Testing, Selection, and Implementation of Random Number Generators

National Research Council Canada - National Science Library

Collins, Joseph C

2008-01-01

An exhaustive evaluation of state-of-the-art random number generators with several well-known suites of tests provides the basis for selection of suitable random number generators for use in stochastic simulations...

Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

Directory of Open Access Journals (Sweden)

Sandip Chakraborty

2016-01-01

Full Text Available Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes’ adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

Selection of peptides interfering with protein-protein interaction.

Science.gov (United States)

Gaida, Annette; Hagemann, Urs B; Mattay, Dinah; Räuber, Christina; Müller, Kristian M; Arndt, Katja M

2009-01-01

Cell physiology depends on a fine-tuned network of protein-protein interactions, and misguided interactions are often associated with various diseases. Consequently, peptides, which are able to specifically interfere with such adventitious interactions, are of high interest for analytical as well as medical purposes. One of the most abundant protein interaction domains is the coiled-coil motif, and thus provides a premier target. Coiled coils, which consist of two or more alpha-helices wrapped around each other, have one of the simplest interaction interfaces, yet they are able to confer highly specific homo- and heterotypic interactions involved in virtually any cellular process. While there are several ways to generate interfering peptides, the combination of library design with a powerful selection system seems to be one of the most effective and promising approaches. This chapter guides through all steps of such a process, starting with library options and cloning, detailing suitable selection techniques and ending with purification for further down-stream characterization. Such generated peptides will function as versatile tools to interfere with the natural function of their targets thereby illuminating their down-stream signaling and, in general, promoting understanding of factors leading to specificity and stability in protein-protein interactions. Furthermore, peptides interfering with medically relevant proteins might become important diagnostics and therapeutics.

Directional Darwinian Selection in proteins.

Science.gov (United States)

McClellan, David A

2013-01-01

Molecular evolution is a very active field of research, with several complementary approaches, including dN/dS, HON90, MM01, and others. Each has documented strengths and weaknesses, and no one approach provides a clear picture of how natural selection works at the molecular level. The purpose of this work is to present a simple new method that uses quantitative amino acid properties to identify and characterize directional selection in proteins. Inferred amino acid replacements are viewed through the prism of a single physicochemical property to determine the amount and direction of change caused by each replacement. This allows the calculation of the probability that the mean change in the single property associated with the amino acid replacements is equal to zero (H0: μ = 0; i.e., no net change) using a simple two-tailed t-test. Example data from calanoid and cyclopoid copepod cytochrome oxidase subunit I sequence pairs are presented to demonstrate how directional selection may be linked to major shifts in adaptive zones, and that convergent evolution at the whole organism level may be the result of convergent protein adaptations. Rather than replace previous methods, this new method further complements existing methods to provide a holistic glimpse of how natural selection shapes protein structure and function over evolutionary time.

Application of random effects to the study of resource selection by animals.

Science.gov (United States)

Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

2006-07-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions

Random heteropolymers preserve protein function in foreign environments

Science.gov (United States)

Panganiban, Brian; Qiao, Baofu; Jiang, Tao; DelRe, Christopher; Obadia, Mona M.; Nguyen, Trung Dac; Smith, Anton A. A.; Hall, Aaron; Sit, Izaac; Crosby, Marquise G.; Dennis, Patrick B.; Drockenmuller, Eric; Olvera de la Cruz, Monica; Xu, Ting

2018-03-01

The successful incorporation of active proteins into synthetic polymers could lead to a new class of materials with functions found only in living systems. However, proteins rarely function under the conditions suitable for polymer processing. On the basis of an analysis of trends in protein sequences and characteristic chemical patterns on protein surfaces, we designed four-monomer random heteropolymers to mimic intrinsically disordered proteins for protein solubilization and stabilization in non-native environments. The heteropolymers, with optimized composition and statistical monomer distribution, enable cell-free synthesis of membrane proteins with proper protein folding for transport and enzyme-containing plastics for toxin bioremediation. Controlling the statistical monomer distribution in a heteropolymer, rather than the specific monomer sequence, affords a new strategy to interface with biological systems for protein-based biomaterials.

Local randomization in neighbor selection improves PRM roadmap quality

KAUST Repository

McMahon, Troy; Jacobs, Sam; Boyd, Bryan; Tapia, Lydia; Amato, Nancy M.

2012-01-01

Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K'), that first computes the K' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

Local randomization in neighbor selection improves PRM roadmap quality

KAUST Repository

McMahon, Troy

2012-10-01

Probabilistic Roadmap Methods (PRMs) are one of the most used classes of motion planning methods. These sampling-based methods generate robot configurations (nodes) and then connect them to form a graph (roadmap) containing representative feasible pathways. A key step in PRM roadmap construction involves identifying a set of candidate neighbors for each node. Traditionally, these candidates are chosen to be the k-closest nodes based on a given distance metric. In this paper, we propose a new neighbor selection policy called LocalRand(k,K\\'), that first computes the K\\' closest nodes to a specified node and then selects k of those nodes at random. Intuitively, LocalRand attempts to benefit from random sampling while maintaining the higher levels of local planner success inherent to selecting more local neighbors. We provide a methodology for selecting the parameters k and K\\'. We perform an experimental comparison which shows that for both rigid and articulated robots, LocalRand results in roadmaps that are better connected than the traditional k-closest policy or a purely random neighbor selection policy. The cost required to achieve these results is shown to be comparable to k-closest. © 2012 IEEE.

The importance of protein in leaf selection of folivorous primates.

Science.gov (United States)

Ganzhorn, Joerg U; Arrigo-Nelson, Summer J; Carrai, Valentina; Chalise, Mukesh K; Donati, Giuseppe; Droescher, Iris; Eppley, Timothy M; Irwin, Mitchell T; Koch, Flávia; Koenig, Andreas; Kowalewski, Martin M; Mowry, Christopher B; Patel, Erik R; Pichon, Claire; Ralison, Jose; Reisdorff, Christoph; Simmen, Bruno; Stalenberg, Eleanor; Starrs, Danswell; Terboven, Juana; Wright, Patricia C; Foley, William J

2017-04-01

Protein limitation has been considered a key factor in hypotheses on the evolution of life history and animal communities, suggesting that animals should prioritize protein in their food choice. This contrasts with the limited support that food selection studies have provided for such a priority in nonhuman primates, particularly for folivores. Here, we suggest that this discrepancy can be resolved if folivores only need to select for high protein leaves when average protein concentration in the habitat is low. To test the prediction, we applied meta-analyses to analyze published and unpublished results of food selection for protein and fiber concentrations from 24 studies (some with multiple species) of folivorous primates. To counter potential methodological flaws, we differentiated between methods analyzing total nitrogen and soluble protein concentrations. We used a meta-analysis to test for the effect of protein on food selection by primates and found a significant effect of soluble protein concentrations, but a non-significant effect for total nitrogen. Furthermore, selection for soluble protein was reinforced in forests where protein was less available. Selection for low fiber content was significant but unrelated to the fiber concentrations in representative leaf samples of a given forest. There was no relationship (either negative or positive) between the concentration of protein and fiber in the food or in representative samples of leaves. Overall our study suggests that protein selection is influenced by the protein availability in the environment, explaining the sometimes contradictory results in previous studies on protein selection. Am. J. Primatol. 79:e22550, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Random close packing in protein cores.

Science.gov (United States)

Gaines, Jennifer C; Smith, W Wendell; Regan, Lynne; O'Hern, Corey S

2016-03-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈ 0.75, a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈ 0.56, which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy.

Directory of Open Access Journals (Sweden)

Lina Zhang

Full Text Available Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information, PSSM (Position Specific Scoring Matrix, RSA (Relative Solvent Accessibility, and CTD (Composition, Transition, Distribution. The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest, SMO (Sequential Minimal Optimization, NNA (Nearest Neighbor Algorithm, and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew's Correlation Coefficient of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

Science.gov (United States)

Pandey, Naresh; Nobles, Christopher L; Zechiedrich, Lynn; Maresso, Anthony W; Silberg, Jonathan J

2015-05-15

Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein-protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein-protein interactions within whole animals.

Use of Random and Site-Directed Mutagenesis to Probe Protein Structure-Function Relationships: Applied Techniques in the Study of Helicobacter pylori.

Science.gov (United States)

Whitmire, Jeannette M; Merrell, D Scott

2017-01-01

Mutagenesis is a valuable tool to examine the structure-function relationships of bacterial proteins. As such, a wide variety of mutagenesis techniques and strategies have been developed. This chapter details a selection of random mutagenesis methods and site-directed mutagenesis procedures that can be applied to an array of bacterial species. Additionally, the direct application of the techniques to study the Helicobacter pylori Ferric Uptake Regulator (Fur) protein is described. The varied approaches illustrated herein allow the robust investigation of the structural-functional relationships within a protein of interest.

Cotranslational protein folding reveals the selective use of ...

Indian Academy of Sciences (India)

to fold properly by decelerating the translation rate at these sites. Thus the cotranslational protein folding is believed to be true for many proteins and is an important selection factor for the selective codon usage to optimize proper gene expres- sion and function (Komar 2009). A web server CS and S has been created by ...

Selectivity determinants of GPCR-G-protein binding

DEFF Research Database (Denmark)

Flock, Tilman; Hauser, Alexander S; Lund, Nadia

2017-01-01

of the G-protein barcode through distinct residues, like multiple keys (receptors) opening the same lock (G protein) using non-identical cuts. Considering the evolutionary history of GPCRs allows the identification of these selectivity-determining residues. These findings lay the foundation...

Random coil chemical shifts in acidic 8 M urea: Implementation of random coil shift data in NMRView

International Nuclear Information System (INIS)

Schwarzinger, Stephan; Kroon, Gerard J.A.; Foss, Ted R.; Wright, Peter E.; Dyson, H. Jane

2000-01-01

Studies of proteins unfolded in acid or chemical denaturant can help in unraveling events during the earliest phases of protein folding. In order for meaningful comparisons to be made of residual structure in unfolded states, it is necessary to use random coil chemical shifts that are valid for the experimental system under study. We present a set of random coil chemical shifts obtained for model peptides under experimental conditions used in studies of denatured proteins. This new set, together with previously published data sets, has been incorporated into a software interface for NMRView, allowing selection of the random coil data set that fits the experimental conditions best

A selection that reports on protein-protein interactions within a thermophilic bacterium.

Science.gov (United States)

Nguyen, Peter Q; Silberg, Jonathan J

2010-07-01

Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein-protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein-protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AK(Tn)). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75 degrees C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78 degrees C by a vector that coexpresses polypeptides corresponding to residues 1-79 and 80-220 of AK(Tn). In contrast, PQN1 growth was not complemented by AK(Tn) fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein-protein interactions, since AK(Tn)-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein-protein interactions.

Comparative vesicle proteomics reveals selective regulation of protein expression in chestnut blight fungus by a hypovirus.

Science.gov (United States)

Wang, Jinzi; Wang, Fangzhen; Feng, Youjun; Mi, Ke; Chen, Qi; Shang, Jinjie; Chen, Baoshan

2013-01-14

The chestnut blight fungus (Cryphonectria parasitica) and hypovirus constitute a model system to study fungal pathogenesis and mycovirus-host interaction. Knowledge in this field has been gained largely from investigations at gene transcription level so far. Here we report a systematic analysis of the vesicle proteins of the host fungus with/without hypovirus infection. Thirty-three differentially expressed protein spots were identified in the purified vesicle protein samples by two-dimensional electrophoresis and mass spectrometry. Down-regulated proteins were mostly cargo proteins involved in primary metabolism and energy generation and up-regulated proteins were mostly vesicle associated proteins and ABC transporter. A virus-encoded protein p48 was found to have four forms with different molecular mass in vesicles from the virus-infected strain. While a few of the randomly selected differentially expressed proteins were in accordance with their transcription profiles, majority were not in agreement with their mRNA accumulation patterns, suggesting that an extensive post-transcriptional regulation may have occurred in the host fungus upon a hypovirus infection. Copyright © 2012 Elsevier B.V. All rights reserved.

Algorithm for selection of optimized EPR distance restraints for de novo protein structure determination

Science.gov (United States)

Kazmier, Kelli; Alexander, Nathan S.; Meiler, Jens; Mchaourab, Hassane S.

2010-01-01

A hybrid protein structure determination approach combining sparse Electron Paramagnetic Resonance (EPR) distance restraints and Rosetta de novo protein folding has been previously demonstrated to yield high quality models (Alexander et al., 2008). However, widespread application of this methodology to proteins of unknown structures is hindered by the lack of a general strategy to place spin label pairs in the primary sequence. In this work, we report the development of an algorithm that optimally selects spin labeling positions for the purpose of distance measurements by EPR. For the α-helical subdomain of T4 lysozyme (T4L), simulated restraints that maximize sequence separation between the two spin labels while simultaneously ensuring pairwise connectivity of secondary structure elements yielded vastly improved models by Rosetta folding. 50% of all these models have the correct fold compared to only 21% and 8% correctly folded models when randomly placed restraints or no restraints are used, respectively. Moreover, the improvements in model quality require a limited number of optimized restraints, the number of which is determined by the pairwise connectivities of T4L α-helices. The predicted improvement in Rosetta model quality was verified by experimental determination of distances between spin labels pairs selected by the algorithm. Overall, our results reinforce the rationale for the combined use of sparse EPR distance restraints and de novo folding. By alleviating the experimental bottleneck associated with restraint selection, this algorithm sets the stage for extending computational structure determination to larger, traditionally elusive protein topologies of critical structural and biochemical importance. PMID:21074624

An Antibiotic Selection System For Protein Overproducing Bacteria

DEFF Research Database (Denmark)

Rennig, Maja; Nørholm, Morten

2015-01-01

Introduction: Protein overproduction is a major bottleneck for analyses of membrane proteins and for the construction of cell factories. Screening for optimized protein production can be very time consuming. In this study we show that the coupling of antibiotic resistance to poorly produced...... membrane proteins of Escherichia coli can be used as a fast and simple selection system for protein overproduction.Methods: We designed an expression plasmid encoding the gene of interest and an additional, inducible antibiotic resistance marker. Both genes were linked by a hairpin structure...... that translationally couples the genes. Consequently, high expressing gene variants also allow for higher production of the coupled antibiotic resistance marker. Therefore, high expressing gene variants in a library can be determined either by plating the expression library on selection plates or by growing...

Evolving artificial metalloenzymes via random mutagenesis

Science.gov (United States)

Yang, Hao; Swartz, Alan M.; Park, Hyun June; Srivastava, Poonam; Ellis-Guardiola, Ken; Upp, David M.; Lee, Gihoon; Belsare, Ketaki; Gu, Yifan; Zhang, Chen; Moellering, Raymond E.; Lewis, Jared C.

2018-03-01

Random mutagenesis has the potential to optimize the efficiency and selectivity of protein catalysts without requiring detailed knowledge of protein structure; however, introducing synthetic metal cofactors complicates the expression and screening of enzyme libraries, and activity arising from free cofactor must be eliminated. Here we report an efficient platform to create and screen libraries of artificial metalloenzymes (ArMs) via random mutagenesis, which we use to evolve highly selective dirhodium cyclopropanases. Error-prone PCR and combinatorial codon mutagenesis enabled multiplexed analysis of random mutations, including at sites distal to the putative ArM active site that are difficult to identify using targeted mutagenesis approaches. Variants that exhibited significantly improved selectivity for each of the cyclopropane product enantiomers were identified, and higher activity than previously reported ArM cyclopropanases obtained via targeted mutagenesis was also observed. This improved selectivity carried over to other dirhodium-catalysed transformations, including N-H, S-H and Si-H insertion, demonstrating that ArMs evolved for one reaction can serve as starting points to evolve catalysts for others.

Zeolite Nanoparticles for Selective Sorption of Plasma Proteins.

Science.gov (United States)

Rahimi, M; Ng, E-P; Bakhtiari, K; Vinciguerra, M; Ali Ahmad, H; Awala, H; Mintova, S; Daghighi, M; Bakhshandeh Rostami, F; de Vries, M; Motazacker, M M; Peppelenbosch, M P; Mahmoudi, M; Rezaee, F

2015-11-30

The affinity of zeolite nanoparticles (diameter of 8-12 nm) possessing high surface area and high pore volume towards human plasma proteins has been investigated. The protein composition (corona) of zeolite nanoparticles has been shown to be more dependent on the plasma protein concentrations and the type of zeolites than zeolite nanoparticles concentration. The number of proteins present in the corona of zeolite nanoparticles at 100% plasma (in vivo state) is less than with 10% plasma exposure. This could be due to a competition between the proteins to occupy the corona of the zeolite nanoparticles. Moreover, a high selective adsorption for apolipoprotein C-III (APOC-III) and fibrinogen on the zeolite nanoparticles at high plasma concentration (100%) was observed. While the zeolite nanoparticles exposed to low plasma concentration (10%) exhibited a high selective adsorption for immunoglobulin gamma (i.e. IGHG1, IGHG2 and IGHG4) proteins. The zeolite nanoparticles can potentially be used for selectively capture of APOC-III in order to reduce the activation of lipoprotein lipase inhibition during hypertriglyceridemia treatment. The zeolite nanoparticles can be adapted to hemophilic patients (hemophilia A (F-VIII deficient) and hemophilia B (F-IX deficient)) with a risk of bleeding, and thus might be potentially used in combination with the existing therapy.

Experimental Rugged Fitness Landscape in Protein Sequence Space

OpenAIRE

HAYASHI, Yuuki; 相田, 拓洋; TOYOTA, Hitoshi; 伏見, 譲; URABE, Itaru; YOMO, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phag...

A multi-directional rapidly exploring random graph (mRRG) for protein folding

KAUST Repository

Nath, Shuvra Kanti; Thomas, Shawna; Ekenna, Chinwe; Amato, Nancy M.

2012-01-01

Modeling large-scale protein motions, such as those involved in folding and binding interactions, is crucial to better understanding not only how proteins move and interact with other molecules but also how proteins misfold, thus causing many devastating diseases. Robotic motion planning algorithms, such as Rapidly Exploring Random Trees (RRTs), have been successful in simulating protein folding pathways. Here, we propose a new multi-directional Rapidly Exploring Random Graph (mRRG) specifically tailored for proteins. Unlike traditional RRGs which only expand a parent conformation in a single direction, our strategy expands the parent conformation in multiple directions to generate new samples. Resulting samples are connected to the parent conformation and its nearest neighbors. By leveraging multiple directions, mRRG can model the protein motion landscape with reduced computational time compared to several other robotics-based methods for small to moderate-sized proteins. Our results on several proteins agree with experimental hydrogen out-exchange, pulse-labeling, and F-value analysis. We also show that mRRG covers the conformation space better as compared to the other computation methods. Copyright © 2012 ACM.

Selective memory generalization by spatial patterning of protein synthesis.

Science.gov (United States)

O'Donnell, Cian; Sejnowski, Terrence J

2014-04-16

Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

Estimates of selection parameters in protein mutants of spring barley

International Nuclear Information System (INIS)

Gaul, H.; Walther, H.; Seibold, K.H.; Brunner, H.; Mikaelsen, K.

1976-01-01

Detailed studies have been made with induced protein mutants regarding a possible genetic advance in selection including the estimation of the genetic variation and heritability coefficients. Estimates were obtained for protein content and protein yield. The variation of mutant lines in different environments was found to be many times as large as the variation of the line means. The detection of improved protein mutants seems therefore possible only in trials with more than one environment. The heritability of protein content and protein yield was estimated in different sets of environments and was found to be low. However, higher values were found with an increasing number of environments. At least four environments seem to be necessary to obtain reliable heritability estimates. The geneticall component of the variation between lines was significant for protein content in all environmental combinations. For protein yield some environmental combinations only showed significant differences. The expected genetic advance with one selection step was small for both protein traits. Genetically significant differences between protein micromutants give, however, a first indication that selection among protein mutants with small differences seems also possible. (author)

Protein and energy metabolism in two lines of chickens selected for growth on high or low protein diets

DEFF Research Database (Denmark)

Chwalibog, André; Eggum, B O; Sørensen, Peter

1983-01-01

Genetic adaptation was investigated in broilers selected for seven generations on a normal (A) or a low (B) protein diet. Protein and energy metabolism were studied in males from these selected lines fed on a diet of intermediate protein content. All selected birds retained more nitrogen than those...

Whole-body protein turnover response to short-term high-protein diets during weight loss: a randomized controlled trial

Science.gov (United States)

Objective: Determine whole-body protein turnover responses to high protein diets during weight loss. Design: Thirty-nine adults (age, 21 ± 1 yr; VO2peak, 48 ± 1 ml'kg-1'min-1; body mass index, 25 ± 1 kg•m2) were randomized to diets providing protein at the recommend dietary allowance (RDA), 2X-RD...

Quantum-Chemical Electron Densities of Proteins and of Selected Protein Sites from Subsystem Density Functional Theory

NARCIS (Netherlands)

Kiewisch, K.; Jacob, C.R.; Visscher, L.

2013-01-01

The ability to calculate accurate electron densities of full proteins or of selected sites in proteins is a prerequisite for a fully quantum-mechanical calculation of protein-protein and protein-ligand interaction energies. Quantum-chemical subsystem methods capable of treating proteins and other

40 CFR 761.308 - Sample selection by random number generation on any two-dimensional square grid.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sample selection by random number... § 761.79(b)(3) § 761.308 Sample selection by random number generation on any two-dimensional square... area created in accordance with paragraph (a) of this section, select two random numbers: one each for...

Applications of random forest feature selection for fine-scale genetic population assignment.

Science.gov (United States)

Sylvester, Emma V A; Bentzen, Paul; Bradbury, Ian R; Clément, Marie; Pearce, Jon; Horne, John; Beiko, Robert G

2018-02-01

Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F ST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon ( Salmo salar ) and a published SNP data set for Alaskan Chinook salmon ( Oncorhynchus tshawytscha ). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than F ST -selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F ST -selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.

Purification-Free, Target-Selective Immobilization of a Protein from Cell Lysates.

Science.gov (United States)

Cha, Jaehyun; Kwon, Inchan

2018-02-27

Protein immobilization has been widely used for laboratory experiments and industrial processes. Preparation of a recombinant protein for immobilization usually requires laborious and expensive purification steps. Here, a novel purification-free, target-selective immobilization technique of a protein from cell lysates is reported. Purification steps are skipped by immobilizing a target protein containing a clickable non-natural amino acid (p-azidophenylalanine) in cell lysates onto alkyne-functionalized solid supports via bioorthogonal azide-alkyne cycloaddition. In order to achieve a target protein-selective immobilization, p-azidophenylalanine was introduced into an exogenous target protein, but not into endogenous non-target proteins using host cells with amber codon-free genomic DNAs. Immobilization of superfolder fluorescent protein (sfGFP) from cell lysates is as efficient as that of the purified sfGFP. Using two fluorescent proteins (sfGFP and mCherry), the authors also demonstrated that the target proteins are immobilized with a minimal immobilization of non-target proteins (target-selective immobilization). © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Statistical distributions of optimal global alignment scores of random protein sequences

Directory of Open Access Journals (Sweden)

Tang Jiaowei

2005-10-01

Full Text Available Abstract Background The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined. Results In this study, random and real but unrelated sequences prepared in six different ways were selected as reference datasets to obtain their respective statistical distributions of global alignment scores. All alignments were carried out with the Needleman-Wunsch algorithm and optimal scores were fitted to the Gumbel, normal and gamma distributions respectively. The three-parameter gamma distribution performs the best as the theoretical distribution function of global alignment scores, as it agrees perfectly well with the distribution of alignment scores. The normal distribution also agrees well with the score distribution frequencies when the shape parameter of the gamma distribution is sufficiently large, for this is the scenario when the normal distribution can be viewed as an approximation of the gamma distribution. Conclusion We have shown that the optimal global alignment scores of random protein sequences fit the three-parameter gamma distribution function. This would be useful for the inference of homology between sequences whose relationship is unknown, through the evaluation of gamma distribution significance between sequences.

Interference-aware random beam selection for spectrum sharing systems

KAUST Repository

Abdallah, Mohamed M.

2012-09-01

Spectrum sharing systems have been introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary transmitter equipped with multiple antennas, our schemes select a random beam, among a set of power- optimized orthogonal random beams, that maximizes the capacity of the secondary link while satisfying the interference constraint at the primary receiver for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the signal-to-noise and interference ratio (SINR) statistics as well as the capacity of the secondary link. Finally, we present numerical results that study the effect of system parameters including number of beams and the maximum transmission power on the capacity of the secondary link attained using the proposed schemes. © 2012 IEEE.

Interference-aware random beam selection for spectrum sharing systems

KAUST Repository

Abdallah, Mohamed M.; Sayed, Mostafa M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

2012-01-01

. In this paper, we develop interference-aware random beam selection schemes that provide enhanced throughput for the secondary link under the condition that the interference observed at the primary link is within a predetermined acceptable value. For a secondary

Changing folding and binding stability in a viral coat protein: a comparison between substitutions accessible through mutation and those fixed by natural selection.

Science.gov (United States)

Miller, Craig R; Lee, Kuo Hao; Wichman, Holly A; Ytreberg, F Marty

2014-01-01

Previous studies have shown that most random amino acid substitutions destabilize protein folding (i.e. increase the folding free energy). No analogous studies have been carried out for protein-protein binding. Here we use a structure-based model of the major coat protein in a simple virus, bacteriophage φX174, to estimate the free energy of folding of a single coat protein and binding of five coat proteins within a pentameric unit. We confirm and extend previous work in finding that most accessible substitutions destabilize both protein folding and protein-protein binding. We compare the pool of accessible substitutions with those observed among the φX174-like wild phage and in experimental evolution with φX174. We find that observed substitutions have smaller effects on stability than expected by chance. An analysis of adaptations at high temperatures suggests that selection favors either substitutions with no effect on stability or those that simultaneously stabilize protein folding and slightly destabilize protein binding. We speculate that these mutations might involve adjusting the rate of capsid assembly. At normal laboratory temperature there is little evidence of directional selection. Finally, we show that cumulative changes in stability are highly variable; sometimes they are well beyond the bounds of single substitution changes and sometimes they are not. The variation leads us to conclude that phenotype selection acts on more than just stability. Instances of larger cumulative stability change (never via a single substitution despite their availability) lead us to conclude that selection views stability at a local, not a global, level.

The signature of positive selection at randomly chosen loci.

OpenAIRE

Przeworski, Molly

2002-01-01

In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequ...

Simulated Performance Evaluation of a Selective Tracker Through Random Scenario Generation

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar

2006-01-01

performance assessment. Therefore, a random target motion scenario is adopted. Its implementation in particular for testing the proposed selective track splitting algorithm using Kalman filters is investigated through a number of performance parameters which gives the activity profile of the tracking scenario......  The paper presents a simulation study on the performance of a target tracker using selective track splitting filter algorithm through a random scenario implemented on a digital signal processor.  In a typical track splitting filter all the observation which fall inside a likelihood ellipse...... are used for update, however, in our proposed selective track splitting filter less number of observations are used for track update.  Much of the previous performance work [1] has been done on specific (deterministic) scenarios. One of the reasons for considering the specific scenarios, which were...

Minimization over randomly selected lines

Directory of Open Access Journals (Sweden)

Ismet Sahin

2013-07-01

Full Text Available This paper presents a population-based evolutionary optimization method for minimizing a given cost function. The mutation operator of this method selects randomly oriented lines in the cost function domain, constructs quadratic functions interpolating the cost function at three different points over each line, and uses extrema of the quadratics as mutated points. The crossover operator modifies each mutated point based on components of two points in population, instead of one point as is usually performed in other evolutionary algorithms. The stopping criterion of this method depends on the number of almost degenerate quadratics. We demonstrate that the proposed method with these mutation and crossover operations achieves faster and more robust convergence than the well-known Differential Evolution and Particle Swarm algorithms.

Selection for altruism through random drift in variable size populations

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Houchmandzadeh Bahram

2012-05-01

Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.

Selection bias and subject refusal in a cluster-randomized controlled trial

Directory of Open Access Journals (Sweden)

Rochelle Yang

2017-07-01

Full Text Available Abstract Background Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. Methods The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. Results There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1

Identification of Protein Complexes from Tandem Affinity Purification/Mass Spectrometry Data via Biased Random Walk.

Science.gov (United States)

Cai, Bingjing; Wang, Haiying; Zheng, Huiru; Wang, Hui

2015-01-01

Systematic identification of protein complexes from protein-protein interaction networks (PPIs) is an important application of data mining in life science. Over the past decades, various new clustering techniques have been developed based on modelling PPIs as binary relations. Non-binary information of co-complex relations (prey/bait) in PPIs data derived from tandem affinity purification/mass spectrometry (TAP-MS) experiments has been unfairly disregarded. In this paper, we propose a Biased Random Walk based algorithm for detecting protein complexes from TAP-MS data, resulting in the random walk with restarting baits (RWRB). RWRB is developed based on Random walk with restart. The main contribution of RWRB is the incorporation of co-complex relations in TAP-MS PPI networks into the clustering process, by implementing a new restarting strategy during the process of random walk. Through experimentation on un-weighted and weighted TAP-MS data sets, we validated biological significance of our results by mapping them to manually curated complexes. Results showed that, by incorporating non-binary, co-membership information, significant improvement has been achieved in terms of both statistical measurements and biological relevance. Better accuracy demonstrates that the proposed method outperformed several state-of-the-art clustering algorithms for the detection of protein complexes in TAP-MS data.

Site-Selective Conjugation of Native Proteins with DNA

DEFF Research Database (Denmark)

Trads, Julie Brender; Tørring, Thomas; Gothelf, Kurt Vesterager

2017-01-01

Conjugation of DNA to proteins is increasingly used in academia and industry to provide proteins with tags for identification or handles for hybridization to other DNA strands. Assay technologies such as immuno-PCR and proximity ligation and the imaging technology DNA-PAINT require DNA-protein....... The introduction of a bioorthogonal handle at a specific position of a protein by recombinant techniques provides an excellent approach to site-specific conjugation, but for many laboratories and for applications where several proteins are to be labeled, the expression of recombinant proteins may be cumbersome...... conjugates. In DNA nanotechnology, the DNA handle is exploited to precisely position proteins by self-assembly. For these applications, site-selective conjugation is almost always desired because fully functional proteins are required to maintain the specificity of antibodies and the activity of enzymes...

Free Energy Self-Averaging in Protein-Sized Random Heteropolymers

International Nuclear Information System (INIS)

Chuang, Jeffrey; Grosberg, Alexander Yu.; Kardar, Mehran

2001-01-01

Current theories of heteropolymers are inherently macroscopic, but are applied to mesoscopic proteins. To compute the free energy over sequences, one assumes self-averaging -- a property established only in the macroscopic limit. By enumerating the states and energies of compact 18, 27, and 36mers on a lattice with an ensemble of random sequences, we test the self-averaging approximation. We find that fluctuations in the free energy between sequences are weak, and that self-averaging is valid at the scale of real proteins. The results validate sequence design methods which exponentially speed up computational design and simplify experimental realizations

Targeted Diazotransfer Reagents Enable Selective Modification of Proteins with Azides.

Science.gov (United States)

Lohse, Jonas; Swier, Lotteke J Y M; Oudshoorn, Ruben C; Médard, Guillaume; Kuster, Bernhard; Slotboom, Dirk-Jan; Witte, Martin D

2017-04-19

In chemical biology, azides are used to chemically manipulate target structures in a bioorthogonal manner for a plethora of applications ranging from target identification to the synthesis of homogeneously modified protein conjugates. While a variety of methods have been established to introduce the azido group into recombinant proteins, a method that directly converts specific amino groups in endogenous proteins is lacking. Here, we report the first biotin-tethered diazotransfer reagent DtBio and demonstrate that it selectively modifies the model proteins streptavidin and avidin and the membrane protein BioY on cell surface. The reagent converts amines in the proximity of the binding pocket to azides and leaves the remaining amino groups in streptavidin untouched. Reagents of this novel class will find use in target identification as well as the selective functionalization and bioorthogonal protection of proteins.

Interference-aware random beam selection schemes for spectrum sharing systems

KAUST Repository

Abdallah, Mohamed; Qaraqe, Khalid; Alouini, Mohamed-Slim

2012-01-01

users. In this work, we develop interference-aware random beam selection schemes that provide enhanced performance for the secondary network under the condition that the interference observed by the receivers of the primary network is below a

A protein engineered to bind uranyl selectively and with femtomolar affinity

Science.gov (United States)

Zhou, Lu; Bosscher, Mike; Zhang, Changsheng; Özçubukçu, Salih; Zhang, Liang; Zhang, Wen; Li, Charles J.; Liu, Jianzhao; Jensen, Mark P.; Lai, Luhua; He, Chuan

2014-03-01

Uranyl (UO22+), the predominant aerobic form of uranium, is present in the ocean at a concentration of ~3.2 parts per 109 (13.7 nM) however, the successful enrichment of uranyl from this vast resource has been limited by the high concentrations of metal ions of similar size and charge, which makes it difficult to design a binding motif that is selective for uranyl. Here we report the design and rational development of a uranyl-binding protein using a computational screening process in the initial search for potential uranyl-binding sites. The engineered protein is thermally stable and offers very high affinity and selectivity for uranyl with a Kd of 7.4 femtomolar (fM) and >10,000-fold selectivity over other metal ions. We also demonstrated that the uranyl-binding protein can repeatedly sequester 30-60% of the uranyl in synthetic sea water. The chemical strategy employed here may be applied to engineer other selective metal-binding proteins for biotechnology and remediation applications.

The effect of palatability of protein source on dietary selection in dairy calves.

Science.gov (United States)

Miller-Cushon, E K; Terré, M; DeVries, T J; Bach, A

2014-07-01

Evidence has shown that soybean meal is perceived as more palatable than canola meal by dairy calves in short-term preference tests. This study evaluated the effect of protein source on longer-term dietary selection of dairy calves. In experiment 1, 40 Holstein bull calves (11.4 ± 4.3 d of age) were randomly assigned to 1 of 2 choice diets for 6 wk: base starter pellet (S; 12% crude protein; CP) and high-protein pellet (40% CP) containing either (1) soybean meal (SB) or (2) canola meal (CM). In wk 7 to 8, all calves were offered a single pelleted diet containing the protein source to which they were previously exposed. In experiment 2, 22 Holstein bull calves (9.9 ± 4.6d of age) were offered, for 6 wk, a choice of 2 mixed pelleted diets: (1) 70% S and 30% SB (SB mix), or (2) 70% S and 30% CM (CM mix). In wk 7 to 8, calves were randomly assigned to 1 of 2 choice diets, as in experiment 1: (1) SB + S, or (2) CM + S. All feeds were provided ad libitum. Calves received 6 L/d of milk replacer [0.75 kg/d of dry matter (DM)] for the duration of both experiments. Feed intake was recorded daily and calves were weighed every 14 d. Feeds were sampled weekly to analyze DM and nutrient intake. Mixed diets in experiment 2 were analyzed for CP in wk 4 and 6 to assess feed sorting (calculated as actual CP intake as a percentage of predicted intake). In experiment 1, calves offered SB + S in wk 1 to 6 consumed more high-protein pellet than calves offered CM + S [73 vs. 42% of DM intake (DMI)] and, consequently, more CP (168 vs. 117 g/d). Solid feed DMI and average daily gain were similar between treatments. When offered a single diet in wk 7 to 8, calves offered starter containing soybean meal increased intake to a greater extent than calves offered the starter containing canola meal. In experiment 2, calves preferred the SB mix to CM mix (preference ratio: 0.7). Calves consumed more CP than predicted from SB mix in wk 4 and 6 (108 ± 2.0%), indicating that they were sorting in

Randomized controlled trial of a protein substitute with prolonged release on the protein status of children with phenylketonuria.

Science.gov (United States)

Giovannini, Marcello; Riva, Enrica; Salvatici, Elisabetta; Cefalo, Graziella; Radaelli, Giovanni

2014-01-01

To examine whether a phenylalanine-free protein substitute with prolonged release may be beneficial to the protein status of children with phenylketonuria (PKU) compared to conventional substitutes. Sixty children with PKU, 7 to 16 years of age, were randomly allocated to receive either a prolonged-release (test) or the current conventional protein substitute for 30 days. Subjects were additionally sex and age matched with 60 subjects with mild hyperphenylalaninemia and 60 unaffected subjects. The protein status in children with PKU was assessed by albumin, transthyretin, and retinol-binding protein (RBP), and changes throughout the trial period were the primary outcome measures. Children with PKU did not differ in anthropometry from children with mild hyperphenylalaninemia or unaffected children but they ingested lower amounts of proteins (p phenylketonuria.

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

International Nuclear Information System (INIS)

Yu, Zhiyong

2013-01-01

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

2013-12-15

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

Modular protein switches derived from antibody mimetic proteins.

Science.gov (United States)

Nicholes, N; Date, A; Beaujean, P; Hauk, P; Kanwar, M; Ostermeier, M

2016-02-01

Protein switches have potential applications as biosensors and selective protein therapeutics. Protein switches built by fusion of proteins with the prerequisite input and output functions are currently developed using an ad hoc process. A modular switch platform in which existing switches could be readily adapted to respond to any ligand would be advantageous. We investigated the feasibility of a modular protein switch platform based on fusions of the enzyme TEM-1 β-lactamase (BLA) with two different antibody mimetic proteins: designed ankyrin repeat proteins (DARPins) and monobodies. We created libraries of random insertions of the gene encoding BLA into genes encoding a DARPin or a monobody designed to bind maltose-binding protein (MBP). From these libraries, we used a genetic selection system for β-lactamase activity to identify genes that conferred MBP-dependent ampicillin resistance to Escherichia coli. Some of these selected genes encoded switch proteins whose enzymatic activity increased up to 14-fold in the presence of MBP. We next introduced mutations into the antibody mimetic domain of these switches that were known to cause binding to different ligands. To different degrees, introduction of the mutations resulted in switches with the desired specificity, illustrating the potential modularity of these platforms. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD

Directory of Open Access Journals (Sweden)

A. Shamsoddini

2017-09-01

Full Text Available Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method

Science.gov (United States)

Shamsoddini, A.; Aboodi, M. R.; Karami, J.

2017-09-01

Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

Velocity and Dispersion for a Two-Dimensional Random Walk

International Nuclear Information System (INIS)

Li Jinghui

2009-01-01

In the paper, we consider the transport of a two-dimensional random walk. The velocity and the dispersion of this two-dimensional random walk are derived. It mainly show that: (i) by controlling the values of the transition rates, the direction of the random walk can be reversed; (ii) for some suitably selected transition rates, our two-dimensional random walk can be efficient in comparison with the one-dimensional random walk. Our work is motivated in part by the challenge to explain the unidirectional transport of motor proteins. When the motor proteins move at the turn points of their tracks (i.e., the cytoskeleton filaments and the DNA molecular tubes), some of our results in this paper can be used to deal with the problem. (general)

Superoxide dismutase 1 is positively selected to minimize protein aggregation in great apes

DEFF Research Database (Denmark)

Dasmeh, Pouria; Kepp, Kasper Planeta

2017-01-01

Positive (adaptive) selection has recently been implied in human superoxide dismutase 1 (SOD1), a highly abundant antioxidant protein with energy signaling and antiaging functions, one of very few examples of direct selection on a human protein product (exon); the molecular drivers...... and SOD1 aggregates and triggered by aging. Our study thus marks an example of direct selection for a particular chemical phenotype (high net charge and stability) in a single human protein with possible implications for the evolution of aging....... of this selection are unknown. We mapped 30 extant SOD1 sequences to the recently established mammalian species tree and inferred ancestors, key substitutions, and signatures of selection during the protein's evolution. We detected elevated substitution rates leading to great apes (Hominidae) at ~1 per 2 million...

Automatic structure classification of small proteins using random forest

Directory of Open Access Journals (Sweden)

Hirst Jonathan D

2010-07-01

Full Text Available Abstract Background Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the similarity of its structural descriptors to those of a template structure with an equal number of secondary structure elements (SSEs. An initial assessment of random forest is carried out for domains consisting of three SSEs. The usability of random forest in classifying larger domains is demonstrated by applying it to domains consisting of four, five and six SSEs. Results Random forest, trained on SCOP version 1.69, achieves a predictive accuracy of up to 94% on an independent and non-overlapping test set derived from SCOP version 1.73. For classification to the SCOP Class, Fold, Super-family or Family levels, the predictive quality of the model in terms of Matthew's correlation coefficient (MCC ranged from 0.61 to 0.83. As the number of constituent SSEs increases the MCC for classification to different structural levels decreases. Conclusions The utility of random forest in classifying domains from the place-holder classes of SCOP to the true Class, Fold, Super-family or Family levels is demonstrated. Issues such as introduction of a new structural level in SCOP and the merger of singleton levels can also be addressed using random forest. A real-world scenario is mimicked by predicting the classification for those protein structures from the PDB, which are yet to be assigned to the SCOP classification hierarchy.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

Science.gov (United States)

Lindsay, Grace W.

2017-01-01

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (�

Performance Evaluation of User Selection Protocols in Random Networks with Energy Harvesting and Hardware Impairments

Directory of Open Access Journals (Sweden)

Tan Nhat Nguyen

2016-01-01

Full Text Available In this paper, we evaluate performances of various user selection protocols under impact of hardware impairments. In the considered protocols, a Base Station (BS selects one of available Users (US to serve, while the remaining USs harvest the energy from the Radio Frequency (RF transmitted by the BS. We assume that all of the US randomly appear around the BS. In the Random Selection Protocol (RAN, the BS randomly selects a US to transmit the data. In the second proposed protocol, named Minimum Distance Protocol (MIND, the US that is nearest to the BS will be chosen. In the Optimal Selection Protocol (OPT, the US providing the highest channel gain between itself and the BS will be served. For performance evaluation, we derive exact and asymptotic closed-form expressions of average Outage Probability (OP over Rayleigh fading channels. We also consider average harvested energy per a US. Finally, Monte-Carlo simulations are then performed to verify the theoretical results.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

Science.gov (United States)

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

Membrane proteins bind lipids selectively to modulate their structure and function.

Science.gov (United States)

Laganowsky, Arthur; Reading, Eamonn; Allison, Timothy M; Ulmschneider, Martin B; Degiacomi, Matteo T; Baldwin, Andrew J; Robinson, Carol V

2014-06-05

Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to determine the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate, in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar experiments identify AmtB as being highly selective for phosphatidylglycerol, prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resolution structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane

The reliability of randomly selected final year pharmacy students in ...

African Journals Online (AJOL)

Employing ANOVA, factorial experimental analysis, and the theory of error, reliability studies were conducted on the assessment of the drug product chloroquine phosphate tablets. The G–Study employed equal numbers of the factors for uniform control, and involved three analysts (randomly selected final year Pharmacy ...

Vitamin D and C-Reactive Protein: A Mendelian Randomization Study.

Directory of Open Access Journals (Sweden)

Marte C Liefaard

Full Text Available Vitamin D deficiency is widely prevalent and has been associated with many diseases. It has been suggested that vitamin D has effects on the immune system and inhibits inflammation. The aim of our study was to investigate whether vitamin D has an inhibitory effect on systemic inflammation by assessing the association between serum levels of vitamin D and C-reactive protein. We studied the association between serum 25-hydroxyvitamin D and C-reactive protein through linear regression in 9,649 participants of the Rotterdam Study, an observational, prospective population-based cohort study. We used genetic variants related to vitamin D and CRP to compute a genetic risk score and perform bi-directional Mendelian randomization analysis. In linear regression adjusted for age, sex, cohort and other confounders, natural log-transformed CRP decreased with 0.06 (95% CI: -0.08, -0.03 unit per standard deviation increase in 25-hydroxyvitamin D. Bi-directional Mendelian randomization analyses showed no association between the vitamin D genetic risk score and lnCRP (Beta per SD = -0.018; p = 0.082 or the CRP genetic risk score and 25-hydroxyvitamin D (Beta per SD = 0.001; p = 0.998. In conclusion, higher levels of Vitamin D are associated with lower levels of C-reactive protein. In this study we did not find evidence for this to be the result of a causal relationship.

