin were determined to be osmoregulation-sensitive OMPs, among which OmpW and OmpV were reported to vary with changed NaCl concentrations in the pattern of osmolarity regulation. Therefore, our results not only expand our knowledge on osmoregulation-related proteins, but also provide a valuable strategy for the screening of salt-sensitive proteins.

Bacterial Outer Membrane Proteins↗
PubMed2003

Biomedical informatics for proteomics.

Success in proteomics depends upon careful study design and high-quality biological samples. Advanced information technologies, and also an ability to use existing knowledge to the full, will be crucial in making sense of the data. Despite its genome-scale potential, proteome analysis is at a much earlier stage of development than genomics and gene expression (microarray) studies. Fundamental issues involving biological variability, pre-analytic factors and analytical reproducibility remain to be resolved. Consequently, the analysis of proteomics data is currently informal and relies heavily on expert opinion. Databases and software tools developed for the analysis of molecular sequences and microarrays are helpful, but are limited owing to the unique attributes of proteomics data and differing research goals.

Biomedical Research↗