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Biological Context (biological + context)
Selected Abstracts"Reverse degradomics", monitoring of proteolytic trimming by multi-CE and confocal detection of fluorescent substrates and reaction productsELECTROPHORESIS, Issue 13 2009Helene Piccard Abstract A platform for profiling of multiple proteolytic activities acting on one specific substrate, based on the use of a 96-channel capillary DNA sequencer with CE-LIF of labeled substrate peptides and reaction products is introduced. The approach consists of synthesis of a substrate peptide of interest, fluorescent labeling of the substrate, either aminoterminally by chemical coupling, or carboxyterminally by transglutaminase reaction, proteolysis by a biological mixture of proteases in the absence or presence of protease inhibitors, multi-channel analysis of substrate and reaction products, and data collection and processing. Intact substrate and reaction products, even when varying by only one amino acid, can be relatively semi-quantified in a high-throughput manner, yielding information on proteases acting in complex biological mixtures and without prepurification. Monitoring, classification and inhibition of multiple proteolytic activities are demonstrated on a model substrate, the aminoterminus of the mouse granulocyte chemotactic protein-2. In view of extensive processing of chemokines into various natural forms with different specific biological activities, and of the fragmentary knowledge of processing proteases, examples of processing by neutrophil degranulate, tumor cell culture fluids and plasma are provided. An example of selection and comparison of inhibitory mAbs illustrates that the platform is suitable for inhibitor screening. Whereas classical degradomics technologies analyze the substrate repertoire of one specific protease, here the complementary concept, namely the study of all proteases acting, in a biological context, on one specific substrate, is developed and tuned to identify key proteases and protease inhibitors for the processing of any biological substrate of interest. [source] Integrated selective enrichment target , a microtechnology platform for matrix-assisted laser desorption/ionization-mass spectrometry applied on protein biomarkers in prostate diseasesELECTROPHORESIS, Issue 21-22 2004Simon Ekström Abstract The performance of a miniaturized sample processing platform for matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS), manufactured by silicon microfabrication, called integrated selective enrichment target (ISET) technology was evaluated in a biological context. The ISET serves as both sample treatment device and MALDI-MS target, and contains an array of 96 perforated nanovials, which each can be filled with 40 nL of reversed-phase beads. This methodology minimizes the number of sample transfers and the total surface area available for undesired adsorption of the analytes in order to provide high-sensitivity analysis. ISET technology was successfully applied for characterization of proteins coisolated by affinity chromatography of prostate-specific antigen (PSA) from human seminal fluid. The application of ISET sample preparation enabled multiple analyses to be performed on a limited sample volume, which resulted in the discovery that prolactin inducible protein (PIP) was coisolated from the samples. [source] Rho kinase activates ezrin-radixin-moesin (ERM) proteins and mediates their function in cortical neuron growth, morphology and motility in vitroJOURNAL OF NEUROSCIENCE RESEARCH, Issue 1 2007Matilda A. Haas Abstract The ezrin-radixin-moesin (ERM) family of proteins contribute to cytoskeletal processes underlying many vital cellular functions. Their previously elucidated roles in non-neuronal cells are an indication of their potential importance in CNS neurons. The specific mechanisms of their activation are unknown, but are likely to depend on factors such as the cell type and biological context. For ERM proteins to become active they must be phosphorylated at a specific C-terminal threonine residue. In non-neuronal cells, several kinases, including the Rho GTPase family member Rho kinase, have been identified as capable of phosphorylating the C-terminal threonine. In these experiments we have investigated specifically the potential role of Rho kinase mediated ERM activation in cortical neurons, utilizing a new pharmacologic inhibitor of Rho kinase and quantitative analysis of aspects of neuronal functions potentially mediated by ERM proteins. Rho kinase inhibition significantly suppressed aspects of neuronal development including neurite initiation and outgrowth, as well as growth cone morphology, with a concomitant loss of phosphorylated ERM immunolabeling in areas associated with neuronal growth. The ability of the Rho kinase inhibitor to decrease the amount of pERM protein was shown by immunoblotting. Post-injury responses were negatively affected by Rho kinase inhibition, namely by a significant decrease in the number of regenerative neurites. We investigated a novel role for ERM proteins in neuron migration using a post-injury motility assay, where Rho kinase inhibition resulted in significant and drastic reduction in neuron motility and phosphorylated ERM immunolabeling. Thus, Rho kinase is an important activator of ERMs in mediating specific neuronal functions. © 2006 Wiley-Liss, Inc. [source] Host,pathogen protein interactions predicted by comparative modelingPROTEIN SCIENCE, Issue 12 2007Fred P. Davis Abstract Pathogens have evolved numerous strategies to infect their hosts, while hosts have evolved immune responses and other defenses to these foreign challenges. The vast majority of host,pathogen interactions involve protein,protein recognition, yet our current understanding of these interactions is limited. Here, we present and apply a computational whole-genome protocol that generates testable predictions of host,pathogen protein interactions. The protocol first scans the host and pathogen genomes for proteins with similarity to known protein complexes, then assesses these putative interactions, using structure if available, and, finally, filters the remaining interactions using biological context, such as the stage-specific expression of pathogen proteins and tissue expression of host proteins. The technique was applied to 10 pathogens, including species of Mycobacterium, apicomplexa, and kinetoplastida, responsible for "neglected" human diseases. The method was assessed by (1) comparison to a set of known host,pathogen