Positive selection neighboring functionally essential sites and disease-implicated regions of mammalian reproductive proteins.

LENUS (Irish Health Repository)

Morgan, Claire C

2010-01-01

ABSTRACT: BACKGROUND: Reproductive proteins are central to the continuation of all mammalian species. The evolution of these proteins has been greatly influenced by environmental pressures induced by pathogens, rival sperm, sexual selection and sexual conflict. Positive selection has been demonstrated in many of these proteins with particular focus on primate lineages. However, the mammalia are a diverse group in terms of mating habits, population sizes and germ line generation times. We have examined the selective pressures at work on a number of novel reproductive proteins across a wide variety of mammalia. RESULTS: We show that selective pressures on reproductive proteins are highly varied. Of the 10 genes analyzed in detail, all contain signatures of positive selection either across specific sites or in specific lineages or a combination of both. Our analysis of SP56 and Col1a1 are entirely novel and the results show positively selected sites present in each gene. Our findings for the Col1a1 gene are suggestive of a link between positive selection and severe disease type. We find evidence in our dataset to suggest that interacting proteins are evolving in symphony: most likely to maintain interacting functionality. CONCLUSION: Our in silico analyses show positively selected sites are occurring near catalytically important regions suggesting selective pressure to maximize efficient fertilization. In those cases where a mechanism of protein function is not fully understood, the sites presented here represent ideal candidates for mutational study. This work has highlighted the widespread rate heterogeneity in mutational rates across the mammalia and specifically has shown that the evolution of reproductive proteins is highly varied depending on the species and interacting partners. We have shown that positive selection and disease are closely linked in the Col1a1 gene.

Course 12: Proteins: Structural, Thermodynamic and Kinetic Aspects

Science.gov (United States)

Finkelstein, A. V.

1 Introduction 2 Overview of protein architectures and discussion of physical background of their natural selection 2.1 Protein structures 2.2 Physical selection of protein structures 3 Thermodynamic aspects of protein folding 3.1 Reversible denaturation of protein structures 3.2 What do denatured proteins look like? 3.3 Why denaturation of a globular protein is the first-order phase transition 3.4 "Gap" in energy spectrum: The main characteristic that distinguishes protein chains from random polymers 4 Kinetic aspects of protein folding 4.1 Protein folding in vivo 4.2 Protein folding in vitro (in the test-tube) 4.3 Theory of protein folding rates and solution of the Levinthal paradox

Site-selective protein-modification chemistry for basic biology and drug development.

Science.gov (United States)

Krall, Nikolaus; da Cruz, Filipa P; Boutureira, Omar; Bernardes, Gonçalo J L

2016-02-01

Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

Protein construct storage: Bayesian variable selection and prediction with mixtures.

Science.gov (United States)

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

Random selection of items. Selection of n1 samples among N items composing a stratum

International Nuclear Information System (INIS)

Jaech, J.L.; Lemaire, R.J.

1987-02-01

STR-224 provides generalized procedures to determine required sample sizes, for instance in the course of a Physical Inventory Verification at Bulk Handling Facilities. The present report describes procedures to generate random numbers and select groups of items to be verified in a given stratum through each of the measurement methods involved in the verification. (author). 3 refs

A conserved mammalian protein interaction network.

Directory of Open Access Journals (Sweden)

Åsa Pérez-Bercoff

Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

Science.gov (United States)

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

Semiotic Selection of Mutated or Misfolded Receptor Proteins

DEFF Research Database (Denmark)

Giorgi, Franco; Bruni, Luis Emilio; Maggio, Roberto

2013-01-01

contention that the plasma membrane acts as the locus where several contextual cues may be integrated. As such it allows the semiotic selection of those receptor configurations that provide cells with the minimum essential requirements for agency. The occurrence of protein misfolding makes it impossible...... focused on the significance and semiotic nature of the interplay between membrane receptors and the epigenetic control of gene expression, as mediated by the control of mismatched repairing and protein folding mechanisms....

Widespread Positive Selection Drives Differentiation of Centromeric Proteins in the Drosophila melanogaster subgroup.

Science.gov (United States)

Beck, Emily A; Llopart, Ana

2015-11-25

Rapid evolution of centromeric satellite repeats is thought to cause compensatory amino acid evolution in interacting centromere-associated kinetochore proteins. Cid, a protein that mediates kinetochore/centromere interactions, displays particularly high amino acid turnover. Rapid evolution of both Cid and centromeric satellite repeats led us to hypothesize that the apparent compensatory evolution may extend to interacting partners in the Condensin I complex (i.e., SMC2, SMC4, Cap-H, Cap-D2, and Cap-G) and HP1s. Missense mutations in these proteins often result in improper centromere formation and aberrant chromosome segregation, thus selection for maintained function and coevolution among proteins of the complex is likely strong. Here, we report evidence of rapid evolution and recurrent positive selection in seven centromere-associated proteins in species of the Drosophila melanogaster subgroup, and further postulate that positive selection on these proteins could be a result of centromere drive and compensatory changes, with kinetochore proteins competing for optimal spindle attachment.

The mathematics of random mutation and natural selection for multiple simultaneous selection pressures and the evolution of antimicrobial drug resistance.

Science.gov (United States)

Kleinman, Alan

2016-12-20

The random mutation and natural selection phenomenon act in a mathematically predictable behavior, which when understood leads to approaches to reduce and prevent the failure of the use of these selection pressures when treating infections and cancers. The underlying principle to impair the random mutation and natural selection phenomenon is to use combination therapy, which forces the population to evolve to multiple selection pressures simultaneously that invoke the multiplication rule of probabilities simultaneously as well. Recently, it has been seen that combination therapy for the treatment of malaria has failed to prevent the emergence of drug-resistant variants. Using this empirical example and the principles of probability theory, the derivation of the equations describing this treatment failure is carried out. These equations give guidance as to how to use combination therapy for the treatment of cancers and infectious diseases and prevent the emergence of drug resistance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

Science.gov (United States)

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

Exploiting translational coupling for the selection of cells producing toxic recombinant proteins from expression vectors.

Science.gov (United States)

Tagliavia, Marcello; Cuttitta, Angela

2016-01-01

High rates of plasmid instability are associated with the use of some expression vectors in Escherichia coli, resulting in the loss of recombinant protein expression. This is due to sequence alterations in vector promoter elements caused by the background expression of the cloned gene, which leads to the selection of fast-growing, plasmid-containing cells that do not express the target protein. This phenomenon, which is worsened when expressing toxic proteins, results in preparations containing very little or no recombinant protein, or even in clone loss; however, no methods to prevent loss of recombinant protein expression are currently available. We have exploited the phenomenon of translational coupling, a mechanism of prokaryotic gene expression regulation, in order to select cells containing plasmids still able to express recombinant proteins. Here we designed an expression vector in which the cloned gene and selection marker are co-expressed. Our approach allowed for the selection of the recombinant protein-expressing cells and proved effective even for clones encoding toxic proteins.

Application of the random coil index to studying protein flexibility

Energy Technology Data Exchange (ETDEWEB)

Berjanskii, Mark V.; Wishart, David S. [University of Alberta, Department of Computing Science (Canada)], E-mail: david.wishart@ualberta.ca

2008-01-15

Protein flexibility lies at the heart of many protein-ligand binding events and enzymatic activities. However, the experimental measurement of protein motions is often difficult, tedious and error-prone. As a result, there is a considerable interest in developing simpler and faster ways of quantifying protein flexibility. Recently, we described a method, called Random Coil Index (RCI), which appears to be able to quantitatively estimate model-free order parameters and flexibility in protein structural ensembles using only backbone chemical shifts. Because of its potential utility, we have undertaken a more detailed investigation of the RCI method in an attempt to ascertain its underlying principles, its general utility, its sensitivity to chemical shift errors, its sensitivity to data completeness, its applicability to other proteins, and its general strengths and weaknesses. Overall, we find that the RCI method is very robust and that it represents a useful addition to traditional methods of studying protein flexibility. We have implemented many of the findings and refinements reported here into a web server that allows facile, automated predictions of model-free order parameters, MD RMSF and NMR RMSD values directly from backbone {sup 1}H, {sup 13}C and {sup 15}N chemical shift assignments. The server is available at http: //wishart.biology.ualberta.ca/rcihttp://wishart.biology.ualberta.ca/rci.

Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

Directory of Open Access Journals (Sweden)

Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

The signature of positive selection at randomly chosen loci.

Science.gov (United States)

Przeworski, Molly

2002-03-01

In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.

Integrative approaches to the prediction of protein functions based on the feature selection

Directory of Open Access Journals (Sweden)

Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

Selective radiolabeling of cell surface proteins to a high specific activity

International Nuclear Information System (INIS)

Thompson, J.A.; Lau, A.L.; Cunningham, D.D.

1987-01-01

A procedure was developed for selective radiolabeling of membrane proteins on cells to higher specific activities than possible with available techniques. Cell surface amino groups were derivatized with 125 I-(hydroxyphenyl)propionyl groups via 125 I-sulfosuccinimidyl (hydroxyphenyl)propionate ( 125 II-sulfo-SHPP). This reagent preferentially labeled membrane proteins exposed at the cell surface of erythrocytes as assessed by the degree of radiolabel incorporation into erythrocyte ghost proteins and hemoglobin. Comparison with the lactoperoxidase-[ 125 I]iodide labeling technique revealed that 125 I-sulfo-SHPP labeled cell surface proteins to a much higher specific activity and hemoglobin to a much lower specific activity. Additionally, this reagent was used for selective radiolabeling of membrane proteins on the cytoplasmic face of the plasma membrane by blocking exofacial amino groups with uniodinated sulfo-SHPP, lysing the cells, and then incubating them with 125 I-sulfo-SHPP. Exclusive labeling of either side of the plasma membrane was demonstrated by the labeling of some marker proteins with well-defined spacial orientations on erythroctyes. Transmembrane proteins such as the epidermal growth factor receptor on cultured cells could also be labeled differentially from either side of the plasma membrane

Differential privacy-based evaporative cooling feature selection and classification with relief-F and random forests.

Science.gov (United States)

Le, Trang T; Simmons, W Kyle; Misaki, Masaya; Bodurka, Jerzy; White, Bill C; Savitz, Jonathan; McKinney, Brett A

2017-09-15

Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classification accuracy but must be incorporated carefully into cross-validation to avoid overfitting. Recently, feature selection methods based on differential privacy, such as differentially private random forests and reusable holdout sets, have been proposed. However, for domains such as bioinformatics, where the number of features is much larger than the number of observations p≫n , these differential privacy methods are susceptible to overfitting. We introduce private Evaporative Cooling, a stochastic privacy-preserving machine learning algorithm that uses Relief-F for feature selection and random forest for privacy preserving classification that also prevents overfitting. We relate the privacy-preserving threshold mechanism to a thermodynamic Maxwell-Boltzmann distribution, where the temperature represents the privacy threshold. We use the thermal statistical physics concept of Evaporative Cooling of atomic gases to perform backward stepwise privacy-preserving feature selection. On simulated data with main effects and statistical interactions, we compare accuracies on holdout and validation sets for three privacy-preserving methods: the reusable holdout, reusable holdout with random forest, and private Evaporative Cooling, which uses Relief-F feature selection and random forest classification. In simulations where interactions exist between attributes, private Evaporative Cooling provides higher classification accuracy without overfitting based on an independent validation set. In simulations without interactions, thresholdout with random forest and private Evaporative Cooling give comparable accuracies. We also apply these privacy methods to human brain resting-state fMRI data from a study of major depressive disorder. Code

A unified conformational selection and induced fit approach to protein-peptide docking.

Directory of Open Access Journals (Sweden)

Mikael Trellet

Full Text Available Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II, flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.

Investigation of selection methods im mutation breeding of barley for protein quantity and quality

International Nuclear Information System (INIS)

Ulonska, E.; Gaul, H.; Baumer, M.; Gesellschaft fuer Strahlen- und Umweltforschung m.b.H., Gruenbach

1975-01-01

This mutation breeding programme is investigating the qualification of micro-mutations for the selection of improved protein quality and quantity. Normally, improvement of protein content in micro-mutations is rather small. Therefore, it is important to develop methods and conditions of selection being (a) capable of measuring these small deviations in protein content and quality, and (b) simple to use. In two experiments carried out in 1971 and 1972 nitrogen fertilization was found to be the most important factor in the improvement of selection conditions. There is a highly significant negative correlation between crude protein content and the standard deviation; i.e. the higher the content of crude protein, the lower the variation coefficient. This in turn leads to an increase of genetic variation necessary for better selection progress. Nitrogen fertilization, especially during ear emergence, covers environmental influences - e.g., planting space, sowing rate, growing in different plots (6, 3, 2, 1 rows or in half-ear hills) - to a great extent. Thus, by applying high doses of nitrogen dressings comparable results can be achieved. In an overall selection experiment (testing the entire crossing and mutation material available at Weihenstephan in a stepwise selection from 1971 to 1973) and two selection experiments conducted in 1971 to 1973 with micro-mutants - variety Nota, 4 times X-rayed and the naked barley strain 1606 treated once with EMS - significant selection results were found. (author)

Native whey induces higher and faster leucinemia than other whey protein supplements and milk: A randomized controlled trial

Science.gov (United States)

Resistance exercise and protein intake are both strong stimuli for muscle protein synthesis. The potential for a protein to acutely increase muscle protein synthesis seems partly dependent on absorption kinetics and the amino acid composition. The aim of this double-blinded randomized cross-over stu...

In vitro Selection and Interaction Studies of a DNA Aptamer Targeting Protein A.

Directory of Open Access Journals (Sweden)

Regina Stoltenburg

Full Text Available A new DNA aptamer targeting Protein A is presented. The aptamer was selected by use of the FluMag-SELEX procedure. The SELEX technology (Systematic Evolution of Ligands by EXponential enrichment is widely applied as an in vitro selection and amplification method to generate target-specific aptamers and exists in various modified variants. FluMag-SELEX is one of them and is characterized by the use of magnetic beads for target immobilization and fluorescently labeled oligonucleotides for monitoring the aptamer selection progress. Structural investigations and sequence truncation experiments of the selected aptamer for Protein A led to the conclusion, that a stem-loop structure at its 5'-end including the 5'-primer binding site is essential for aptamer-target binding. Extensive interaction analyses between aptamer and Protein A were performed by methods like surface plasmon resonance, MicroScale Thermophoresis and bead-based binding assays using fluorescence measurements. The binding of the aptamer to its target was thus investigated in assays with immobilization of one of the binding partners each, and with both binding partners in solution. Affinity constants were determined in the low micromolar to submicromolar range, increasing to the nanomolar range under the assumption of avidity. Protein A provides more than one binding site for the aptamer, which may overlap with the known binding sites for immunoglobulins. The aptamer binds specifically to both native and recombinant Protein A, but not to other immunoglobulin-binding proteins like Protein G and L. Cross specificity to other proteins was not found. The application of the aptamer is directed to Protein A detection or affinity purification. Moreover, whole cells of Staphylococcus aureus, presenting Protein A on the cell surface, could also be bound by the aptamer.

In vitro Selection and Interaction Studies of a DNA Aptamer Targeting Protein A.

Science.gov (United States)

Stoltenburg, Regina; Schubert, Thomas; Strehlitz, Beate

2015-01-01

A new DNA aptamer targeting Protein A is presented. The aptamer was selected by use of the FluMag-SELEX procedure. The SELEX technology (Systematic Evolution of Ligands by EXponential enrichment) is widely applied as an in vitro selection and amplification method to generate target-specific aptamers and exists in various modified variants. FluMag-SELEX is one of them and is characterized by the use of magnetic beads for target immobilization and fluorescently labeled oligonucleotides for monitoring the aptamer selection progress. Structural investigations and sequence truncation experiments of the selected aptamer for Protein A led to the conclusion, that a stem-loop structure at its 5'-end including the 5'-primer binding site is essential for aptamer-target binding. Extensive interaction analyses between aptamer and Protein A were performed by methods like surface plasmon resonance, MicroScale Thermophoresis and bead-based binding assays using fluorescence measurements. The binding of the aptamer to its target was thus investigated in assays with immobilization of one of the binding partners each, and with both binding partners in solution. Affinity constants were determined in the low micromolar to submicromolar range, increasing to the nanomolar range under the assumption of avidity. Protein A provides more than one binding site for the aptamer, which may overlap with the known binding sites for immunoglobulins. The aptamer binds specifically to both native and recombinant Protein A, but not to other immunoglobulin-binding proteins like Protein G and L. Cross specificity to other proteins was not found. The application of the aptamer is directed to Protein A detection or affinity purification. Moreover, whole cells of Staphylococcus aureus, presenting Protein A on the cell surface, could also be bound by the aptamer.

Interference-aware random beam selection schemes for spectrum sharing systems

KAUST Repository

Abdallah, Mohamed

2012-10-19

Spectrum sharing systems have been recently introduced to alleviate the problem of spectrum scarcity by allowing secondary unlicensed networks to share the spectrum with primary licensed networks under acceptable interference levels to the primary users. In this work, we develop interference-aware random beam selection schemes that provide enhanced performance for the secondary network under the condition that the interference observed by the receivers of the primary network is below a predetermined/acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a primary link composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes select a beam, among a set of power-optimized random beams, that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint for different levels of feedback information describing the interference level at the primary receiver. For the proposed schemes, we develop a statistical analysis for the SINR statistics as well as the capacity and bit error rate (BER) of the secondary link.

Protein selectivity with immobilized metal ion-tacn sorbents: chromatographic studies with human serum proteins and several other globular proteins.

Science.gov (United States)

Jiang, W; Graham, B; Spiccia, L; Hearn, M T

1998-01-01

The chromatographic selectivity of the immobilized chelate system, 1,4,7-triazocyclononane (tacn), complexed with the borderline metal ions Cu2+, Cr3+, Mn2+, Co2+, Zn2+, and Ni2+ has been investigated with hen egg white lysozyme, horse heart cytochrome c, and horse skeletal muscle myoglobin, as well as proteins present in partially fractionated preparations of human plasma. The effects of ionic strength and pH of the loading and elution buffers on protein selectivities of these new immobilized metal ion affinity chromatographic (IMAC) systems have been examined. The results confirm that immobilized Mn;pl-tacn sorbents exhibit a novel type of IMAC behavior with proteins. In particular, the chromatographic properties of these immobilized M(n+)-tacn ligand systems were significantly different compared to the IMAC behavior observed with other types of immobilized tri- and tetradentate chelating ligands, such as iminodiacetic acid, O-phosphoserine, or nitrilotriacetic acid, when complexed with borderline metal ions. The experimental results have consequently been evaluated in terms of the additional contributions to the interactive processes mediated by effects other than solely the conventional lone pair Lewis soft acid-Lewis soft base coordination interactions, typically found for the IMAC of proteins with borderline and soft metal ions, such as Cu2+ or Ni2+.

Topology-selective jamming of fully-connected, code-division random-access networks

Science.gov (United States)

Polydoros, Andreas; Cheng, Unjeng

1990-01-01

The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling

DEFF Research Database (Denmark)

Simonsen, Martin; Maetschke, S.R.; Ragan, M.A.

2012-01-01

Motivation: Phylogenetic profiling methods can achieve good accuracy in predicting protein–protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly......: We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...... phylogenetic profiles often require very different RT sets to support high prediction accuracy....

The adverse effect of selective cyclooxygenase-2 inhibitor on random skin flap survival in rats.

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Haiyong Ren

Full Text Available BACKGROUND: Cyclooxygenase-2(COX-2 inhibitors provide desired analgesic effects after injury or surgery, but evidences suggested they also attenuate wound healing. The study is to investigate the effect of COX-2 inhibitor on random skin flap survival. METHODS: The McFarlane flap model was established in 40 rats and evaluated within two groups, each group gave the same volume of Parecoxib and saline injection for 7 days. The necrotic area of the flap was measured, the specimens of the flap were stained with haematoxylin-eosin(HE for histologic analysis. Immunohistochemical staining was performed to analyse the level of VEGF and COX-2 . RESULTS: 7 days after operation, the flap necrotic area ratio in study group (66.65 ± 2.81% was significantly enlarged than that of the control group(48.81 ± 2.33%(P <0.01. Histological analysis demonstrated angiogenesis with mean vessel density per mm(2 being lower in study group (15.4 ± 4.4 than in control group (27.2 ± 4.1 (P <0.05. To evaluate the expression of COX-2 and VEGF protein in the intermediate area II in the two groups by immunohistochemistry test .The expression of COX-2 in study group was (1022.45 ± 153.1, and in control group was (2638.05 ± 132.2 (P <0.01. The expression of VEGF in the study and control groups were (2779.45 ± 472.0 vs (4938.05 ± 123.6(P <0.01.In the COX-2 inhibitor group, the expressions of COX-2 and VEGF protein were remarkably down-regulated as compared with the control group. CONCLUSION: Selective COX-2 inhibitor had adverse effect on random skin flap survival. Suppression of neovascularization induced by low level of VEGF was supposed to be the biological mechanism.

Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication.

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Andreas Martin Lisewski

2008-09-01

Full Text Available The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions and in structure (structural defects trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a sensitive to random errors and (b restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.

Peculiarities of the statistics of spectrally selected fluorescence radiation in laser-pumped dye-doped random media

Science.gov (United States)

Yuvchenko, S. A.; Ushakova, E. V.; Pavlova, M. V.; Alonova, M. V.; Zimnyakov, D. A.

2018-04-01

We consider the practical realization of a new optical probe method of the random media which is defined as the reference-free path length interferometry with the intensity moments analysis. A peculiarity in the statistics of the spectrally selected fluorescence radiation in laser-pumped dye-doped random medium is discussed. Previously established correlations between the second- and the third-order moments of the intensity fluctuations in the random interference patterns, the coherence function of the probe radiation, and the path difference probability density for the interfering partial waves in the medium are confirmed. The correlations were verified using the statistical analysis of the spectrally selected fluorescence radiation emitted by a laser-pumped dye-doped random medium. Water solution of Rhodamine 6G was applied as the doping fluorescent agent for the ensembles of the densely packed silica grains, which were pumped by the 532 nm radiation of a solid state laser. The spectrum of the mean path length for a random medium was reconstructed.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction.

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Akhter, Nasrin; Shehu, Amarda

2018-01-19

Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction

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Nasrin Akhter

2018-01-01

Full Text Available Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

Correlation of random urine protein creatinine (P-C ratio with 24-hour urine protein and P-C ratio, based on physical activity: a pilot study

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Seyed-Ali Sadjadi

2010-07-01

Full Text Available Seyed-Ali Sadjadi1,2, Navin Jaipaul1,21Jerry L Pettis Memorial VA Medical Center, 2Loma Linda University School of Medicine, Loma Linda, CA, USAAbstract: Quantification of proteinuria is usually predicated upon 24-hour urine collection. Multiple factors influence urine collection and the rate of protein and creatinine excretion. Urine collection is often incomplete, and therefore creatinine and protein excretion rates are underestimated. A random urine protein-creatinine (P-C ratio has been shown over the years to be a reliable alternative to the 24-hour collection for detection and follow up of proteinuria. However, urine protein excretion may be influenced by physical activity. We studied 48 patients with proteinuria and varying levels of physical activity to determine the correlation between the measures of urine protein excretion. The correlation coefficient (r between 24-hour urine total protein and random urine P-C ratio was 0.75 (P < 0.01 in the overall study population, but varied according to the level of proteinuria and physical activity in a stratified analysis: r = 0.99 (P < 0.001 and r = 0.95 (P < 0.01 in bedridden patients; r = 0.44 (P = not significant [NS] and r = 0.54 (P = NS in semiactive patients; and r = 0.44 (P = NS and r = 0.58 (P < 0.05 in active patients with nephrotic- (>3500 mg/day and non-nephrotic (<3500 mg/day range proteinuria, respectively. The correlation appeared to be stronger between random urine and 24-hour urine P-C ratio for the overall study population (r = 0.84; P < 0.001, and when stratified according to the level of proteinuria and physical activity: r = 0.99 (P < 0.001 and r = 0.92 (P < 0.01 in bedridden patients; r = 0.61 (P = NS and r = 0.54 (P = NS in semiactive patients; and r = 0.64 (P < 0.02 and r = 0.52 (P < 0.05 in active patients with nephrotic and non-nephrotic range proteinuria, respectively. We conclude that the random urine P-C ratio is a reliable and practical way of estimating and

Correlation of random urine protein creatinine (P-C) ratio with 24-hour urine protein and P-C ratio, based on physical activity: a pilot study.

Science.gov (United States)

Sadjadi, Seyed-Ali; Jaipaul, Navin

2010-09-07

Quantification of proteinuria is usually predicated upon 24-hour urine collection. Multiple factors influence urine collection and the rate of protein and creatinine excretion. Urine collection is often incomplete, and therefore creatinine and protein excretion rates are underestimated. A random urine protein-creatinine (P-C) ratio has been shown over the years to be a reliable alternative to the 24-hour collection for detection and follow up of proteinuria. However, urine protein excretion may be influenced by physical activity. We studied 48 patients with proteinuria and varying levels of physical activity to determine the correlation between the measures of urine protein excretion. The correlation coefficient (r) between 24-hour urine total protein and random urine P-C ratio was 0.75 (P r = 0.99 (P r = 0.95 (P bedridden patients; r = 0.44 (P = not significant [NS]) and r = 0.54 (P = NS) in semiactive patients; and r = 0.44 (P = NS) and r = 0.58 (P 3500 mg/day) and non-nephrotic (r = 0.84; P r = 0.99 (P r = 0.92 (P bedridden patients; r = 0.61 (P = NS) and r = 0.54 (P = NS) in semiactive patients; and r = 0.64 (P r = 0.52 (P < 0.05) in active patients with nephrotic and non-nephrotic range proteinuria, respectively. We conclude that the random urine P-C ratio is a reliable and practical way of estimating and following proteinuria, but its precision and accuracy may be affected by the level of patient physical activity.

Site-selective 13C labeling of proteins using erythrose

International Nuclear Information System (INIS)

Weininger, Ulrich

2017-01-01

NMR-spectroscopy enables unique experimental studies on protein dynamics at atomic resolution. In order to obtain a full atom view on protein dynamics, and to study specific local processes like ring-flips, proton-transfer, or tautomerization, one has to perform studies on amino-acid side chains. A key requirement for these studies is site-selective labeling with 13 C and/or 1 H, which is achieved in the most general way by using site-selectively 13 C-enriched glucose (1- and 2- 13 C) as the carbon source in bacterial expression systems. Using this strategy, multiple sites in side chains, including aromatics, become site-selectively labeled and suitable for relaxation studies. Here we systematically investigate the use of site-selectively 13 C-enriched erythrose (1-, 2-, 3- and 4- 13 C) as a suitable precursor for 13 C labeled aromatic side chains. We quantify 13 C incorporation in nearly all sites in all 20 amino acids and compare the results to glucose based labeling. In general the erythrose approach results in more selective labeling. While there is only a minor gain for phenylalanine and tyrosine side-chains, the 13 C incorporation level for tryptophan is at least doubled. Additionally, the Phe ζ and Trp η2 positions become labeled. In the aliphatic side chains, labeling using erythrose yields isolated 13 C labels for certain positions, like Ile β and His β, making these sites suitable for dynamics studies. Using erythrose instead of glucose as a source for site-selective 13 C labeling enables unique or superior labeling for certain positions and is thereby expanding the toolbox for customized isotope labeling of amino-acid side-chains.

Protein-enriched familiar foods and drinks improve protein intake of hospitalized older patients: A randomized controlled trial.

Science.gov (United States)

Beelen, Janne; Vasse, Emmelyne; Janssen, Nancy; Janse, André; de Roos, Nicole M; de Groot, Lisette C P G M

2017-05-18

Adequate protein intake is important in preventing and treating undernutrition. Hospitalized older patients are recommended to consume 1.2-1.5 g of protein per kg body weight per day (g/kg/d) but most of them fail to do so. Therefore, we investigated whether a range of newly developed protein-enriched familiar foods and drinks were effective in increasing protein intake of hospitalized older patients. This randomized controlled trial involved 147 patients of ≥65 years (mean age: 78.5 ± 7.4 years). The control group (n = 80) received the standard energy and protein rich hospital menu. The intervention group (n = 67) received the same menu with various protein-enriched intervention products replacing regular products or added to the menu. Macronutrient intake on the fourth day of hospitalization, based on food ordering data, was compared between the two groups by using Independent T-tests and Mann Whitney U-tests. In the intervention group 30% of total protein was provided by the intervention products. The intervention group consumed 105.7 ± 34.2 g protein compared to 88.2 ± 24.4 g in the control group (p intervention group than in the control group reached a protein intake of 1.2 g/kg/d (79.1% vs 47.5%). Protein intake was significantly higher in the intervention group at breakfast, during the morning between breakfast and lunch, and at dinner. This study shows that providing protein-enriched familiar foods and drinks, as replacement of regular products or as additions to the hospital menu, better enables hospitalized older patients to reach protein intake recommendations. This trial is registered on ClinicalTrials.gov, Identifier: NCT02213393. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

RSARF: Prediction of residue solvent accessibility from protein sequence using random forest method

KAUST Repository

Ganesan, Pugalenthi; Kandaswamy, Krishna Kumar Umar; Chou -, Kuochen; Vivekanandan, Saravanan; Kolatkar, Prasanna R.

2012-01-01

Prediction of protein structure from its amino acid sequence is still a challenging problem. The complete physicochemical understanding of protein folding is essential for the accurate structure prediction. Knowledge of residue solvent accessibility gives useful insights into protein structure prediction and function prediction. In this work, we propose a random forest method, RSARF, to predict residue accessible surface area from protein sequence information. The training and testing was performed using 120 proteins containing 22006 residues. For each residue, buried and exposed state was computed using five thresholds (0%, 5%, 10%, 25%, and 50%). The prediction accuracy for 0%, 5%, 10%, 25%, and 50% thresholds are 72.9%, 78.25%, 78.12%, 77.57% and 72.07% respectively. Further, comparison of RSARF with other methods using a benchmark dataset containing 20 proteins shows that our approach is useful for prediction of residue solvent accessibility from protein sequence without using structural information. The RSARF program, datasets and supplementary data are available at http://caps.ncbs.res.in/download/pugal/RSARF/. - See more at: http://www.eurekaselect.com/89216/article#sthash.pwVGFUjq.dpuf

An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteins.

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Cheng Zheng

Full Text Available Zinc-binding proteins are the most abundant metalloproteins in the Protein Data Bank where the zinc ions usually have catalytic, regulatory or structural roles critical for the function of the protein. Accurate prediction of zinc-binding sites is not only useful for the inference of protein function but also important for the prediction of 3D structure. Here, we present a new integrative framework that combines multiple sequence and structural properties and graph-theoretic network features, followed by an efficient feature selection to improve prediction of zinc-binding sites. We investigate what information can be retrieved from the sequence, structure and network levels that is relevant to zinc-binding site prediction. We perform a two-step feature selection using random forest to remove redundant features and quantify the relative importance of the retrieved features. Benchmarking on a high-quality structural dataset containing 1,103 protein chains and 484 zinc-binding residues, our method achieved >80% recall at a precision of 75% for the zinc-binding residues Cys, His, Glu and Asp on 5-fold cross-validation tests, which is a 10%-28% higher recall at the 75% equal precision compared to SitePredict and zincfinder at residue level using the same dataset. The independent test also indicates that our method has achieved recall of 0.790 and 0.759 at residue and protein levels, respectively, which is a performance better than the other two methods. Moreover, AUC (the Area Under the Curve and AURPC (the Area Under the Recall-Precision Curve by our method are also respectively better than those of the other two methods. Our method can not only be applied to large-scale identification of zinc-binding sites when structural information of the target is available, but also give valuable insights into important features arising from different levels that collectively characterize the zinc-binding sites. The scripts and datasets are available at http://protein.cau.edu.cn/zincidentifier/.

Moderate alcohol consumption reduces plasma C-reactive protein and fibrinogen levels : a randomized, diet-controlled intervention study

NARCIS (Netherlands)

Sierksma, A.; Gaag, M.S. van der; Kluft, C.; Hendriks, H.F.J.

2002-01-01

Objective: To evaluate the effect of moderate alcohol consumption on the acute phase proteins C-reactive protein and fibrinogen. Design: Randomized, diet-controlled, cross-over study. Setting: The study was performed at TNO Nutrition and Food Research, Zeist, The Netherlands. Subjects: Ten

Blind Measurement Selection: A Random Matrix Theory Approach

KAUST Repository

Elkhalil, Khalil

2016-12-14

This paper considers the problem of selecting a set of $k$ measurements from $n$ available sensor observations. The selected measurements should minimize a certain error function assessing the error in estimating a certain $m$ dimensional parameter vector. The exhaustive search inspecting each of the $n\\\\choose k$ possible choices would require a very high computational complexity and as such is not practical for large $n$ and $k$. Alternative methods with low complexity have recently been investigated but their main drawbacks are that 1) they require perfect knowledge of the measurement matrix and 2) they need to be applied at the pace of change of the measurement matrix. To overcome these issues, we consider the asymptotic regime in which $k$, $n$ and $m$ grow large at the same pace. Tools from random matrix theory are then used to approximate in closed-form the most important error measures that are commonly used. The asymptotic approximations are then leveraged to select properly $k$ measurements exhibiting low values for the asymptotic error measures. Two heuristic algorithms are proposed: the first one merely consists in applying the convex optimization artifice to the asymptotic error measure. The second algorithm is a low-complexity greedy algorithm that attempts to look for a sufficiently good solution for the original minimization problem. The greedy algorithm can be applied to both the exact and the asymptotic error measures and can be thus implemented in blind and channel-aware fashions. We present two potential applications where the proposed algorithms can be used, namely antenna selection for uplink transmissions in large scale multi-user systems and sensor selection for wireless sensor networks. Numerical results are also presented and sustain the efficiency of the proposed blind methods in reaching the performances of channel-aware algorithms.

Selective autophagy of non-ubiquitylated targets in plants: looking for cognate receptor/adaptor proteins

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Vasko eVeljanovski

2014-06-01

Full Text Available Cellular homeostasis is essential for the physiology of eukaryotic cells. Eukaryotic cells, including plant cells, utilize two main pathways to adjust the level of cytoplasmic components, namely the proteasomal and the lysosomal/vacuolar pathways. Macroautophagy is a lysosomal/vacuolar pathway which, until recently, was thought to be non-specific and a bulk degradation process. However, selective autophagy which can be activated in the cell under various physiological conditions, involves the specific degradation of defined macromolecules or organelles by a conserved molecular mechanism. For this process to be efficient, the mechanisms underlying the recognition and selection of the cargo to be engulfed by the double-membrane autophagosome are critical, and not yet well understood. Ubiquitin (poly-ubiquitin conjugation to the target appears to be a conserved ligand mechanism in many types of selective autophagy, and defined receptors/adaptors recognizing and regulating the autophagosomal capture of the ubiquitylated target have been characterized. However, non-proteinaceous and non-ubiquitylated cargoes are also selectively degraded by this pathway. This ubiquitin-independent selective autophagic pathway also involves receptor and/or adaptor proteins linking the cargo to the autophagic machinery. Some of these receptor/adaptor proteins including accessory autophagy-related (Atg and non-Atg proteins have been described in yeast and animal cells but not yet in plants. In this review we discuss the ubiquitin-independent cargo selection mechanisms in selective autophagy degradation of organelles and macromolecules and speculate on potential plant receptor/adaptor proteins.

Tuning a Protein-Labeling Reaction to Achieve Highly Site Selective Lysine Conjugation.

Science.gov (United States)

Pham, Grace H; Ou, Weijia; Bursulaya, Badry; DiDonato, Michael; Herath, Ananda; Jin, Yunho; Hao, Xueshi; Loren, Jon; Spraggon, Glen; Brock, Ansgar; Uno, Tetsuo; Geierstanger, Bernhard H; Cellitti, Susan E

2018-04-16

Activated esters are widely used to label proteins at lysine side chains and N termini. These reagents are useful for labeling virtually any protein, but robust reactivity toward primary amines generally precludes site-selective modification. In a unique case, fluorophenyl esters are shown to preferentially label human kappa antibodies at a single lysine (Lys188) within the light-chain constant domain. Neighboring residues His189 and Asp151 contribute to the accelerated rate of labeling at Lys188 relative to the ≈40 other lysine sites. Enriched Lys188 labeling can be enhanced from 50-70 % to >95 % by any of these approaches: lowering reaction temperature, applying flow chemistry, or mutagenesis of specific residues in the surrounding protein environment. Our results demonstrated that activated esters with fluoro-substituted aromatic leaving groups, including a fluoronaphthyl ester, can be generally useful reagents for site-selective lysine labeling of antibodies and other immunoglobulin-type proteins. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Origins of Protein Functions in Cells

Science.gov (United States)

Seelig, Burchard; Pohorille, Andrzej

2011-01-01

. Recently it was found that, as in the previous case, the proteins have a structure unknown among modern enzymes. In this case, in vitro evolution started from a small, non-enzymatic protein. A similar selection process initiated from a library of random polypeptides is in progress. These results not only allow for estimating the occurrence of function in random protein assemblies but also provide evidence for the possibility of alternative protein worlds. Extant proteins might simply represent a frozen accident in the world of possible proteins. Alternative collections of proteins, even with similar functions, could originate alternative evolutionary paths.

Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti.

Science.gov (United States)

Wampler, Peter J; Rediske, Richard R; Molla, Azizur R

2013-01-18

A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only rarely was local knowledge required to identify and locate households. This

Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

Directory of Open Access Journals (Sweden)

Wampler Peter J

2013-01-01

Full Text Available Abstract Background A remote sensing technique was developed which combines a Geographic Information System (GIS; Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti. The method was used to select homes for ethnographic and water quality research in a region of rural Haiti located within 9 km of a local hospital and source of health education in Deschapelles, Haiti. The technique does not require access to governmental records or ground based surveys to collect household location data and can be performed in a rapid, cost-effective manner. Methods The random selection of households and the location of these households during field surveys were accomplished using GIS, Google Earth, Microsoft Excel, and handheld Garmin GPSmap 76CSx GPS units. Homes were identified and mapped in Google Earth, exported to ArcMap 10.0, and a random list of homes was generated using Microsoft Excel which was then loaded onto handheld GPS units for field location. The development and use of a remote sensing method was essential to the selection and location of random households. Results A total of 537 homes initially were mapped and a randomized subset of 96 was identified as potential survey locations. Over 96% of the homes mapped using Google Earth imagery were correctly identified as occupied dwellings. Only 3.6% of the occupants of mapped homes visited declined to be interviewed. 16.4% of the homes visited were not occupied at the time of the visit due to work away from the home or market days. A total of 55 households were located using this method during the 10 days of fieldwork in May and June of 2012. Conclusions The method used to generate and field locate random homes for surveys and water sampling was an effective means of selecting random households in a rural environment lacking geolocation infrastructure. The success rate for locating households using a handheld GPS was excellent and only

Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.

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Aditi Gupta

2016-03-01

Full Text Available Epistatic interactions between residues determine a protein's adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1 using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient condition that detects epistasis in most cases. We analyze the "fossils" of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing

Rats free to select between pure protein and a fat-carbohydrate mix ingest high-protein mixed meals during the dark period and protein meals during the light period.

Science.gov (United States)

Makarios-Lahham, Lina; Roseau, Suzanne M; Fromentin, Gilles; Tome, Daniel; Even, Patrick C

2004-03-01

Rats that are allowed to select their diets [dietary self- selection (DSS)] often ingest >30% of their daily energy in the form of protein. Such an intake may seem unhealthy, but the consistency of this choice suggests that it is motivated by physiologic drives. To gain a clearer understanding of how protein selection is structured during DSS, we adapted 12 rats to a standard diet (14% Protein) and then allowed them to choose between two diets, i.e., total milk protein (P) and a mix of carbohydrates and lipids (FC). The protein intake during DSS rose above 40%; assuming an intermeal interval of 10 min, 70% of the energy intake occurred with meals that included both P and FC, with the sequence of FC followed by P preferred to the sequence of P followed by FC (70 vs. 30%, P energy intake during the light period was reduced to only 10% of the daily energy intake [vs. 30% with the control P14 diet or a with a high-protein diet (50%)], and 90% of the intake was in the form of pure protein meals. In complementary studies, we verified that the high protein intake also occurred when rats were offered casein and whey and was not due to the high palatability of the milk protein. We conclude that a specific feeding pattern accompanies high protein intake in rats allowed DSS. The mechanisms underlying this behavior and its potential beneficial/adverse consequences over the long term still must be clarified.

Optimizing Event Selection with the Random Grid Search

Energy Technology Data Exchange (ETDEWEB)

Bhat, Pushpalatha C. [Fermilab; Prosper, Harrison B. [Florida State U.; Sekmen, Sezen [Kyungpook Natl. U.; Stewart, Chip [Broad Inst., Cambridge

2017-06-29

The random grid search (RGS) is a simple, but efficient, stochastic algorithm to find optimal cuts that was developed in the context of the search for the top quark at Fermilab in the mid-1990s. The algorithm, and associated code, have been enhanced recently with the introduction of two new cut types, one of which has been successfully used in searches for supersymmetry at the Large Hadron Collider. The RGS optimization algorithm is described along with the recent developments, which are illustrated with two examples from particle physics. One explores the optimization of the selection of vector boson fusion events in the four-lepton decay mode of the Higgs boson and the other optimizes SUSY searches using boosted objects and the razor variables.

Non-random mating for selection with restricted rates of inbreeding and overlapping generations

NARCIS (Netherlands)

Sonesson, A.K.; Meuwissen, T.H.E.

2002-01-01

Minimum coancestry mating with a maximum of one offspring per mating pair (MC1) is compared with random mating schemes for populations with overlapping generations. Optimum contribution selection is used, whereby $\\\\\\\\Delta F$ is restricted. For schemes with $\\\\\\\\Delta F$ restricted to 0.25% per

Measurement of conformational constraints in an elastin-mimetic protein by residue-pair selected solid-state NMR

International Nuclear Information System (INIS)

Hong, Mei; McMillan, R. Andrew; Conticello, Vincent P.

2002-01-01

We introduce a solid-state NMR technique for selective detection of a residue pair in multiply labeled proteins to obtain site-specific structural constraints. The method exploits the frequency-offset dependence of cross polarization to achieve 13 CO i → 15 N i → 13 Cα i transfer between two residues. A 13 C, 15 N-labeled elastin mimetic protein (VPGVG) n is used to demonstrate the method. The technique selected the Gly3 Cα signal while suppressing the Gly5 Cα signal, and allowed the measurement of the Gly3 Cα chemical shift anisotropy to derive information on the protein conformation. This residue-pair selection technique should simplify the study of protein structure at specific residues

Sexual selection and the adaptive evolution of PKDREJ protein in primates and rodents.

Science.gov (United States)

Vicens, Alberto; Gómez Montoto, Laura; Couso-Ferrer, Francisco; Sutton, Keith A; Roldan, Eduardo R S

2015-02-01

PKDREJ is a testis-specific protein thought to be located on the sperm surface. Functional studies in the mouse revealed that loss of PKDREJ has effects on sperm transport and the ability to undergo an induced acrosome reaction. Thus, PKDREJ has been considered a potential target of post-copulatory sexual selection in the form of sperm competition. Proteins involved in reproductive processes often show accelerated evolution. In many cases, this rapid divergence is promoted by positive selection which may be driven, at least in part, by post-copulatory sexual selection. We analysed the evolution of the PKDREJ protein in primates and rodents and assessed whether PKDREJ divergence is associated with testes mass relative to body mass, which is a reliable proxy of sperm competition levels. Evidence of an association between the evolutionary rate of the PKDREJ gene and testes mass relative to body mass was not found in primates. Among rodents, evidence of positive selection was detected in the Pkdrej gene in the family Cricetidae but not in Muridae. We then assessed whether Pkdrej divergence is associated with episodes of sperm competition in these families. We detected a positive significant correlation between the evolutionary rates of Pkdrej and testes mass relative to body mass in cricetids. These findings constitute the first evidence of post-copulatory sexual selection influencing the evolution of a protein that participates in the mechanisms regulating sperm transport and the acrosome reaction, strongly suggesting that positive selection may act on these fertilization steps, leading to advantages in situations of sperm competition. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparative Evaluations of Randomly Selected Four Point-of-Care Glucometer Devices in Addis Ababa, Ethiopia.

Science.gov (United States)

Wolde, Mistire; Tarekegn, Getahun; Kebede, Tedla

2018-05-01

Point-of-care glucometer (PoCG) devices play a significant role in self-monitoring of the blood sugar level, particularly in the follow-up of high blood sugar therapeutic response. The aim of this study was to evaluate blood glucose test results performed with four randomly selected glucometers on diabetes and control subjects versus standard wet chemistry (hexokinase) methods in Addis Ababa, Ethiopia. A prospective cross-sectional study was conducted on randomly selected 200 study participants (100 participants with diabetes and 100 healthy controls). Four randomly selected PoCG devices (CareSens N, DIAVUE Prudential, On Call Extra, i-QARE DS-W) were evaluated against hexokinase method and ISO 15197:2003 and ISO 15197:2013 standards. The minimum and maximum blood sugar values were recorded by CareSens N (21 mg/dl) and hexokinase method (498.8 mg/dl), respectively. The mean sugar values of all PoCG devices except On Call Extra showed significant differences compared with the reference hexokinase method. Meanwhile, all four PoCG devices had strong positive relationship (>80%) with the reference method (hexokinase). On the other hand, none of the four PoCG devices fulfilled the minimum accuracy measurement set by ISO 15197:2003 and ISO 15197:2013 standards. In addition, the linear regression analysis revealed that all four selected PoCG overestimated the glucose concentrations. The overall evaluation of the selected four PoCG measurements were poorly correlated with standard reference method. Therefore, before introducing PoCG devices to the market, there should be a standardized evaluation platform for validation. Further similar large-scale studies on other PoCG devices also need to be undertaken.

Geography and genography: prediction of continental origin using randomly selected single nucleotide polymorphisms

Directory of Open Access Journals (Sweden)

Ramoni Marco F

2007-03-01

Full Text Available Abstract Background Recent studies have shown that when individuals are grouped on the basis of genetic similarity, group membership corresponds closely to continental origin. There has been considerable debate about the implications of these findings in the context of larger debates about race and the extent of genetic variation between groups. Some have argued that clustering according to continental origin demonstrates the existence of significant genetic differences between groups and that these differences may have important implications for differences in health and disease. Others argue that clustering according to continental origin requires the use of large amounts of genetic data or specifically chosen markers and is indicative only of very subtle genetic differences that are unlikely to have biomedical significance. Results We used small numbers of randomly selected single nucleotide polymorphisms (SNPs from the International HapMap Project to train naïve Bayes classifiers for prediction of ancestral continent of origin. Predictive accuracy was tested on two independent data sets. Genetically similar groups should be difficult to distinguish, especially if only a small number of genetic markers are used. The genetic differences between continentally defined groups are sufficiently large that one can accurately predict ancestral continent of origin using only a minute, randomly selected fraction of the genetic variation present in the human genome. Genotype data from only 50 random SNPs was sufficient to predict ancestral continent of origin in our primary test data set with an average accuracy of 95%. Genetic variations informative about ancestry were common and widely distributed throughout the genome. Conclusion Accurate characterization of ancestry is possible using small numbers of randomly selected SNPs. The results presented here show how investigators conducting genetic association studies can use small numbers of arbitrarily

A versatile selection system for folding competent proteins using genetic complementation in a eukaryotic host

DEFF Research Database (Denmark)

Lyngsø, C.; Kjaerulff, S.; Muller, S.

2010-01-01

in vivo selection system for folded proteins. It is based on genetic complementation of the Schizosaccharomyces pombe growth marker gene invertase fused C-terminally to a protein library. The fusion proteins are directed to the secretion system, utilizing the ability of the eukaryotic protein quality...

Deep recurrent conditional random field network for protein secondary prediction

DEFF Research Database (Denmark)

Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

2017-01-01

Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

Protein structure and ionic selectivity in calcium channels: selectivity filter size, not shape, matters.

Science.gov (United States)

Malasics, Attila; Gillespie, Dirk; Nonner, Wolfgang; Henderson, Douglas; Eisenberg, Bob; Boda, Dezso

2009-12-01

Calcium channels have highly charged selectivity filters (4 COO(-) groups) that attract cations in to balance this charge and minimize free energy, forcing the cations (Na(+) and Ca(2+)) to compete for space in the filter. A reduced model was developed to better understand the mechanism of ion selectivity in calcium channels. The charge/space competition (CSC) mechanism implies that Ca(2+) is more efficient in balancing the charge of the filter because it provides twice the charge as Na(+) while occupying the same space. The CSC mechanism further implies that the main determinant of Ca(2+) versus Na(+) selectivity is the density of charged particles in the selectivity filter, i.e., the volume of the filter (after fixing the number of charged groups in the filter). In this paper we test this hypothesis by changing filter length and/or radius (shape) of the cylindrical selectivity filter of our reduced model. We show that varying volume and shape together has substantially stronger effects than varying shape alone with volume fixed. Our simulations show the importance of depletion zones of ions in determining channel conductance calculated with the integrated Nernst-Planck equation. We show that confining the protein side chains with soft or hard walls does not influence selectivity.

Selective cell-surface labeling of the molecular motor protein prestin

International Nuclear Information System (INIS)

McGuire, Ryan M.; Silberg, Jonathan J.; Pereira, Fred A.; Raphael, Robert M.

2011-01-01

Highlights: → Trafficking to the plasma membrane is required for prestin function. → Biotin acceptor peptide (BAP) was fused to prestin through a transmembrane domain. → BAP-prestin can be metabolically labeled with biotin in HEK293 cells. → Biotin-BAP-prestin allows for selective imaging of fully trafficked prestin. → The biotin-BAP-prestin displays voltage-sensitive activity. -- Abstract: Prestin, a multipass transmembrane protein whose N- and C-termini are localized to the cytoplasm, must be trafficked to the plasma membrane to fulfill its cellular function as a molecular motor. One challenge in studying prestin sequence-function relationships within living cells is separating the effects of amino acid substitutions on prestin trafficking, plasma membrane localization and function. To develop an approach for directly assessing prestin levels at the plasma membrane, we have investigated whether fusion of prestin to a single pass transmembrane protein results in a functional fusion protein with a surface-exposed N-terminal tag that can be detected in living cells. We find that fusion of the biotin-acceptor peptide (BAP) and transmembrane domain of the platelet-derived growth factor receptor (PDGFR) to the N-terminus of prestin-GFP yields a membrane protein that can be metabolically-labeled with biotin, trafficked to the plasma membrane, and selectively detected at the plasma membrane using fluorescently-tagged streptavidin. Furthermore, we show that the addition of a surface detectable tag and a single-pass transmembrane domain to prestin does not disrupt its voltage-sensitive activity.

Fast and Selective Modification of Thiol Proteins/Peptides by N-(Phenylseleno)phthalimide

Science.gov (United States)

Wang, Zhengfang; Zhang, Yun; Zhang, Hao; Harrington, Peter B.; Chen, Hao

2012-03-01

We previously reported that selenamide reagents such as ebselen and N-(phenylseleno)phthalimide (NPSP) can be used to selectively derivatize thiols for mass spectrometric analysis, and the introduced selenium tags are useful as they could survive or removed with collision-induced dissociation (CID). Described herein is the further study of the reactivity of various protein/peptide thiols toward NPSP and its application to derivatize thiol peptides in protein digests. With a modified protocol (i.e., dissolving NPSP in acetonitrile instead of aqueous solvent), we found that quantitative conversion of thiols can be obtained in seconds, using NPSP in a slight excess amount (NPSP:thiol of 1.1-2:1). Further investigation shows that the thiol reactivity toward NPSP reflects its chemical environment and accessibility in proteins/peptides. For instance, adjacent basic amino acid residues increase the thiol reactivity, probably because they could stabilize the thiolate form to facilitate the nucleophilic attack of thiol on NPSP. In the case of creatine phosphokinase, the native protein predominately has one thiol reacted with NPSP while all of four thiol groups of the denatured protein can be derivatized, in accordance with the corresponding protein conformation. In addition, thiol peptides in protein/peptide enzymatic digests can be quickly and effectively tagged by NPSP following tri- n-butylphosphine (TBP) reduction. Notably, all three thiols of the peptide QCCASVCSL in the insulin peptic digest can be modified simultaneously by NPSP. These results suggest a novel and selective method for protecting thiols in the bottom-up approach for protein structure analysis.

Positive selection and propeptide repeats promote rapid interspecific divergence of a gastropod sperm protein.

Science.gov (United States)

Hellberg, M E; Moy, G W; Vacquier, V D

2000-03-01

Male-specific proteins have increasingly been reported as targets of positive selection and are of special interest because of the role they may play in the evolution of reproductive isolation. We report the rapid interspecific divergence of cDNA encoding a major acrosomal protein of unknown function (TMAP) of sperm from five species of teguline gastropods. A mitochondrial DNA clock (calibrated by congeneric species divided by the Isthmus of Panama) estimates that these five species diverged 2-10 MYA. Inferred amino acid sequences reveal a propeptide that has diverged rapidly between species. The mature protein has diverged faster still due to high nonsynonymous substitution rates (> 25 nonsynonymous substitutions per site per 10(9) years). cDNA encoding the mature protein (89-100 residues) shows evidence of positive selection (Dn/Ds > 1) for 4 of 10 pairwise species comparisons. cDNA and predicted secondary-structure comparisons suggest that TMAP is neither orthologous nor paralogous to abalone lysin, and thus marks a second, phylogenetically independent, protein subject to strong positive selection in free-spawning marine gastropods. In addition, an internal repeat in one species (Tegula aureotincta) produces a duplicated cleavage site which results in two alternatively processed mature proteins differing by nine amino acid residues. Such alternative processing may provide a mechanism for introducing novel amino acid sequence variation at the amino-termini of proteins. Highly divergent TMAP N-termini from two other tegulines (Tegula regina and Norrisia norrisii) may have originated by such a mechanism.

A theory for the origin of a self-replicating chemical system. I - Natural selection of the autogen from short, random oligomers

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White, D. H.

1980-01-01

A general theory is presented for the origin of a self-replicating chemical system, termed an autogen, which is capable of both crude replication and translation (protein synthesis). The theory requires the availability of free energy and monomers to the system, a significant background low-yield synthesis of kinetically stable oligopeptides and oligonucleotides, the localization of the oligomers, crude oligonucleotide selectivity of amino acids during oligopeptide synthesis, crude oligonucleotide replication, and two short peptide families which catalyze replication and translation, to produce a localized group of at least one copy each of two protogenes and two protoenzymes. The model posits a process of random oligomerization, followed by the random nucleation of functional components and the rapid autocatalytic growth of the functioning autogen to macroscopic amounts, to account for the origin of the first self-replicating system. Such a process contains steps of such high probability and short time periods that it is suggested that the emergence of an autogen in a laboratory experiment of reasonable time scale may be possible.

Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

Science.gov (United States)

Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

2010-10-01

To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

Pediatric selective mutism therapy: a randomized controlled trial.

Science.gov (United States)

Esposito, Maria; Gimigliano, Francesca; Barillari, Maria R; Precenzano, Francesco; Ruberto, Maria; Sepe, Joseph; Barillari, Umberto; Gimigliano, Raffaele; Militerni, Roberto; Messina, Giovanni; Carotenuto, Marco

2017-10-01

Selective mutism (SM) is a rare disease in children coded by DSM-5 as an anxiety disorder. Despite the disabling nature of the disease, there is still no specific treatment. The aims of this study were to verify the efficacy of six-month standard psychomotor treatment and the positive changes in lifestyle, in a population of children affected by SM. Randomized controlled trial registered in the European Clinical Trials Registry (EuDract 2015-001161-36). University third level Centre (Child and Adolescent Neuropsychiatry Clinic). Study population was composed by 67 children in group A (psychomotricity treatment) (35 M, mean age 7.84±1.15) and 71 children in group B (behavioral and educational counseling) (37 M, mean age 7.75±1.36). Psychomotor treatment was administered by trained child therapists in residential settings three times per week. Each child was treated for the whole period by the same therapist and all the therapists shared the same protocol. The standard psychomotor session length is of 45 minutes. At T0 and after 6 months (T1) of treatments, patients underwent a behavioral and SM severity assessment. To verify the effects of the psychomotor management, the Child Behavior Checklist questionnaire (CBCL) and Selective Mutism Questionnaire (SMQ) were administered to the parents. After 6 months of psychomotor treatment SM children showed a significant reduction among CBCL scores such as in social relations, anxious/depressed, social problems and total problems (Pselective mutism, even if further studies are needed. The present study identifies in psychomotricity a safe and efficacy therapy for pediatric selective mutism.

Selecting highly structure-specific antibodies using structured synthetic mimics of the cystine knot protein sclerostin

NARCIS (Netherlands)

Back, J.W.; Frisch, C.; Van Pee, K.; Boschert, V.; van Vught, R.; Puijk, W.; Mueller, T. D.; Knappik, A.; Timmerman, P.

2012-01-01

Antibodies directed against specific regions of a protein have traditionally been raised against full proteins, protein domains or simple unstructured peptides, containing contiguous stretches of primary sequence. We have used a new approach of selecting antibodies against restrained peptides

The different roles of selective autophagic protein degradation in mammalian cells.

Science.gov (United States)

Wang, Da-wei; Peng, Zhen-ju; Ren, Guang-fang; Wang, Guang-xin

2015-11-10

Autophagy is an intracellular pathway for bulk protein degradation and the removal of damaged organelles by lysosomes. Autophagy was previously thought to be unselective; however, studies have increasingly confirmed that autophagy-mediated protein degradation is highly regulated. Abnormal autophagic protein degradation has been associated with multiple human diseases such as cancer, neurological disability and cardiovascular disease; therefore, further elucidation of protein degradation by autophagy may be beneficial for protein-based clinical therapies. Macroautophagy and chaperone-mediated autophagy (CMA) can both participate in selective protein degradation in mammalian cells, but the process is quite different in each case. Here, we summarize the various types of macroautophagy and CMA involved in determining protein degradation. For this summary, we divide the autophagic protein degradation pathways into four categories: the post-translational modification dependent and independent CMA pathways and the ubiquitin dependent and independent macroautophagy pathways, and describe how some non-canonical pathways and modifications such as phosphorylation, acetylation and arginylation can influence protein degradation by the autophagy lysosome system (ALS). Finally, we comment on why autophagy can serve as either diagnostics or therapeutic targets in different human diseases.

Site-selective {sup 13}C labeling of proteins using erythrose

Energy Technology Data Exchange (ETDEWEB)

Weininger, Ulrich, E-mail: ulrich.weininger@physik.uni-halle.de [Lund University, Department of Biophysical Chemistry, Center for Molecular Protein Science (Sweden)

2017-03-15

NMR-spectroscopy enables unique experimental studies on protein dynamics at atomic resolution. In order to obtain a full atom view on protein dynamics, and to study specific local processes like ring-flips, proton-transfer, or tautomerization, one has to perform studies on amino-acid side chains. A key requirement for these studies is site-selective labeling with {sup 13}C and/or {sup 1}H, which is achieved in the most general way by using site-selectively {sup 13}C-enriched glucose (1- and 2-{sup 13}C) as the carbon source in bacterial expression systems. Using this strategy, multiple sites in side chains, including aromatics, become site-selectively labeled and suitable for relaxation studies. Here we systematically investigate the use of site-selectively {sup 13}C-enriched erythrose (1-, 2-, 3- and 4-{sup 13}C) as a suitable precursor for {sup 13}C labeled aromatic side chains. We quantify {sup 13}C incorporation in nearly all sites in all 20 amino acids and compare the results to glucose based labeling. In general the erythrose approach results in more selective labeling. While there is only a minor gain for phenylalanine and tyrosine side-chains, the {sup 13}C incorporation level for tryptophan is at least doubled. Additionally, the Phe ζ and Trp η2 positions become labeled. In the aliphatic side chains, labeling using erythrose yields isolated {sup 13}C labels for certain positions, like Ile β and His β, making these sites suitable for dynamics studies. Using erythrose instead of glucose as a source for site-selective {sup 13}C labeling enables unique or superior labeling for certain positions and is thereby expanding the toolbox for customized isotope labeling of amino-acid side-chains.

Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification

Science.gov (United States)

Murphy, Patrick J. M.; Stone, Orrin J.; Anderson, Michelle E.

2011-01-01

In contrast to other chromatographic methods for purifying proteins (e.g. gel filtration, affinity, and ion exchange), hydrophobic interaction chromatography (HIC) commonly requires experimental determination (referred to as screening or "scouting") in order to select the most suitable chromatographic medium for purifying a given protein 1. The method presented here describes an automated approach to scouting for an optimal HIC media to be used in protein purification. HIC separates proteins and other biomolecules from a crude lysate based on differences in hydrophobicity. Similar to affinity chromatography (AC) and ion exchange chromatography (IEX), HIC is capable of concentrating the protein of interest as it progresses through the chromatographic process. Proteins best suited for purification by HIC include those with hydrophobic surface regions and able to withstand exposure to salt concentrations in excess of 2 M ammonium sulfate ((NH4)2SO4). HIC is often chosen as a purification method for proteins lacking an affinity tag, and thus unsuitable for AC, and when IEX fails to provide adequate purification. Hydrophobic moieties on the protein surface temporarily bind to a nonpolar ligand coupled to an inert, immobile matrix. The interaction between protein and ligand are highly dependent on the salt concentration of the buffer flowing through the chromatography column, with high ionic concentrations strengthening the protein-ligand interaction and making the protein immobile (i.e. bound inside the column) 2. As salt concentrations decrease, the protein-ligand interaction dissipates, the protein again becomes mobile and elutes from the column. Several HIC media are commercially available in pre-packed columns, each containing one of several hydrophobic ligands (e.g. S-butyl, butyl, octyl, and phenyl) cross-linked at varying densities to agarose beads of a specific diameter 3. Automated column scouting allows for an efficient approach for determining which HIC media

Measurement of conformational constraints in an elastin-mimetic protein by residue-pair selected solid-state NMR

Energy Technology Data Exchange (ETDEWEB)

Hong, Mei [Iowa State University, Department of Chemistry (United States)], E-mail: mhong@iastate.edu; McMillan, R. Andrew; Conticello, Vincent P. [Emory University, Department of Chemistry (United States)

2002-02-15

We introduce a solid-state NMR technique for selective detection of a residue pair in multiply labeled proteins to obtain site-specific structural constraints. The method exploits the frequency-offset dependence of cross polarization to achieve {sup 13}CO{sub i} {sup {yields}} {sup 15}N{sub i} {sup {yields}} {sup 13}C{alpha}{sub i} transfer between two residues. A {sup 13}C, {sup 15}N-labeled elastin mimetic protein (VPGVG){sub n} is used to demonstrate the method. The technique selected the Gly3 C{alpha} signal while suppressing the Gly5 C{alpha} signal, and allowed the measurement of the Gly3 C{alpha} chemical shift anisotropy to derive information on the protein conformation. This residue-pair selection technique should simplify the study of protein structure at specific residues.

Random copolymers that protect proteins

Science.gov (United States)

Alexander-Katz, Alfredo; Van Lehn, Reid C.

2018-03-01

Scientists have tried and in some limited cases succeeded to harness proteins to do chemistry (1) or use them in functional materials. However, most proteins only function correctly if they fold into specific conformations, which typically occurs with the assistance of other proteins (such as chaperones, translocons, or transporters) that mediate structure formation, membrane insertion, and intracellular trafficking (2, 3). Several methods have been used to improve protein stability in nonbiological environments—including micelle encapsulation, polymer conjugation, and sol-gel trapping (4)—but for most intended applications, they suffer from low levels of functionality, difficult chemical postfunctionalization, or the requirement of very specific solvent environments. On page 1239 of this issue, Panganiban et al. (5) introduce an approach for stabilizing proteins in disparate solvent environments that does not suffer from these drawbacks.

Primitive polynomials selection method for pseudo-random number generator

Science.gov (United States)

Anikin, I. V.; Alnajjar, Kh

2018-01-01

In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.

Positively selected sites in cetacean myoglobins contribute to protein stability

DEFF Research Database (Denmark)

Dasmeh, Pouria; Serohijos, Adrian W R; Kepp, Kasper P

2013-01-01

Since divergence ∼50 Ma ago from their terrestrial ancestors, cetaceans underwent a series of adaptations such as a ∼10-20 fold increase in myoglobin (Mb) concentration in skeletal muscle, critical for increasing oxygen storage capacity and prolonging dive time. Whereas the O2-binding affinity...... between Mb folding stability and protein abundance, suggesting that a selection pressure for stability acts proportionally to higher expression. We also identify a major divergence event leading to the common ancestor of whales, during which major stabilization occurred. Most of the positively selected...

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

Directory of Open Access Journals (Sweden)

Can Tolga

2009-09-01

Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

Science.gov (United States)

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Lack of efficacy of resveratrol on C-reactive protein and selected cardiovascular risk factors--Results from a systematic review and meta-analysis of randomized controlled trials.

Science.gov (United States)

Sahebkar, Amirhossein; Serban, Corina; Ursoniu, Sorin; Wong, Nathan D; Muntner, Paul; Graham, Ian M; Mikhailidis, Dimitri P; Rizzo, Manfredi; Rysz, Jacek; Sperling, Laurence S; Lip, Gregory Y H; Banach, Maciej

2015-01-01

Numerous studies have suggested that oral supplementation with resveratrol exerts cardioprotective effects, but evidence of the effects on C-reactive protein (CRP) plasma levels and other cardiovascular (CV) risk factors is inconclusive. Therefore, we performed a meta-analysis to evaluate the efficacy of resveratrol supplementation on plasma CRP concentrations and selected predictors of CV risk. The search included PUBMED, Cochrane Library, Web of Science, Scopus, and EMBASE (up to August 31, 2014) to identify RCTs investigating the effects of resveratrol supplementation on selected CV risk factors. Quantitative data synthesis was performed using a random-effects model, with weighted mean difference (WMD) and 95% confidence intervals (CI) as summary statistics. Meta-analysis of data from 10 RCTs (11 treatment arms) did not support a significant effect of resveratrol supplementation in altering plasma CRP concentrations (WMD: -0.144 mg/L, 95% CI: -0.968-0.680, p = 0.731). Resveratrol supplementation was not found to alter plasma levels of total cholesterol (WMD: 1.49 mg/dL, 95% CI: -14.96-17.93, p = 0.859), low density lipoprotein cholesterol (WMD: -0.31 mg/dL, 95% CI: -9.57-8.95, p = 0.948), triglycerides (WMD: 2.67 mg/dL, 95% CI: -28.34-33.67, p = 0.866), and glucose (WMD: 1.28 mg/dL, 95% CI: -5.28-7.84, p = 0.703). It also slightly reduced high density lipoprotein cholesterol concentrations (WMD: -4.18 mg/dL, 95% CI: -6.54 to -1.82, p = 0.001). Likewise, no significant effect was observed on systolic (WMD: 0.82 mmHg, 95% CI: -8.86-10.50, p = 0.868) and diastolic blood pressure (WMD: 1.72 mm Hg, 95% CI: -6.29-9.73, p=0.674). This meta-analysis of available RCTs does not suggest any benefit of resveratrol supplementation on CV risk factors. Larger, well-designed trials are necessary to confirm these results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Selective Labeling of Proteins on Living Cell Membranes Using Fluorescent Nanodiamond Probes

Directory of Open Access Journals (Sweden)

Shingo Sotoma

2016-03-01

Full Text Available The impeccable photostability of fluorescent nanodiamonds (FNDs is an ideal property for use in fluorescence imaging of proteins in living cells. However, such an application requires highly specific labeling of the target proteins with FNDs. Furthermore, the surface of unmodified FNDs tends to adsorb biomolecules nonspecifically, which hinders the reliable targeting of proteins with FNDs. Here, we combined hyperbranched polyglycerol modification of FNDs with the β-lactamase-tag system to develop a strategy for selective imaging of the protein of interest in cells. The combination of these techniques enabled site-specific labeling of Interleukin-18 receptor alpha chain, a membrane receptor, with FNDs, which eventually enabled tracking of the diffusion trajectory of FND-labeled proteins on the membrane surface.

Decarboxylative alkylation for site-selective bioconjugation of native proteins via oxidation potentials

Science.gov (United States)

Bloom, Steven; Liu, Chun; Kölmel, Dominik K.; Qiao, Jennifer X.; Zhang, Yong; Poss, Michael A.; Ewing, William R.; MacMillan, David W. C.

2018-02-01

The advent of antibody-drug conjugates as pharmaceuticals has fuelled a need for reliable methods of site-selective protein modification that furnish homogeneous adducts. Although bioorthogonal methods that use engineered amino acids often provide an elegant solution to the question of selective functionalization, achieving homogeneity using native amino acids remains a challenge. Here, we explore visible-light-mediated single-electron transfer as a mechanism towards enabling site- and chemoselective bioconjugation. Specifically, we demonstrate the use of photoredox catalysis as a platform to selectivity wherein the discrepancy in oxidation potentials between internal versus C-terminal carboxylates can be exploited towards obtaining C-terminal functionalization exclusively. This oxidation potential-gated technology is amenable to endogenous peptides and has been successfully demonstrated on the protein insulin. As a fundamentally new approach to bioconjugation this methodology provides a blueprint toward the development of photoredox catalysis as a generic platform to target other redox-active side chains for native conjugation.

Decarboxylative alkylation for site-selective bioconjugation of native proteins via oxidation potentials.

Science.gov (United States)

Bloom, Steven; Liu, Chun; Kölmel, Dominik K; Qiao, Jennifer X; Zhang, Yong; Poss, Michael A; Ewing, William R; MacMillan, David W C

2018-02-01

The advent of antibody-drug conjugates as pharmaceuticals has fuelled a need for reliable methods of site-selective protein modification that furnish homogeneous adducts. Although bioorthogonal methods that use engineered amino acids often provide an elegant solution to the question of selective functionalization, achieving homogeneity using native amino acids remains a challenge. Here, we explore visible-light-mediated single-electron transfer as a mechanism towards enabling site- and chemoselective bioconjugation. Specifically, we demonstrate the use of photoredox catalysis as a platform to selectivity wherein the discrepancy in oxidation potentials between internal versus C-terminal carboxylates can be exploited towards obtaining C-terminal functionalization exclusively. This oxidation potential-gated technology is amenable to endogenous peptides and has been successfully demonstrated on the protein insulin. As a fundamentally new approach to bioconjugation this methodology provides a blueprint toward the development of photoredox catalysis as a generic platform to target other redox-active side chains for native conjugation.

Vegetable versus animal protein diet in cirrhotic patients with chronic encephalopathy. A randomized cross-over comparison.

Science.gov (United States)

Bianchi, G P; Marchesini, G; Fabbri, A; Rondelli, A; Bugianesi, E; Zoli, M; Pisi, E

1993-05-01

In a randomized cross-over comparison, the effects of a mainly vegetable protein diet were compared with an animal protein diet in eight patients with cirrhosis and chronic permanent encephalopathy, under optimum lactulose therapy. After a run-in period, patients were fed two equi-caloric, equi-nitrogenous diets for 7 days (71 g total proteins), containing either 50 g protein of animal origin or 50 g vegetable proteins. In the last 3 days of each period, nitrogen balance was significantly better during the vegetable protein diet (+0.2 (SD 1.4) g vs. -1.7 (2.4); P vegetable proteins, whereas insulin, plasma amino acids and ammonia were lower. The clinical grading of encephalopathy improved slightly on vegetable proteins, and psychometric tests improved significantly, but remained grossly abnormal. Compliance to dietary manipulation was good. The data prove that a mainly vegetable protein diet is worthwhile in cirrhotic patients with chronic encephalopathy under optimum lactulose therapy. Improved nitrogen balance may be related to more effective nitrogen use for protein synthesis, probably due to blunted hormonal response, and largely outweighs the effects on encephalopathy.

Effect of Protein Intake on Lean Body Mass in Functionally Limited Older Men: A Randomized Clinical Trial.

Science.gov (United States)

Bhasin, Shalender; Apovian, Caroline M; Travison, Thomas G; Pencina, Karol; Moore, Lynn L; Huang, Grace; Campbell, Wayne W; Li, Zhuoying; Howland, Andrew S; Chen, Ruo; Knapp, Philip E; Singer, Martha R; Shah, Mitali; Secinaro, Kristina; Eder, Richard V; Hally, Kathleen; Schram, Haley; Bearup, Richelle; Beleva, Yusnie M; McCarthy, Ashley C; Woodbury, Erin; McKinnon, Jennifer; Fleck, Geeta; Storer, Thomas W; Basaria, Shehzad

2018-04-01

The Institute of Medicine set the recommended dietary allowance (RDA) for protein at 0.8 g/kg/d for the entire adult population. It remains controversial whether protein intake greater than the RDA is needed to maintain protein anabolism in older adults. To investigate whether increasing protein intake to 1.3 g/kg/d in older adults with physical function limitations and usual protein intake within the RDA improves lean body mass (LBM), muscle performance, physical function, fatigue, and well-being and augments LBM response to a muscle anabolic drug. This randomized clinical trial with a 2 × 2 factorial design was conducted in a research center. A modified intent-to-treat analytic strategy was used. Participants were 92 functionally limited men 65 years or older with usual protein intake less thanor equal to 0.83 g/kg/d within the RDA. The first participant was randomized on September 21, 2011, and the last participant completed the study on January 19, 2017. Participants were randomized for 6 months to controlled diets with 0.8 g/kg/d of protein plus placebo, 1.3 g/kg/d of protein plus placebo, 0.8 g/kg/d of protein plus testosterone enanthate (100 mg weekly), or 1.3 g/kg/d of protein plus testosterone. Prespecified energy and protein contents were provided through custom-prepared meals and supplements. The primary outcome was change in LBM. Secondary outcomes were muscle strength, power, physical function, health-related quality of life, fatigue, affect balance, and well-being. Among 92 men (mean [SD] age, 73.0 [5.8] years), the 4 study groups did not differ in baseline characteristics. Changes from baseline in LBM (0.31 kg; 95% CI, -0.46 to 1.08 kg; P = .43) and appendicular (0.04 kg; 95% CI, -0.48 to 0.55 kg; P = .89) and trunk (0.24 kg; 95% CI, -0.17 to 0.66 kg; P = .24) lean mass, as well as muscle strength and power, walking speed and stair-climbing power, health-related quality of life, fatigue, and well-being, did not differ between men

Randomizing Roaches: Exploring the "Bugs" of Randomization in Experimental Design

Science.gov (United States)

Wagler, Amy; Wagler, Ron

2014-01-01

Understanding the roles of random selection and random assignment in experimental design is a central learning objective in most introductory statistics courses. This article describes an activity, appropriate for a high school or introductory statistics course, designed to teach the concepts, values and pitfalls of random selection and assignment…

Identifying Bacterial Immune Evasion Proteins Using Phage Display.

Science.gov (United States)

Fevre, Cindy; Scheepmaker, Lisette; Haas, Pieter-Jan

2017-01-01

Methods aimed at identification of immune evasion proteins are mainly rely on in silico prediction of sequence, structural homology to known evasion proteins or use a proteomics driven approach. Although proven successful these methods are limited by a low efficiency and or lack of functional identification. Here we describe a high-throughput genomic strategy to functionally identify bacterial immune evasion proteins using phage display technology. Genomic bacterial DNA is randomly fragmented and ligated into a phage display vector that is used to create a phage display library expressing bacterial secreted and membrane bound proteins. This library is used to select displayed bacterial secretome proteins that interact with host immune components.

Controlling the rejection of protein during membrane filtration by adding selected polyelectrolytes

DEFF Research Database (Denmark)

Pinelo, Manuel; Ferrer Roca, Carme; Meyer, Anne S.

2012-01-01

Electrostatic interactions among the charged groups on proteins and/or between proteins and other solutes significantly affect the aggregation/deposition phenomena that induce fouling and decrease permeate flux during membrane purification of proteins. Such interactions can be turned...... help enhance the performance of membrane filtration for fractionation/purification of a target protein by significantly reducing fouling and modifying rejection/selectivity.......) changing the pH, on the permeate flux and membrane transmission of bovin serum albumina (BSA) through a PVDF membrane. The addition of PS-co-AA to the feed solution resulted in significant increases of the BSA transmission at pH 7.4 as compared to the transmission of a pure BSA solution (1g...

Materials selection for oxide-based resistive random access memories

International Nuclear Information System (INIS)

Guo, Yuzheng; Robertson, John

2014-01-01

The energies of atomic processes in resistive random access memories (RRAMs) are calculated for four typical oxides, HfO 2 , TiO 2 , Ta 2 O 5 , and Al 2 O 3 , to define a materials selection process. O vacancies have the lowest defect formation energy in the O-poor limit and dominate the processes. A band diagram defines the operating Fermi energy and O chemical potential range. It is shown how the scavenger metal can be used to vary the O vacancy formation energy, via controlling the O chemical potential, and the mean Fermi energy. The high endurance of Ta 2 O 5 RRAM is related to its more stable amorphous phase and the adaptive lattice rearrangements of its O vacancy

Integration of carboxyl modified magnetic particles and aqueous two-phase extraction for selective separation of proteins.

Science.gov (United States)

Gai, Qingqing; Qu, Feng; Zhang, Tao; Zhang, Yukui

2011-07-15

Both of the magnetic particle adsorption and aqueous two-phase extraction (ATPE) were simple, fast and low-cost method for protein separation. Selective proteins adsorption by carboxyl modified magnetic particles was investigated according to protein isoelectric point, solution pH and ionic strength. Aqueous two-phase system of PEG/sulphate exhibited selective separation and extraction for proteins before and after magnetic adsorption. The two combination ways, magnetic adsorption followed by ATPE and ATPE followed by magnetic adsorption, for the separation of proteins mixture of lysozyme, bovine serum albumin, trypsin, cytochrome C and myloglobin were discussed and compared. The way of magnetic adsorption followed by ATPE was also applied to human serum separation. Copyright © 2011 Elsevier B.V. All rights reserved.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Science.gov (United States)

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Emergence of multilevel selection in the prisoner's dilemma game on coevolving random networks

International Nuclear Information System (INIS)

Szolnoki, Attila; Perc, Matjaz

2009-01-01

We study the evolution of cooperation in the prisoner's dilemma game, whereby a coevolutionary rule is introduced that molds the random topology of the interaction network in two ways. First, existing links are deleted whenever a player adopts a new strategy or its degree exceeds a threshold value; second, new links are added randomly after a given number of game iterations. These coevolutionary processes correspond to the generic formation of new links and deletion of existing links that, especially in human societies, appear frequently as a consequence of ongoing socialization, change of lifestyle or death. Due to the counteraction of deletions and additions of links the initial heterogeneity of the interaction network is qualitatively preserved, and thus cannot be held responsible for the observed promotion of cooperation. Indeed, the coevolutionary rule evokes the spontaneous emergence of a powerful multilevel selection mechanism, which despite the sustained random topology of the evolving network, maintains cooperation across the whole span of defection temptation values.

A transposase strategy for creating libraries of circularly permuted proteins.

Science.gov (United States)

Mehta, Manan M; Liu, Shirley; Silberg, Jonathan J

2012-05-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions.

Severe negative energy balance during 21 d at high altitude decreases fat-free mass regardless of dietary protein intake: a randomized controlled trial.

Science.gov (United States)

Berryman, Claire E; Young, Andrew J; Karl, J Philip; Kenefick, Robert W; Margolis, Lee M; Cole, Renee E; Carbone, John W; Lieberman, Harris R; Kim, Il-Young; Ferrando, Arny A; Pasiakos, Stefan M

2018-02-01

In this 2-phase randomized controlled study, we examined whether consuming a higher-protein (HP) diet would attenuate fat-free mass (FFM) loss during energy deficit (ED) at high altitude (HA) in 17 healthy males (mean ± sd: 23 ± 6 yr; 82 ± 14 kg). During phase 1 at sea level (SL, 55 m), participants consumed a eucaloric diet providing standard protein (SP; 1.0 g protein/kg,) for 21 d. During phase 2, participants resided at HA (4300 m) for 22 d and were randomly assigned to either an SP or HP (2.0 g protein/kg) diet designed to elicit a 40% ED. Body composition, substrate oxidation, and postabsorptive whole-body protein kinetics were measured. Participants were weight stable during SL and lost 7.9 ± 1.9 kg ( P Berryman, C. E., Young, A. J., Karl, J. P., Kenefick, R. W., Margolis, L. M., Cole, R. E., Carbone, J. W., Lieberman, H. R., Kim, I.-Y., Ferrando, A. A., Pasiakos, S. M. Severe negative energy balance during 21 d at high altitude decreases fat-free mass regardless of dietary protein intake: a randomized controlled trial.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

Science.gov (United States)

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

Optimization of the Dutch Matrix Test by Random Selection of Sentences From a Preselected Subset

Directory of Open Access Journals (Sweden)

Rolph Houben

2015-04-01

Full Text Available Matrix tests are available for speech recognition testing in many languages. For an accurate measurement, a steep psychometric function of the speech materials is required. For existing tests, it would be beneficial if it were possible to further optimize the available materials by increasing the function’s steepness. The objective is to show if the steepness of the psychometric function of an existing matrix test can be increased by selecting a homogeneous subset of recordings with the steepest sentence-based psychometric functions. We took data from a previous multicenter evaluation of the Dutch matrix test (45 normal-hearing listeners. Based on half of the data set, first the sentences (140 out of 311 with a similar speech reception threshold and with the steepest psychometric function (≥9.7%/dB were selected. Subsequently, the steepness of the psychometric function for this selection was calculated from the remaining (unused second half of the data set. The calculation showed that the slope increased from 10.2%/dB to 13.7%/dB. The resulting subset did not allow the construction of enough balanced test lists. Therefore, the measurement procedure was changed to randomly select the sentences during testing. Random selection may interfere with a representative occurrence of phonemes. However, in our material, the median phonemic occurrence remained close to that of the original test. This finding indicates that phonemic occurrence is not a critical factor. The work highlights the possibility that existing speech tests might be improved by selecting sentences with a steep psychometric function.

Evolvability of thermophilic proteins from archaea and bacteria.

Science.gov (United States)

Takano, Kazufumi; Aoi, Atsushi; Koga, Yuichi; Kanaya, Shigenori

2013-07-16

Proteins from thermophiles possess high thermostability. The stabilization mechanisms differ between archaeal and bacterial proteins, whereby archaeal proteins are mainly stabilized via hydrophobic interactions and bacterial proteins by ion pairs. High stability is an important factor in promoting protein evolution, but the precise means by which different stabilization mechanisms affect the evolution process remain unclear. In this study, we investigated a random mutational drift of esterases from thermophilic archaea and bacteria at high temperatures. Our results indicate that mutations in archaeal proteins lead to improved function with no loss of stability, while mutant bacterial proteins are largely destabilized with decreased activity at high temperatures. On the basis of these findings, we suggest that archaeal proteins possess higher "evolvability" than bacterial proteins under temperature selection and are additionally able to evolve into eukaryotic proteins.

Automation of specimen selection and data acquisition for protein electron crystallography

NARCIS (Netherlands)

Oostergetel, G.T.; Keegstra, W.; Brisson, A.D R

A system is presented for semi-automatic specimen selection and data acquisition for protein electron crystallography, based on a slow-scan CCD camera connected to a transmission electron microscope and control from an external computer. Areas of interest on the specimen are localised at low

BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

KAUST Repository

Kandaswamy, Krishna Kumar

2011-08-17

Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.

BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

KAUST Repository

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Hazrati, Mehrnaz Khodam; Kalies, Kai-Uwe; Martinetz, Thomas

2011-01-01

Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.

High GC content causes orphan proteins to be intrinsically disordered.

Directory of Open Access Journals (Sweden)

Walter Basile

2017-03-01

Full Text Available De novo creation of protein coding genes involves the formation of short ORFs from noncoding regions; some of these ORFs might then become fixed in the population. These orphan proteins need to, at the bare minimum, not cause serious harm to the organism, meaning that they should for instance not aggregate. Therefore, although the creation of short ORFs could be truly random, the fixation should be subjected to some selective pressure. The selective forces acting on orphan proteins have been elusive, and contradictory results have been reported. In Drosophila young proteins are more disordered than ancient ones, while the opposite trend is present in yeast. To the best of our knowledge no valid explanation for this difference has been proposed. To solve this riddle we studied structural properties and age of proteins in 187 eukaryotic organisms. We find that, with the exception of length, there are only small differences in the properties between proteins of different ages. However, when we take the GC content into account we noted that it could explain the opposite trends observed for orphans in yeast (low GC and Drosophila (high GC. GC content is correlated with codons coding for disorder promoting amino acids. This leads us to propose that intrinsic disorder is not a strong determining factor for fixation of orphan proteins. Instead these proteins largely resemble random proteins given a particular GC level. During evolution the properties of a protein change faster than the GC level causing the relationship between disorder and GC to gradually weaken.

Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants.

Science.gov (United States)

Karkov, Hanne Sophie; Krogh, Berit Olsen; Woo, James; Parimal, Siddharth; Ahmadian, Haleh; Cramer, Steven M

2015-11-01

In this study, a unique set of antibody Fab fragments was designed in silico and produced to examine the relationship between protein surface properties and selectivity in multimodal chromatographic systems. We hypothesized that multimodal ligands containing both hydrophobic and charged moieties would interact strongly with protein surface regions where charged groups and hydrophobic patches were in close spatial proximity. Protein surface property characterization tools were employed to identify the potential multimodal ligand binding regions on the Fab fragment of a humanized antibody and to evaluate the impact of mutations on surface charge and hydrophobicity. Twenty Fab variants were generated by site-directed mutagenesis, recombinant expression, and affinity purification. Column gradient experiments were carried out with the Fab variants in multimodal, cation-exchange, and hydrophobic interaction chromatographic systems. The results clearly indicated that selectivity in the multimodal system was different from the other chromatographic modes examined. Column retention data for the reduced charge Fab variants identified a binding site comprising light chain CDR1 as the main electrostatic interaction site for the multimodal and cation-exchange ligands. Furthermore, the multimodal ligand binding was enhanced by additional hydrophobic contributions as evident from the results obtained with hydrophobic Fab variants. The use of in silico protein surface property analyses combined with molecular biology techniques, protein expression, and chromatographic evaluations represents a previously undescribed and powerful approach for investigating multimodal selectivity with complex biomolecules. © 2015 Wiley Periodicals, Inc.

Construction and Selection of Affilin® Phage Display Libraries.