interactions, (2) comparison to gene expression and essentiality data describing host and pathogen genes involved in infection, and (3) analysis of the functional properties of the human proteins predicted to interact with pathogen proteins, demonstrating an enrichment for functionally relevant host,pathogen interactions. We present several specific predictions that warrant experimental follow-up, including interactions from previously characterized mechanisms, such as cytoadhesion and protease inhibition, as well as suspected interactions in hypothesized networks, such as apoptotic pathways. Our computational method provides a means to mine whole-genome data and is complementary to experimental efforts in elucidating networks of host,pathogen protein interactions. [source] Testing a Partial Ordering of Population Means with Application to Inference about Growth Habits of Cowpea GenotypesBIOMETRICS, Issue 4 2007Daniel R. Jeske Summary Using general results available in the literature, we derive the likelihood ratio test for a particular partial ordering of means that naturally arises in a biological context. We then show that the conceptual and computational complexity of the derivation can be substantially reduced by equivalently deriving the test using the intersection-union principle for decomposing a complex null hypothesis into elemental forms. A Monte Carlo algorithm for obtaining the p -value of the test is proposed. The test procedure is illustrated with a data set of the competitive ability of several cowpea genotypes, where previous experiments have indicated the proposed partial order of the means. A simulation study is used to examine the power of the test. [source] Exploring the interactions of gliadins with model membranes: Effect of confined geometry and interfacesBIOPOLYMERS, Issue 8 2009Amélie Banc Abstract Mechanisms leading to the assembly of wheat storage proteins into proteins bodies within the endoplasmic reticulum (ER) of endosperm cells are unresolved today. In this work, physical chemistry parameters which could be involved in these processes were explored. To model the confined environment of proteins within the ER, the dynamic behavior of ,-gliadins inserted inside lyotropic lamellar phases was studied using FRAP experiments. The evolution of the diffusion coefficient as a function of the lamellar periodicity enabled to propose the hypothesis of an interaction between ,-gliadins and membranes. This interaction was further studied with the help of phospholipid Langmuir monolayers. ,- and ,-gliadins were injected under DMPC and DMPG monolayers and the two-dimensional (2D) systems were studied by Brewster angle microscopy (BAM), polarization modulation infrared reflection-absorption spectroscopy (PM-IRRAS), and surface tension measurements. Results showed that both gliadins adsorbed under phospholipid monolayers, considered as biological membrane models, and formed micrometer-sized domains at equilibrium. However, their thicknesses, probed by reflectance measurements, were different: ,-gliadins aggregates displayed a constant thickness, consistent with a monolayer, while the thickness of ,-gliadins aggregates increased with the quantity of protein injected. These different behaviors could find some explanations in the difference of aminoacid sequence distribution: an alternate repeated - unrepeated domain within ,-gliadin sequence, while one unique repeated domain was present within ,-gliadin sequence. All these findings enabled to propose a model of gliadins self-assembly via a membrane interface and to highlight the predominant role of wheat prolamin repeated domain in the membrane interaction. In the biological context, these results would mean that the repeated domain could be considered as an anchor for the interaction with the ER membrane and a nucleus point for the formation and growth of protein bodies within endosperm cells. © 2009 Wiley Periodicals, Inc. Biopolymers 91: 610,622, 2009. This article was originally published online as an accepted preprint. The "Published Online" date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com [source] THE DIFFUSIVE SPREAD OF ALLELES IN HETEROGENEOUS POPULATIONSEVOLUTION, Issue 3 2004Garrick T. Skalski Abstract The spread of genes and individuals through space in populations is relevant in many biological contexts. I study, via systems of reaction-diffusion equations, the spatial spread of advantageous alleles through structured populations. The results show that the temporally asymptotic rate of spread of an advantageous allele, a kind of invasion speed, can be approximated for a class of linear partial differential equations via a relatively simple formula, c= 2,rD, that is reminiscent of a classic formula attributed to R. A. Fisher. The parameters r and D, represent an asymptotic growth rate and an average diffusion rate, respectively, and can be interpreted in terms of eigenvalues and eigenvectors that depend on the population's demographic structure. The results can be applied, under certain conditions, to a wide class of nonlinear partial differential equations that are relevant to a variety of ecological and evolutionary scenarios in population biology. I illustrate the approach for computing invasion speed with three examples that allow for heterogeneous dispersal rates among different classes of individuals within model populations. [source] Bayesian methods for proteomicsPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 16 2007Gil Alterovitz Dr. Abstract Biological and medical data have been growing exponentially over the past several years [1, 2]. In particular, proteomics has seen automation dramatically change the rate at which data are generated [3]. Analysis that systemically incorporates prior information is becoming essential to making inferences about the myriad, complex data [4,6]. A Bayesian approach can help capture such information and incorporate it seamlessly through a rigorous, probabilistic framework. This paper starts with a review of the background mathematics behind the Bayesian methodology: from parameter estimation to Bayesian networks. The article then goes on to discuss how emerging Bayesian approaches have already been successfully applied to research across proteomics, a field for which Bayesian methods are particularly well suited [7,9]. After reviewing the literature on the subject of Bayesian methods in biological contexts, the article discusses some of the recent applications in proteomics and emerging directions in the field. [source] | |||||||||||||