Science.gov (United States)

Settele, Florian; Zwarg, Madlen; Fiedler, Sebastian; Koscheinz, Daniel; Bosse-Doenecke, Eva

2018-01-01

Affilin ® molecules represent a new class of so-called scaffold proteins. The concept of scaffold proteins is to use stable and versatile protein structures which can be endowed with de novo binding properties and specificities by introducing mutations in surface exposed amino acid residues. Complex variations and combinations are generated by genetic methods of randomization resulting in large cDNA libraries. The selection for candidates binding to a desired target can be executed by display methods, especially the very robust and flexible phage display. Here, we describe the construction of ubiquitin based Affilin ® phage display libraries and their use in biopanning experiments for the identification of novel protein ligands.

Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords.

Science.gov (United States)

Bentley, R Alexander

2008-08-27

The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.

ZP Domain Proteins in the Abalone Egg Coat Include a Paralog of VERL under Positive Selection That Binds Lysin and 18-kDa Sperm Proteins

Science.gov (United States)

Aagaard, Jan E.; Vacquier, Victor D.; MacCoss, Michael J.; Swanson, Willie J.

2010-01-01

Identifying fertilization molecules is key to our understanding of reproductive biology, yet only a few examples of interacting sperm and egg proteins are known. One of the best characterized comes from the invertebrate archeogastropod abalone (Haliotis spp.), where sperm lysin mediates passage through the protective egg vitelline envelope (VE) by binding to the VE protein vitelline envelope receptor for lysin (VERL). Rapid adaptive divergence of abalone lysin and VERL are an example of positive selection on interacting fertilization proteins contributing to reproductive isolation. Previously, we characterized a subset of the abalone VE proteins that share a structural feature, the zona pellucida (ZP) domain, which is common to VERL and the egg envelopes of vertebrates. Here, we use additional expressed sequence tag sequencing and shotgun proteomics to characterize this family of proteins in the abalone egg VE. We expand 3-fold the number of known ZP domain proteins present within the VE (now 30 in total) and identify a paralog of VERL (vitelline envelope zona pellucida domain protein [VEZP] 14) that contains a putative lysin-binding motif. We find that, like VERL, the divergence of VEZP14 among abalone species is driven by positive selection on the lysin-binding motif alone and that these paralogous egg VE proteins bind a similar set of sperm proteins including a rapidly evolving 18-kDa paralog of lysin, which may mediate sperm–egg fusion. This work identifies an egg coat paralog of VERL under positive selection and the candidate sperm proteins with which it may interact during abalone fertilization. PMID:19767347

Statistical properties of random clique networks

Science.gov (United States)

Ding, Yi-Min; Meng, Jun; Fan, Jing-Fang; Ye, Fang-Fu; Chen, Xiao-Song

2017-10-01

In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) model and the concept of cliques. We find that random clique networks having a small average degree differ from the ER network in that they have a large clustering coefficient and a power law clustering spectrum, while networks having a high average degree have similar properties as the ER model. In addition, we find that the relation between the clustering coefficient and the average degree shows a non-monotonic behavior and that the degree distributions can be fit by multiple Poisson curves; we explain the origin of such novel behaviors and degree distributions.

Identification and Structure-Function Analysis of Subfamily Selective G Protein-Coupled Receptor Kinase Inhibitors

Energy Technology Data Exchange (ETDEWEB)

Homan, Kristoff T.; Larimore, Kelly M.; Elkins, Jonathan M.; Szklarz, Marta; Knapp, Stefan; Tesmer, John J.G. [Michigan; (Oxford)

2015-02-13

Selective inhibitors of individual subfamilies of G protein-coupled receptor kinases (GRKs) would serve as useful chemical probes as well as leads for therapeutic applications ranging from heart failure to Parkinson’s disease. To identify such inhibitors, differential scanning fluorimetry was used to screen a collection of known protein kinase inhibitors that could increase the melting points of the two most ubiquitously expressed GRKs: GRK2 and GRK5. Enzymatic assays on 14 of the most stabilizing hits revealed that three exhibit nanomolar potency of inhibition for individual GRKs, some of which exhibiting orders of magnitude selectivity. Most of the identified compounds can be clustered into two chemical classes: indazole/dihydropyrimidine-containing compounds that are selective for GRK2 and pyrrolopyrimidine-containing compounds that potently inhibit GRK1 and GRK5 but with more modest selectivity. The two most potent inhibitors representing each class, GSK180736A and GSK2163632A, were cocrystallized with GRK2 and GRK1, and their atomic structures were determined to 2.6 and 1.85 Å spacings, respectively. GSK180736A, developed as a Rho-associated, coiled-coil-containing protein kinase inhibitor, binds to GRK2 in a manner analogous to that of paroxetine, whereas GSK2163632A, developed as an insulin-like growth factor 1 receptor inhibitor, occupies a novel region of the GRK active site cleft that could likely be exploited to achieve more selectivity. However, neither compound inhibits GRKs more potently than their initial targets. This data provides the foundation for future efforts to rationally design even more potent and selective GRK inhibitors.

Selective labeling of a single organelle by using two-photon conversion of a photoconvertible fluorescent protein

Science.gov (United States)

Watanabe, Wataru; Shimada, Tomoko; Matsunaga, Sachihiro; Kurihara, Daisuke; Arimura, Shin-ichi; Tsutsumi, Nobuhiro; Fukui, Kiichi; Itoh, Kazuyoshi

2008-02-01

We present space-selective labeling of organelles by using two-photon conversion of a photoconvertible fluorescent protein with near-infrared femtosecond laser pulses. Two-photon excitation of photoconvertible fluorescent-protein, Kaede, enables space-selective labeling of organelles. We alter the fluorescence of target mitochondria in a tobacco BY-2 cell from green to red by focusing femtosecond laser pulses with a wavelength of 750 nm.

Highly Selective Fluorescent Sensing of Proteins Based on a Fluorescent Molecularly Imprinted Nanosensor

Directory of Open Access Journals (Sweden)

Shuo Wang

2013-09-01

Full Text Available A fluorescent molecularly imprinted nanosensor was obtained by grafting imprinted polymer onto the surface of multi-wall carbon nanotubes and post-imprinting treatment with fluorescein isothiocyanate (FITC. The fluorescence of lysozyme-imprinted polymer (Lys-MIP was quenched more strongly by Lys than that of nonimprinted polymer (NIP, which indicated that the Lys-MIP could recognize Lys. The resulted imprinted material has the ability to selectively sense a target protein, and an imprinting factor of 3.34 was achieved. The Lys-MIP also showed selective detection for Lys among other proteins such as cytochrome C (Cyt C, hemoglobin (HB and bovine serum albumin (BSA due to the imprinted sites in the Lys-MIP. This approach combines the high selectivity of surface molecular imprinting technology and fluorescence, and converts binding events into detectable signals by monitoring fluorescence spectra. Therefore, it will have further applications for Lys sensing.

Materials selection for oxide-based resistive random access memories

Energy Technology Data Exchange (ETDEWEB)

Guo, Yuzheng; Robertson, John [Engineering Department, Cambridge University, Cambridge CB2 1PZ (United Kingdom)

2014-12-01

The energies of atomic processes in resistive random access memories (RRAMs) are calculated for four typical oxides, HfO{sub 2}, TiO{sub 2}, Ta{sub 2}O{sub 5}, and Al{sub 2}O{sub 3}, to define a materials selection process. O vacancies have the lowest defect formation energy in the O-poor limit and dominate the processes. A band diagram defines the operating Fermi energy and O chemical potential range. It is shown how the scavenger metal can be used to vary the O vacancy formation energy, via controlling the O chemical potential, and the mean Fermi energy. The high endurance of Ta{sub 2}O{sub 5} RRAM is related to its more stable amorphous phase and the adaptive lattice rearrangements of its O vacancy.

A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins.

Science.gov (United States)

Pagan, Rafael F; Massey, Steven E

2014-02-01

Proteins are regarded as being robust to the deleterious effects of mutations. Here, the neutral emergence of mutational robustness in a population of single domain proteins is explored using computer simulations. A pairwise contact model was used to calculate the ΔG of folding (ΔG folding) using the three dimensional protein structure of leech eglin C. A random amino acid sequence with low mutational robustness, defined as the average ΔΔG resulting from a point mutation (ΔΔG average), was threaded onto the structure. A population of 1,000 threaded sequences was evolved under selection for stability, using an upper and lower energy threshold. Under these conditions, mutational robustness increased over time in the most common sequence in the population. In contrast, when the wild type sequence was used it did not show an increase in robustness. This implies that the emergence of mutational robustness is sequence specific and that wild type sequences may be close to maximal robustness. In addition, an inverse relationship between ∆∆G average and protein stability is shown, resulting partly from a larger average effect of point mutations in more stable proteins. The emergence of mutational robustness was also observed in the Escherichia coli colE1 Rop and human CD59 proteins, implying that the property may be common in single domain proteins under certain simulation conditions. The results indicate that at least a portion of mutational robustness in small globular proteins might have arisen by a process of neutral emergence, and could be an example of a beneficial trait that has not been directly selected for, termed a "pseudaptation."

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Science.gov (United States)

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

Habituation to low or high protein intake does not modulate basal or postprandial muscle protein synthesis rates: a randomized trial.

Science.gov (United States)

Gorissen, Stefan Hm; Horstman, Astrid Mh; Franssen, Rinske; Kouw, Imre Wk; Wall, Benjamin T; Burd, Nicholas A; de Groot, Lisette Cpgm; van Loon, Luc Jc

2017-02-01

Muscle mass maintenance is largely regulated by basal muscle protein synthesis rates and the ability to increase muscle protein synthesis after protein ingestion. To our knowledge, no previous studies have evaluated the impact of habituation to either low protein intake (LOW PRO) or high protein intake (HIGH PRO) on the postprandial muscle protein synthetic response. We assessed the impact of LOW PRO compared with HIGH PRO on basal and postprandial muscle protein synthesis rates after the ingestion of 25 g whey protein. Twenty-four healthy, older men [age: 62 ± 1 y; body mass index (in kg/m 2 ): 25.9 ± 0.4 (mean ± SEM)] participated in a parallel-group randomized trial in which they adapted to either a LOW PRO diet (0.7 g · kg -1 · d -1 ; n = 12) or a HIGH PRO diet (1.5 g · kg -1 · d -1 ; n = 12) for 14 d. On day 15, participants received primed continuous l-[ring- 2 H 5 ]-phenylalanine and l-[1- 13 C]-leucine infusions and ingested 25 g intrinsically l-[1- 13 C]-phenylalanine- and l-[1- 13 C]-leucine-labeled whey protein. Muscle biopsies and blood samples were collected to assess muscle protein synthesis rates as well as dietary protein digestion and absorption kinetics. Plasma leucine concentrations and exogenous phenylalanine appearance rates increased after protein ingestion (P 0.05). Plasma exogenous phenylalanine availability over the 5-h postprandial period was greater after LOW PRO than after HIGH PRO (61% ± 1% compared with 56% ± 2%, respectively; P protein synthesis rates increased from 0.031% ± 0.004% compared with 0.039% ± 0.007%/h in the fasted state to 0.062% ± 0.005% compared with 0.057% ± 0.005%/h in the postprandial state after LOW PRO compared with HIGH PRO, respectively (P protein-derived amino acids in the circulation and does not lower basal muscle protein synthesis rates or increase postprandial muscle protein synthesis rates after ingestion of 25 g protein in older men. This trial was registered at clinicaltrials.gov as NCT

A genetic replacement system for selection-based engineering of essential proteins

Science.gov (United States)

2012-01-01

Background Essential genes represent the core of biological functions required for viability. Molecular understanding of essentiality as well as design of synthetic cellular systems includes the engineering of essential proteins. An impediment to this effort is the lack of growth-based selection systems suitable for directed evolution approaches. Results We established a simple strategy for genetic replacement of an essential gene by a (library of) variant(s) during a transformation. The system was validated using three different essential genes and plasmid combinations and it reproducibly shows transformation efficiencies on the order of 107 transformants per microgram of DNA without any identifiable false positives. This allowed for reliable recovery of functional variants out of at least a 105-fold excess of non-functional variants. This outperformed selection in conventional bleach-out strains by at least two orders of magnitude, where recombination between functional and non-functional variants interfered with reliable recovery even in recA negative strains. Conclusions We propose that this selection system is extremely suitable for evaluating large libraries of engineered essential proteins resulting in the reliable isolation of functional variants in a clean strain background which can readily be used for in vivo applications as well as expression and purification for use in in vitro studies. PMID:22898007

Using random forests for assistance in the curation of G-protein coupled receptor databases.

Science.gov (United States)

Shkurin, Aleksei; Vellido, Alfredo

2017-08-18

Biology is experiencing a gradual but fast transformation from a laboratory-centred science towards a data-centred one. As such, it requires robust data engineering and the use of quantitative data analysis methods as part of database curation. This paper focuses on G protein-coupled receptors, a large and heterogeneous super-family of cell membrane proteins of interest to biology in general. One of its families, Class C, is of particular interest to pharmacology and drug design. This family is quite heterogeneous on its own, and the discrimination of its several sub-families is a challenging problem. In the absence of known crystal structure, such discrimination must rely on their primary amino acid sequences. We are interested not as much in achieving maximum sub-family discrimination accuracy using quantitative methods, but in exploring sequence misclassification behavior. Specifically, we are interested in isolating those sequences showing consistent misclassification, that is, sequences that are very often misclassified and almost always to the same wrong sub-family. Random forests are used for this analysis due to their ensemble nature, which makes them naturally suited to gauge the consistency of misclassification. This consistency is here defined through the voting scheme of their base tree classifiers. Detailed consistency results for the random forest ensemble classification were obtained for all receptors and for all data transformations of their unaligned primary sequences. Shortlists of the most consistently misclassified receptors for each subfamily and transformation, as well as an overall shortlist including those cases that were consistently misclassified across transformations, were obtained. The latter should be referred to experts for further investigation as a data curation task. The automatic discrimination of the Class C sub-families of G protein-coupled receptors from their unaligned primary sequences shows clear limits. This study has

Markov analysis of alpha-helical, beta-sheet and random coil regions of proteins

International Nuclear Information System (INIS)

Macchiato, M.; Tramontano, A.

1983-01-01

The rules up to now used to predict the spatial configuration of proteins from their primary structure are mostly based on the recurrence analysis of some doublets, triplets and so on of contiguous amino acids, but they do not take into account the correlation characteristics of the whole amino acid sequence. A statistical analysis of amino acid sequences for the alpha-helical, beta-sheet and random coil regions of about twenty proteins with known secondary structure by considering correlations effects has been carried out. The obtained results demonstrate that these sequences are at least a second-order Markov chain, i.e. they appear as if they were generated by a source that remembers at least the two aminoacids before the one being generated and that these two previous symbols influence the present choice

40 CFR 761.306 - Sampling 1 meter square surfaces by random selection of halves.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sampling 1 meter square surfaces by...(b)(3) § 761.306 Sampling 1 meter square surfaces by random selection of halves. (a) Divide each 1 meter square portion where it is necessary to collect a surface wipe test sample into two equal (or as...

From Protocols to Publications: A Study in Selective Reporting of Outcomes in Randomized Trials in Oncology

Science.gov (United States)

Raghav, Kanwal Pratap Singh; Mahajan, Sminil; Yao, James C.; Hobbs, Brian P.; Berry, Donald A.; Pentz, Rebecca D.; Tam, Alda; Hong, Waun K.; Ellis, Lee M.; Abbruzzese, James; Overman, Michael J.

2015-01-01

Purpose The decision by journals to append protocols to published reports of randomized trials was a landmark event in clinical trial reporting. However, limited information is available on how this initiative effected transparency and selective reporting of clinical trial data. Methods We analyzed 74 oncology-based randomized trials published in Journal of Clinical Oncology, the New England Journal of Medicine, and The Lancet in 2012. To ascertain integrity of reporting, we compared published reports with their respective appended protocols with regard to primary end points, nonprimary end points, unplanned end points, and unplanned analyses. Results A total of 86 primary end points were reported in 74 randomized trials; nine trials had greater than one primary end point. Nine trials (12.2%) had some discrepancy between their planned and published primary end points. A total of 579 nonprimary end points (median, seven per trial) were planned, of which 373 (64.4%; median, five per trial) were reported. A significant positive correlation was found between the number of planned and nonreported nonprimary end points (Spearman r = 0.66; P < .001). Twenty-eight studies (37.8%) reported a total of 65 unplanned end points; 52 (80.0%) of which were not identified as unplanned. Thirty-one (41.9%) and 19 (25.7%) of 74 trials reported a total of 52 unplanned analyses involving primary end points and 33 unplanned analyses involving nonprimary end points, respectively. Studies reported positive unplanned end points and unplanned analyses more frequently than negative outcomes in abstracts (unplanned end points odds ratio, 6.8; P = .002; unplanned analyses odd ratio, 8.4; P = .007). Conclusion Despite public and reviewer access to protocols, selective outcome reporting persists and is a major concern in the reporting of randomized clinical trials. To foster credible evidence-based medicine, additional initiatives are needed to minimize selective reporting. PMID:26304898

Joint random beam and spectrum selection for spectrum sharing systems with partial channel state information

KAUST Repository

Abdallah, Mohamed M.

2013-11-01

In this work, we develop joint interference-aware random beam and spectrum selection scheme that provide enhanced performance for the secondary network under the condition that the interference observed at the primary receiver is below a predetermined acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a set of primary links composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes jointly select a beam, among a set of power-optimized random beams, as well as the primary spectrum that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint. In particular, we consider the case where the interference level is described by a q-bit description of its magnitude, whereby we propose a technique to find the optimal quantizer thresholds in a mean square error (MSE) sense. © 2013 IEEE.

Joint random beam and spectrum selection for spectrum sharing systems with partial channel state information

KAUST Repository

Abdallah, Mohamed M.; Sayed, Mostafa M.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

2013-01-01

In this work, we develop joint interference-aware random beam and spectrum selection scheme that provide enhanced performance for the secondary network under the condition that the interference observed at the primary receiver is below a predetermined acceptable value. We consider a secondary link composed of a transmitter equipped with multiple antennas and a single-antenna receiver sharing the same spectrum with a set of primary links composed of a single-antenna transmitter and a single-antenna receiver. The proposed schemes jointly select a beam, among a set of power-optimized random beams, as well as the primary spectrum that maximizes the signal-to-interference-plus-noise ratio (SINR) of the secondary link while satisfying the primary interference constraint. In particular, we consider the case where the interference level is described by a q-bit description of its magnitude, whereby we propose a technique to find the optimal quantizer thresholds in a mean square error (MSE) sense. © 2013 IEEE.

The RANDOM computer program: A linear congruential random number generator

Science.gov (United States)

Miles, R. F., Jr.

1986-01-01

The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.

Analysis and applications of a frequency selective surface via a random distribution method

International Nuclear Information System (INIS)

Xie Shao-Yi; Huang Jing-Jian; Yuan Nai-Chang; Liu Li-Guo

2014-01-01

A novel frequency selective surface (FSS) for reducing radar cross section (RCS) is proposed in this paper. This FSS is based on the random distribution method, so it can be called random surface. In this paper, the stacked patches serving as periodic elements are employed for RCS reduction. Previous work has demonstrated the efficiency by utilizing the microstrip patches, especially for the reflectarray. First, the relevant theory of the method is described. Then a sample of a three-layer variable-sized stacked patch random surface with a dimension of 260 mm×260 mm is simulated, fabricated, and measured in order to demonstrate the validity of the proposed design. For the normal incidence, the 8-dB RCS reduction can be achieved both by the simulation and the measurement in 8 GHz–13 GHz. The oblique incidence of 30° is also investigated, in which the 7-dB RCS reduction can be obtained in a frequency range of 8 GHz–14 GHz. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Diversity of T cell epitopes in Plasmodium falciparum circumsporozoite protein likely due to protein-protein interactions.

Directory of Open Access Journals (Sweden)

Nagesh R Aragam

Full Text Available Circumsporozoite protein (CS is a leading vaccine antigen for falciparum malaria, but is highly polymorphic in natural parasite populations. The factors driving this diversity are unclear, but non-random assortment of the T cell epitopes TH2 and TH3 has been observed in a Kenyan parasite population. The recent publication of the crystal structure of the variable C terminal region of the protein allows the assessment of the impact of diversity on protein structure and T cell epitope assortment. Using data from the Gambia (55 isolates and Malawi (235 isolates, we evaluated the patterns of diversity within and between epitopes in these two distantly-separated populations. Only non-synonymous mutations were observed with the vast majority in both populations at similar frequencies suggesting strong selection on this region. A non-random pattern of T cell epitope assortment was seen in Malawi and in the Gambia, but structural analysis indicates no intramolecular spatial interactions. Using the information from these parasite populations, structural analysis reveals that polymorphic amino acids within TH2 and TH3 colocalize to one side of the protein, surround, but do not involve, the hydrophobic pocket in CS, and predominately involve charge switches. In addition, free energy analysis suggests residues forming and behind the novel pocket within CS are tightly constrained and well conserved in all alleles. In addition, free energy analysis shows polymorphic residues tend to be populated by energetically unfavorable amino acids. In combination, these findings suggest the diversity of T cell epitopes in CS may be primarily an evolutionary response to intermolecular interactions at the surface of the protein potentially counteracting antibody-mediated immune recognition or evolving host receptor diversity.

Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords.

Directory of Open Access Journals (Sweden)

R Alexander Bentley

Full Text Available The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.

On theoretical models of gene expression evolution with random genetic drift and natural selection.

Directory of Open Access Journals (Sweden)

Osamu Ogasawara

2009-11-01

Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

Identification of physicochemical selective pressure on protein encoding nucleotide sequences

Directory of Open Access Journals (Sweden)

Sainudiin Raazesh

2006-03-01

Full Text Available Abstract Background Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. Results We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC and from the abalone sperm lysine. Conclusion Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties.

From Protocols to Publications: A Study in Selective Reporting of Outcomes in Randomized Trials in Oncology.

Science.gov (United States)

Raghav, Kanwal Pratap Singh; Mahajan, Sminil; Yao, James C; Hobbs, Brian P; Berry, Donald A; Pentz, Rebecca D; Tam, Alda; Hong, Waun K; Ellis, Lee M; Abbruzzese, James; Overman, Michael J

2015-11-01

The decision by journals to append protocols to published reports of randomized trials was a landmark event in clinical trial reporting. However, limited information is available on how this initiative effected transparency and selective reporting of clinical trial data. We analyzed 74 oncology-based randomized trials published in Journal of Clinical Oncology, the New England Journal of Medicine, and The Lancet in 2012. To ascertain integrity of reporting, we compared published reports with their respective appended protocols with regard to primary end points, nonprimary end points, unplanned end points, and unplanned analyses. A total of 86 primary end points were reported in 74 randomized trials; nine trials had greater than one primary end point. Nine trials (12.2%) had some discrepancy between their planned and published primary end points. A total of 579 nonprimary end points (median, seven per trial) were planned, of which 373 (64.4%; median, five per trial) were reported. A significant positive correlation was found between the number of planned and nonreported nonprimary end points (Spearman r = 0.66; P medicine, additional initiatives are needed to minimize selective reporting. © 2015 by American Society of Clinical Oncology.

Estimation of Daily Proteinuria in Patients with Amyloidosis by Using the Protein-To-Creatinine ratio in Random Urine Samples.

Science.gov (United States)

Talamo, Giampaolo; Mir Muhammad, A; Pandey, Manoj K; Zhu, Junjia; Creer, Michael H; Malysz, Jozef

2015-02-11

Measurement of daily proteinuria in patients with amyloidosis is recommended at the time of diagnosis for assessing renal involvement, and for monitoring disease activity. Renal involvement is usually defined by proteinuria >500 mg/day. We evaluated the accuracy of the random urine protein-to-creatinine ratio (Pr/Cr) in predicting 24 hour proteinuria in patient with amyloidosis. We compared results of random urine Pr/Cr ratio and concomitant 24-hour urine collections in 44 patients with amyloidosis. We found a strong correlation (Spearman's ρ=0.874) between the Pr/Cr ratio and the 24 hour urine protein excretion. For predicting renal involvement, the optimal cut-off point of the Pr/Cr ratio was 715 mg/g. The sensitivity and specificity for this point were 91.8% and 95.5%, respectively, and the area under the curve value was 97.4%. We conclude that the random urine Pr/Cr ratio could be useful in the screening of renal involvement in patients with amyloidosis. If validated in a prospective study, the random urine Pr/Cr ratio could replace the 24 hour urine collection for the assessment of daily proteinuria and presence of nephrotic syndrome in patients with amyloidosis.

Structural optimization and structure-functional selectivity relationship studies of G protein-biased EP2 receptor agonists.

Science.gov (United States)

Ogawa, Seiji; Watanabe, Toshihide; Moriyuki, Kazumi; Goto, Yoshikazu; Yamane, Shinsaku; Watanabe, Akio; Tsuboi, Kazuma; Kinoshita, Atsushi; Okada, Takuya; Takeda, Hiroyuki; Tani, Kousuke; Maruyama, Toru

2016-05-15

The modification of the novel G protein-biased EP2 agonist 1 has been investigated to improve its G protein activity and develop a better understanding of its structure-functional selectivity relationship (SFSR). The optimization of the substituents on the phenyl ring of 1, followed by the inversion of the hydroxyl group on the cyclopentane moiety led to compound 9, which showed a 100-fold increase in its G protein activity compared with 1 without any increase in β-arrestin recruitment. Furthermore, SFSR studies revealed that the combination of meta and para substituents on the phenyl moiety was crucial to the functional selectivity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Defining an essence of structure determining residue contacts in proteins.

Science.gov (United States)

Sathyapriya, R; Duarte, Jose M; Stehr, Henning; Filippis, Ioannis; Lappe, Michael

2009-12-01

The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this "structural essence" has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts-such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed "cone-peeling" that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 A Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This "structural essence" opens new avenues in the

High Entropy Random Selection Protocols

NARCIS (Netherlands)

H. Buhrman (Harry); M. Christandl (Matthias); M. Koucky (Michal); Z. Lotker (Zvi); B. Patt-Shamir; M. Charikar; K. Jansen; O. Reingold; J. Rolim

2007-01-01

textabstractIn this paper, we construct protocols for two parties that do not trust each other, to generate random variables with high Shannon entropy. We improve known bounds for the trade off between the number of rounds, length of communication and the entropy of the outcome.

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

Science.gov (United States)

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and

Evaluation of fishmeal protein supplementation to commercial feeds ...

African Journals Online (AJOL)

A total of 140 Lohman pullets layers at eighteenth week of lay were randomly selected and used to study effects of graded levels of fishmeal protein supplementation to two commercial feeds (type A & B) on egg production and quality. Layers were divided into two equal groups each of which was divided into five equal sub ...

Integrated Behavior Therapy for Selective Mutism: a randomized controlled pilot study.

Science.gov (United States)

Bergman, R Lindsey; Gonzalez, Araceli; Piacentini, John; Keller, Melody L

2013-10-01

To evaluate the feasibility, acceptability, and preliminary efficacy of a novel behavioral intervention for reducing symptoms of selective mutism and increasing functional speech. A total of 21 children ages 4 to 8 with primary selective mutism were randomized to 24 weeks of Integrated Behavior Therapy for Selective Mutism (IBTSM) or a 12-week Waitlist control. Clinical outcomes were assessed using blind independent evaluators, parent-, and teacher-report, and an objective behavioral measure. Treatment recipients completed a three-month follow-up to assess durability of treatment gains. Data indicated increased functional speaking behavior post-treatment as rated by parents and teachers, with a high rate of treatment responders as rated by blind independent evaluators (75%). Conversely, children in the Waitlist comparison group did not experience significant improvements in speaking behaviors. Children who received IBTSM also demonstrated significant improvements in number of words spoken at school compared to baseline, however, significant group differences did not emerge. Treatment recipients also experienced significant reductions in social anxiety per parent, but not teacher, report. Clinical gains were maintained over 3 month follow-up. IBTSM appears to be a promising new intervention that is efficacious in increasing functional speaking behaviors, feasible, and acceptable to parents and teachers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Field-based random sampling without a sampling frame: control selection for a case-control study in rural Africa.

Science.gov (United States)

Crampin, A C; Mwinuka, V; Malema, S S; Glynn, J R; Fine, P E

2001-01-01

Selection bias, particularly of controls, is common in case-control studies and may materially affect the results. Methods of control selection should be tailored both for the risk factors and disease under investigation and for the population being studied. We present here a control selection method devised for a case-control study of tuberculosis in rural Africa (Karonga, northern Malawi) that selects an age/sex frequency-matched random sample of the population, with a geographical distribution in proportion to the population density. We also present an audit of the selection process, and discuss the potential of this method in other settings.

Tolerance of a knotted near infrared fluorescent protein to random circular permutation

Science.gov (United States)

Pandey, Naresh; Kuypers, Brianna E.; Nassif, Barbara; Thomas, Emily E.; Alnahhas, Razan N.; Segatori, Laura; Silberg, Jonathan J.

2016-01-01

Bacteriophytochrome photoreceptors (BphP) are knotted proteins that have been developed as near-infrared fluorescent protein (iRFP) reporters of gene expression. To explore how rearrangements in the peptides that interlace into the knot within the BphP photosensory core affect folding, we subjected iRFP to random circular permutation using an improved transposase mutagenesis strategy and screened for variants that fluoresce. We identified twenty seven circularly permuted iRFP that display biliverdin-dependent fluorescence in Escherichia coli. The variants with the brightest whole cell fluorescence initiated translation at residues near the domain linker and knot tails, although fluorescent variants were discovered that initiated translation within the PAS and GAF domains. Circularly permuted iRFP retained sufficient cofactor affinity to fluoresce in tissue culture without the addition of biliverdin, and one variant displayed enhanced fluorescence when expressed in bacteria and tissue culture. This variant displayed a similar quantum yield as iRFP, but exhibited increased resistance to chemical denaturation, suggesting that the observed signal increase arose from more efficient protein maturation. These results show how the contact order of a knotted BphP can be altered without disrupting chromophore binding and fluorescence, an important step towards the creation of near-infrared biosensors with expanded chemical-sensing functions for in vivo imaging. PMID:27304983

Treatment selection in a randomized clinical trial via covariate-specific treatment effect curves.

Science.gov (United States)

Ma, Yunbei; Zhou, Xiao-Hua

2017-02-01

For time-to-event data in a randomized clinical trial, we proposed two new methods for selecting an optimal treatment for a patient based on the covariate-specific treatment effect curve, which is used to represent the clinical utility of a predictive biomarker. To select an optimal treatment for a patient with a specific biomarker value, we proposed pointwise confidence intervals for each covariate-specific treatment effect curve and the difference between covariate-specific treatment effect curves of two treatments. Furthermore, to select an optimal treatment for a future biomarker-defined subpopulation of patients, we proposed confidence bands for each covariate-specific treatment effect curve and the difference between each pair of covariate-specific treatment effect curve over a fixed interval of biomarker values. We constructed the confidence bands based on a resampling technique. We also conducted simulation studies to evaluate finite-sample properties of the proposed estimation methods. Finally, we illustrated the application of the proposed method in a real-world data set.

Major membrane surface proteins of Mycoplasma hyopneumoniae selectively modified by covalently bound lipid

International Nuclear Information System (INIS)

Wise, K.S.; Kim, M.F.

1987-01-01

Surface protein antigens of Mycoplasma hyopneumoniae were identified by direct antibody-surface binding or by radioimmunoprecipitation of surface 125 I-labeled proteins with a series of monoclonal antibodies (MAbs). Radioimmunoprecipitation of TX-114-phase proteins from cells labeled with [ 35 S] methionine, 14 C-amino acids, or [ 3 H] palmitic acid showed that proteins p65, p50, and p44 were abundant and (with one other hydrophobic protein, p60) were selectively labeled with lipid. Alkaline hydroxylamine treatment of labeled proteins indicated linkage of lipids by amide or stable O-linked ester bonds. Proteins p65, p50, and p44 were highly immunogenic in the natural host as measured by immunoblots of TX-114-phase proteins with antisera from swine inoculated with whole organisms. These proteins were antigenically and structurally unrelated, since hyperimmune mouse antibodies to individual gel-purified proteins were monospecific and gave distinct proteolytic epitope maps. Intraspecies size variants of one surface antigen of M. hyopneumoniae were revealed by a MAb to p70 (defined in strain J, ATCC 25934), which recognized a large p73 component on strain VPP11 (ATCC 25617). In addition, MAb to internal, aqueous-phase protein p82 of strain J failed to bind an analogous antigen in strain VPP11

Major membrane surface proteins of Mycoplasma hyopneumoniae selectively modified by covalently bound lipid

Energy Technology Data Exchange (ETDEWEB)

Wise K.S.; Kim, M.F.

1987-12-01

Surface protein antigens of Mycoplasma hyopneumoniae were identified by direct antibody-surface binding or by radioimmunoprecipitation of surface /sup 125/I-labeled proteins with a series of monoclonal antibodies (MAbs). Radioimmunoprecipitation of TX-114-phase proteins from cells labeled with (/sup 35/S) methionine, /sup 14/C-amino acids, or (/sup 3/H) palmitic acid showed that proteins p65, p50, and p44 were abundant and (with one other hydrophobic protein, p60) were selectively labeled with lipid. Alkaline hydroxylamine treatment of labeled proteins indicated linkage of lipids by amide or stable O-linked ester bonds. Proteins p65, p50, and p44 were highly immunogenic in the natural host as measured by immunoblots of TX-114-phase proteins with antisera from swine inoculated with whole organisms. These proteins were antigenically and structurally unrelated, since hyperimmune mouse antibodies to individual gel-purified proteins were monospecific and gave distinct proteolytic epitope maps. Intraspecies size variants of one surface antigen of M. hyopneumoniae were revealed by a MAb to p70 (defined in strain J, ATCC 25934), which recognized a large p73 component on strain VPP11 (ATCC 25617). In addition, MAb to internal, aqueous-phase protein p82 of strain J failed to bind an analogous antigen in strain VPP11.

Selective association of a fragment of the knob protein with spectrin, actin and the red cell membrane.

Science.gov (United States)

Kilejian, A; Rashid, M A; Aikawa, M; Aji, T; Yang, Y F

1991-02-01

The knob protein of Plasmodium falciparum is essential for the formation of knob-like protrusions on the host erythrocyte membrane. A functional domain of the knob protein was identified. This peptide formed stable complexes with the two major red cell skeletal proteins, spectrin and actin. When introduced into resealed normal erythrocytes, the peptide associated selectively with the cytoplasmic surface of the membrane and formed knob-like electron dense deposits. Knobs are thought to play an important role in the immunopathology of P. falciparum infections. Our findings provide a first step towards understanding the molecular basis for selective membrane changes at knobs.

The effects of soy protein on chronic kidney disease: a meta-analysis of randomized controlled trials.

Science.gov (United States)

Zhang, J; Liu, J; Su, J; Tian, F

2014-09-01

There is a growing body of evidence to indicate that soy protein consumption may have a beneficial effect on kidney function. We performed a meta-analysis to evaluate the effects of soy protein consumption compared with animal protein consumption in patients with pre-dialysis chronic kidney disease (CKD). We conducted a structured electronic search of the databases PubMed, EMBASE, Cochrane Library and Chinese Biological Medicine for randomized controlled trials published up to March 2014. The outcome measures were serum creatinine (SCR), triglyceride (TG), total cholesterol (TC), calcium (Ca) and phosphorus concentrations. Weighted or standard mean differences were calculated for net changes using random-effects models. The meta-analysis consisted of nine trials, comprising 197 subjects. Soy protein intake significantly reduced SCR and serum phosphorus concentrations. The mean difference was -6.231 μmol/l (95% confidence interval (CI): -11.109, -1.352 μmol/l) for SCR (P=0.012) and -0.804 (95% CI: -1.143, -0.464 μmol/l) for serum phosphorus (P=0.00). It also significantly reduced serum TG, with a pooled estimated change of -0.223 mmol/l (95% CI: -0.396, -0.051 mmol/l; P=0.011) after the exclusion of one trial indicated by sensitivity analyses. No statistically significant effects were observed for TC (-0.135 mmol/l (95% CI: -0.289, 0.019 mmol/l)) or Ca (0.023 mmol/l (95% CI: -0.016, 0.062 mmol/l)). The meta-analysis suggested a protective effect of soy protein consumption on SCR and serum phosphorus concentrations in pre-dialysis CKD patients. It may also have a significant effect on lowering serum TG concentrations. However, nonsignificant effects on TC and Ca were observed. Evidence was limited because of the relatively small number of available trials and subjects.

Random coil chemical shift for intrinsically disordered proteins

DEFF Research Database (Denmark)

Kjærgaard, Magnus; Brander, Søren; Poulsen, Flemming Martin

2011-01-01

. Temperature has a non-negligible effect on the (13)C random coil chemical shifts, so temperature coefficients are reported for the random coil chemical shifts to allow extrapolation to other temperatures. The pH dependence of the histidine random coil chemical shifts is investigated in a titration series......, which allows the accurate random coil chemical shifts to be obtained at any pH. By correcting the random coil chemical shifts for the effects of temperature and pH, systematic biases of the secondary chemical shifts are minimized, which will improve the reliability of detection of transient secondary...

Meals based on vegetable protein sources (beans and peas) are more satiating than meals based on animal protein sources (veal and pork) - a randomized cross-over meal test study

DEFF Research Database (Denmark)

Kristensen, Marlene Dahlwad; Bendsen, Nathalie Tommerup; Christensen, Sheena M

2016-01-01

BACKGROUND: Recent nutrition recommendations advocate a reduction in protein from animal sources (pork, beef) because of environmental concerns. Instead, protein from vegetable sources (beans, peas) should be increased. However, little is known about the effect of these vegetable protein sources...... on appetite regulation. OBJECTIVE: To examine whether meals based on vegetable protein sources (beans/peas) are comparable to meals based on animal protein sources (veal/pork) regarding meal-induced appetite sensations. DESIGN: In total, 43 healthy, normal-weight, young men completed this randomized, double......-Legume compared to HP-Meat or LP-Legume (pVegetable-based meals (beans/peas) influenced appetite sensations favorably compared to animal-based meals (pork/veal) with similar energy and protein content, but lower fiber content. Interestingly, a vegetable-based meal with low protein content...

Estimation of daily proteinuria in patients with amyloidosis by using the protein-to-creatinine ratio in random urine sample

Directory of Open Access Journals (Sweden)

Giampaolo Talamo

2015-02-01

Full Text Available Measurement of daily proteinuria in patients with amyloidosis is recommended at the time of diagnosis for assessing renal involvement, and for monitoring disease activity. Renal involvement is usually defined by proteinuria >500 mg/day. We evaluated the accuracy of the random urine protein-to-creatinine ratio (Pr/Cr in predicting 24 hour proteinuria in patient with amyloidosis. We com- pared results of random urine Pr/Cr ratio and concomitant 24-hour urine collections in 44 patients with amyloidosis. We found a strong correlation (Spearman’s ρ=0.874 between the Pr/Cr ratio and the 24 hour urine protein excretion. For predicting renal involvement, the optimal cut-off point of the Pr/Cr ratio was 715 mg/g. The sensitivity and specificity for this point were 91.8% and 95.5%, respectively, and the area under the curve value was 97.4%. We conclude that the random urine Pr/Cr ratio could be useful in the screening of renal involvement in patients with amyloidosis. If validated in a prospective study, the random urine Pr/Cr ratio could replace the 24 hour urine collection for the assessment of daily proteinuria and presence of nephrotic syndrome in patients with amyloidosis.

Feature selection and nearest centroid classification for protein mass spectrometry

Directory of Open Access Journals (Sweden)

Levner Ilya

2005-03-01

selection methods using the nearest centroid classifier and found that several reportedly state-of-the-art algorithms in fact perform rather poorly when tested via stratified cross-validation. The revealed inconsistencies provide clear evidence that algorithm evaluation should be performed on several data sets using a consistent (i.e., non-randomized, stratified cross-validation procedure in order for the conclusions to be statistically sound.

Electrostatics promotes molecular crowding and selects the aggregation pathway in fibril-forming protein solutions

International Nuclear Information System (INIS)

Raccosta, S.; Martorana, V.; Manno, M.; Blanco, M.; Roberts, C.J.

2016-01-01

The role of intermolecular interaction in fibril-forming protein solutions and its relation with molecular conformation are crucial aspects for the control and inhibition of amyloid structures. Here, we study the fibril formation and the protein-protein interactions for two proteins at acidic ph, lysozyme and α-chymotrypsinogen. By using light scattering experiments and the Kirkwood-Buff integral approach, we show how concentration fluctuations are damped even at moderate protein concentrations by the dominant long-ranged electrostatic repulsion, which determines an effective crowded environment. In denaturing conditions, electrostatic repulsion keeps the monomeric solution in a thermodynamically metastable state, which is escaped through kinetically populated conformational sub-states. This explains how electrostatics acts as a gatekeeper in selecting a specific aggregation pathway.

An α-Helix-Mimicking 12,13-Helix: Designed α/β/γ-Foldamers as Selective Inhibitors of Protein-Protein Interactions.

Science.gov (United States)

Grison, Claire M; Miles, Jennifer A; Robin, Sylvie; Wilson, Andrew J; Aitken, David J

2016-09-05

A major current challenge in bioorganic chemistry is the identification of effective mimics of protein secondary structures that act as inhibitors of protein-protein interactions (PPIs). In this work, trans-2-aminocyclobutanecarboxylic acid (tACBC) was used as the key β-amino acid component in the design of α/β/γ-peptides to structurally mimic a native α-helix. Suitably functionalized α/β/γ-peptides assume an α-helix-mimicking 12,13-helix conformation in solution, exhibit enhanced proteolytic stability in comparison to the wild-type α-peptide parent sequence from which they are derived, and act as selective inhibitors of the p53/hDM2 interaction. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Selective inhibition of Biotin Protein Ligase from Staphylococcus aureus*

Science.gov (United States)

Soares da Costa, Tatiana P.; Tieu, William; Yap, Min Y.; Pendini, Nicole R.; Polyak, Steven W.; Sejer Pedersen, Daniel; Morona, Renato; Turnidge, John D.; Wallace, John C.; Wilce, Matthew C. J.; Booker, Grant W.; Abell, Andrew D.

2012-01-01

There is a well documented need to replenish the antibiotic pipeline with new agents to combat the rise of drug resistant bacteria. One strategy to combat resistance is to discover new chemical classes immune to current resistance mechanisms that inhibit essential metabolic enzymes. Many of the obvious drug targets that have no homologous isozyme in the human host have now been investigated. Bacterial drug targets that have a closely related human homologue represent a new frontier in antibiotic discovery. However, to avoid potential toxicity to the host, these inhibitors must have very high selectivity for the bacterial enzyme over the human homolog. We have demonstrated that the essential enzyme biotin protein ligase (BPL) from the clinically important pathogen Staphylococcus aureus could be selectively inhibited. Linking biotin to adenosine via a 1,2,3 triazole yielded the first BPL inhibitor selective for S. aureus BPL over the human equivalent. The synthesis of new biotin 1,2,3-triazole analogues using click chemistry yielded our most potent structure (Ki 90 nm) with a >1100-fold selectivity for the S. aureus BPL over the human homologue. X-ray crystallography confirmed the mechanism of inhibitor binding. Importantly, the inhibitor showed cytotoxicity against S. aureus but not cultured mammalian cells. The biotin 1,2,3-triazole provides a novel pharmacophore for future medicinal chemistry programs to develop this new antibiotic class. PMID:22437830

Selective inhibition of biotin protein ligase from Staphylococcus aureus.

Science.gov (United States)

Soares da Costa, Tatiana P; Tieu, William; Yap, Min Y; Pendini, Nicole R; Polyak, Steven W; Sejer Pedersen, Daniel; Morona, Renato; Turnidge, John D; Wallace, John C; Wilce, Matthew C J; Booker, Grant W; Abell, Andrew D

2012-05-18

There is a well documented need to replenish the antibiotic pipeline with new agents to combat the rise of drug resistant bacteria. One strategy to combat resistance is to discover new chemical classes immune to current resistance mechanisms that inhibit essential metabolic enzymes. Many of the obvious drug targets that have no homologous isozyme in the human host have now been investigated. Bacterial drug targets that have a closely related human homologue represent a new frontier in antibiotic discovery. However, to avoid potential toxicity to the host, these inhibitors must have very high selectivity for the bacterial enzyme over the human homolog. We have demonstrated that the essential enzyme biotin protein ligase (BPL) from the clinically important pathogen Staphylococcus aureus could be selectively inhibited. Linking biotin to adenosine via a 1,2,3 triazole yielded the first BPL inhibitor selective for S. aureus BPL over the human equivalent. The synthesis of new biotin 1,2,3-triazole analogues using click chemistry yielded our most potent structure (K(i) 90 nM) with a >1100-fold selectivity for the S. aureus BPL over the human homologue. X-ray crystallography confirmed the mechanism of inhibitor binding. Importantly, the inhibitor showed cytotoxicity against S. aureus but not cultured mammalian cells. The biotin 1,2,3-triazole provides a novel pharmacophore for future medicinal chemistry programs to develop this new antibiotic class.

Natural selection and algorithmic design of mRNA.

Science.gov (United States)

Cohen, Barry; Skiena, Steven

2003-01-01

Messenger RNA (mRNA) sequences serve as templates for proteins according to the triplet code, in which each of the 4(3) = 64 different codons (sequences of three consecutive nucleotide bases) in RNA either terminate transcription or map to one of the 20 different amino acids (or residues) which build up proteins. Because there are more codons than residues, there is inherent redundancy in the coding. Certain residues (e.g., tryptophan) have only a single corresponding codon, while other residues (e.g., arginine) have as many as six corresponding codons. This freedom implies that the number of possible RNA sequences coding for a given protein grows exponentially in the length of the protein. Thus nature has wide latitude to select among mRNA sequences which are informationally equivalent, but structurally and energetically divergent. In this paper, we explore how nature takes advantage of this freedom and how to algorithmically design structures more energetically favorable than have been built through natural selection. In particular: (1) Natural Selection--we perform the first large-scale computational experiment comparing the stability of mRNA sequences from a variety of organisms to random synonymous sequences which respect the codon preferences of the organism. This experiment was conducted on over 27,000 sequences from 34 microbial species with 36 genomic structures. We provide evidence that in all genomic structures highly stable sequences are disproportionately abundant, and in 19 of 36 cases highly unstable sequences are disproportionately abundant. This suggests that the stability of mRNA sequences is subject to natural selection. (2) Artificial Selection--motivated by these biological results, we examine the algorithmic problem of designing the most stable and unstable mRNA sequences which code for a target protein. We give a polynomial-time dynamic programming solution to the most stable sequence problem (MSSP), which is asymptotically no more complex

Pea proteins oral supplementation promotes muscle thickness gains during resistance training: a double-blind, randomized, Placebo-controlled clinical trial vs. Whey protein.

Science.gov (United States)

Babault, Nicolas; Païzis, Christos; Deley, Gaëlle; Guérin-Deremaux, Laetitia; Saniez, Marie-Hélène; Lefranc-Millot, Catherine; Allaert, François A

2015-01-01

The effects of protein supplementation on muscle thickness and strength seem largely dependent on its composition. The current study aimed at comparing the impact of an oral supplementation with vegetable Pea protein (NUTRALYS®) vs. Whey protein and Placebo on biceps brachii muscle thickness and strength after a 12-week resistance training program. One hundred and sixty one males, aged 18 to 35 years were enrolled in the study and underwent 12 weeks of resistance training on upper limb muscles. According to randomization, they were included in the Pea protein (n = 53), Whey protein (n = 54) or Placebo (n = 54) group. All had to take 25 g of the proteins or placebo twice a day during the 12-week training period. Tests were performed on biceps muscles at inclusion (D0), mid (D42) and post training (D84). Muscle thickness was evaluated using ultrasonography, and strength was measured on an isokinetic dynamometer. Results showed a significant time effect for biceps brachii muscle thickness (P Pea, Whey and Placebo, respectively; P Pea group as compared to Placebo whereas there was no difference between Whey and the two other conditions. Muscle strength also increased with time with no statistical difference between groups. In addition to an appropriate training, the supplementation with pea protein promoted a greater increase of muscle thickness as compared to Placebo and especially for people starting or returning to a muscular strengthening. Since no difference was obtained between the two protein groups, vegetable pea proteins could be used as an alternative to Whey-based dietary products. The present trial has been registered at ClinicalTrials.gov (NCT02128516).

Selective decontamination in pediatric liver transplants. A randomized prospective study.

Science.gov (United States)

Smith, S D; Jackson, R J; Hannakan, C J; Wadowsky, R M; Tzakis, A G; Rowe, M I

1993-06-01

Although it has been suggested that selective decontamination of the digestive tract (SDD) decreases postoperative aerobic Gram-negative and fungal infections in orthotopic liver transplantation (OLT), no controlled trials exist in pediatric patients. This prospective, randomized controlled study of 36 pediatric OLT patients examines the effect of short-term SDD on postoperative infection and digestive tract flora. Patients were randomized into two groups. The control group received perioperative parenteral antibiotics only. The SDD group received in addition polymyxin E, tobramycin, and amphotericin B enterally and by oropharyngeal swab postoperatively until oral intake was tolerated (6 +/- 4 days). Indications for operation, preoperative status, age, and intensive care unit and hospital length of stay were no different in SDD (n = 18) and control (n = 18) groups. A total of 14 Gram-negative infections (intraabdominal abscess 7, septicemia 5, pneumonia 1, urinary tract 1) developed in the 36 patients studied. Mortality was not significantly different in the two groups. However, there were significantly fewer patients with Gram-negative infections in the SDD group: 3/18 patients (11%) vs. 11/18 patients (50%) in the control group, P < 0.001. There was also significant reduction in aerobic Gram-negative flora in the stool and pharynx in patients receiving SDD. Gram-positive and anaerobic organisms were unaffected. We conclude that short-term postoperative SDD significantly reduces Gram-negative infections in pediatric OLT patients.

Pure-Phase Selective Excitation in Fast-Relaxing Systems

Science.gov (United States)

Zangger, Klaus; Oberer, Monika; Sterk, Heinz

2001-09-01

Selective pulses have been used frequently for small molecules. However, their application to proteins and other macromolecules has been limited. The long duration of shaped-selective pulses and the short T2 relaxation times in proteins often prohibited the use of highly selective pulses especially on larger biomolecules. A very selective excitation can be obtained within a short time by using the selective excitation sequence presented in this paper. Instead of using a shaped low-intensity radiofrequency pulse, a cluster of hard 90° pulses, delays of free precession, and pulsed field gradients can be used to selectively excite a narrow chemical shift range within a relatively short time. Thereby, off-resonance magnetization, which is allowed to evolve freely during the free precession intervals, is destroyed by the gradient pulses. Off-resonance excitation artifacts can be removed by random variation of the interpulse delays. This leads to an excitation profile with selectivity as well as phase and relaxation behavior superior to that of commonly used shaped-selective pulses. Since the evolution of scalar coupling is inherently suppressed during the double-selective excitation of two different scalar-coupled nuclei, the presented pulse cluster is especially suited for simultaneous highly selective excitation of N-H and C-H fragments. Experimental examples are demonstrated on hen egg white lysozyme (14 kD) and the bacterial antidote ParD (19 kD).

Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

Science.gov (United States)

Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

2013-01-01

We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

Day-ahead load forecast using random forest and expert input selection

International Nuclear Information System (INIS)

Lahouar, A.; Ben Hadj Slama, J.

2015-01-01

Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

Science.gov (United States)

Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

2017-12-15

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

Effect of a high-protein diet on maintenance of blood pressure levels achieved after initial weight loss : the DiOGenes randomized study

NARCIS (Netherlands)

Engberink, M. F.; Geleijnse, J. M.; Bakker, S. J. L.; Larsen, T. M.; Handjieva-Darlesnka, T.; Kafatos, A.; Martinez, J. A.; Pfeiffer, A. F. H.; Kunesova, M.; Jebb, S. A.; Holst, C.; Astrup, A.; Saris, W. H. M.; Brink, E. J.; van Baak, M. A.

Randomized trials have shown significant blood pressure (BP) reductions after increased protein compared with carbohydrate intake, but the effect on BP maintenance after initial weight loss is unclear. We examined the effect of a high-protein diet on the maintenance of reduced BP after weight loss

Effect of a high-protein diet on maintenance of blood pressure levels achieved after initial weight loss: the DiOGenes randomized study

NARCIS (Netherlands)

Engberink, M.F.; Geleijnse, J.M.; Bakker, S.J.L.; Larsen, T.

2015-01-01

Randomized trials have shown significant blood pressure (BP) reductions after increased protein compared with carbohydrate intake, but the effect on BP maintenance after initial weight loss is unclear. We examined the effect of a high-protein diet on the maintenance of reduced BP after weight loss

A single extracellular amino acid in Free Fatty Acid Receptor 2 defines antagonist species selectivity and G protein selection bias

DEFF Research Database (Denmark)

Sergeev, Eugenia; Hansen, Anders Højgaard; Bolognini, Daniele

2017-01-01

selectivity and mutational swap studies confirmed this hypothesis. Extending these studies to agonist function indicated that although the lysine - arginine variation between human and mouse orthologs had limited effect on G protein-mediated signal transduction, removal of positive charge from this residue...... produced a signalling-biased variant of Free Fatty Acid Receptor 2 in which Gi-mediated signalling by both short chain fatty acids and synthetic agonists was maintained whilst there was marked loss of agonist potency for signalling via Gq/11 and G12/13 G proteins. A single residue at the extracellular face...

Effect of high-protein or normal-protein diet on weight loss, body composition, hormone, and metabolic profile in southern Brazilian women with polycystic ovary syndrome: a randomized study.

Science.gov (United States)

Toscani, Mariana K; Mario, Fernanda M; Radavelli-Bagatini, Simone; Wiltgen, Denusa; Matos, Maria Cristina; Spritzer, Poli Maria

2011-11-01

The aim of the present study was to assess the effects of a high protein (HP) and a normal protein (NP) diet on patients with polycystic ovary syndrome (PCOS) and body mass index-matched controls in a sample of southern Brazilian women. This 8-week randomized trial was carried out at a university gynecological endocrinology clinic and included 18 patients with PCOS and 22 controls. Changes in weight, body composition, hormone, and metabolic profile were analyzed in women randomized to receive HP (30% protein, 40% carbohydrate, and 30% lipid) or NP (15% protein, 55% carbohydrate, and 30% lipid). The energy content was estimated for each participant at 20-25 kcal/kg current weight/day. Physical activity, blood pressure, homeostasis model assessment (HOMA) index, and fasting and 2-h glucose and insulin remained stable during the intervention in PCOS and controls, even in the presence of weight loss. There were no changes in lipid profile in either group. In contrast, body weight, body mass index (BMI), waist circumference, percent of body fat, and sum of trunk skinfolds decreased significantly after both diets in both groups. Total testosterone also decreased in PCOS and controls regardless of diet. In conclusion, calorie reduction, rather than protein content, seemed to affect body composition and hormonal profile in this short-term study. These findings emphasize the role of non-pharmacological interventions to reduce weight and ameliorate the anthropometric and clinical phenotype in PCOS.

Effect of a High-Protein Diet versus Standard-Protein Diet on Weight Loss and Biomarkers of Metabolic Syndrome: A Randomized Clinical Trial.

Science.gov (United States)

Campos-Nonato, Ismael; Hernandez, Lucia; Barquera, Simon

2017-01-01

Some studies have shown that protein-enriched diets can lead to greater weight loss and improvements in biomarkers of metabolic syndrome (MeS) than standard protein diets. Therefore, the aim of this study was to determine the effect of increased protein intake on weight loss in Mexican adults with MeS. Randomized controlled trial in 118 adults aged 47.4 ± 11.5 years and meeting the established criteria for MeS were randomized to prescribed hypocaloric diets (500 kcal less than resting metabolic rate) providing either 0.8 g/kg body weight (standard protein diet (SPD)) or 1.34 g/kg body weight (higher protein diet (HPD)) for 6 months. Body weight, waist circumference, percent body fat by bioimpedance analysis, fasting blood glucose, fasting insulin, hemoglobin A1c, total cholesterol, high-density lipoprotein (HDL) cholesterol, very-low-density lipoprotein (VLDL) cholesterol, triglycerides, C-reactive protein, creatinine, blood urea nitrogen, alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyl transferase were measured at baseline, 3 months and at 6 months. There were 105 subjects (51 for SPD and 54 for HPD) who completed the trial. Overall weight loss was 5.1 ± 3.6 kg in the SPD group compared to 7.0 ± 3.7 kg in the in HPD group. Both groups lost a significant percent of centimeters of waist circumference (SPD -6.5 ± 2.6 cm and HPD -8.8 ± 2.6 cm). There was no statistical difference Except for the varying weight losses the two groups did not show any further differences overall. However in the subgroup judged to be adherent more than 75% of the time with the prescribed diets, there was a significant difference in mean weight loss (SPD -5.8% vs. HPD -9.5%) after adjusting for baseline BMI. Both groups demonstrated significant decreases in waist circumference, glucose, insulin, triglycerides, and VLDL cholesterol, but there were no differences between the groups. There were no changes in blood tests for liver or renal function. There were no

Effect of a High-Protein Diet versus Standard-Protein Diet on Weight Loss and Biomarkers of Metabolic Syndrome: A Randomized Clinical Trial

Directory of Open Access Journals (Sweden)

Ismael Campos-Nonato

2017-06-01

Full Text Available Background: Some studies have shown that protein-enriched diets can lead to greater weight loss and improvements in biomarkers of metabolic syndrome (MeS than standard protein diets. Therefore, the aim of this study was to determine the effect of increased protein intake on weight loss in Mexican adults with MeS. Methods: Randomized controlled trial in 118 adults aged 47.4 ± 11.5 years and meeting the established criteria for MeS were randomized to prescribed hypocaloric diets (500 kcal less than resting metabolic rate providing either 0.8 g/kg body weight (standard protein diet (SPD or 1.34 g/kg body weight (higher protein diet (HPD for 6 months. Body weight, waist circumference, percent body fat by bioimpedance analysis, fasting blood glucose, fasting insulin, hemoglobin A1c, total cholesterol, high-density lipoprotein (HDL cholesterol, very-low-density lipoprotein (VLDL cholesterol, triglycerides, C-reactive protein, creatinine, blood urea nitrogen, alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyl transferase were measured at baseline, 3 months and at 6 months. Results: There were 105 subjects (51 for SPD and 54 for HPD who completed the trial. Overall weight loss was 5.1 ± 3.6 kg in the SPD group compared to 7.0 ± 3.7 kg in the in HPD group. Both groups lost a significant percent of centimeters of waist circumference (SPD -6.5 ± 2.6 cm and HPD -8.8 ± 2.6 cm. There was no statistical difference Except for the varying weight losses the two groups did not show any further differences overall. However in the subgroup judged to be adherent more than 75% of the time with the prescribed diets, there was a significant difference in mean weight loss (SPD -5.8% vs. HPD -9.5% after adjusting for baseline BMI. Both groups demonstrated significant decreases in waist circumference, glucose, insulin, triglycerides, and VLDL cholesterol, but there were no differences between the groups. There were no changes in blood tests for

In vitro Selection and Interaction Studies of a DNA Aptamer Targeting Protein A

OpenAIRE

Stoltenburg, Regina; Schubert, Thomas; Strehlitz, Beate

2015-01-01

A new DNA aptamer targeting Protein A is presented. The aptamer was selected by use of the FluMag-SELEX procedure. The SELEX technology (Systematic Evolution of Ligands by EXponential enrichment) is widely applied as an in vitro selection and amplification method to generate target-specific aptamers and exists in various modified variants. FluMag-SELEX is one of them and is characterized by the use of magnetic beads for target immobilization and fluorescently labeled oligonucleotides for moni...

Use of hydrostatic pressure for modulation of protein chemical modification and enzymatic selectivity.

Science.gov (United States)

Makarov, Alexey A; Helmy, Roy; Joyce, Leo; Reibarkh, Mikhail; Maust, Mathew; Ren, Sumei; Mergelsberg, Ingrid; Welch, Christopher J

2016-05-11

Using hydrostatic pressure to induce protein conformational changes can be a powerful tool for altering the availability of protein reactive sites and for changing the selectivity of enzymatic reactions. Using a pressure apparatus, it has been demonstrated that hydrostatic pressure can be used to modulate the reactivity of lysine residues of the protein ubiquitin with a water-soluble amine-specific homobifunctional coupling agent. Fewer reactive lysine residues were observed when the reaction was carried out under elevated pressure of 3 kbar, consistent with a pressure-induced conformational change of ubiquitin that results in fewer exposed lysine residues. Additionally, modulation of the stereoselectivity of an enzymatic transamination reaction was observed at elevated hydrostatic pressure. In one case, the minor diasteromeric product formed at atmospheric pressure became the major product at elevated pressure. Such pressure-induced alterations of protein reactivity may provide an important new tool for enzymatic reactions and the chemical modification of proteins.

Evidence of positive selection at codon sites localized in extracellular domains of mammalian CC motif chemokine receptor proteins

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Metzger Kelsey J

2010-05-01

Full Text Available Abstract Background CC chemokine receptor proteins (CCR1 through CCR10 are seven-transmembrane G-protein coupled receptors whose signaling pathways are known for their important roles coordinating immune system responses through targeted trafficking of white blood cells. In addition, some of these receptors have been identified as fusion proteins for viral pathogens: for example, HIV-1 strains utilize CCR5, CCR2 and CCR3 proteins to obtain cellular entry in humans. The extracellular domains of these receptor proteins are involved in ligand-binding specificity as well as pathogen recognition interactions. In mammals, the majority of chemokine receptor genes are clustered together; in humans, seven of the ten genes are clustered in the 3p21-24 chromosome region. Gene conversion events, or exchange of DNA sequence between genes, have been reported in chemokine receptor paralogs in various mammalian lineages, especially between the cytogenetically closely located pairs CCR2/5 and CCR1/3. Datasets of mammalian orthologs for each gene were analyzed separately to minimize the potential confounding impact of analyzing highly similar sequences resulting from gene conversion events. Molecular evolution approaches and the software package Phylogenetic Analyses by Maximum Likelihood (PAML were utilized to investigate the signature of selection that has acted on the mammalian CC chemokine receptor (CCR gene family. The results of neutral vs. adaptive evolution (positive selection hypothesis testing using Site Models are reported. In general, positive selection is defined by a ratio of nonsynonymous/synonymous nucleotide changes (dN/dS, or ω >1. Results Of the ten mammalian CC motif chemokine receptor sequence datasets analyzed, only CCR2 and CCR3 contain amino acid codon sites that exhibit evidence of positive selection using site based hypothesis testing in PAML. Nineteen of the twenty codon sites putatively indentified as likely to be under positive

Tolerance of a Knotted Near-Infrared Fluorescent Protein to Random Circular Permutation.

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Pandey, Naresh; Kuypers, Brianna E; Nassif, Barbara; Thomas, Emily E; Alnahhas, Razan N; Segatori, Laura; Silberg, Jonathan J

2016-07-12

Bacteriophytochrome photoreceptors (BphP) are knotted proteins that have been developed as near-infrared fluorescent protein (iRFP) reporters of gene expression. To explore how rearrangements in the peptides that interlace into the knot within the BphP photosensory core affect folding, we subjected iRFPs to random circular permutation using an improved transposase mutagenesis strategy and screened for variants that fluoresce. We identified 27 circularly permuted iRFPs that display biliverdin-dependent fluorescence in Escherichia coli. The variants with the brightest whole cell fluorescence initiated translation at residues near the domain linker and knot tails, although fluorescent variants that initiated translation within the PAS and GAF domains were discovered. Circularly permuted iRFPs retained sufficient cofactor affinity to fluoresce in tissue culture without the addition of biliverdin, and one variant displayed enhanced fluorescence when expressed in bacteria and tissue culture. This variant displayed a quantum yield similar to that of iRFPs but exhibited increased resistance to chemical denaturation, suggesting that the observed increase in the magnitude of the signal arose from more efficient protein maturation. These results show how the contact order of a knotted BphP can be altered without disrupting chromophore binding and fluorescence, an important step toward the creation of near-infrared biosensors with expanded chemical sensing functions for in vivo imaging.

Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies.

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Sadeh, Sadra; Rotter, Stefan

2014-01-01

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.

Magnetic deep eutectic solvents molecularly imprinted polymers for the selective recognition and separation of protein

International Nuclear Information System (INIS)

Liu, Yanjin; Wang, Yuzhi; Dai, Qingzhou; Zhou, Yigang

2016-01-01

A novel and facile magnetic deep eutectic solvents (DES) molecularly imprinted polymers (MIPs) for the selective recognition and separation of Bovine hemoglobin (BHb) was prepared. The new-type DES was adopted as the functional monomer which would bring molecular imprinted technology to a new direction. The amounts of DES were optimized. The obtained magnetic DES-MIPs were characterized with fourier transform infrared spectrometry (FT-IR), thermogravimetric analysis (TGA), field emission scanning electron microscope (FESEM), dynamic light scattering (DLS), elemental analysis and vibrating sample magnetometer (VSM). The results suggested that the imprinted polymers were successfully formed and possessed a charming magnetism. The maximum adsorption capability (Q_m_a_x) and dissociation constant (K_L) were analyzed by Langmuir isotherms (R"2 = 0.9983) and the value were estimated to be 175.44 mg/g and 0.035 mg/mL for the imprinted particles. And the imprinted particles showed a high imprinting factor of 4.77. In addition, the magnetic DES-MIPs presented outstanding recognition specificity and selectivity so that it can be utilized to separate template protein from the mixture of proteins and real samples. Last but not least, the combination of deep eutectic solvents and molecular imprinted technology in this paper provides a new perspective for the recognition and separation of proteins. - Highlights: • Combined green deep eutectic solvents (DES) and molecular imprinted technology in recognition and separation of proteins. • DES was adopted as a new-type functional monomer. • The obtained magnetic DES-MIPs can separate proteins rapidly by an external magnetic field. • Adsorption and selectivity properties were discussed.

Magnetic deep eutectic solvents molecularly imprinted polymers for the selective recognition and separation of protein

Energy Technology Data Exchange (ETDEWEB)

Liu, Yanjin [State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082 (China); Wang, Yuzhi, E-mail: wyzss@hnu.edu.cn [State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082 (China); Dai, Qingzhou [State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082 (China); Zhou, Yigang [Department of Microbiology, College of Basic Medicine, Central South University, Changsha, 410083 (China)

2016-09-14

A novel and facile magnetic deep eutectic solvents (DES) molecularly imprinted polymers (MIPs) for the selective recognition and separation of Bovine hemoglobin (BHb) was prepared. The new-type DES was adopted as the functional monomer which would bring molecular imprinted technology to a new direction. The amounts of DES were optimized. The obtained magnetic DES-MIPs were characterized with fourier transform infrared spectrometry (FT-IR), thermogravimetric analysis (TGA), field emission scanning electron microscope (FESEM), dynamic light scattering (DLS), elemental analysis and vibrating sample magnetometer (VSM). The results suggested that the imprinted polymers were successfully formed and possessed a charming magnetism. The maximum adsorption capability (Q{sub max}) and dissociation constant (K{sub L}) were analyzed by Langmuir isotherms (R{sup 2} = 0.9983) and the value were estimated to be 175.44 mg/g and 0.035 mg/mL for the imprinted particles. And the imprinted particles showed a high imprinting factor of 4.77. In addition, the magnetic DES-MIPs presented outstanding recognition specificity and selectivity so that it can be utilized to separate template protein from the mixture of proteins and real samples. Last but not least, the combination of deep eutectic solvents and molecular imprinted technology in this paper provides a new perspective for the recognition and separation of proteins. - Highlights: • Combined green deep eutectic solvents (DES) and molecular imprinted technology in recognition and separation of proteins. • DES was adopted as a new-type functional monomer. • The obtained magnetic DES-MIPs can separate proteins rapidly by an external magnetic field. • Adsorption and selectivity properties were discussed.

Dynamic Proteomics Emphasizes the Importance of Selective mRNA Translation and Protein Turnover during Arabidopsis Seed Germination*

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Galland, Marc; Huguet, Romain; Arc, Erwann; Cueff, Gwendal; Job, Dominique; Rajjou, Loïc

2014-01-01

During seed germination, the transition from a quiescent metabolic state in a dry mature seed to a proliferative metabolic state in a vigorous seedling is crucial for plant propagation as well as for optimizing crop yield. This work provides a detailed description of the dynamics of protein synthesis during the time course of germination, demonstrating that mRNA translation is both sequential and selective during this process. The complete inhibition of the germination process in the presence of the translation inhibitor cycloheximide established that mRNA translation is critical for Arabidopsis seed germination. However, the dynamics of protein turnover and the selectivity of protein synthesis (mRNA translation) during Arabidopsis seed germination have not been addressed yet. Based on our detailed knowledge of the Arabidopsis seed proteome, we have deepened our understanding of seed mRNA translation during germination by combining two-dimensional gel-based proteomics with dynamic radiolabeled proteomics using a radiolabeled amino acid precursor, namely [35S]-methionine, in order to highlight de novo protein synthesis, stability, and turnover. Our data confirm that during early imbibition, the Arabidopsis translatome keeps reflecting an embryonic maturation program until a certain developmental checkpoint. Furthermore, by dividing the seed germination time lapse into discrete time windows, we highlight precise and specific patterns of protein synthesis. These data refine and deepen our knowledge of the three classical phases of seed germination based on seed water uptake during imbibition and reveal that selective mRNA translation is a key feature of seed germination. Beyond the quantitative control of translational activity, both the selectivity of mRNA translation and protein turnover appear as specific regulatory systems, critical for timing the molecular events leading to successful germination and seedling establishment. PMID:24198433

Radioresistance related genes screened by protein-protein interaction network analysis in nasopharyngeal carcinoma

International Nuclear Information System (INIS)

Zhu Xiaodong; Guo Ya; Qu Song; Li Ling; Huang Shiting; Li Danrong; Zhang Wei

2012-01-01

Objective: To discover radioresistance associated molecular biomarkers and its mechanism in nasopharyngeal carcinoma by protein-protein interaction network analysis. Methods: Whole genome expression microarray was applied to screen out differentially expressed genes in two cell lines CNE-2R and CNE-2 with different radiosensitivity. Four differentially expressed genes were randomly selected for further verification by the semi-quantitative RT-PCR analysis with self-designed primers. The common differentially expressed genes from two experiments were analyzed with the SNOW online database in order to find out the central node related to the biomarkers of nasopharyngeal carcinoma radioresistance. The expression of STAT1 in CNE-2R and CNE-2 cells was measured by Western blot. Results: Compared with CNE-2 cells, 374 genes in CNE-2R cells were differentially expressed while 197 genes showed significant differences. Four randomly selected differentially expressed genes were verified by RT-PCR and had same change trend in consistent with the results of chip assay. Analysis with the SNOW database demonstrated that those 197 genes could form a complicated interaction network where STAT1 and JUN might be two key nodes. Indeed, the STAT1-α expression in CNE-2R was higher than that in CNE-2 (t=4.96, P<0.05). Conclusions: The key nodes of STAT1 and JUN may be the molecular biomarkers leading to radioresistance in nasopharyngeal carcinoma, and STAT1-α might have close relationship with radioresistance. (authors)

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

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Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene

Experimental Rugged Fitness Landscape in Protein Sequence Space

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

Experimental rugged fitness landscape in protein sequence space.

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-12-20

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Experimental rugged fitness landscape in protein sequence space.

Directory of Open Access Journals (Sweden)

Yuuki Hayashi

Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

Directory of Open Access Journals (Sweden)

Huilin Wang

Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

Post-Exercise Protein Trial: Interactions between Diet and Exercise (PEPTIDE): study protocol for randomized controlled trial.

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Alghannam, Abdullah F; Tsintzas, Kostas; Thompson, Dylan; Bilzon, James; Betts, James A

2014-11-24

Performing regular exercise is known to manifest a number of health benefits that mainly relate to cardiovascular and muscular adaptations to allow for greater oxygen extraction and utilization. There is increasing evidence that nutrient intake can affect the adaptive response to a single exercise bout, and that protein feeding is important to facilitate this process. Thus, the exercise-nutrient interaction may potentially lead to a greater response to training. The role of post-exercise protein ingestion in enhancing the effects of running-based endurance exercise training relative to energy-matched carbohydrate intervention remains to be established. Additionally, the influence of immediate versus overnight protein ingestion in mediating these training effects is currently unknown. The current protocol aims to establish whether post-exercise nutrient intake and timing would influence the magnitude of improvements during a prescribed endurance training program. The project involves two phases with each involving two treatment arms applied in a randomized investigator-participant double-blind parallel group design. For each treatment, participants will be required to undergo six weeks of running-based endurance training. Immediately post-exercise, participants will be prescribed solutions providing 0.4 grams per kilogram of body mass (g · kg(-1)) of whey protein hydrolysate plus 0.4 g · kg(-1) sucrose, relative to an isocaloric sucrose control (0.8 g · kg(-1); Phase I). In Phase II, identical protein supplements will be provided (0.4 + 0.4 g · kg(-1) · h(-1) of whey protein hydrolysate and sucrose, respectively), with the timing of ingestion manipulated to compare immediate versus overnight recovery feedings. Anthropometric, expired gas, venous blood and muscle biopsy samples will be obtained at baseline and following the six-week training period. By investigating the role of nutrition in enhancing the effects of endurance exercise training, we will provide

Selectivity analysis of protein kinase CK2 inhibitors DMAT, TBB and resorufin in cisplatin-induced stress responses

DEFF Research Database (Denmark)

Fritz, Gerhard; Issinger, Olaf-Georg; Olsen, Birgitte Brinkmann

2009-01-01

Targeting protein kinases as a therapeutic approach to treat various diseases, especially cancer is currently a fast growing business. Although many inhibitors are available, exhibiting remarkable potency, the major challenge is their selectivity. Here we show that the protein kinase CK2 inhibito...

A Peptidomimetic Antibiotic Targets Outer Membrane Proteins and Disrupts Selectively the Outer Membrane in Escherichia coli.

Science.gov (United States)

Urfer, Matthias; Bogdanovic, Jasmina; Lo Monte, Fabio; Moehle, Kerstin; Zerbe, Katja; Omasits, Ulrich; Ahrens, Christian H; Pessi, Gabriella; Eberl, Leo; Robinson, John A

2016-01-22

Increasing antibacterial resistance presents a major challenge in antibiotic discovery. One attractive target in Gram-negative bacteria is the unique asymmetric outer membrane (OM), which acts as a permeability barrier that protects the cell from external stresses, such as the presence of antibiotics. We describe a novel β-hairpin macrocyclic peptide JB-95 with potent antimicrobial activity against Escherichia coli. This peptide exhibits no cellular lytic activity, but electron microscopy and fluorescence studies reveal an ability to selectively disrupt the OM but not the inner membrane of E. coli. The selective targeting of the OM probably occurs through interactions of JB-95 with selected β-barrel OM proteins, including BamA and LptD as shown by photolabeling experiments. Membrane proteomic studies reveal rapid depletion of many β-barrel OM proteins from JB-95-treated E. coli, consistent with induction of a membrane stress response and/or direct inhibition of the Bam folding machine. The results suggest that lethal disruption of the OM by JB-95 occurs through a novel mechanism of action at key interaction sites within clusters of β-barrel proteins in the OM. These findings open new avenues for developing antibiotics that specifically target β-barrel proteins and the integrity of the Gram-negative OM. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays.

Science.gov (United States)

Kanie, Kei; Kondo, Yuto; Owaki, Junki; Ikeda, Yurika; Narita, Yuji; Kato, Ryuji; Honda, Hiroyuki

2016-11-19

The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM) provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV), an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I), and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides.

Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays

Directory of Open Access Journals (Sweden)

Kei Kanie

2016-11-01

Full Text Available The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV, an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I, and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides.

Chemical biology based on target-selective degradation of proteins and carbohydrates using light-activatable organic molecules.

Science.gov (United States)

Toshima, Kazunobu

2013-05-01

Proteins and carbohydrates play crucial roles in a wide range of biological processes, including serious diseases. The development of novel and innovative methods for selective control of specific proteins and carbohydrates functions has attracted much attention in the field of chemical biology. In this account article, the development of novel chemical tools, which can degrade target proteins and carbohydrates by irradiation with a specific wavelength of light under mild conditions without any additives, is introduced. This novel class of photochemical agents promise bright prospects for finding not only molecular-targeted bioprobes for understanding of the structure-activity relationships of proteins and carbohydrates but also novel therapeutic drugs targeting proteins and carbohydrates.

Effect of Gamma Radiation and Electron Beam on Microbiological Quality and Protein Patterns of 4 Selected Beans

International Nuclear Information System (INIS)

Chookaew, S.; Eamsir, J.; Pewlong, W.; Sajjabut, S.

2014-01-01

The aim of the present study was to evaluate the effect of gamma ray and electron beam on microbiological quality and protein pattern of four selected beans: mung beans, soy beans, peanuts and black beans. All beans samples were exposed to irradiation at doses of 0, 0.5, 1, and 2 kGy before evaluated for their microbiological quality using AOAC method and protein analysis by gel electrophoresis. Results showed that the amount of bacteria, yeast and mold of irradiated mung beans and peanuts were reduced, whereas these microbiological quality values remained relatively the same for irradiated soy beans and black beans compared to non-irradiated samples. In terms of protein analysis, the protein patterns of the irradiated beans were of the same quality as the non-irradiated samples. To further tested the effect of irradiation on the bean's protein at higher doses, all four selected beans were exposed to gamma ray at 10, 50, 100, 150 and 200 kGy. We found that the protein patterns of mung beans, peanuts and black beans were altered at doses above 50 kGy.

Selective and extensive 13C labeling of a membrane protein for solid-state NMR investigations

International Nuclear Information System (INIS)

Hong, M.; Jakes, K.

1999-01-01

The selective and extensive 13C labeling of mostly hydrophobic amino acid residues in a 25 kDa membrane protein, the colicin Ia channel domain, is reported. The novel 13C labeling approach takes advantage of the amino acid biosynthetic pathways in bacteria and suppresses the synthesis of the amino acid products of the citric acid cycle. The selectivity and extensiveness of labeling significantly simplify the solid-state NMR spectra, reduce line broadening, and should permit the simultaneous measurement of multiple structural constraints. We show the assignment of most 13C resonances to specific amino acid types based on the characteristic chemical shifts, the 13C labeling pattern, and the amino acid composition of the protein. The assignment is partly confirmed by a 2D homonuclear double-quantum-filter experiment under magic-angle spinning. The high sensitivity and spectral resolution attained with this 13C-labeling protocol, which is termed TEASE for ten-amino acid selective and extensive labeling, are demonstrated

Differential Nanos 2 protein stability results in selective germ cell accumulation in the sea urchin.

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Oulhen, Nathalie; Wessel, Gary M

2016-10-01

Nanos is a translational regulator required for the survival and maintenance of primordial germ cells. In the sea urchin, Strongylocentrotus purpuratus (Sp), Nanos 2 mRNA is broadly transcribed but accumulates specifically in the small micromere (sMic) lineage, in part because of the 3'UTR element GNARLE leads to turnover in somatic cells but retention in the sMics. Here we found that the Nanos 2 protein is also selectively stabilized; it is initially translated throughout the embryo but turned over in the future somatic cells and retained only in the sMics, the future germ line in this animal. This differential stability of Nanos protein is dependent on the open reading frame (ORF), and is independent of the sumoylation and ubiquitylation pathways. Manipulation of the ORF indicates that 68 amino acids in the N terminus of the Nanos protein are essential for its stability in the sMics whereas a 45 amino acid element adjacent to the zinc fingers targets its degradation. Further, this regulation of Nanos protein is cell autonomous, following formation of the germ line. These results are paradigmatic for the unique presence of Nanos in the germ line by a combination of selective RNA retention, distinctive translational control mechanisms (Oulhen et al., 2013), and now also by defined Nanos protein stability. Copyright © 2016 Elsevier Inc. All rights reserved.

Improved labeling strategy for 13C relaxation measurements of methyl groups in proteins

International Nuclear Information System (INIS)

Lee, Andrew L.; Urbauer, Jeffrey L.; Wand, A. Joshua

1997-01-01

Selective incorporation of 13 C into the methyl groups of protein side chains is described as a means for simplifying the measurement and interpretation of 13 C relaxation parameters.High incorporation (>90%) is accomplished by using pyruvate(3- 13 C, 99%) as the sole carbon source in the growth media for protein overexpression in E. coli. This improved labeling scheme increases the sensitivity of the relaxation experiments by approximately fivefold when compared to randomly fractionally 13 C-labeled protein, allowing high-quality measurements on relatively dilute (<1 mM)protein samples at a relatively low cost

Acetylation of pregnane X receptor protein determines selective function independent of ligand activation

International Nuclear Information System (INIS)

Biswas, Arunima; Pasquel, Danielle; Tyagi, Rakesh Kumar; Mani, Sridhar

2011-01-01

Research highlights: → Pregnane X receptor (PXR), a major regulatory protein, is modified by acetylation. → PXR undergoes dynamic deacetylation upon ligand-mediated activation. → SIRT1 partially mediates PXR deacetylation. → PXR deacetylation per se induces lipogenesis mimicking ligand-mediated activation. -- Abstract: Pregnane X receptor (PXR), like other members of its class of nuclear receptors, undergoes post-translational modification [PTM] (e.g., phosphorylation). However, it is unknown if acetylation (a major and common form of protein PTM) is observed on PXR and, if it is, whether it is of functional consequence. PXR has recently emerged as an important regulatory protein with multiple ligand-dependent functions. In the present work we show that PXR is indeed acetylated in vivo. SIRT1 (Sirtuin 1), a NAD-dependent class III histone deacetylase and a member of the sirtuin family of proteins, partially mediates deacetylation of PXR. Most importantly, the acetylation status of PXR regulates its selective function independent of ligand activation.

Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins

DEFF Research Database (Denmark)

Santos, Anderson R; Pereira, Vanessa Bastos; Barbosa, Eudes

2013-01-01

. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection. RESULTS: We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called...... Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic...... proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online...

Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

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Lu-Lu Zheng

Full Text Available Pyrrolidone carboxylic acid (PCA is formed during a common post-translational modification (PTM of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR and incremental feature selection (IFS. We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations.

Identification of potential nuclear reprogramming and differentiation factors by a novel selection method for cloning chromatin-binding proteins

International Nuclear Information System (INIS)

Wang Liu; Zheng Aihua; Yi Ling; Xu Chongren; Ding Mingxiao; Deng Hongkui

2004-01-01

Nuclear reprogramming is critical for animal cloning and stem cell creation through nuclear transfer, which requires extensive remodeling of chromosomal architecture involving dramatic changes in chromatin-binding proteins. To understand the mechanism of nuclear reprogramming, it is critical to identify chromatin-binding factors specify the reprogramming process. In this report, we have developed a high-throughput selection method, based on T7 phage display and chromatin immunoprecipitation, to isolate chromatin-binding factors expressed in mouse embryonic stem cells using primary mouse embryonic fibroblast chromatin. Seven chromatin-binding proteins have been isolated by this method. We have also isolated several chromatin-binding proteins involved in hepatocyte differentiation. Our method provides a powerful tool to rapidly and selectively identify chromatin-binding proteins. The method can be used to study epigenetic modification of chromatin during nuclear reprogramming, cell differentiation, and transdifferentiation

Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

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Hui Wang

2017-10-01

Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

Prediction of Protein Structural Class Based on Gapped-Dipeptides and a Recursive Feature Selection Approach

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Taigang Liu

2015-12-01

Full Text Available The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE. These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.

pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach.

Science.gov (United States)

Jia, Jianhua; Liu, Zi; Xiao, Xuan; Liu, Bingxiang; Chou, Kuo-Chen

2016-04-07

Being one type of post-translational modifications (PTMs), protein lysine succinylation is important in regulating varieties of biological processes. It is also involved with some diseases, however. Consequently, from the angles of both basic research and drug development, we are facing a challenging problem: for an uncharacterized protein sequence having many Lys residues therein, which ones can be succinylated, and which ones cannot? To address this problem, we have developed a predictor called pSuc-Lys through (1) incorporating the sequence-coupled information into the general pseudo amino acid composition, (2) balancing out skewed training dataset by random sampling, and (3) constructing an ensemble predictor by fusing a series of individual random forest classifiers. Rigorous cross-validations indicated that it remarkably outperformed the existing methods. A user-friendly web-server for pSuc-Lys has been established at http://www.jci-bioinfo.cn/pSuc-Lys, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. It has not escaped our notice that the formulation and approach presented here can also be used to analyze many other problems in computational proteomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Phage display peptide libraries: deviations from randomness and correctives

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Ryvkin, Arie; Ashkenazy, Haim; Weiss-Ottolenghi, Yael; Piller, Chen; Pupko, Tal; Gershoni, Jonathan M

2018-01-01

Abstract Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications. PMID:29420788

A Venom Gland Extracellular Chitin-Binding-Like Protein from Pupal Endoparasitoid Wasps, Pteromalus Puparum, Selectively Binds Chitin

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Yu Zhu

2015-11-01

Full Text Available Chitin-binding proteins (CBPs are present in many species and they act in a variety of biological processes. We analyzed a Pteromalus puparum venom apparatus proteome and transcriptome and identified a partial gene encoding a possible CBP. Here, we report cloning a full-length cDNA of a sequence encoding a chitin-binding-like protein (PpCBP from P. puparum, a pupal endoparasitoid of Pieris rapae. The cDNA encoded a 96-amino-acid protein, including a secretory signal peptide and a chitin-binding peritrophin-A domain. Phylogenetic analysis of chitin binding domains (CBDs of cuticle proteins and peritrophic matrix proteins in selected insects revealed that the CBD of PpCBP clustered with the CBD of Nasonia vitripennis. The PpCBP is specifically expressed in the venom apparatus of P. puparum, mostly in the venom gland. PpCBP expression was highest at day one after adult eclosion and much lower for the following five days. We produced a recombinant PpCBP and binding assays showed the recombinant protein selectively binds chitin but not cellulose in vitro. We infer that PpCBP serves a structural role in the venom reservoir, or may be injected into the host to help wound healing of the host exoskeleton.

Effects of conjugated linoleic acid supplementation on serum C-reactive protein: A systematic review and meta-analysis of randomized controlled trials.

Science.gov (United States)

Mazidi, Mohsen; Karimi, Ehsan; Rezaie, Peyman; Ferns, Gordon A

2017-12-01

To undertake a systematic review and meta-analysis of prospective studies to determine the effect of conjugated linoleic acids (CLAs) supplementation on serum C-reactive protein (CRP). PubMed-Medline, Web of Science, Cochrane Database, and Google Scholar databases were searched (up until May 2016) to identify prospective studies evaluating the impact of CLAs supplementation on serum CRP. Random-effects models meta-analysis was used for quantitative data synthesis. Sensitivity analysis was conducted using the leave-one-out method. Heterogeneity was quantitatively assessed using the I 2 index. Systematic review registration: CRD42016038945. From a total of 85 entries identified via searches, 14 studies were included in the final selection. The meta-analysis indicated a significant increase in serum CRP concentrations following supplementation with CLAs (weighted mean difference [WMD] 0.63 mg/dL, 95% confidence interval [95% CI] 0.13-1.13, N=21 arms, heterogeneity P=.026; I 2 =52.3%). These findings were robust in sensitivity analyses. Random-effects meta-regression revealed that changes in serum CRP levels were independent of the dosage of CLAs supplementation (slope: -0.02; 95% CI: -0.10, 0.12; P=.889) or duration of follow-up (slope: 0.271; 95% CI: -0.05, 0.59; P=.098). This meta-analysis suggests that CLA supplementation is associated with an increase in plasma CRP concentrations and a reduction in serum adiponectin concentrations, which indicates that CLA supplements have a proinflammatory effect. Randomized control trials with larger sample size and a longer follow-up period may be required for future investigations to provide an unequivocal answer. © 2017 John Wiley & Sons Ltd.

Tolerability, pharmacokinetics and pharmacodynamics of TA-8995, a selective cholesteryl ester transfer protein (CETP) inhibitor, in healthy subjects

NARCIS (Netherlands)

Ford, John; Lawson, Matt; Fowler, David; Maruyama, Nobuko; Mito, Seiji; Tomiyasu, Koichi; Kinoshita, Shuji; Suzuki, Chisa; Kawaguchi, Atsuhiro; Round, Patrick; Boyce, Malcolm; Warrington, Steve; Weber, Werner; van Deventer, Sander; Kastelein, John J. P.

2014-01-01

Two double-blind, randomized studies were conducted to assess the tolerability, pharmacokinetics and pharmacodynamics of oral TA-8995, a new cholesteryl ester transfer protein (CETP) inhibitor, in healthy subjects. Study 1: Subjects received single doses of TA-8995 or placebo (fasted). Doses were 5,

New Milk Protein-Derived Peptides with Potential Antimicrobial Activity: An Approach Based on Bioinformatic Studies

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Bartłomiej Dziuba

2014-08-01

Full Text Available New peptides with potential antimicrobial activity, encrypted in milk protein sequences, were searched for with the use of bioinformatic tools. The major milk proteins were hydrolyzed in silico by 28 enzymes. The obtained peptides were characterized by the following parameters: molecular weight, isoelectric point, composition and number of amino acid residues, net charge at pH 7.0, aliphatic index, instability index, Boman index, and GRAVY index, and compared with those calculated for known 416 antimicrobial peptides including 59 antimicrobial peptides (AMPs from milk proteins listed in the BIOPEP database. A simple analysis of physico-chemical properties and the values of biological activity indicators were insufficient to select potentially antimicrobial peptides released in silico from milk proteins by proteolytic enzymes. The final selection was made based on the results of multidimensional statistical analysis such as support vector machines (SVM, random forest (RF, artificial neural networks (ANN and discriminant analysis (DA available in the Collection of Anti-Microbial Peptides (CAMP database. Eleven new peptides with potential antimicrobial activity were selected from all peptides released during in silico proteolysis of milk proteins.

Selective induction of cyclin B protein abrogates the G2 delay after irradiation

International Nuclear Information System (INIS)

Kao, G.; Muschel, R.J.; Maity, A.; Kunig, A.; McKenna, W.G.

1996-01-01

Purpose/Objective: Irradiation of tumor cells commonly results in G2 delay, which has been postulated to allow DNA repair and cell survival. The G2 delay after irradiation is also often marked in some cell lines by delayed expression of cyclin B protein, suggesting a role for cyclin B regulation. Investigations of these hypotheses however has been hampered by the inability to selectively perturb the G2 delay in a physiologic manner. Materials and Methods: We have devised a system, with which we are able to selectively induce cyclin B protein expression in vivo at specific points in the cell cycle, by transfecting Hela cells with an expression vector under control of a dexamethasone-inducible promoter. Experiments were subsequently performed by synchronizing, releasing, irradiating, inducing, and harvesting these cells through the cell cycle. Results: Irradiation with 5 Gy led to a pronounced G2 delay, reflected by markedly slowed progression into mitosis, concomitant with reduced expression of cyclin B protein. Induction of cyclin B after radiation in these cells abrogated the G2 delay by approximately doubling the rate at which the cells re-enter mitosis. Treatment of irradiated untransfected control cells with dexamethasone, in which cyclin B is not induced, led to minimal changes. Studies of effects of cyclin B induction on cyclin B localization (using immunofluorescence), cdc2 phosphorylation and activation will also be presented. Conclusion: This system should allow further investigations into fundamental mechanisms of cell cycle regulation after irradiation and DNA damage. This also provides direct evidence for the first time that cyclin B protein regulation may play a role in the G2 delay following irradiation in Hela cells, perhaps complementing phosphorylation events

Effect of Replacing Animal Protein with Plant Protein on Glycemic Control in Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Science.gov (United States)

Viguiliouk, Effie; Stewart, Sarah E; Jayalath, Viranda H; Ng, Alena Praneet; Mirrahimi, Arash; de Souza, Russell J; Hanley, Anthony J; Bazinet, Richard P; Blanco Mejia, Sonia; Leiter, Lawrence A; Josse, Robert G; Kendall, Cyril W C; Jenkins, David J A; Sievenpiper, John L

2015-12-01

Previous research on the effect of replacing sources of animal protein with plant protein on glycemic control has been inconsistent. We therefore conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to assess the effect of this replacement on glycemic control in individuals with diabetes. We searched MEDLINE, EMBASE, and Cochrane databases through 26 August 2015. We included RCTs ≥ 3-weeks comparing the effect of replacing animal with plant protein on HbA1c, fasting glucose (FG), and fasting insulin (FI). Two independent reviewers extracted relevant data, assessed study quality and risk of bias. Data were pooled by the generic inverse variance method and expressed as mean differences (MD) with 95% confidence intervals (CIs). Heterogeneity was assessed (Cochran Q-statistic) and quantified (I²-statistic). Thirteen RCTs (n = 280) met the eligibility criteria. Diets emphasizing a replacement of animal with plant protein at a median level of ~35% of total protein per day significantly lowered HbA1c (MD = -0.15%; 95%-CI: -0.26, -0.05%), FG (MD = -0.53 mmol/L; 95%-CI: -0.92, -0.13 mmol/L) and FI (MD = -10.09 pmol/L; 95%-CI: -17.31, -2.86 pmol/L) compared with control arms. Overall, the results indicate that replacing sources of animal with plant protein leads to modest improvements in glycemic control in individuals with diabetes. Owing to uncertainties in our analyses there is a need for larger, longer, higher quality trials. ClinicalTrials.gov registration number: NCT02037321.

Affinity selection-mass spectrometry and its emerging application to the high throughput screening of G protein-coupled receptors.

Science.gov (United States)

Whitehurst, Charles E; Annis, D Allen

2008-07-01

Advances in combinatorial chemistry and genomics have inspired the development of novel affinity selection-based screening techniques that rely on mass spectrometry to identify compounds that preferentially bind to a protein target. Of the many affinity selection-mass spectrometry techniques so far documented, only a few solution-based implementations that separate target-ligand complexes away from unbound ligands persist today as routine high throughput screening platforms. Because affinity selection-mass spectrometry techniques do not rely on radioactive or fluorescent reporters or enzyme activities, they can complement traditional biochemical and cell-based screening assays and enable scientists to screen targets that may not be easily amenable to other methods. In addition, by employing mass spectrometry for ligand detection, these techniques enable high throughput screening of massive library collections of pooled compound mixtures, vastly increasing the chemical space that a target can encounter during screening. Of all drug targets, G protein coupled receptors yield the highest percentage of therapeutically effective drugs. In this manuscript, we present the emerging application of affinity selection-mass spectrometry to the high throughput screening of G protein coupled receptors. We also review how affinity selection-mass spectrometry can be used as an analytical tool to guide receptor purification, and further used after screening to characterize target-ligand binding interactions, enabling the classification of orthosteric and allosteric binders.

Selection for a Zinc-Finger Protein Contributes to Seed Oil Increase during Soybean Domestication.

Science.gov (United States)

Li, Qing-Tian; Lu, Xiang; Song, Qing-Xin; Chen, Hao-Wei; Wei, Wei; Tao, Jian-Jun; Bian, Xiao-Hua; Shen, Ming; Ma, Biao; Zhang, Wan-Ke; Bi, Ying-Dong; Li, Wei; Lai, Yong-Cai; Lam, Sin-Man; Shui, Guang-Hou; Chen, Shou-Yi; Zhang, Jin-Song

2017-04-01

Seed oil is a momentous agronomical trait of soybean ( Glycine max ) targeted by domestication in breeding. Although multiple oil-related genes have been uncovered, knowledge of the regulatory mechanism of seed oil biosynthesis is currently limited. We demonstrate that the seed-preferred gene GmZF351 , encoding a tandem CCCH zinc finger protein, is selected during domestication. Further analysis shows that GmZF351 facilitates oil accumulation by directly activating WRINKLED1 , BIOTIN CARBOXYL CARRIER PROTEIN2 , 3-KETOACYL-ACYL CARRIER PROTEIN SYNTHASE III , DIACYLGLYCEROL O-ACYLTRANSFERASE1 , and OLEOSIN2 in transgenic Arabidopsis ( Arabidopsis thaliana ) seeds. Overexpression of GmZF351 in transgenic soybean also activates lipid biosynthesis genes, thereby accelerating seed oil accumulation. The ZF351 haplotype from the cultivated soybean group and the wild soybean ( Glycine soja ) subgroup III correlates well with high gene expression level, seed oil contents and promoter activity, suggesting that selection of GmZF351 expression leads to increased seed oil content in cultivated soybean. Our study provides novel insights into the regulatory mechanism for seed oil accumulation, and the manipulation of GmZF351 may have great potential in the improvement of oil production in soybean and other related crops. © 2017 American Society of Plant Biologists. All Rights Reserved.

Selective Permeation and Organic Extraction of Recombinant Green Fluorescent Protein (gfpuv from Escherichia coli

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Ishii Marina

2002-04-01

Full Text Available Abstract Background Transformed cells of Escherichia coli DH5-α with pGFPuv, induced by IPTG (isopropyl-β-d-thiogalactopyranoside, express the green fluorescent protein (gfpuv during growth phases. E. coli subjected to the combination of selective permeation by freezing/thawing/sonication cycles followed by the three-phase partitioning extraction (TPP method were compared to the direct application of TPP to the same culture of E. coli on releasing gfpuv from the over-expressing cells. Material and Methods Cultures (37°C/100 rpm/ 24 h; μ = 0.99 h-1 - 1.10 h-1 of transformed (pGFP Escherichia coli DH5-α, expressing the green fluorescent protein (gfpuv, absorbance at 394 nm and emission at 509 nm were sonicated in successive intervals of sonication (25 vibrations/pulse to determine the maximum amount of gfpuv released from the cells. For selective permeation, the transformed previously frozen (-75°C cells were subjected to three freeze/thaw (-20°C/ 0.83°C/min cycles interlaid by sonication (3 pulses/ 6 seconds/ 25 vibrations. The intracellular permeate with gfpuv in extraction buffer (TE solution (25 mM Tris-HCl, pH 8.0, 1 mM β-mercaptoethanol β-ME, 0.1 mM PMSF was subjected to the three-phase partitioning (TPP method with t-butanol and 1.6 M ammonium sulfate. Sonication efficiency was verified on the application to the cells previously treated by the TPP method. The intra-cell releases were mixed and eluted through methyl HIC column with a buffer solution (10 mM Tris-HCl, 10 mM EDTA, pH 8.0. Results The sonication maximum released amount obtained from the cells was 327.67 μg gfpuv/mL (20.73 μg gfpuv/mg total proteins – BSA, after 9 min of treatment. Through the selective permeation by three repeated freezing/thawing/sonication cycles applied to the cells, a close content of 241.19 μg gfpuv/mL (29.74 μg gfpuv/mg BSA was obtained. The specific mass range of gfpuv released from the same cultures, by the three-phase partitioning (TPP

Structure of the Regulator of G Protein Signaling 8 (RGS8)-Gαq Complex: MOLECULAR BASIS FOR Gα SELECTIVITY.

Science.gov (United States)

Taylor, Veronica G; Bommarito, Paige A; Tesmer, John J G

2016-03-04

Regulator of G protein signaling (RGS) proteins interact with activated Gα subunits via their RGS domains and accelerate the hydrolysis of GTP. Although the R4 subfamily of RGS proteins generally accepts both Gαi/o and Gαq/11 subunits as substrates, the R7 and R12 subfamilies select against Gαq/11. In contrast, only one RGS protein, RGS2, is known to be selective for Gαq/11. The molecular basis for this selectivity is not clear. Previously, the crystal structure of RGS2 in complex with Gαq revealed a non-canonical interaction that could be due to interfacial differences imposed by RGS2, the Gα subunit, or both. To resolve this ambiguity, the 2.6 Å crystal structure of RGS8, an R4 subfamily member, was determined in complex with Gαq. RGS8 adopts the same pose on Gαq as it does when bound to Gαi3, indicating that the non-canonical interaction of RGS2 with Gαq is due to unique features of RGS2. Based on the RGS8-Gαq structure, residues in RGS8 that contact a unique α-helical domain loop of Gαq were converted to those typically found in R12 subfamily members, and the reverse substitutions were introduced into RGS10, an R12 subfamily member. Although these substitutions perturbed their ability to stimulate GTP hydrolysis, they did not reverse selectivity. Instead, selectivity for Gαq seems more likely determined by whether strong contacts can be maintained between α6 of the RGS domain and Switch III of Gαq, regions of high sequence and conformational diversity in both protein families. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

The nucleoid protein Dps binds genomic DNA of Escherichia coli in a non-random manner

Science.gov (United States)

Kondrashov, F. A.; Toshchakov, S. V.; Dominova, I.; Shvyreva, U. S.; Vrublevskaya, V. V.; Morenkov, O. S.; Panyukov, V. V.

2017-01-01

Dps is a multifunctional homododecameric protein that oxidizes Fe2+ ions accumulating them in the form of Fe2O3 within its protein cavity, interacts with DNA tightly condensing bacterial nucleoid upon starvation and performs some other functions. During the last two decades from discovery of this protein, its ferroxidase activity became rather well studied, but the mechanism of Dps interaction with DNA still remains enigmatic. The crucial role of lysine residues in the unstructured N-terminal tails led to the conventional point of view that Dps binds DNA without sequence or structural specificity. However, deletion of dps changed the profile of proteins in starved cells, SELEX screen revealed genomic regions preferentially bound in vitro and certain affinity of Dps for artificial branched molecules was detected by atomic force microscopy. Here we report a non-random distribution of Dps binding sites across the bacterial chromosome in exponentially growing cells and show their enrichment with inverted repeats prone to form secondary structures. We found that the Dps-bound regions overlap with sites occupied by other nucleoid proteins, and contain overrepresented motifs typical for their consensus sequences. Of the two types of genomic domains with extensive protein occupancy, which can be highly expressed or transcriptionally silent only those that are enriched with RNA polymerase molecules were preferentially occupied by Dps. In the dps-null mutant we, therefore, observed a differentially altered expression of several targeted genes and found suppressed transcription from the dps promoter. In most cases this can be explained by the relieved interference with Dps for nucleoid proteins exploiting sequence-specific modes of DNA binding. Thus, protecting bacterial cells from different stresses during exponential growth, Dps can modulate transcriptional integrity of the bacterial chromosome hampering RNA biosynthesis from some genes via competition with RNA polymerase

Random Insertion of mCherry Into VP3 Domain of Adeno-associated Virus Yields Fluorescent Capsids With no Loss of Infectivity

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Justin Judd

2012-01-01

Full Text Available Adeno-associated virus (AAV-derived vectors are promising gene delivery systems, and a number of design strategies have been pursued to improve their performance. For example, genetic insertion of proteins into the capsid may be used to achieve vector retargeting, reduced immunogenicity, or to track vector transport. Unfortunately, rational approaches to genetic insertion have experienced limited success due to the unpredictable context-dependent nature of protein folding and the complexity of the capsid's macroassembly. We report the construction and use of a frame-enriched DNase-based random insertion library based on AAV2 cap, called pAAV2_RaPID (Random Peptide Insertion by DNase. The fluorescent mCherry protein was inserted randomly throughout the AAV2 capsid and the library was selected for fluorescent and infectious variants. A capsid site was identified in VP3 that can tolerate the large protein insertion. In contrast to previous efforts to incorporate fluorescent proteins into the AAV2 capsid, the isolated mCherry mutant maintains native infectivity while displaying robust fluorescence. Collectively, these results demonstrate that the pAAV2_RaPID platform library can be used to create fully infectious AAV vectors carrying large functional protein domains on the capsid.

EcmPred: Prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection

KAUST Repository

Kandaswamy, Krishna Kumar Umar; Ganesan, Pugalenthi; Kalies, Kai Uwe; Hartmann, Enno; Martinetz, Thomas M.

2013-01-01

The extracellular matrix (ECM) is a major component of tissues of multicellular organisms. It consists of secreted macromolecules, mainly polysaccharides and glycoproteins. Malfunctions of ECM proteins lead to severe disorders such as marfan

Determination of the Influence of Substrate Concentration on Enzyme Selectivity Using Whey Protein Isolate and Bacillus licheniformis Protease

NARCIS (Netherlands)

Butré, C.I.; Sforza, S.; Gruppen, H.; Wierenga, P.A.

2014-01-01

Increasing substrate concentration during enzymatic protein hydrolysis results in a decrease in hydrolysis rate. To test if changes in the mechanism of hydrolysis also occur, the enzyme selectivity was determined. The selectivity is defined quantitatively as the relative rate of hydrolysis of each

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

Science.gov (United States)

Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

2015-01-01

Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed

Prediction of hot spots in protein interfaces using a random forest model with hybrid features.

Science.gov (United States)

Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan

2012-03-01

Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot.

Screening and expression of selected taxonomically conserved and unique hypothetical proteins in Burkholderia pseudomallei K96243

Science.gov (United States)

Akhir, Nor Azurah Mat; Nadzirin, Nurul; Mohamed, Rahmah; Firdaus-Raih, Mohd

2015-09-01

Hypothetical proteins of bacterial pathogens represent a large numbers of novel biological mechanisms which could belong to essential pathways in the bacteria. They lack functional characterizations mainly due to the inability of sequence homology based methods to detect functional relationships in the absence of detectable sequence similarity. The dataset derived from this study showed 550 candidates conserved in genomes that has pathogenicity information and only present in the Burkholderiales order. The dataset has been narrowed down to taxonomic clusters. Ten proteins were selected for ORF amplification, seven of them were successfully amplified, and only four proteins were successfully expressed. These proteins will be great candidates in determining the true function via structural biology.

Effect of Whey Supplementation on Circulating C-Reactive Protein: A Meta-Analysis of Randomized Controlled Trials

Science.gov (United States)

Zhou, Ling-Mei; Xu, Jia-Ying; Rao, Chun-Ping; Han, Shufen; Wan, Zhongxiao; Qin, Li-Qiang

2015-01-01

Whey supplementation is beneficial for human health, possibly by reducing the circulating C-reactive protein (CRP) level, a sensitive marker of inflammation. Thus, a meta-analysis of randomized controlled trials was conducted to evaluate their relationship. A systematic literature search was conducted in July, 2014, to identify eligible studies. Either a fixed-effects model or a random-effects model was used to calculate pooled effects. The meta-analysis results of nine trials showed a slight, but no significant, reduction of 0.42 mg/L (95% CI −0.96, 0.13) in CRP level with the supplementation of whey protein and its derivates. Relatively high heterogeneity across studies was observed. Subgroup analyses showed that whey significantly lowered CRP by 0.72 mg/L (95% CI −0.97, −0.47) among trials with a daily whey dose ≥20 g/day and by 0.67 mg/L (95% CI −1.21, −0.14) among trials with baseline CRP ≥3 mg/L. Meta-regression analysis revealed that the baseline CRP level was a potential effect modifier of whey supplementation in reducing CRP. In conclusion, our meta-analysis did not find sufficient evidence that whey and its derivates elicited a beneficial effect in reducing circulating CRP. However, they may significantly reduce CRP among participants with highly supplemental doses or increased baseline CRP levels. PMID:25671415

Intracellular delivery of cell-penetrating peptide-transcriptional factor fusion protein and its role in selective osteogenesis

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Suh JS

2014-03-01

alginate gel for the purpose of localization and controlled release. The LMWP-TAZ fusion protein-loaded alginate gel matrix significantly increased bone formation in rabbit calvarial defects compared with alginate gel matrix mixed with free TAZ protein. The protein transduction of TAZ fused with cell-penetrating LMWP peptide was able selectively to stimulate osteogenesis in vitro and in vivo. Taken together, this fusion protein-transduction technology for osteogenic protein can thus be applied in combination with biomaterials for tissue regeneration and controlled release for tissue-engineering purposes. Keywords: protein transduction, low-molecular-weight protamine (LMWP, transcriptional coactivator with PDZ-binding motif (TAZ, selective osteogenesis, bone-tissue engineering

Beneficial effects of a high-protein, low-glycemic-load hypocaloric diet in overweight and obese women with polycystic ovary syndrome: a randomized controlled intervention study.

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Mehrabani, Homeira Hamayeli; Salehpour, Saghar; Amiri, Zohreh; Farahani, Sara Jalali; Meyer, Barbara J; Tahbaz, Farideh

2012-04-01

The recommended composition of a hypocaloric diet for obese women with polycystic ovary syndrome (PCOS) is unclear. The aim of this study was to investigate the effects of a high-protein, low-glycemic-load diet compared with a conventional hypocaloric diet on reproductive hormones, inflammatory markers, lipids, glucose, and insulin levels in obese women with PCOS. A total of 60 overweight and obese women with PCOS who did not use insulin-sensitizing agents were recruited and randomly assigned to 1 of the 2 hypocaloric diet groups for a single-blind clinical trial. The groups included a conventional hypocaloric diet (CHCD) (15% of daily energy from protein) and a modified hypocaloric diet (MHCD) with a high-protein, low-glycemic load (30% of daily energy from protein plus low-glycemic-load foods selected from a list) that was prescribed via counseling visits weekly during 12 weeks of study. Anthropometric assessments and biochemical measurements including reproductive hormones, inflammatory factors, lipids, glucose, and insulin were performed on fasting blood samples at baseline and after 12 weeks of dietary intervention. Weight loss was significant and similar in the 2 groups. Mean of testosterone in the MHCD and CHCD groups decreased from 1.78 ± 0.32 to 1.31 ± 0.26 ng/ml and from 1.51 ± 0.12 to 1.15 ± 0.11 ng/ml, respectively (p hypocaloric diets significantly led to reduced body weight and androgen levels in these two groups of women with PCOS. The combination of high-protein and low-glycemic-load foods in a modified diet caused a significant increase in insulin sensitivity and a decrease in hsCRP level when compared with a conventional diet.

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

Science.gov (United States)

Young-Rae Cho; Yanan Xin; Speegle, Greg

2015-01-01

Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

Implementation of a Parallel Protein Structure Alignment Service on Cloud

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Che-Lun Hung

2013-01-01

Full Text Available Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

Effect of Replacing Animal Protein with Plant Protein on Glycemic Control in Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

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Effie Viguiliouk

2015-12-01

Full Text Available Previous research on the effect of replacing sources of animal protein with plant protein on glycemic control has been inconsistent. We therefore conducted a systematic review and meta-analysis of randomized controlled trials (RCTs to assess the effect of this replacement on glycemic control in individuals with diabetes. We searched MEDLINE, EMBASE, and Cochrane databases through 26 August 2015. We included RCTs ≥ 3-weeks comparing the effect of replacing animal with plant protein on HbA1c, fasting glucose (FG, and fasting insulin (FI. Two independent reviewers extracted relevant data, assessed study quality and risk of bias. Data were pooled by the generic inverse variance method and expressed as mean differences (MD with 95% confidence intervals (CIs. Heterogeneity was assessed (Cochran Q-statistic and quantified (I2-statistic. Thirteen RCTs (n = 280 met the eligibility criteria. Diets emphasizing a replacement of animal with plant protein at a median level of ~35% of total protein per day significantly lowered HbA1c (MD = −0.15%; 95%-CI: −0.26, −0.05%, FG (MD = −0.53 mmol/L; 95%-CI: −0.92, −0.13 mmol/L and FI (MD = −10.09 pmol/L; 95%-CI: −17.31, −2.86 pmol/L compared with control arms. Overall, the results indicate that replacing sources of animal with plant protein leads to modest improvements in glycemic control in individuals with diabetes. Owing to uncertainties in our analyses there is a need for larger, longer, higher quality trials. Trial Registration: ClinicalTrials.gov registration number: NCT02037321.

Structure-Function Analysis of Chloroplast Proteins via Random Mutagenesis Using Error-Prone PCR.

Science.gov (United States)

Dumas, Louis; Zito, Francesca; Auroy, Pascaline; Johnson, Xenie; Peltier, Gilles; Alric, Jean

2018-06-01

Site-directed mutagenesis of chloroplast genes was developed three decades ago and has greatly advanced the field of photosynthesis research. Here, we describe a new approach for generating random chloroplast gene mutants that combines error-prone polymerase chain reaction of a gene of interest with chloroplast complementation of the knockout Chlamydomonas reinhardtii mutant. As a proof of concept, we targeted a 300-bp sequence of the petD gene that encodes subunit IV of the thylakoid membrane-bound cytochrome b 6 f complex. By sequencing chloroplast transformants, we revealed 149 mutations in the 300-bp target petD sequence that resulted in 92 amino acid substitutions in the 100-residue target subunit IV sequence. Our results show that this method is suited to the study of highly hydrophobic, multisubunit, and chloroplast-encoded proteins containing cofactors such as hemes, iron-sulfur clusters, and chlorophyll pigments. Moreover, we show that mutant screening and sequencing can be used to study photosynthetic mechanisms or to probe the mutational robustness of chloroplast-encoded proteins, and we propose that this method is a valuable tool for the directed evolution of enzymes in the chloroplast. © 2018 American Society of Plant Biologists. All rights reserved.

Participant-selected music and physical activity in older adults following cardiac rehabilitation: a randomized controlled trial.

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Clark, Imogen N; Baker, Felicity A; Peiris, Casey L; Shoebridge, Georgie; Taylor, Nicholas F

2017-03-01

To evaluate effects of participant-selected music on older adults' achievement of activity levels recommended in the physical activity guidelines following cardiac rehabilitation. A parallel group randomized controlled trial with measurements at Weeks 0, 6 and 26. A multisite outpatient rehabilitation programme of a publicly funded metropolitan health service. Adults aged 60 years and older who had completed a cardiac rehabilitation programme. Experimental participants selected music to support walking with guidance from a music therapist. Control participants received usual care only. The primary outcome was the proportion of participants achieving activity levels recommended in physical activity guidelines. Secondary outcomes compared amounts of physical activity, exercise capacity, cardiac risk factors, and exercise self-efficacy. A total of 56 participants, mean age 68.2 years (SD = 6.5), were randomized to the experimental ( n = 28) and control groups ( n = 28). There were no differences between groups in proportions of participants achieving activity recommended in physical activity guidelines at Week 6 or 26. Secondary outcomes demonstrated between-group differences in male waist circumference at both measurements (Week 6 difference -2.0 cm, 95% CI -4.0 to 0; Week 26 difference -2.8 cm, 95% CI -5.4 to -0.1), and observed effect sizes favoured the experimental group for amounts of physical activity (d = 0.30), exercise capacity (d = 0.48), and blood pressure (d = -0.32). Participant-selected music did not increase the proportion of participants achieving recommended amounts of physical activity, but may have contributed to exercise-related benefits.

r2VIM: A new variable selection method for random forests in genome-wide association studies.

Science.gov (United States)

Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

2016-01-01

Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

The influence of anti-infective periodontal treatment on C-reactive protein: a systematic review and meta-analysis of randomized controlled trials.

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Ryan T Demmer

Full Text Available Periodontal infections are hypothesized to increase the risk of adverse systemic outcomes through inflammatory mechanisms. The magnitude of effect, if any, of anti-infective periodontal treatment on systemic inflammation is unknown, as are the patient populations most likely to benefit. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs to test the hypothesis that anti-infective periodontal treatment reduces systemic c-reactive protein (CRP.MEDLINE, EMBASE, CENTRAL and CINAHL databases were searched using sensitivity-enhancing search terms. Eligible RCTs enrolled patients with periodontal infection, compared a clearly defined anti-infective periodontal intervention (experimental group to an "inactive control" (no periodontal intervention or to an "active control" (lower treatment intensity than the experimental group. Mean differences in final CRP values at the earliest post-treatment time point (typically 1-3 months between experimental and control groups were analyzed using random-effects regression. Among 2,753 possible studies 20 were selected, which included 2,561 randomized patients(median=57. Baseline CRP values were >3.0 mg/L in 40% of trials. Among studies with a control group receiving no treatment, the mean difference in CRP final values among experimental treatment vs. control groups was -0.37 mg/L [95%CI=-0.64, -0.11], (P=0.005, favoring experimental treatment. Trials for which the experimental group received antibiotics had stronger effects (P for interaction=0.03 and the mean difference in CRP final values among experimental treatment vs. control was -0.75 mg/L [95%CI=-1.17,-0.33]. No treatment effect was observed among studies using an active treatment comparator. Treatment effects were stronger for studies that included patients with co-morbidities vs. studies that included "systemically healthy" patients, although the interaction was not significant (P=0.48.Anti-infective periodontal

DENDRIMER CONJUGATES FOR SELECTIVE OF PROTEIN AGGREGATES

DEFF Research Database (Denmark)

2004-01-01

Dendrimer conjugates are presented, which are formed between a dendrimer and a protein solubilising substance. Such dendrimer conjugates are effective in the treatment of protein aggregate-related diseases (e.g. prion-related diseases). The protein solubilising substance and the dendrimer together...

Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein-Protein Interaction Inhibitors of CaV Function.

Science.gov (United States)

Findeisen, Felix; Campiglio, Marta; Jo, Hyunil; Abderemane-Ali, Fayal; Rumpf, Christine H; Pope, Lianne; Rossen, Nathan D; Flucher, Bernhard E; DeGrado, William F; Minor, Daniel L

2017-06-21

For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (Ca V ) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (Ca V β). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:Ca V β interactions and reduce the entropic penalty associated with AID binding to Ca V β. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the Ca V α 1 :Ca V β interaction that modulate Ca V function in an Ca V β isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based Ca V modulator design.

Better preservation of residual renal function in peritoneal dialysis patients treated with a low-protein diet supplemented with keto acids: a prospective, randomized trial.

Science.gov (United States)

Jiang, Na; Qian, Jiaqi; Sun, Weilan; Lin, Aiwu; Cao, Liou; Wang, Qin; Ni, Zhaohui; Wan, Yanping; Linholm, Bengt; Axelsson, Jonas; Yao, Qiang

2009-08-01

While a low-protein diet may preserve residual renal function (RRF) in chronic kidney disease (CKD) patients before the start of dialysis, a high-protein intake is usually recommended in dialysis patients to prevent protein-energy wasting. Keto acids, which were often recommended to pre-dialysis CKD patients treated with a low-protein diet, had also been reported to be associated with both RRF and nutrition maintenance. We conducted a randomized trial to test whether a low-protein diet with or without keto acids would be safe and associated with a preserved RRF during peritoneal dialysis (PD). To assess the safety of low protein, we first conducted a nitrogen balance study in 34 incident PD patients randomized to receive in-centre diets containing 1.2, 0.9 or 0.6 g of protein/kg ideal body weight (IBW)/day for 10 days. Second, 60 stable PD patients [RRF 4.04 +/- 2.30 ml/ min/1.73 m(2), urine output 1226 +/- 449 ml/day, aged 53.6 +/- 12.8 years, PD duration 8.8 (1.5-17.8) months] were randomized to receive either a low- (LP: 0.6-0.8 g/kg IBW/day), keto acid-supplemented low- (sLP: 0.6-0.8 g/kg IBW/day with 0.12 g/kg IBW/day of keto acids) or high-protein (HP: 1.0-1.2 g/kg IBW/day) diet. The groups were followed for 1 year and RRF as well as nutritional status was evaluated serially. A neutral or positive nitrogen balance was achieved in all three groups. RRF remained stable in group sLP (3.84 +/- 2.17 to 3.39 +/- 3.23 ml/min/1.73 m(2), P = ns) while it decreased in group LP (4.02 +/- 2.49 to 2.29 +/- 1.72 ml/min/1.73 m(2), P diet containing 0.6-0.8 g of protein/kg IBW/day is safe and, when combined with keto acids, is associated with an improved preservation of RRF in relatively new PD patients without significant malnutrition or inflammation.

Palatability of water-soluble extracts of protein sources and replacement of fishmeal by a selected mixture of protein sources for juvenile turbot ( Scophthalmus maximus)

Science.gov (United States)

Dong, Chun; He, Gen; Mai, Kangsen; Zhou, Huihui; Xu, Wei

2016-06-01

Poor palatability is a limiting factor for replacing fishmeal with other protein sources in aquaculture. The water-soluble molecules with low molecular weights are the major determinants of the palatability of diets. The present study was conducted to investigate the palatability of water-soluble extracts from single protein source (single extract pellets) and the mixture of these extracts with different proportions (blended extract pellets) in juvenile turbot ( Scophthalmus maximus). Then according to the palatability of blended extract pellets, an optimal mixture proportion was selected, and a new protein source made from raw protein materials with the selected proportion was formulated to replace fishmeal. Summarily, the palatability of single extract pellets for turbot was descendent from fishmeal to pet-food grade poultry by-product meal, wheat gluten meal, soybean meal, peanut meal, meat and bone meal, and corn gluten meal. Subsequently, according to the palatability of single extract pellets, 52 kinds of blended extract pellets were designed to test their palatability. The results showed that the pellets presented remarkably different palatability, and the optimal one was diet 52 (wheat gluten meal: pet-food grade poultry by-product meal: meat and bone meal: corn gluten meal = 1:6:1:2). The highest ingestion ratio (the number of pellets ingested/the number of pellets fed) was 0.73 ± 0.03, which was observed in Diet 52. Then five isonitrogenous (52% crude protein) and isocaloric (20 kJ g-1 gross energy) diets were formulated by replacing 0 (control), 35%, 50%, 65% and 80% of fishmeal with No.52 blending proportion. After a 10-weeks feeding trial, a consistent feed intake was found among all replacement treatments. Replacement level of fishmeal up to 35% did not significantly influence final body weight, specific growth rate, feed efficiency ratio, and protein efficiency ratio of turbot. Therefore, the water-soluble extracts of protein sources play an

ASUPAN PROTEIN NABATI DAN KEJADIAN ANEMIA WANITA USIA SUBUR VEGAN

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Fajar Ari Nugroho

2016-04-01

Full Text Available ABSTRACTThe purpose of this study was to determined the role of vegetable protein intake and anaemia incidence among vegan reproductive aged women. This study was observational research with cross-sectional study design. Sixty-five subjects were selected by simple random sampling method. Data collection for intake was done by 24-hours recall technique, and haemoglobin levels was measured by cyanmethemogloblin method. The results showed that 26.1% from 31-anaemia vegan subjects classified as less vegetable protein intake individuals, and 43% from 34-non anaemia vegan subjects known as enough vegetable protein intake individuals. Chi-square test authenticate that there was a significant relationship between the vegetable protein intakes with anaemia incidence among vegan reproductive aged women (p=0.002. The conclusion showed that vegetable protein intake has a role to the risk of anaemia incidence among vegan reproductive aged women.Keywords: anaemia, reproductive aged women, vegan, vegetable proteinABSTRAKTujuan penelitian ini adalah mengetahui peran asupan protein nabati terhadap kejadian anemia pada wanita usia subur (WUS vegan. Penelitian yang dilakukan adalah penelitian observasional dengan desain cross sectional. Sebanyak 65 subjek WUS dipilih menggunakan metode simple random sampling. Pengambilan data asupan dilakukan menggunakan metode 24-hours recall, sedangkan kadar hemoglobin dianalisis menggunakan metode cyanmethemoglobin. Hasil penelitian menunjukkan 31 WUS vegan yang anemia sebesar 26,1% diantaranya menunjukkan memiliki asupan protein kurang, sedangkan 34 WUS vegan yang tidak anemia (43%, memiliki asupan protein nabati cukup. Analisis chi square menunjukkan bahwa terdapat hubungan yang signifikan antara asupan protein nabati dengan kejadian anemia (p=0,002. Kesimpulan penelitian ini adalah asupan protein nabati berperan terhadap risiko anemia pada WUS vegan.Kata kunci: anemia, protein nabati, vegan, WUS

Randomly organized lipids and marginally stable proteins: a coupling of weak interactions to optimize membrane signaling.

Science.gov (United States)

Rice, Anne M; Mahling, Ryan; Fealey, Michael E; Rannikko, Anika; Dunleavy, Katie; Hendrickson, Troy; Lohese, K Jean; Kruggel, Spencer; Heiling, Hillary; Harren, Daniel; Sutton, R Bryan; Pastor, John; Hinderliter, Anne

2014-09-01

Eukaryotic lipids in a bilayer are dominated by weak cooperative interactions. These interactions impart highly dynamic and pliable properties to the membrane. C2 domain-containing proteins in the membrane also interact weakly and cooperatively giving rise to a high degree of conformational plasticity. We propose that this feature of weak energetics and plasticity shared by lipids and C2 domain-containing proteins enhance a cell's ability to transduce information across the membrane. We explored this hypothesis using information theory to assess the information storage capacity of model and mast cell membranes, as well as differential scanning calorimetry, carboxyfluorescein release assays, and tryptophan fluorescence to assess protein and membrane stability. The distribution of lipids in mast cell membranes encoded 5.6-5.8bits of information. More information resided in the acyl chains than the head groups and in the inner leaflet of the plasma membrane than the outer leaflet. When the lipid composition and information content of model membranes were varied, the associated C2 domains underwent large changes in stability and denaturation profile. The C2 domain-containing proteins are therefore acutely sensitive to the composition and information content of their associated lipids. Together, these findings suggest that the maximum flow of signaling information through the membrane and into the cell is optimized by the cooperation of near-random distributions of membrane lipids and proteins. This article is part of a Special Issue entitled: Interfacially Active Peptides and Proteins. Guest Editors: William C. Wimley and Kalina Hristova. Copyright © 2014 Elsevier B.V. All rights reserved.

Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

Science.gov (United States)

Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

2018-01-01

The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

Structural Elements in the Gαs and Gαq C Termini That Mediate Selective G Protein-coupled Receptor (GPCR) Signaling.

Science.gov (United States)

Semack, Ansley; Sandhu, Manbir; Malik, Rabia U; Vaidehi, Nagarajan; Sivaramakrishnan, Sivaraj

2016-08-19

Although the importance of the C terminus of the α subunit of the heterotrimeric G protein in G protein-coupled receptor (GPCR)-G protein pairing is well established, the structural basis of selective interactions remains unknown. Here, we combine live cell FRET-based measurements and molecular dynamics simulations of the interaction between the GPCR and a peptide derived from the C terminus of the Gα subunit (Gα peptide) to dissect the molecular mechanisms of G protein selectivity. We observe a direct link between Gα peptide binding and stabilization of the GPCR conformational ensemble. We find that cognate and non-cognate Gα peptides show deep and shallow binding, respectively, and in distinct orientations within the GPCR. Binding of the cognate Gα peptide stabilizes the agonist-bound GPCR conformational ensemble resulting in favorable binding energy and lower flexibility of the agonist-GPCR pair. We identify three hot spot residues (Gαs/Gαq-Gln-384/Leu-349, Gln-390/Glu-355, and Glu-392/Asn-357) that contribute to selective interactions between the β2-adrenergic receptor (β2-AR)-Gαs and V1A receptor (V1AR)-Gαq The Gαs and Gαq peptides adopt different orientations in β2-AR and V1AR, respectively. The β2-AR/Gαs peptide interface is dominated by electrostatic interactions, whereas the V1AR/Gαq peptide interactions are predominantly hydrophobic. Interestingly, our study reveals a role for both favorable and unfavorable interactions in G protein selection. Residue Glu-355 in Gαq prevents this peptide from interacting strongly with β2-AR. Mutagenesis to the Gαs counterpart (E355Q) imparts a cognate-like interaction. Overall, our study highlights the synergy in molecular dynamics and FRET-based approaches to dissect the structural basis of selective G protein interactions. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Anabolic effects of leucine-rich whey protein, carbohydrate, and soy protein with and without β-hydroxy-β-methylbutyrate (HMB) during fasting-induced catabolism: A human randomized crossover trial.

Science.gov (United States)

Rittig, Nikolaj; Bach, Ermina; Thomsen, Henrik H; Møller, Andreas B; Hansen, Jakob; Johannsen, Mogens; Jensen, Erik; Serena, Anja; Jørgensen, Jens O; Richelsen, Bjørn; Jessen, Niels; Møller, Niels

2017-06-01

Protein-rich beverages are widely used clinically to preserve muscle protein and improve physical performance. Beverages with high contents of leucine or its keto-metabolite β-hydroxy-β-methylbutyrate (HMB) are especially anabolic in muscle, but it is uncertain whether this also applies to catabolic conditions such as fasting and whether common or separate intracellular signaling cascades are involved. To compare a specific leucine-rich whey protein beverage (LWH) with isocaloric carbohydrate- (CHO), soy protein (SOY), and soy protein +3 g HMB (HMB) during fasting-induced catabolic conditions. Eight healthy lean male subjects underwent four interventions (LWH, CHO, SOY, and HMB) using a randomized crossover design. Each trial included a 36 h fast and consisted of a 3 h basal fasting period and a 4 h 'sipping' period. Forearm net balances of phenylalanine (NB phe , measure of net protein loss) improved for all groups (p HMB compared with SOY (p HMB have superior anabolic effects on muscle protein kinetics after 36 h of fasting, and LWH distinctly activates the mTOR pathway. These novel findings suggest that leucine-rich whey protein and/or HMB are specifically beneficial during fasting-induced catabolic conditions. Copyright © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Two-year Randomized Clinical Trial of Self-etching Adhesives and Selective Enamel Etching.

Science.gov (United States)

Pena, C E; Rodrigues, J A; Ely, C; Giannini, M; Reis, A F

2016-01-01

The aim of this randomized, controlled prospective clinical trial was to evaluate the clinical effectiveness of restoring noncarious cervical lesions with two self-etching adhesive systems applied with or without selective enamel etching. A one-step self-etching adhesive (Xeno V(+)) and a two-step self-etching system (Clearfil SE Bond) were used. The effectiveness of phosphoric acid selective etching of enamel margins was also evaluated. Fifty-six cavities were restored with each adhesive system and divided into two subgroups (n=28; etch and non-etch). All 112 cavities were restored with the nanohybrid composite Esthet.X HD. The clinical effectiveness of restorations was recorded in terms of retention, marginal integrity, marginal staining, caries recurrence, and postoperative sensitivity after 3, 6, 12, 18, and 24 months (modified United States Public Health Service). The Friedman test detected significant differences only after 18 months for marginal staining in the groups Clearfil SE non-etch (p=0.009) and Xeno V(+) etch (p=0.004). One restoration was lost during the trial (Xeno V(+) etch; p>0.05). Although an increase in marginal staining was recorded for groups Clearfil SE non-etch and Xeno V(+) etch, the clinical effectiveness of restorations was considered acceptable for the single-step and two-step self-etching systems with or without selective enamel etching in this 24-month clinical trial.

A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

Directory of Open Access Journals (Sweden)

Himmelreich Uwe

2009-07-01

Full Text Available Abstract Background Regularized regression methods such as principal component or partial least squares regression perform well in learning tasks on high dimensional spectral data, but cannot explicitly eliminate irrelevant features. The random forest classifier with its associated Gini feature importance, on the other hand, allows for an explicit feature elimination, but may not be optimally adapted to spectral data due to the topology of its constituent classification trees which are based on orthogonal splits in feature space. Results We propose to combine the best of both approaches, and evaluated the joint use of a feature selection based on a recursive feature elimination using the Gini importance of random forests' together with regularized classification methods on spectral data sets from medical diagnostics, chemotaxonomy, biomedical analytics, food science, and synthetically modified spectral data. Here, a feature selection using the Gini feature importance with a regularized classification by discriminant partial least squares regression performed as well as or better than a filtering according to different univariate statistical tests, or using regression coefficients in a backward feature elimination. It outperformed the direct application of the random forest classifier, or the direct application of the regularized classifiers on the full set of features. Conclusion The Gini importance of the random forest provided superior means for measuring feature relevance on spectral data, but – on an optimal subset of features – the regularized classifiers might be preferable over the random forest classifier, in spite of their limitation to model linear dependencies only. A feature selection based on Gini importance, however, may precede a regularized linear classification to identify this optimal subset of features, and to earn a double benefit of both dimensionality reduction and the elimination of noise from the classification task.

Multi-Population Selective Genotyping to Identify Soybean [Glycine max (L.) Merr.] Seed Protein and Oil QTLs.

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Phansak, Piyaporn; Soonsuwon, Watcharin; Hyten, David L; Song, Qijian; Cregan, Perry B; Graef, George L; Specht, James E

2016-06-01

Plant breeders continually generate ever-higher yielding cultivars, but also want to improve seed constituent value, which is mainly protein and oil, in soybean [Glycine max (L.) Merr.]. Identification of genetic loci governing those two traits would facilitate that effort. Though genome-wide association offers one such approach, selective genotyping of multiple biparental populations offers a complementary alternative, and was evaluated here, using 48 F2:3 populations (n = ∼224 plants) created by mating 48 high protein germplasm accessions to cultivars of similar maturity, but with normal seed protein content. All F2:3 progeny were phenotyped for seed protein and oil, but only 22 high and 22 low extreme progeny in each F2:3 phenotypic distribution were genotyped with a 1536-SNP chip (ca 450 bimorphic SNPs detected per mating). A significant quantitative trait locus (QTL) on one or more chromosomes was detected for protein in 35 (73%), and for oil in 25 (52%), of the 48 matings, and these QTL exhibited additive effects of ≥ 4 g kg(-1) and R(2) values of 0.07 or more. These results demonstrated that a multiple-population selective genotyping strategy, when focused on matings between parental phenotype extremes, can be used successfully to identify germplasm accessions possessing large-effect QTL alleles. Such accessions would be of interest to breeders to serve as parental donors of those alleles in cultivar development programs, though 17 of the 48 accessions were not unique in terms of SNP genotype, indicating that diversity among high protein accessions in the germplasm collection is less than what might ordinarily be assumed. Copyright © 2016 Phansak et al.

Positive Selection Drives the Evolution of rhino, a Member of the Heterochromatin Protein 1 Family in Drosophila.

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2005-07-01

Full Text Available Heterochromatin comprises a significant component of many eukaryotic genomes. In comparison to euchromatin, heterochromatin is gene poor, transposon rich, and late replicating. It serves many important biological roles, from gene silencing to accurate chromosome segregation, yet little is known about the evolutionary constraints that shape heterochromatin. A complementary approach to the traditional one of directly studying heterochromatic DNA sequence is to study the evolution of proteins that bind and define heterochromatin. One of the best markers for heterochromatin is the heterochromatin protein 1 (HP1, which is an essential, nonhistone chromosomal protein. Here we investigate the molecular evolution of five HP1 paralogs present in Drosophila melanogaster. Three of these paralogs have ubiquitous expression patterns in adult Drosophila tissues, whereas HP1D/rhino and HP1E are expressed predominantly in ovaries and testes respectively. The HP1 paralogs also have distinct localization preferences in Drosophila cells. Thus, Rhino localizes to the heterochromatic compartment in Drosophila tissue culture cells, but in a pattern distinct from HP1A and lysine-9 dimethylated H3. Using molecular evolution and population genetic analyses, we find that rhino has been subject to positive selection in all three domains of the protein: the N-terminal chromo domain, the C-terminal chromo-shadow domain, and the hinge region that connects these two modules. Maximum likelihood analysis of rhino sequences from 20 species of Drosophila reveals that a small number of residues of the chromo and shadow domains have been subject to repeated positive selection. The rapid and positive selection of rhino is highly unusual for a gene encoding a chromosomal protein and suggests that rhino is involved in a genetic conflict that affects the germline, belying the notion that heterochromatin is simply a passive recipient of "junk DNA" in eukaryotic genomes.

Positive selection drives the evolution of rhino, a member of the heterochromatin protein 1 family in Drosophila.

Directory of Open Access Journals (Sweden)

Danielle Vermaak

2005-07-01

Full Text Available Heterochromatin comprises a significant component of many eukaryotic genomes. In comparison to euchromatin, heterochromatin is gene poor, transposon rich, and late replicating. It serves many important biological roles, from gene silencing to accurate chromosome segregation, yet little is known about the evolutionary constraints that shape heterochromatin. A complementary approach to the traditional one of directly studying heterochromatic DNA sequence is to study the evolution of proteins that bind and define heterochromatin. One of the best markers for heterochromatin is the heterochromatin protein 1 (HP1, which is an essential, nonhistone chromosomal protein. Here we investigate the molecular evolution of five HP1 paralogs present in Drosophila melanogaster. Three of these paralogs have ubiquitous expression patterns in adult Drosophila tissues, whereas HP1D/rhino and HP1E are expressed predominantly in ovaries and testes respectively. The HP1 paralogs also have distinct localization preferences in Drosophila cells. Thus, Rhino localizes to the heterochromatic compartment in Drosophila tissue culture cells, but in a pattern distinct from HP1A and lysine-9 dimethylated H3. Using molecular evolution and population genetic analyses, we find that rhino has been subject to positive selection in all three domains of the protein: the N-terminal chromo domain, the C-terminal chromo-shadow domain, and the hinge region that connects these two modules. Maximum likelihood analysis of rhino sequences from 20 species of Drosophila reveals that a small number of residues of the chromo and shadow domains have been subject to repeated positive selection. The rapid and positive selection of rhino is highly unusual for a gene encoding a chromosomal protein and suggests that rhino is involved in a genetic conflict that affects the germline, belying the notion that heterochromatin is simply a passive recipient of "junk DNA" in eukaryotic genomes.

Random effect selection in generalised linear models

DEFF Research Database (Denmark)

Denwood, Matt; Houe, Hans; Forkman, Björn

We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...

Selective functional activity measurement of a PEGylated protein with a modification-dependent activity assay.

Science.gov (United States)

Weber, Alfred; Engelmaier, Andrea; Mohr, Gabriele; Haindl, Sonja; Schwarz, Hans Peter; Turecek, Peter L

2017-01-05

BAX 855 (ADYNOVATE) is a PEGylated recombinant factor VIII (rFVIII) that showed prolonged circulatory half-life compared to unmodified rFVIII in hemophilic patients. Here, the development and validation of a novel assay is described that selectively measures the activity of BAX 855 as cofactor for the serine protease factor IX, which actives factor X. This method type, termed modification-dependent activity assay, is based on PEG-specific capture of BAX 855 by an anti-PEG IgG preparation, followed by a chromogenic FVIII activity assay. The assay principle enabled sensitive measurement of the FVIII cofactor activity of BAX 855 down to the pM-range without interference by non-PEGylated FVIII. The selectivity of the capture step, shown by competition studies to primarily target the terminal methoxy group of PEG, also allowed assessment of the intactness of the attached PEG chains. Altogether, the modification-dependent activity not only enriches, but complements the group of methods to selectively, accurately, and precisely measure a PEGylated drug in complex biological matrices. In contrast to all other methods described so far, it allows measurement of the biological activity of the PEGylated protein. Data obtained demonstrate that this new method principle can be extended to protein modifications other than PEGylation and to a variety of functional activity assays. Copyright © 2016 Elsevier B.V. All rights reserved.

The effect of yeast β-glucan on the amount of albumin, globulin, urea and total protein of broiler chickens

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ali kargarirezapour

2013-08-01

Full Text Available Glucans derived from yeast cell wall are promising alternatives to antibiotics, as they have been shown to improve growth performance and stimulate the immune system of immature broilers. In this study we evaluated the effect of different levels of yeast beta-glucan (YBG on some blood parametrs of broiler chickens. In a factorial experiment based on completely randomized design (the first factor: YBG levels: 0, 0.04 and 0.08% of basal diet and sex as a second factor 144 day old chicks (72 male and 72 female were selected and allocated to different treatments (three replicates of each treatment. The overall experimental period was 34 days. At the end of study, two birds from each pen were randomly selected as a sample. The level of albumin, globulin, urea and total protein was measured on blood samples. Statistical analysis of the results showed that the YBG had no significant effect on albumin, globulin, urea and total protein level. But the amount of plasma albumin and total protein in female chicks was significantly higher than male chicks (p

Quantitative and Selective Analysis of Feline Growth Related Proteins Using Parallel Reaction Monitoring High Resolution Mass Spectrometry.

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Mårten Sundberg

Full Text Available Today immunoassays are widely used in veterinary medicine, but lack of species specific assays often necessitates the use of assays developed for human applications. Mass spectrometry (MS is an attractive alternative due to high specificity and versatility, allowing for species-independent analysis. Targeted MS-based quantification methods are valuable complements to large scale shotgun analysis. A method referred to as parallel reaction monitoring (PRM, implemented on Orbitrap MS, has lately been presented as an excellent alternative to more traditional selected reaction monitoring/multiple reaction monitoring (SRM/MRM methods. The insulin-like growth factor (IGF-system is not well described in the cat but there are indications of important differences between cats and humans. In feline medicine IGF-I is mainly analyzed for diagnosis of growth hormone disorders but also for research, while the other proteins in the IGF-system are not routinely analyzed within clinical practice. Here, a PRM method for quantification of IGF-I, IGF-II, IGF binding protein (BP -3 and IGFBP-5 in feline serum is presented. Selective quantification was supported by the use of a newly launched internal standard named QPrEST™. Homology searches demonstrated the possibility to use this standard of human origin for quantification of the targeted feline proteins. Excellent quantitative sensitivity at the attomol/μL (pM level and selectivity were obtained. As the presented approach is very generic we show that high resolution mass spectrometry in combination with PRM and QPrEST™ internal standards is a versatile tool for protein quantitation across multispecies.

Effect of dataset selection on the topological interpretation of protein interaction networks

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Robertson David L

2005-09-01

Full Text Available Abstract Background Studies of the yeast protein interaction network have revealed distinct correlations between the connectivity of individual proteins within the network and the average connectivity of their neighbours. Although a number of biological mechanisms have been proposed to account for these findings, the significance and influence of the specific datasets included in these studies has not been appreciated adequately. Results We show how the use of different interaction data sets, such as those resulting from high-throughput or small-scale studies, and different modelling methodologies for the derivation pair-wise protein interactions, can dramatically change the topology of these networks. Furthermore, we show that some of the previously reported features identified in these networks may simply be the result of experimental or methodological errors and biases. Conclusion When performing network-based studies, it is essential to define what is meant by the term "interaction" and this must be taken into account when interpreting the topologies of the networks generated. Consideration must be given to the type of data included and appropriate controls that take into account the idiosyncrasies of the data must be selected

A randomized trial of energy-restricted high-protein versus high-carbohydrate, low-fat diet in morbid obesity.

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Dalle Grave, Riccardo; Calugi, Simona; Gavasso, Ilaria; El Ghoch, Marwan; Marchesini, Giulio

2013-09-01

Conflicting evidence exists as to weight loss produced by diets with different carbohydrate/protein ratio. The aim was to compare the long-term effects of high-protein vs. high-carbohydrate diet (HPD, HCD), combined with cognitive behavior therapy (CBT). In a randomized trial, 88 obese participants (mean age, 46.7; mean BMI, 45.6 kg m(-2) ) were enrolled in a 3-week inpatient and 48-week outpatient treatment, with continuous CBT during the study period. All subjects consumed a restricted diet (1,200 kcal day(-1) for women, 1,500 for men; 20% energy from fat, fat). HPD derived 34% energy from proteins, 46% from carbohydrates; HCD 17% from proteins, 64% from carbohydrates. The primary outcome was 1-year percent weight loss. Secondary outcomes were attrition rates and changes in cardiovascular risk factors and psychological profile. Attrition rates were similar between groups (25.6%). In the intention-to-treat analysis, weight loss averaged 15.0% in HPD and 13.3% in HCD at 1 year, without any difference throughout the study period. Both diets produced a similar improvement in secondary outcomes. The relative carbohydrate and protein content of the diet, when combined with intensive CBT, does not significantly affect attrition rate, weight loss and psychosocial outcome in patients with severe obesity. Copyright © 2013 The Obesity Society.

Selection on Coding and Regulatory Variation Maintains Individuality in Major Urinary Protein Scent Marks in Wild Mice.

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Michael J Sheehan

2016-03-01

Full Text Available Recognition of individuals by scent is widespread across animal taxa. Though animals can often discriminate chemical blends based on many compounds, recent work shows that specific protein pheromones are necessary and sufficient for individual recognition via scent marks in mice. The genetic nature of individuality in scent marks (e.g. coding versus regulatory variation and the evolutionary processes that maintain diversity are poorly understood. The individual signatures in scent marks of house mice are the protein products of a group of highly similar paralogs in the major urinary protein (Mup gene family. Using the offspring of wild-caught mice, we examine individuality in the major urinary protein (MUP scent marks at the DNA, RNA and protein levels. We show that individuality arises through a combination of variation at amino acid coding sites and differential transcription of central Mup genes across individuals, and we identify eSNPs in promoters. There is no evidence of post-transcriptional processes influencing phenotypic diversity as transcripts accurately predict the relative abundance of proteins in urine samples. The match between transcripts and urine samples taken six months earlier also emphasizes that the proportional relationships across central MUP isoforms in urine is stable. Balancing selection maintains coding variants at moderate frequencies, though pheromone diversity appears limited by interactions with vomeronasal receptors. We find that differential transcription of the central Mup paralogs within and between individuals significantly increases the individuality of pheromone blends. Balancing selection on gene regulation allows for increased individuality via combinatorial diversity in a limited number of pheromones.

Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

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Thandi Kapwata

2016-11-01

Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

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Strecker, Claas; Meyer, Bernd

2018-05-02

Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks

DEFF Research Database (Denmark)

Heide, J; Zhang, Qi; Fitzek, F H P

2013-01-01

This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...... reduction in the number of transmitted packets can be achieved. However, NC introduces additional computations and potentially a non-negligible transmission overhead, both of which depend on the chosen coding parameters. Therefore it is necessary to consider the trade-off that these coding parameters...... present in order to obtain the lowest energy consumption per transmitted bit. This problem is analyzed and suitable coding parameters are determined for the popular Tmote Sky platform. Compared to the use of traditional RLNC, these parameters enable a reduction in the energy spent per bit which grows...

Signal sequence and keyword trap in silico for selection of full-length human cDNAs encoding secretion or membrane proteins from oligo-capped cDNA libraries.

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Otsuki, Tetsuji; Ota, Toshio; Nishikawa, Tetsuo; Hayashi, Koji; Suzuki, Yutaka; Yamamoto, Jun-ichi; Wakamatsu, Ai; Kimura, Kouichi; Sakamoto, Katsuhiko; Hatano, Naoto; Kawai, Yuri; Ishii, Shizuko; Saito, Kaoru; Kojima, Shin-ichi; Sugiyama, Tomoyasu; Ono, Tetsuyoshi; Okano, Kazunori; Yoshikawa, Yoko; Aotsuka, Satoshi; Sasaki, Naokazu; Hattori, Atsushi; Okumura, Koji; Nagai, Keiichi; Sugano, Sumio; Isogai, Takao

2005-01-01

We have developed an in silico method of selection of human full-length cDNAs encoding secretion or membrane proteins from oligo-capped cDNA libraries. Fullness rates were increased to about 80% by combination of the oligo-capping method and ATGpr, software for prediction of translation start point and the coding potential. Then, using 5'-end single-pass sequences, cDNAs having the signal sequence were selected by PSORT ('signal sequence trap'). We also applied 'secretion or membrane protein-related keyword trap' based on the result of BLAST search against the SWISS-PROT database for the cDNAs which could not be selected by PSORT. Using the above procedures, 789 cDNAs were primarily selected and subjected to full-length sequencing, and 334 of these cDNAs were finally selected as novel. Most of the cDNAs (295 cDNAs: 88.3%) were predicted to encode secretion or membrane proteins. In particular, 165(80.5%) of the 205 cDNAs selected by PSORT were predicted to have signal sequences, while 70 (54.2%) of the 129 cDNAs selected by 'keyword trap' preserved the secretion or membrane protein-related keywords. Many important cDNAs were obtained, including transporters, receptors, and ligands, involved in significant cellular functions. Thus, an efficient method of selecting secretion or membrane protein-encoding cDNAs was developed by combining the above four procedures.

IRaPPA: information retrieval based integration of biophysical models for protein assembly selection.

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Moal, Iain H; Barradas-Bautista, Didier; Jiménez-García, Brian; Torchala, Mieczyslaw; van der Velde, Arjan; Vreven, Thom; Weng, Zhiping; Bates, Paul A; Fernández-Recio, Juan

2017-06-15

In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. Atomic modeling of protein-protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. IRaPPA has been implemented in the SwarmDock server ( http://bmm.crick.ac.uk/∼SwarmDock/ ), pyDock server ( http://life.bsc.es/pid/pydockrescoring/ ) and ZDOCK server ( http://zdock.umassmed.edu/ ), with code available on request. moal@ebi.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Application of random coherence order selection in gradient-enhanced multidimensional NMR

International Nuclear Information System (INIS)

Bostock, Mark J.; Nietlispach, Daniel

2016-01-01

Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1 -norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1 -norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended

Protein-protein networks construction and their relevance measurement based on multi-epitope-ligand-kartographie and gene ontology data of T-cell surface proteins for polymyositis.

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Li, Fang-Zhen; Gao, Feng

2012-08-01

Polymyositis is an inflammatory myopathy characterized by muscle invasion of T-cells penetrating the basal lamina and displacing the plasma membrane of normal muscle fibers. In order to understand the different adhesive mechanisms at the T-cell surface, Schubert randomly selected 19 proteins expressed at the T-cell surface and studied them using MELK technique [4], among which 15 proteins are picked up for further study by us. Two types of functional similarity networks are constructed for these proteins. The first type is MELK similarity network, which is constructed based on their MELK data by using the McNemar's test [24]. The second type is GO similarity network, which is constructed based on their GO annotation data by using the RSS method to measuring functional similarity. Then the subset surprisology theory is employed to measure the degree of similarity between two networks. Our computing results show that these two types of networks are high related. This conclusion added new values on MELK technique and expanded its applications greatly.

Phage display selection of efficient glutamine-donor substrate peptides for transglutaminase 2.

Science.gov (United States)

Keresztessy, Zsolt; Csosz, Eva; Hársfalvi, Jolán; Csomós, Krisztián; Gray, Joe; Lightowlers, Robert N; Lakey, Jeremy H; Balajthy, Zoltán; Fésüs, László

2006-11-01

Understanding substrate specificity and identification of natural targets of transglutaminase 2 (TG2), the ubiquitous multifunctional cross-linking enzyme, which forms isopeptide bonds between protein-linked glutamine and lysine residues, is crucial in the elucidation of its physiological role. As a novel means of specificity analysis, we adapted the phage display technique to select glutamine-donor substrates from a random heptapeptide library via binding to recombinant TG2 and elution with a synthetic amine-donor substrate. Twenty-six Gln-containing sequences from the second and third biopanning rounds were susceptible for TG2-mediated incorporation of 5-(biotinamido)penthylamine, and the peptides GQQQTPY, GLQQASV, and WQTPMNS were modified most efficiently. A consensus around glutamines was established as pQX(P,T,S)l, which is consistent with identified substrates listed in the TRANSDAB database. Database searches showed that several proteins contain peptides similar to the phage-selected sequences, and the N-terminal glutamine-rich domain of SWI1/SNF1-related chromatin remodeling proteins was chosen for detailed analysis. MALDI/TOF and tandem mass spectrometry-based studies of a representative part of the domain, SGYGQQGQTPYYNQQSPHPQQQQPPYS (SnQ1), revealed that Q(6), Q(8), and Q(22) are modified by TG2. Kinetic parameters of SnQ1 transamidation (K(M)(app) = 250 microM, k(cat) = 18.3 sec(-1), and k(cat)/K(M)(app) = 73,200) classify it as an efficient TG2 substrate. Circular dichroism spectra indicated that SnQ1 has a random coil conformation, supporting its accessibility in the full-length parental protein. Added together, here we report a novel use of the phage display technology with great potential in transglutaminase research.

On Random Numbers and Design

Science.gov (United States)

Ben-Ari, Morechai

2004-01-01

The term "random" is frequently used in discussion of the theory of evolution, even though the mathematical concept of randomness is problematic and of little relevance in the theory. Therefore, since the core concept of the theory of evolution is the non-random process of natural selection, the term random should not be used in teaching the…

Molecular Mechanism of Selectivity among G Protein-Coupled Receptor Kinase 2 Inhibitors

Energy Technology Data Exchange (ETDEWEB)

Thal, David M.; Yeow, Raymond Y.; Schoenau, Christian; Huber, Jochen; Tesmer, John J.G. (Sanofi); (Michigan)

2012-07-11

G protein-coupled receptors (GPCRs) are key regulators of cell physiology and control processes ranging from glucose homeostasis to contractility of the heart. A major mechanism for the desensitization of activated GPCRs is their phosphorylation by GPCR kinases (GRKs). Overexpression of GRK2 is strongly linked to heart failure, and GRK2 has long been considered a pharmaceutical target for the treatment of cardiovascular disease. Several lead compounds developed by Takeda Pharmaceuticals show high selectivity for GRK2 and therapeutic potential for the treatment of heart failure. To understand how these drugs achieve their selectivity, we determined crystal structures of the bovine GRK2-G{beta}{gamma} complex in the presence of two of these inhibitors. Comparison with the apoGRK2-G{beta}{gamma} structure demonstrates that the compounds bind in the kinase active site in a manner similar to that of the AGC kinase inhibitor balanol. Both balanol and the Takeda compounds induce a slight closure of the kinase domain, the degree of which correlates with the potencies of the inhibitors. Based on our crystal structures and homology modeling, we identified five amino acids surrounding the inhibitor binding site that we hypothesized could contribute to inhibitor selectivity. However, our results indicate that these residues are not major determinants of selectivity among GRK subfamilies. Rather, selectivity is achieved by the stabilization of a unique inactive conformation of the GRK2 kinase domain.

Dietary protein level and performance of growing Baladi kids.

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Abdelrahman, M M; Aljumaah, R S

2014-01-01

A study was conducted to evaluate the effect of feeding different levels of protein to black Baladi breed kids. Weanling Baladi kids (n=18; 75 to 90 days old) were selected and individually housed at our experimental farm. Kids were divided randomly to one of the three treatments for 12 weeks. The three dietary treatments were: T1: control ration, formulated according to NRC to cover the protein (level 1) and other nutrients requirements. T2: ration formulated to cover only 75% of protein (level 2) recommended by NRC. T3: control diet + 2.4 g undegradable methionine (Smartamine®)/day/kid (level 3). Feed intake, initial and monthly body weights were recorded. Blood samples were collected monthly and analyzed for metabolites and Co, Zn and Cu levels. Decreasing the dietary level of protein (T2) negatively affected (Pkids below the NRC requirements of protein negatively affect the growth performance and feed efficiency. The recommended protein level by NRC for growing kids cover the requirements of growing black Baladi kids for maximum growth and productivity.

Whey Protein Supplementation Enhances Body Fat and Weight Loss in Women Long After Bariatric Surgery: a Randomized Controlled Trial.

Science.gov (United States)

Lopes Gomes, Daniela; Moehlecke, Milene; Lopes da Silva, Fernanda Bassan; Dutra, Eliane Said; D'Agord Schaan, Beatriz; Baiocchi de Carvalho, Kenia Mara

2017-02-01

The ideal nutritional approach for weight regain after bariatric surgery remains unclear. The objective of this study is to assess the effect of whey protein supplementation on weight loss and body composition of women who regained weight 24 or more months after bariatric surgery. This is a 16-week open-label, parallel-group, randomized controlled trial of women who regained at least 5 % of their lowest postoperative weight after a Roux-en-Y gastric bypass (RYGB). A total of 34 participants were treated with hypocaloric diet and randomized (1:1) to receive or not supplementation with whey protein, 0.5 g/kg of the ideal body weight. The primary outcomes were changes in body weight, fat free mass (FFM), and fat mass (FM), evaluated by tetrapolar bioelectrical impedance analysis (BIA). Secondary outcomes included resting energy expenditure, blood glucose, lipids, adiponectin, interleukin 6 (IL-6), and cholecystokinin levels. Statistical analyses included generalized estimating equations adjusted for age and physical activity. Fifteen patients in each group were evaluated: mean age was 45 ± 11 years, body mass index (BMI) was 35.7 ± 5.2 kg/m 2 , and time since surgery was 69 ± 23 months. Protein intake during follow-up increased by approximately 75 % in the intervention group (p = 0.01). The intervention group presented more body weight loss (1.86 kg, p = 0.017), accounted for FM loss (2.78, p = 0.021) and no change in FFM, as compared to controls (gain of 0.42 kg of body weight and 0.6 kg of FM). No differences in secondary outcomes were observed between groups. Whey protein supplementation promoted body weight and FM loss in women with long-term weight regain following RYGB.

A simple and reliable approach to docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints

International Nuclear Information System (INIS)

Tang, Chun; Clore, G. Marius

2006-01-01

A simple and reliable approach for docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints (as few as three from a single point) in combination with a novel representation for an attractive potential between mapped interaction surfaces is described. Unambiguous assignments of very sparse intermolecular NOEs are obtained using a reverse labeling strategy in which one the components is fully deuterated with the exception of selective protonation of the δ-methyl groups of isoleucine, while the other component is uniformly 13 C-labeled. This labeling strategy can be readily extended to selective protonation of Ala, Leu, Val or Met. The attractive potential is described by a 'reduced' radius of gyration potential applied specifically to a subset of interfacial residues (those with an accessible surface area ≥ 50% in the free proteins) that have been delineated by chemical shift perturbation. Docking is achieved by rigid body minimization on the basis of a target function comprising the sparse NOE distance restraints, a van der Waals repulsion potential and the 'reduced' radius of gyration potential. The method is demonstrated for two protein-protein complexes (EIN-HPr and IIA Glc -HPr) from the bacterial phosphotransferase system. In both cases, starting from 100 different random orientations of the X-ray structures of the free proteins, 100% convergence is achieved to a single cluster (with near identical atomic positions) with an overall backbone accuracy of ∼2 A. The approach described is not limited to NMR, since interfaces can also be mapped by alanine scanning mutagenesis, and sparse intermolecular distance restraints can be derived from double cycle mutagenesis, cross-linking combined with mass spectrometry, or fluorescence energy transfer

Protein engineering for metabolic engineering: current and next-generation tools

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Marcheschi, Ryan J.; Gronenberg, Luisa S.; Liao, James C.

2014-01-01

Protein engineering in the context of metabolic engineering is increasingly important to the field of industrial biotechnology. As the demand for biologically-produced food, fuels, chemicals, food additives, and pharmaceuticals continues to grow, the ability to design and modify proteins to accomplish new functions will be required to meet the high productivity demands for the metabolism of engineered organisms. This article reviews advances of selecting, modeling, and engineering proteins to improve or alter their activity. Some of the methods have only recently been developed for general use and are just beginning to find greater application in the metabolic engineering community. We also discuss methods of generating random and targeted diversity in proteins to generate mutant libraries for analysis. Recent uses of these techniques to alter cofactor use, produce non-natural amino acids, alcohols, and carboxylic acids, and alter organism phenotypes are presented and discussed as examples of the successful engineering of proteins for metabolic engineering purposes. PMID:23589443

BMRF-Net: a software tool for identification of protein interaction subnetworks by a bagging Markov random field-based method.

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Shi, Xu; Barnes, Robert O; Chen, Li; Shajahan-Haq, Ayesha N; Hilakivi-Clarke, Leena; Clarke, Robert; Wang, Yue; Xuan, Jianhua

2015-07-15

Identification of protein interaction subnetworks is an important step to help us understand complex molecular mechanisms in cancer. In this paper, we develop a BMRF-Net package, implemented in Java and C++, to identify protein interaction subnetworks based on a bagging Markov random field (BMRF) framework. By integrating gene expression data and protein-protein interaction data, this software tool can be used to identify biologically meaningful subnetworks. A user friendly graphic user interface is developed as a Cytoscape plugin for the BMRF-Net software to deal with the input/output interface. The detailed structure of the identified networks can be visualized in Cytoscape conveniently. The BMRF-Net package has been applied to breast cancer data to identify significant subnetworks related to breast cancer recurrence. The BMRF-Net package is available at http://sourceforge.net/projects/bmrfcjava/. The package is tested under Ubuntu 12.04 (64-bit), Java 7, glibc 2.15 and Cytoscape 3.1.0. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A randomized trial of high-dairy-protein, variable-carbohydrate diets and exercise on body composition in adults with obesity.

Science.gov (United States)

Parr, Evelyn B; Coffey, Vernon G; Cato, Louise E; Phillips, Stuart M; Burke, Louise M; Hawley, John A

2016-05-01

This study determined the effects of 16-week high-dairy-protein, variable-carbohydrate (CHO) diets and exercise training (EXT) on body composition in men and women with overweight/obesity. One hundred and eleven participants (age 47 ± 6 years, body mass 90.9 ± 11.7 kg, BMI 33 ± 4 kg/m(2) , values mean ± SD) were randomly stratified to diets with either: high dairy protein, moderate CHO (40% CHO: 30% protein: 30% fat; ∼4 dairy servings); high dairy protein, high CHO (55%: 30%: 15%; ∼4 dairy servings); or control (55%: 15%: 30%; ∼1 dairy serving). Energy restriction (500 kcal/day) was achieved through diet (∼250 kcal/day) and EXT (∼250 kcal/day). Body composition was measured using dual-energy X-ray absorptiometry before, midway, and upon completion of the intervention. Eighty-nine (25 M/64 F) of 115 participants completed the 16-week intervention, losing 7.7 ± 3.2 kg fat mass (P exercise stimulus. © 2016 The Obesity Society.

Information assessment on predicting protein-protein interactions

Directory of Open Access Journals (Sweden)

Gerstein Mark

2004-10-01

Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the

Selection of unadapted, pathogenic SHIVs encoding newly transmitted HIV-1 envelope proteins.

Science.gov (United States)

Del Prete, Gregory Q; Ailers, Braiden; Moldt, Brian; Keele, Brandon F; Estes, Jacob D; Rodriguez, Anthony; Sampias, Marissa; Oswald, Kelli; Fast, Randy; Trubey, Charles M; Chertova, Elena; Smedley, Jeremy; LaBranche, Celia C; Montefiori, David C; Burton, Dennis R; Shaw, George M; Markowitz, Marty; Piatak, Michael; KewalRamani, Vineet N; Bieniasz, Paul D; Lifson, Jeffrey D; Hatziioannou, Theodora

2014-09-10

Infection of macaques with chimeric viruses based on SIVMAC but expressing the HIV-1 envelope (Env) glycoproteins (SHIVs) remains the most powerful model for evaluating prevention and therapeutic strategies against AIDS. Unfortunately, only a few SHIVs are currently available. Furthermore, their generation has required extensive adaptation of the HIV-1 Env sequences in macaques so they may not accurately represent HIV-1 Env proteins circulating in humans, potentially limiting their translational utility. We developed a strategy for generating large numbers of SHIV constructs expressing Env proteins from newly transmitted HIV-1 strains. By inoculating macaques with cocktails of multiple SHIV variants, we selected SHIVs that can replicate and cause AIDS-like disease in immunologically intact rhesus macaques without requiring animal-to-animal passage. One of these SHIVs could be transmitted mucosally. We demonstrate the utility of the SHIVs generated by this method for evaluating neutralizing antibody administration as a protection against mucosal SHIV challenge. Copyright © 2014 Elsevier Inc. All rights reserved.

Nickel nanoparticle decorated graphene for highly selective isolation of polyhistidine-tagged proteins

Science.gov (United States)

Liu, Jia-Wei; Yang, Ting; Ma, Lin-Yu; Chen, Xu-Wei; Wang, Jian-Hua

2013-12-01

Nickel nanoparticle decorated graphene (GP-Ni) is prepared by one-pot hydrothermal reduction of graphene oxide and nickel cations by hydrazine hydrate in the presence of poly(sodium-p-styrenesulfonate) (PSS). The GP-Ni hybrid is characterized by XRD, TEM, SEM, XPS, Raman and FT-IR spectra, demonstrating the formation of poly-dispersed nickel nanoparticles with an average size of 83 nm attached on the surface of graphene sheets. The GP-Ni hybrid exhibits ferromagnetic behavior with a magnetization saturation of 31.1 emu g-1 at 10 000 Oersted (Oe). The GP-Ni also possesses favorable stability in aqueous medium and rapid magnetic response to an external magnetic field. These make it a novel magnetic adsorbent for the separation/isolation of His6-tagged recombinant proteins from a complex sample matrix (cell lysate). The targeted protein species is captured onto the surface of the GP-Ni hybrid via specific metal affinity force between polyhistidine groups and nickel nanoparticles. The SDS-PAGE assay indicates highly selective separation of His6-tagged Smt A from cell lysate. The GP-Ni hybrid displays favorable performance on the separation/isolation of His6-tagged recombinant proteins with respect to the commercial NTA-Ni2+ column.

Effects of protein intake and gender on body composition changes: a randomized clinical weight loss trial

Directory of Open Access Journals (Sweden)

Evans Ellen M

2012-06-01

Full Text Available Abstract Limited data on sex differences in body composition changes in response to higher protein diets (PRO compared to higher carbohydrate diets (CARB suggest that a PRO diet helps preserve lean mass (LM in women more so than in men. Objective To compare male and female body composition responses to weight loss diets differing in macronutrient content. Design Twelve month randomized clinical trial with 4mo of weight loss and 8mo weight maintenance. Subjects Overweight (N = 130; 58 male (M, 72 female (F; BMI = 32.5 ± 0.5 kg/m2 middle-aged subjects were randomized to energy-restricted (deficit ~500 kcal/d diets providing protein at 1.6 g.kg-1.d-1 (PRO or 0.8 g.kg-1.d-1 (CARB. LM and fat mass (FM were measured using dual X-ray absorptiometry. Body composition outcomes were tested in a repeated measures ANOVA controlling for sex, diet, time and their two- and three-way interactions at 0, 4, 8 and 12mo. Results When expressed as percent change from baseline, males and females lost similar amounts of weight at 12mo (M:-11.2 ± 7.1 %, F:-9.9 ± 6.0 %, as did diet groups (PRO:-10.7 ± 6.8 %, CARB:-10.1 ± 6.2 %, with no interaction of gender and diet. A similar pattern emerged for fat mass and lean mass, however percent body fat was significantly influenced by both gender (M:-18.0 ± 12.8 %, F:-7.3 ± 8.1 %, p  Conclusion PRO was more effective in reducing percent body fat vs. CARB over 12mo weight loss and maintenance. Men lost percent total body fat and trunk fat more effectively than women. No interactive effects of protein intake and gender are evident.

From micelles to fibers: balancing self-assembling and random coiling domains in pH-responsive silk-collagen-like protein-based polymers

NARCIS (Netherlands)

Beun, L.H.; Storm, I.M.; Werten, M.W.T.; Wolf, de F.A.; Cohen Stuart, M.A.; Vries, de R.J.

2014-01-01

We study the self-assembly of genetically engineered protein-based triblock copolymers consisting of a central pH-responsive silk-like middle block (SHn, where SH is a silk-like octapeptide, (GA)3GH and n is the number of repeats) flanked by hydrophilic random coil outer blocks (C2). Our previous

A Permutation Importance-Based Feature Selection Method for Short-Term Electricity Load Forecasting Using Random Forest

Directory of Open Access Journals (Sweden)

Nantian Huang

2016-09-01

Full Text Available The prediction accuracy of short-term load forecast (STLF depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.

Formylbenzene diazonium hexafluorophosphate reagent for tyrosine-selective modification of proteins and the introduction of a bioorthogonal aldehyde.

Science.gov (United States)

Gavrilyuk, Julia; Ban, Hitoshi; Nagano, Masanobu; Hakamata, Wataru; Barbas, Carlos F

2012-12-19

4-Formylbenzene diazonium hexafluorophosphate (FBDP) is a novel bench-stable crystalline diazonium salt that reacts selectively with tyrosine to install a bioorthogonal aldehyde functionality. Model studies with N-acyl-tyrosine methylamide allowed us to identify conditions optimal for tyrosine ligation reactions with small peptides and proteins. FBDP-based conjugation was used for the facile introduction of small molecule tags, poly(ethylene glycol) chains (PEGylation), and functional small molecules onto model proteins and to label the surface of living cells.

Automated selected reaction monitoring software for accurate label-free protein quantification.

Science.gov (United States)

Teleman, Johan; Karlsson, Christofer; Waldemarson, Sofia; Hansson, Karin; James, Peter; Malmström, Johan; Levander, Fredrik

2012-07-06

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

Direct random insertion mutagenesis of Helicobacter pylori

NARCIS (Netherlands)

de Jonge, Ramon; Bakker, Dennis; van Vliet, Arnoud H. M.; Kuipers, Ernst J.; Vandenbroucke-Grauls, Christina M. J. E.; Kusters, Johannes G.

2003-01-01

Random insertion mutagenesis is a widely used technique for the identification of bacterial virulence genes. Most strategies for random mutagenesis involve cloning in Escherichia coli for passage of plasmids or for phenotypic selection. This can result in biased selection due to restriction or

Direct random insertion mutagenesis of Helicobacter pylori.

NARCIS (Netherlands)

Jonge, de R.; Bakker, D.; Vliet, van AH; Kuipers, E.J.; Vandenbroucke-Grauls, C.M.J.E.; Kusters, J.G.

2003-01-01

Random insertion mutagenesis is a widely used technique for the identification of bacterial virulence genes. Most strategies for random mutagenesis involve cloning in Escherichia coli for passage of plasmids or for phenotypic selection. This can result in biased selection due to restriction or

Proteome Analysis of Thyroid Cancer Cells After Long-Term Exposure to a Random Positioning Machine

Science.gov (United States)

Pietsch, Jessica; Bauer, Johann; Weber, Gerhard; Nissum, Mikkel; Westphal, Kriss; Egli, Marcel; Grosse, Jirka; Schönberger, Johann; Eilles, Christoph; Infanger, Manfred; Grimm, Daniela

2011-11-01

Annulling gravity during cell culturing triggers various types of cells to change their protein expression in a time dependent manner. We therefore decided to determine gravity sensitive proteins and their period of sensitivity to the effects of gravity. In this study, thyroid cancer cells of the ML-1 cell line were cultured under normal gravity (1 g) or in a random positioning machine (RPM), which simulated near weightlessness for 7 and 11 days. Cells were then sonicated and proteins released into the supernatant were separated from those that remained attached to the cell fragments. Subsequently, both types of proteins were fractionated by free-flow isoelectric focussing (FF-IEF). The fractions obtained were further separated by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) to which comparable FF-IEF fractions derived from cells cultured either under 1 g or on the RPM had been applied side by side. The separation resulted in pairs of lanes, on which a number of identical bands were observed. Selected gel pieces were excised and their proteins determined by mass spectrometry. Equal proteins from cells cultured under normal gravity and the RPM, respectively, were detected in comparable gel pieces. However, many of these proteins had received different Mascot scores. Quantifying heat shock cognate 71 kDa protein, glutathione S-transferase P, nucleoside diphosphate kinase A and annexin-2 by Western blotting using whole cell lysates indicated usefulness of Mascot scores for selecting the most efficient antibodies.

Maximizing Selective Cleavages at Aspartic Acid and Proline Residues for the Identification of Intact Proteins

Science.gov (United States)

Foreman, David J.; Dziekonski, Eric T.; McLuckey, Scott A.

2018-04-01

A new approach for the identification of intact proteins has been developed that relies on the generation of relatively few abundant products from specific cleavage sites. This strategy is intended to complement standard approaches that seek to generate many fragments relatively non-selectively. Specifically, this strategy seeks to maximize selective cleavage at aspartic acid and proline residues via collisional activation of precursor ions formed via electrospray ionization (ESI) under denaturing conditions. A statistical analysis of the SWISS-PROT database was used to predict the number of arginine residues for a given intact protein mass and predict a m/z range where the protein carries a similar charge to the number of arginine residues thereby enhancing cleavage at aspartic acid residues by limiting proton mobility. Cleavage at aspartic acid residues is predicted to be most favorable in the m/z range of 1500-2500, a range higher than that normally generated by ESI at low pH. Gas-phase proton transfer ion/ion reactions are therefore used for precursor ion concentration from relatively high charge states followed by ion isolation and subsequent generation of precursor ions within the optimal m/z range via a second proton transfer reaction step. It is shown that the majority of product ion abundance is concentrated into cleavages C-terminal to aspartic acid residues and N-terminal to proline residues for ions generated by this process. Implementation of a scoring system that weights both ion fragment type and ion fragment area demonstrated identification of standard proteins, ranging in mass from 8.5 to 29.0 kDa. [Figure not available: see fulltext.

Selection of antifungal protein-producing molds from dry-cured meat products.

Science.gov (United States)

Acosta, Raquel; Rodríguez-Martín, Andrea; Martín, Alberto; Núñez, Félix; Asensio, Miguel A

2009-09-30

To control unwanted molds in dry-cured meats it is necessary to allow the fungal development essential for the desired characteristics of the final product. Molds producing antifungal proteins could be useful to prevent hazards due to the growth of mycotoxigenic molds. The objective has been to select Penicillium spp. that produce antifungal proteins against toxigenic molds. To obtain strains adapted to these products, molds were isolated from dry-cured ham. A first screening with 281 isolates by the radial inhibition assay revealed that 166 were active against some of the toxigenic P. echinulatum, P. commune, and Aspergillusniger used as reference molds. The activity of different extracts from cultured medium was evaluated by a microspectroscopic assay. Molds producing active chloroform extracts were eliminated from further consideration. A total of 16 Penicillium isolates were screened for antifungal activity from both cell-free media and the aqueous residues obtained after chloroform extraction. The cell-free media of 10 isolates that produced a strong inhibition of the three reference molds were fractionated by FPLC on a cationic column. For protein purification, the fractions of the three molds that showed high inhibitory activity were further chromatographed on a gel filtration column, and the subfractions containing the highest absorbance peaks were assayed against the most sensitive reference molds. One subfraction each from strains AS51D and RP42C from Penicilliumchrysogenum confirmed the inhibitory activity against the reference molds. SDS-PAGE revealed a single band from each subfraction, with estimated molecular masses of 37kDa for AS51D and 9kDa for RP42C. Although further characterisation is required, both these proteins and the producing strains can be of interest to control unwanted molds on foods.

Meals based on vegetable protein sources (beans and peas) are more satiating than meals based on animal protein sources (veal and pork) – a randomized cross-over meal test study

Science.gov (United States)

Kristensen, Marlene D.; Bendsen, Nathalie T.; Christensen, Sheena M.; Astrup, Arne; Raben, Anne

2016-01-01

Background Recent nutrition recommendations advocate a reduction in protein from animal sources (pork, beef) because of environmental concerns. Instead, protein from vegetable sources (beans, peas) should be increased. However, little is known about the effect of these vegetable protein sources on appetite regulation. Objective To examine whether meals based on vegetable protein sources (beans/peas) are comparable to meals based on animal protein sources (veal/pork) regarding meal-induced appetite sensations. Design In total, 43 healthy, normal-weight, young men completed this randomized, double-blind, placebo-controlled, three-way, cross-over meal test. The meals (all 3.5 MJ, 28 energy-% (E%) fat) were either high protein based on veal and pork meat, HP-Meat (19 E% protein, 53 E% carbohydrate, 6 g fiber/100 g); high protein based on legumes (beans and peas), HP-Legume (19 E% protein, 53 E% carbohydrate, 25 g fiber/100 g); or low-protein based on legumes, LP-Legume (9 E% protein, 62 E% carbohydrate, 10 g fiber/100 g). Subjective appetite sensations were recorded at baseline and every half hour using visual analog scales until the ad libitum meal 3 h after the test meal. Repeated measurements analyses and summary analyses were performed using ANCOVA (SAS). Results HP-Legume induced lower composite appetite score, hunger, prospective food consumption, and higher fullness compared to HP-Meat and LP-Legume (ppeas) influenced appetite sensations favorably compared to animal-based meals (pork/veal) with similar energy and protein content, but lower fiber content. Interestingly, a vegetable-based meal with low protein content was as satiating and palatable as an animal-based meal with high protein content. PMID:27765144

Effect of whey protein supplementation on long and short term appetite: A meta-analysis of randomized controlled trials.

Science.gov (United States)

Mollahosseini, Mehdi; Shab-Bidar, Sakineh; Rahimi, Mohammad Hossein; Djafarian, Kurosh

2017-08-01

Specific components of dairy, such as whey proteins may have beneficial effects on body composition by suppressing appetite, although the findings of existing studies have been inconsistent. Therefore, a meta-analysis of randomized controlled trials was performed to investigate effect of whey protein supplementation on long and short term appetite. A systematic search was conducted to identify eligible publications. Means and SDs for hunger, fullness, satiety, desire to eat and prospective consumption of food, before and after intervention, were extracted and then composite appetite score (CAS) calculated. To pool data, either a fixed-effects model or a random-effects model and for assessing heterogeneity, Cochran's Q and I 2 tests were used. Eight publications met inclusion criteria that 5 records were on short term and 3 records on long term appetite. The meta-analysis showed a significant reduction in long term appetite by 4.13 mm in combined appetite score (CAS) (95% Confidence interval (CI): -6.57, -1.96; p = 0.001). No significant reduction in short term appetite was also seen (Mean difference (MD) = -0.39 95% CI = -2.07, 1.30; p = 0.653). Subgroup analyses by time showed that compared with carbohydrate, the reduction in appetite following consumption of whey consumption was not significant (MD = -0.39, 95% CI = -2.07, 1.3, p = 0.65, I 2  = 0.0%.)A significant reduction in prospective food consumption was seen (MD = -2.17, 95% CI = -3.86, -0.48). The results of our meta-analysis showed that whey protein may reduce the long and short term appetite, but our finding did not show any significant difference in appetite reduction between whey protein and carbohydrate in short duration. Copyright © 2017 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.

From Never Born Proteins to Minimal Living Cells: two projects in synthetic biology.

Science.gov (United States)

Luisi, Pier Luigi; Chiarabelli, Cristiano; Stano, Pasquale

2006-12-01

The Never Born Proteins (NBPs) and the Minimal Cell projects are two currently developed research lines belonging to the field of synthetic biology. The first deals with the investigation of structural and functional properties of de novo proteins with random sequences, selected and isolated using phage display methods. The minimal cell is the simplest cellular construct which displays living properties, such as self-maintenance, self-reproduction and evolvability. The semi-synthetic approach to minimal cells involves the use of extant genes and proteins in order to build a supramolecular construct based on lipid vesicles. Results and outlooks on these two research lines are shortly discussed, mainly focusing on their relevance to the origin of life studies.

Selection for a Zinc-Finger Protein Contributes to Seed Oil Increase during Soybean Domestication1[OPEN

Science.gov (United States)

Li, Qing-Tian; Lu, Xiang; Song, Qing-Xin; Chen, Hao-Wei; Wei, Wei; Tao, Jian-Jun; Ma, Biao; Bi, Ying-Dong; Li, Wei; Lai, Yong-Cai; Shui, Guang-Hou; Chen, Shou-Yi

2017-01-01

Seed oil is a momentous agronomical trait of soybean (Glycine max) targeted by domestication in breeding. Although multiple oil-related genes have been uncovered, knowledge of the regulatory mechanism of seed oil biosynthesis is currently limited. We demonstrate that the seed-preferred gene GmZF351, encoding a tandem CCCH zinc finger protein, is selected during domestication. Further analysis shows that GmZF351 facilitates oil accumulation by directly activating WRINKLED1, BIOTIN CARBOXYL CARRIER PROTEIN2, 3-KETOACYL-ACYL CARRIER PROTEIN SYNTHASE III, DIACYLGLYCEROL O-ACYLTRANSFERASE1, and OLEOSIN2 in transgenic Arabidopsis (Arabidopsis thaliana) seeds. Overexpression of GmZF351 in transgenic soybean also activates lipid biosynthesis genes, thereby accelerating seed oil accumulation. The ZF351 haplotype from the cultivated soybean group and the wild soybean (Glycine soja) subgroup III correlates well with high gene expression level, seed oil contents and promoter activity, suggesting that selection of GmZF351 expression leads to increased seed oil content in cultivated soybean. Our study provides novel insights into the regulatory mechanism for seed oil accumulation, and the manipulation of GmZF351 may have great potential in the improvement of oil production in soybean and other related crops. PMID:28184009

Selective {sup 2}H and {sup 13}C labeling in NMR analysis of solution protein structure and dynamics

Energy Technology Data Exchange (ETDEWEB)

LeMaster, D.M. [Northwestern Univ., Evanston, IL (United States)

1994-12-01

Preparation of samples bearing combined isotope enrichment patterns has played a central role in the recent advances in NMR analysis of proteins in solution. In particular, uniform {sup 13}C, {sup 15}N enrichment has made it possible to apply heteronuclear multidimensional correlation experiments for the mainchain assignments of proteins larger than 30 KDa. In contrast, selective labeling approaches can offer advantages in terms of the directedness of the information provided, such as chirality and residue type assignments, as well as through enhancements in resolution and sensitivity that result from editing the spectral complexity, the relaxation pathways and the scalar coupling networks. In addition, the combination of selective {sup 13}C and {sup 2}H enrichment can greatly facilitate the determination of heteronuclear relaxation behavior.

Antisense oligonucleotides targeting translation inhibitory elements in 5' UTRs can selectively increase protein levels.

Science.gov (United States)

Liang, Xue-Hai; Sun, Hong; Shen, Wen; Wang, Shiyu; Yao, Joyee; Migawa, Michael T; Bui, Huynh-Hoa; Damle, Sagar S; Riney, Stan; Graham, Mark J; Crooke, Rosanne M; Crooke, Stanley T

2017-09-19

A variety of diseases are caused by deficiencies in amounts or activity of key proteins. An approach that increases the amount of a specific protein might be of therapeutic benefit. We reasoned that translation could be specifically enhanced using trans-acting agents that counter the function of negative regulatory elements present in the 5' UTRs of some mRNAs. We recently showed that translation can be enhanced by antisense oligonucleotides (ASOs) that target upstream open reading frames. Here we report the amount of a protein can also be selectively increased using ASOs designed to hybridize to other translation inhibitory elements in 5' UTRs. Levels of human RNASEH1, LDLR, and ACP1 and of mouse ACP1 and ARF1 were increased up to 2.7-fold in different cell types and species upon treatment with chemically modified ASOs targeting 5' UTR inhibitory regions in the mRNAs encoding these proteins. The activities of ASOs in enhancing translation were sequence and position dependent and required helicase activity. The ASOs appear to improve the recruitment of translation initiation factors to the target mRNA. Importantly, ASOs targeting ACP1 mRNA significantly increased the level of ACP1 protein in mice, suggesting that this approach has therapeutic and research potentials. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index.

Directory of Open Access Journals (Sweden)

Ping Wang

2011-02-01

Full Text Available Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI diet improved weight maintenance.To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study.Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured.Angiotensin I converting enzyme (ACE was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%.A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss.ClinicalTrials.gov NCT00390637.

Intake of total protein, plant protein and animal protein in relation to blood pressure : a meta-analysis of observational and intervention studies

NARCIS (Netherlands)

Tielemans, S. M. A. J.; Altorf-van der Kuil, W.; Engberink, M. F.; Brink, E. J.; van Baak, M. A.; Bakker, S. J. L.; Geleijnse, J. M.

There is growing evidence from epidemiological studies that dietary protein may beneficially influence blood pressure (BP), but findings are inconclusive. We performed a meta-analysis of 29 observational studies and randomized controlled trials (RCTs) of dietary protein and types of protein in

Intake of total protein, plant protein and animal protein in relation to blood pressure: a meta-analysis of observatinoal and intervention studies

NARCIS (Netherlands)

Tielemans, S.M.A.J.; Altorf-van der Kuil, W.; Engberink, M.F.; Brink, E.J.; Baak, van M.A.; Bakker, S.J.; Geleijnse, J.M.

2013-01-01

There is growing evidence from epidemiological studies that dietary protein may beneficially influence blood pressure (BP), but findings are inconclusive. We performed a meta-analysis of 29 observational studies and randomized controlled trials (RCTs) of dietary protein and types of protein in

Selective oropharyngeal decontamination versus selective digestive decontamination in critically ill patients: a meta-analysis of randomized controlled trials

Directory of Open Access Journals (Sweden)

Zhao D

2015-07-01

Full Text Available Di Zhao,1,* Jian Song,2,* Xuan Gao,3 Fei Gao,4 Yupeng Wu,2 Yingying Lu,5 Kai Hou1 1Department of Neurosurgery, The First Hospital of Hebei Medical University, 2Department of Neurosurgery, 3Department of Neurology, The Second Hospital of Hebei Medical University, 4Hebei Provincial Procurement Centers for Medical Drugs and Devices, 5Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang People’s Republic of China *These authors contributed equally to this work Background: Selective digestive decontamination (SDD and selective oropharyngeal decontamination (SOD are associated with reduced mortality and infection rates among patients in intensive care units (ICUs; however, whether SOD has a superior effect than SDD remains uncertain. Hence, we conducted a meta-analysis of randomized controlled trials (RCTs to compare SOD with SDD in terms of clinical outcomes and antimicrobial resistance rates in patients who were critically ill. Methods: RCTs published in PubMed, Embase, and Web of Science were systematically reviewed to compare the effects of SOD and SDD in patients who were critically ill. Outcomes included day-28 mortality, length of ICU stay, length of hospital stay, duration of mechanical ventilation, ICU-acquired bacteremia, and prevalence of antibiotic-resistant Gram-negative bacteria. Results were expressed as risk ratio (RR with 95% confidence intervals (CIs, and weighted mean differences (WMDs with 95% CIs. Pooled estimates were performed using a fixed-effects model or random-effects model, depending on the heterogeneity among studies. Results: A total of four RCTs involving 23,822 patients met the inclusion criteria and were included in this meta-analysis. Among patients whose admitting specialty was surgery, cardiothoracic surgery (57.3% and neurosurgery (29.7% were the two main types of surgery being performed. Pooled results showed that SOD had similar effects as SDD in day-28 mortality (RR =1

Cardiac protein expression patterns are associated with distinct inborn exercise capacity in non-selectively bred rats

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L.P. Ribeiro

2018-01-01

Full Text Available In the present study, we successfully demonstrated for the first time the existence of cardiac proteomic differences between non-selectively bred rats with distinct intrinsic exercise capacities. A proteomic approach based on two-dimensional gel electrophoresis coupled to mass spectrometry was used to study the left ventricle (LV tissue proteome of rats with distinct intrinsic exercise capacity. Low running performance (LRP and high running performance (HRP rats were categorized by a treadmill exercise test, according to distance run to exhaustion. The running capacity of HRPs was 3.5-fold greater than LRPs. Protein profiling revealed 29 differences between HRP and LRP rats (15 proteins were identified. We detected alterations in components involved in metabolism, antioxidant and stress response, microfibrillar and cytoskeletal proteins. Contractile proteins were upregulated in the LVs of HRP rats (α-myosin heavy chain-6, myosin light chain-1 and creatine kinase, whereas the LVs of LRP rats exhibited upregulation in proteins associated with stress response (aldehyde dehydrogenase 2, α-crystallin B chain and HSPβ-2. In addition, the cytoskeletal proteins desmin and α-actin were upregulated in LRPs. Taken together, our results suggest that the increased contractile protein levels in HRP rats partly accounted for their improved exercise capacity, and that proteins considered risk factors to the development of cardiovascular disease were expressed in higher amounts in LRP animals.

Peptidomics of Peptic Digest of Selected Potato Tuber Proteins: Post-Translational Modifications and Limited Cleavage Specificity.

Science.gov (United States)

C K Rajendran, Subin R; Mason, Beth; Udenigwe, Chibuike C

2016-03-23

Bioinformatic tools are useful in predicting bioactive peptides from food proteins. This study was focused on using bioinformatics and peptidomics to evaluate the specificity of peptide release and post-translational modifications (PTMs) in a peptic digest of potato protein isolate. Peptides in the protein hydrolysate were identified by LC-MS/MS and subsequently aligned to their parent potato tuber proteins. Five major proteins were selected for further analysis, namely, lipoxygenase, α-1,4-glucan phosphorylase, annexin, patatin, and polyubiquitin, based on protein coverage, abundance, confidence levels, and function. Comparison of the in silico peptide profile generated with ExPASy PeptideCutter and experimental peptidomics data revealed several differences. The experimental peptic cleavage sites were found to vary in number and specificity from PeptideCutter predictions. Average peptide chain length was also found to be higher than predicted with hexapeptides as the smallest detected peptides. Moreover, PTMs, particularly Met oxidation and Glu/Asp deamidation, were observed in some peptides, and these were unaccounted for during in silico analysis. PTMs can be formed during aging of potato tubers, or as a result of processing conditions during protein isolation and hydrolysis. The findings provide insights on the limitations of current bioinformatics tools for predicting bioactive peptide release from proteins, and on the existence of structural modifications that can alter the peptide bioactivity and functionality.

Strategyproof Peer Selection using Randomization, Partitioning, and Apportionment

OpenAIRE

Aziz, Haris; Lev, Omer; Mattei, Nicholas; Rosenschein, Jeffrey S.; Walsh, Toby

2016-01-01

Peer review, evaluation, and selection is a fundamental aspect of modern science. Funding bodies the world over employ experts to review and select the best proposals of those submitted for funding. The problem of peer selection, however, is much more general: a professional society may want to give a subset of its members awards based on the opinions of all members; an instructor for a MOOC or online course may want to crowdsource grading; or a marketing company may select ideas from group b...

Effect of a Protein Supplement on the Gut Microbiota of Endurance Athletes: A Randomized, Controlled, Double-Blind Pilot Study

Directory of Open Access Journals (Sweden)

Diego Moreno-Pérez

2018-03-01

Full Text Available Nutritional supplements are popular among athletes to improve performance and physical recovery. Protein supplements fulfill this function by improving performance and increasing muscle mass; however, their effect on other organs or systems is less well known. Diet alterations can induce gut microbiota imbalance, with beneficial or deleterious consequences for the host. To test this, we performed a randomized pilot study in cross-country runners whose diets were complemented with a protein supplement (whey isolate and beef hydrolysate (n = 12 or maltodextrin (control (n = 12 for 10 weeks. Microbiota, water content, pH, ammonia, and short-chain fatty acids (SCFAs were analyzed in fecal samples, whereas malondialdehyde levels (oxidative stress marker were determined in plasma and urine. Fecal pH, water content, ammonia, and SCFA concentrations did not change, indicating that protein supplementation did not increase the presence of these fermentation-derived metabolites. Similarly, it had no impact on plasma or urine malondialdehyde levels; however, it increased the abundance of the Bacteroidetes phylum and decreased the presence of health-related taxa including Roseburia, Blautia, and Bifidobacterium longum. Thus, long-term protein supplementation may have a negative impact on gut microbiota. Further research is needed to establish the impact of protein supplements on gut microbiota.

Analysis of phage Mu DNA transposition by whole-genome Escherichia coli tiling arrays reveals a complex relationship to distribution of target selection protein B, transcription and chromosome architectural elements.

Science.gov (United States)

Ge, Jun; Lou, Zheng; Cui, Hong; Shang, Lei; Harshey, Rasika M

2011-09-01

Of all known transposable elements, phage Mu exhibits the highest transposition efficiency and the lowest target specificity. In vitro, MuB protein is responsible for target choice. In this work, we provide a comprehensive assessment of the genome-wide distribution of MuB and its relationship to Mu target selection using high-resolution Escherichia coli tiling DNA arrays. We have also assessed how MuB binding and Mu transposition are influenced by chromosome-organizing elements such as AT-rich DNA signatures, or the binding of the nucleoid-associated protein Fis, or processes such as transcription. The results confirm and extend previous biochemical and lower resolution in vivo data. Despite the generally random nature of Mu transposition and MuB binding, there were hot and cold insertion sites and MuB binding sites in the genome, and differences between the hottest and coldest sites were large. The new data also suggest that MuB distribution and subsequent Mu integration is responsive to DNA sequences that contribute to the structural organization of the chromosome.

Intracellular delivery of cell-penetrating peptide-transcriptional factor fusion protein and its role in selective osteogenesis

Science.gov (United States)

Suh, Jin Sook; Lee, Jue Yeon; Choi, Yoon Jung; You, Hyung Keun; Hong, Seong-Doo; Chung, Chong Pyoung; Park, Yoon Jeong

2014-01-01

Protein-transduction technology has been attempted to deliver macromolecular materials, including protein, nucleic acids, and polymeric drugs, for either diagnosis or therapeutic purposes. Herein, fusion protein composed of an arginine-rich cell-penetrating peptide, termed low-molecular-weight protamine (LMWP), and a transcriptional coactivator with a PDZ-binding motif (TAZ) protein was prepared and applied in combination with biomaterials to increase bone-forming capacity. TAZ has been recently identified as a specific osteogenic stimulating transcriptional coactivator in human mesenchymal stem cell (hMSC) differentiation, while simultaneously blocking adipogenic differentiation. However, TAZ by itself cannot penetrate the cells, and thus needs a transfection tool for translocalization. The LMWP-TAZ fusion proteins were efficiently translocalized into the cytosol of hMSCs. The hMSCs treated with cell-penetrating LMWP-TAZ exhibited increased expression of osteoblastic genes and protein, producing significantly higher quantities of mineralized matrix compared to free TAZ. In contrast, adipogenic differentiation of the hMSCs was blocked by treatment of LMWP-TAZ fusion protein, as reflected by reduced marker-protein expression, adipocyte fatty acid-binding protein 2, and peroxisome proliferator-activated receptor-γ messenger ribonucleic acid levels. LMWP-TAZ was applied in alginate gel for the purpose of localization and controlled release. The LMWP-TAZ fusion protein-loaded alginate gel matrix significantly increased bone formation in rabbit calvarial defects compared with alginate gel matrix mixed with free TAZ protein. The protein transduction of TAZ fused with cell-penetrating LMWP peptide was able selectively to stimulate osteogenesis in vitro and in vivo. Taken together, this fusion protein-transduction technology for osteogenic protein can thus be applied in combination with biomaterials for tissue regeneration and controlled release for tissue

Natural selection in avian protein-coding genes expressed in brain.

Science.gov (United States)

Axelsson, Erik; Hultin-Rosenberg, Lina; Brandström, Mikael; Zwahlén, Martin; Clayton, David F; Ellegren, Hans

2008-06-01

The evolution of birds from theropod dinosaurs took place approximately 150 million years ago, and was associated with a number of specific adaptations that are still evident among extant birds, including feathers, song and extravagant secondary sexual characteristics. Knowledge about the molecular evolutionary background to such adaptations is lacking. Here, we analyse the evolution of > 5000 protein-coding gene sequences expressed in zebra finch brain by comparison to orthologous sequences in chicken. Mean d(N)/d(S) is 0.085 and genes with their maximal expression in the eye and central nervous system have the lowest mean d(N)/d(S) value, while those expressed in digestive and reproductive tissues exhibit the highest. We find that fast-evolving genes (those which have higher than expected rate of nonsynonymous substitution, indicative of adaptive evolution) are enriched for biological functions such as fertilization, muscle contraction, defence response, response to stress, wounding and endogenous stimulus, and cell death. After alignment to mammalian orthologues, we identify a catalogue of 228 genes that show a significantly higher rate of protein evolution in the two bird lineages than in mammals. These accelerated bird genes, representing candidates for avian-specific adaptations, include genes implicated in vocal learning and other cognitive processes. Moreover, colouration genes evolve faster in birds than in mammals, which may have been driven by sexual selection for extravagant plumage characteristics.

Effect of white striping myopathy on breast muscle (Pectoralis major) protein turnover and gene expression in broilers.

Science.gov (United States)

Vignale, Karen; Caldas, Justina V; England, Judy A; Boonsinchai, Nirun; Magnuson, Andrew; Pollock, Erik D; Dridi, Sami; Owens, Casey M; Coon, Craig N

2017-04-01

A study was conducted to evaluate the effect of white striping ( ) of broiler breast muscle ( Pectoralis major ) on protein turnover and gene expression of genes related to protein degradation and fatty acid synthesis. A total of 560 day-old male broiler chicks Cobb 500 were allocated in a total of 16 pens, 35 chicks per pen. A completely randomized design was conducted with a 2 × 3 factorial arrangement (2 scores: severe and normal, and 3 breast meat samples sites). At d 60, 20 birds were randomly selected, euthanized, and scored for white striping. Scoring was either normal ( , no WS) or severe ( ). Also, the same day, 17 birds (16 infused, one control) were randomly selected and infused with a solution of 15 N Phen 40% ( ). Breast muscle tissue was taken for gene expression analysis of the following genes: MuRF1, atrogin-1, IGF-1, insulin receptor ( ), fatty acid synthetase, and acetyl CoA carboxylase ( ). Each bird was humanely euthanized after 10 minutes of infusion and scored for WS (NORM or SEV). Samples of the breast muscle ( Pectoralis major ) were taken at different layers (3 samples per bird: ventral, medial, dorsal), along with a sample of excreta for 3-methylhistidine analysis. Out of the 16 breast samples taken, only 10 were selected for analysis based on the WS score (5 NORM and 5 SEV). No significant differences ( P > 0.05) were found in fractional synthesis rate ( ) between SEV WS, NORM and sample sites for breast meat. However, fractional breakdown rate ( ) was significantly higher in birds with SEV WS compared to NORM (8.2 and 4.28, respectively, P white striping are degrading more muscular protein and mobilizing more fat. © 2016 Poultry Science Association Inc.

Arbitrary protein−protein docking targets biologically relevant interfaces

International Nuclear Information System (INIS)

Martin, Juliette; Lavery, Richard

2012-01-01

Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding

Arbitrary protein−protein docking targets biologically relevant interfaces

Directory of Open Access Journals (Sweden)

Martin Juliette

2012-05-01

Full Text Available Abstract Background Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. Results In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking

Effect of beta-hydroxy-beta-methylbutyrate (HMB) on protein metabolism in whole body and in selected tissues.

Science.gov (United States)

Holecek, M; Muthny, T; Kovarik, M; Sispera, L

2009-01-01

Beta-hydroxy-beta-methylbutyrate (HMB) is a leucine metabolite with protein anabolic effect. The aim of the study was to examine the role of exogenous HMB on leucine and protein metabolism in whole body and selected tissues. Rats were administered by HMB (0.1 g/kg b.w.) or by saline. The parameters of whole-body protein metabolism were evaluated 24 h later using L-[1-14C]leucine and L-[3,4,5-3H]phenylalanine. Changes in proteasome dependent proteolysis and protein synthesis were determined according the "chymotrypsin-like" enzyme activity and labeled leucine and phenylalanine incorporation into the protein. A decrease in leucine clearance and whole-body protein turnover (i.e., a decrease in whole-body proteolysis and protein synthesis) was observed in HMB treated rats. Proteasome-dependent proteolysis decreased significantly in skeletal muscle, changes in heart, liver, jejunum, colon, kidney, and spleen were insignificant. Decrease in protein synthesis was observed in the heart, colon, kidney, and spleen, while an increase was observed in the liver. There were no significant changes in leucine oxidation. We conclude that protein anabolic effect of HMB in skeletal muscle is related to inhibition of proteolysis in proteasome. Alterations in protein synthesis in visceral tissues may affect several important functions and the metabolic status of the whole body.

A novel typing method for Streptococcus pneumoniae using selected surface proteins

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Arnau eDomenech

2016-03-01

Full Text Available The diverse pneumococcal diseases are associated with different pneumococcal lineages, or clonal complexes. Nevertheless, intra-clonal genomic variability, which influences pathogenicity, has been reported for surface virulence factors. These factors constitute the communication interface between the pathogen and its host and their corresponding genes are subjected to strong selective pressures affecting functionality and immunogenicity. First, the presence and allelic dispersion of 97 outer protein families were screened in 19 complete pneumococcal genomes. Seventeen families were deemed variable and were then examined in 216 draft genomes. This procedure allowed the generation of binary vectors with 17 positions and the classification of strains into surfotypes. They represent the outer protein subsets with the highest inter-strain discriminative power. A total of 116 non-redundant surfotypes were identified. Those sharing a critical number of common protein features were hierarchically clustered into 18 surfogroups. Most clonal complexes with comparable epidemiological characteristics belonged to the same or similar surfogroups. However, the very large CC156 clonal complex was dispersed over several surfogroups. In order to establish a relationship between surfogroup and pathogenicity, the surfotypes of 95 clinical isolates with different serogroup/serotype combinations were analysed. We found a significant correlation between surfogroup and type of pathogenic behaviour (primary invasive, opportunistic invasive and non-invasive. We conclude that the virulent behaviour of S. pneumoniae is related to the activity of collections of, rather than individual, surface virulence factors. Since surfotypes evolve faster than MLSTs and directly reflect virulence potential, this novel typing protocol is appropriate for the identification of emerging clones.

A simple and reliable approach to docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints

Energy Technology Data Exchange (ETDEWEB)

Tang, Chun; Clore, G. Marius [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)], E-mail: mariusc@intra.niddk.nih.gov

2006-09-15

A simple and reliable approach for docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints (as few as three from a single point) in combination with a novel representation for an attractive potential between mapped interaction surfaces is described. Unambiguous assignments of very sparse intermolecular NOEs are obtained using a reverse labeling strategy in which one the components is fully deuterated with the exception of selective protonation of the {delta}-methyl groups of isoleucine, while the other component is uniformly {sup 13}C-labeled. This labeling strategy can be readily extended to selective protonation of Ala, Leu, Val or Met. The attractive potential is described by a 'reduced' radius of gyration potential applied specifically to a subset of interfacial residues (those with an accessible surface area {>=} 50% in the free proteins) that have been delineated by chemical shift perturbation. Docking is achieved by rigid body minimization on the basis of a target function comprising the sparse NOE distance restraints, a van der Waals repulsion potential and the 'reduced' radius of gyration potential. The method is demonstrated for two protein-protein complexes (EIN-HPr and IIA{sup Glc}-HPr) from the bacterial phosphotransferase system. In both cases, starting from 100 different random orientations of the X-ray structures of the free proteins, 100% convergence is achieved to a single cluster (with near identical atomic positions) with an overall backbone accuracy of {approx}2 A. The approach described is not limited to NMR, since interfaces can also be mapped by alanine scanning mutagenesis, and sparse intermolecular distance restraints can be derived from double cycle mutagenesis, cross-linking combined with mass spectrometry, or fluorescence energy transfer.

47 CFR 1.1604 - Post-selection hearings.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 1 2010-10-01 2010-10-01 false Post-selection hearings. 1.1604 Section 1.1604 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1604 Post-selection hearings. (a) Following the random...

The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families.

Science.gov (United States)

Suplatov, Dmitry; Sharapova, Yana; Timonina, Daria; Kopylov, Kirill; Švedas, Vytas

2018-04-01

The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e.g. a substrate or a crystallographic water molecule), and long-range correlations, annotate and rank binding sites on the protein surface by the presence of statistically significant co-evolving positions. The results of the visualCMAT are organized for a convenient visual analysis and can be downloaded to a local computer as a content-rich all-in-one PyMol session file with multiple layers of annotation corresponding to bioinformatic, statistical and structural analyses of the predicted co-evolution, or further studied online using the built-in interactive analysis tools. The online interactivity is implemented in HTML5 and therefore neither plugins nor Java are required. The visualCMAT web-server is integrated with the Mustguseal web-server capable of constructing large structure-guided sequence alignments of protein families and superfamilies using all available information about their structures and sequences in public databases. The visualCMAT web-server can be used to understand the relationship between structure and function in proteins, implemented at selecting hotspots and compensatory mutations for rational design and directed evolution experiments to produce novel enzymes with improved properties, and employed at studying the mechanism of selective ligand's binding and allosteric communication between topologically independent sites in protein structures. The web-server is freely available at https

Automated design evolution of stereochemically randomized protein foldamers

Science.gov (United States)

Ranbhor, Ranjit; Kumar, Anil; Patel, Kirti; Ramakrishnan, Vibin; Durani, Susheel

2018-05-01

Diversification of chain stereochemistry opens up the possibilities of an ‘in principle’ increase in the design space of proteins. This huge increase in the sequence and consequent structural variation is aimed at the generation of smart materials. To diversify protein structure stereochemically, we introduced L- and D-α-amino acids as the design alphabet. With a sequence design algorithm, we explored the usage of specific variables such as chirality and the sequence of this alphabet in independent steps. With molecular dynamics, we folded stereochemically diverse homopolypeptides and evaluated their ‘fitness’ for possible design as protein-like foldamers. We propose a fitness function to prune the most optimal fold among 1000 structures simulated with an automated repetitive simulated annealing molecular dynamics (AR-SAMD) approach. The highly scored poly-leucine fold with sequence lengths of 24 and 30 amino acids were later sequence-optimized using a Dead End Elimination cum Monte Carlo based optimization tool. This paper demonstrates a novel approach for the de novo design of protein-like foldamers.

Moderate carbohydrate, moderate protein weight loss diet reduces cardiovascular disease risk compared to high carbohydrate, low protein diet in obese adults: A randomized clinical trial

Directory of Open Access Journals (Sweden)

Evans Ellen M

2008-11-01

Full Text Available Abstract Background To evaluate the metabolic effects of two weight loss diets differing in macronutrient composition on features of dyslipidemia and post-prandial insulin (INS response to a meal challenge in overweight/obese individuals. Methods This study was a parallel-arm randomized 4 mo weight loss trial. Adults (n = 50, 47 ± 7 y matched on BMI (33.6 ± 0.6 kg/m2, P = 0.79 consumed energy restricted diets (deficit ~500 kcal/d: PRO (1.6 g.kg-1.d-1 protein and -1.d-1 protein and > 220 g/d carbohydrate for 4 mos. Meal challenges of respective diets were utilized for determination of blood lipids and post-prandial INS and glucose response at the beginning and end of the study. Results There was a trend for PRO to lose more weight (-9.1% vs. -7.3%, P = 0.07 with a significant reduction in percent fat mass compared to CHO (-8.7% vs. -5.7%; P = 0.03. PRO also favored reductions in triacylglycerol (-34% vs. -14%; P P = 0.05; however, CHO favored reduction in LDL-C (-7% vs. +2.5%; P P P Conclusion A weight loss diet with moderate carbohydrate, moderate protein results in more favorable changes in body composition, dyslipidemia, and post-prandial INS response compared to a high carbohydrate, low protein diet suggesting an additional benefit beyond weight management to include augmented risk reduction for metabolic disease.

Effect of restricted protein diet supplemented with keto analogues in chronic kidney disease: a systematic review and meta-analysis.

Science.gov (United States)

Jiang, Zheng; Zhang, Xiaoyan; Yang, Lichuan; Li, Zi; Qin, Wei

2016-03-01

To evaluate the efficacy and safety of the restricted protein diet (low or very low protein diet) supplemented with keto analogues in the treatment of chronic kidney disease (CKD). The Cochrane library, PubMed, Embase, CBM and CENTRAL databases were searched and reviewed up to April 2015. Clinical trials were analyzed using RevMan 5.3 software. Seven random control trials, one cross-over trial and one non-randomized concurrent control trial were selected and included in this study according to our inclusion and exclusion criteria. The changes of eGFR, BUN, Scr, albumin, PTH, triglyceride, cholesterol, calcium, phosphorus and nutrition indexes (BMI, lean body mass and mid-arm muscular circumference) before and after treatment were analyzed. The meta-analysis results indicated that, comparing with normal protein diet, low protein diet (LPD) or very low protein diet (vLPD) supplemented with keto analogues (s(v)LPD) could significantly prevent the deterioration of eGFR (P diet supplemented with keto analogues (s(v)LPD) could delay the progression of CKD effectively without causing malnutrition.

Random genetic drift, natural selection, and noise in human cranial evolution.

Science.gov (United States)

Roseman, Charles C

2016-08-01

This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Locating protein-coding sequences under selection for additional, overlapping functions in 29 mammalian genomes

DEFF Research Database (Denmark)

Lin, Michael F; Kheradpour, Pouya; Washietl, Stefan

2011-01-01

conservation compared to typical protein-coding genes—especially at synonymous sites. In this study, we use genome alignments of 29 placental mammals to systematically locate short regions within human ORFs that show conspicuously low estimated rates of synonymous substitution across these species. The 29......-species alignment provides statistical power to locate more than 10,000 such regions with resolution down to nine-codon windows, which are found within more than a quarter of all human protein-coding genes and contain ~2% of their synonymous sites. We collect numerous lines of evidence that the observed...... synonymous constraint in these regions reflects selection on overlapping functional elements including splicing regulatory elements, dual-coding genes, RNA secondary structures, microRNA target sites, and developmental enhancers. Our results show that overlapping functional elements are common in mammalian...

Animal versus plant protein and adult bone health: A systematic review and meta-analysis from the National Osteoporosis Foundation.

Directory of Open Access Journals (Sweden)

Marissa M Shams-White

Full Text Available Protein may have both beneficial and detrimental effects on bone health depending on a variety of factors, including protein source.The aim was to conduct a systematic review and meta-analysis evaluating the effects of animal versus plant protein intake on bone mineral density (BMD, bone mineral content (BMC and select bone biomarkers in healthy adults.Searches across five databases were conducted through 10/31/16 for randomized controlled trials (RCTs and prospective cohort studies in healthy adults that examined the effects of animal versus plant protein intake on 1 total body (TB, total hip (TH, lumbar spine (LS or femoral neck (FN BMD or TB BMC for at least one year, or 2 select bone formation and resorption biomarkers for at least six months. Strength of evidence (SOE was assessed and random effect meta-analyses were performed.Seven RCTs examining animal vs. isoflavone-rich soy (Soy+ protein intake in 633 healthy peri-menopausal (n = 1 and post-menopausal (n = 6 women were included. Overall risk of bias was medium. Limited SOE suggests no significant difference between Soy+ vs. animal protein on LS, TH, FN and TB BMD, TB BMC, and bone turnover markers BSAP and NTX. Meta-analysis results showed on average, the differences between Soy+ and animal protein groups were close to zero and not significant for BMD outcomes (LS: n = 4, pooled net % change: 0.24%, 95% CI: -0.80%, 1.28%; TB: n = 3, -0.24%, 95% CI: -0.81%, 0.33%; FN: n = 3, 0.13%, 95% CI: -0.94%, 1.21%. All meta-analyses had no statistical heterogeneity.These results do not support soy protein consumption as more advantageous than animal protein, or vice versa. Future studies are needed examining the effects of different protein sources in different populations on BMD, BMC, and fracture.

A potential new selection criterion for breeding winter barley optimal protein and amino acid profiles for liquid pig feed

DEFF Research Database (Denmark)

Christensen, Jesper Bjerg; Blaabjerg, Karoline; Poulsen, Hanne Damgaard

The hypothesis is that cereal proteases in liquid feed degrade and convert water insoluble storage protein into water soluble protein, which may improve the digestibility of protein in pigs compared with dry feeding. Protein utilization is increased by matching the amino acid (AAs) content...... of the diet as close as possible to the pigs’ requirement. By improving the availability of isoleucine, leucine, histidine and phenylalanine, which are limiting and commercial unavailable, the amount of crude protein in the pig feed can be reduced, resulting in a decreased excretion of nitrogen. The aim...... of glutamic acid revealed differences between the cultivars and the solubilised protein at all three times. These preliminary results may indicate that improvements of the nitrogen utilization in pigs fed soaked winter barley depends on the choice of cultivar and soaking time, and may serve as a new selection...

Emergence, Retention and Selection: A Trilogy of Origination for Functional De Novo Proteins from Ancestral LncRNAs in Primates.

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Jia-Yu Chen

2015-07-01

Full Text Available While some human-specific protein-coding genes have been proposed to originate from ancestral lncRNAs, the transition process remains poorly understood. Here we identified 64 hominoid-specific de novo genes and report a mechanism for the origination of functional de novo proteins from ancestral lncRNAs with precise splicing structures and specific tissue expression profiles. Whole-genome sequencing of dozens of rhesus macaque animals revealed that these lncRNAs are generally not more selectively constrained than other lncRNA loci. The existence of these newly-originated de novo proteins is also not beyond anticipation under neutral expectation, as they generally have longer theoretical lifespan than their current age, due to their GC-rich sequence property enabling stable ORFs with lower chance of non-sense mutations. Interestingly, although the emergence and retention of these de novo genes are likely driven by neutral forces, population genetics study in 67 human individuals and 82 macaque animals revealed signatures of purifying selection on these genes specifically in human population, indicating a proportion of these newly-originated proteins are already functional in human. We thus propose a mechanism for creation of functional de novo proteins from ancestral lncRNAs during the primate evolution, which may contribute to human-specific genetic novelties by taking advantage of existed genomic contexts.

Proteotoxic stress induces phosphorylation of p62/SQSTM1 by ULK1 to regulate selective autophagic clearance of protein aggregates.

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Junghyun Lim

Full Text Available Disruption of proteostasis, or protein homeostasis, is often associated with aberrant accumulation of misfolded proteins or protein aggregates. Autophagy offers protection to cells by removing toxic protein aggregates and injured organelles in response to proteotoxic stress. However, the exact mechanism whereby autophagy recognizes and degrades misfolded or aggregated proteins has yet to be elucidated. Mounting evidence demonstrates the selectivity of autophagy, which is mediated through autophagy receptor proteins (e.g. p62/SQSTM1 linking autophagy cargos and autophagosomes. Here we report that proteotoxic stress imposed by the proteasome inhibition or expression of polyglutamine expanded huntingtin (polyQ-Htt induces p62 phosphorylation at its ubiquitin-association (UBA domain that regulates its binding to ubiquitinated proteins. We find that autophagy-related kinase ULK1 phosphorylates p62 at a novel phosphorylation site S409 in UBA domain. Interestingly, phosphorylation of p62 by ULK1 does not occur upon nutrient starvation, in spite of its role in canonical autophagy signaling. ULK1 also phosphorylates S405, while S409 phosphorylation critically regulates S405 phosphorylation. We find that S409 phosphorylation destabilizes the UBA dimer interface, and increases binding affinity of p62 to ubiquitin. Furthermore, lack of S409 phosphorylation causes accumulation of p62, aberrant localization of autophagy proteins and inhibition of the clearance of ubiquitinated proteins or polyQ-Htt. Therefore, our data provide mechanistic insights into the regulation of selective autophagy by ULK1 and p62 upon proteotoxic stress. Our study suggests a potential novel drug target in developing autophagy-based therapeutics for the treatment of proteinopathies including Huntington's disease.

Selectable high-yield recombinant protein production in human cells using a GFP/YFP nanobody affinity support.

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Schellenberg, Matthew J; Petrovich, Robert M; Malone, Christine C; Williams, R Scott

2018-03-25

Recombinant protein expression systems that produce high yields of pure proteins and multi-protein complexes are essential to meet the needs of biologists, biochemists, and structural biologists using X-ray crystallography and cryo-electron microscopy. An ideal expression system for recombinant human proteins is cultured human cells where the correct translation and chaperone machinery are present. However, compared to bacterial expression systems, human cell cultures present several technical challenges to their use as an expression system. We developed a method that utilizes a YFP fusion-tag to generate recombinant proteins using suspension-cultured HEK293F cells. YFP is a dual-function tag that enables direct visualization and fluorescence-based selection of high expressing clones for and rapid purification using a high-stringency, high-affinity anti-GFP/YFP nanobody support. We demonstrate the utility of this system by expressing two large human proteins, TOP2α (340 KDa dimer) and a TOP2β catalytic core (260 KDa dimer). This robustly and reproducibly yields >10 mg/L liter of cell culture using transient expression or 2.5 mg/L using stable expression. Published 2018. This article is a US Government work and is in the public domain in the USA.

Detecting consistent patterns of directional adaptation using differential selection codon models.

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Parto, Sahar; Lartillot, Nicolas

2017-06-23

Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

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Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

Chloroform-assisted phenol extraction improving proteome profiling of maize embryos through selective depletion of high-abundance storage proteins.

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Erhui Xiong

Full Text Available The presence of abundant storage proteins in plant embryos greatly impedes seed proteomics analysis. Vicilin (or globulin-1 is the most abundant storage protein in maize embryo. There is a need to deplete the vicilins from maize embryo extracts for enhanced proteomics analysis. We here reported a chloroform-assisted phenol extraction (CAPE method for vicilin depletion. By CAPE, maize embryo proteins were first extracted in an aqueous buffer, denatured by chloroform and then subjected to phenol extraction. We found that CAPE can effectively deplete the vicilins from maize embryo extract, allowing the detection of low-abundance proteins that were masked by vicilins in 2-DE gel. The novelty of CAPE is that it selectively depletes abundant storage proteins from embryo extracts of both monocot (maize and dicot (soybean and pea seeds, whereas other embryo proteins were not depleted. CAPE can significantly improve proteome profiling of embryos and extends the application of chloroform and phenol extraction in plant proteomics. In addition, the rationale behind CAPE depletion of abundant storage proteins was explored.

Biotin-tagged proteins: Reagents for efficient ELISA-based serodiagnosis and phage display-based affinity selection.

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Verma, Vaishali; Kaur, Charanpreet; Grover, Payal; Gupta, Amita; Chaudhary, Vijay K

2018-01-01

The high-affinity interaction between biotin and streptavidin has opened avenues for using recombinant proteins with site-specific biotinylation to achieve efficient and directional immobilization. The site-specific biotinylation of proteins carrying a 15 amino acid long Biotin Acceptor Peptide tag (BAP; also known as AviTag) is effected on a specific lysine either by co-expressing the E. coli BirA enzyme in vivo or by using purified recombinant E. coli BirA enzyme in the presence of ATP and biotin in vitro. In this paper, we have designed a T7 promoter-lac operator-based expression vector for rapid and efficient cloning, and high-level cytosolic expression of proteins carrying a C-terminal BAP tag in E. coli with TEV protease cleavable N-terminal deca-histidine tag, useful for initial purification. Furthermore, a robust three-step purification pipeline integrated with well-optimized protocols for TEV protease-based H10 tag removal, and recombinant BirA enzyme-based site-specific in vitro biotinylation is described to obtain highly pure biotinylated proteins. Most importantly, the paper demonstrates superior sensitivities in indirect ELISA with directional and efficient immobilization of biotin-tagged proteins on streptavidin-coated surfaces in comparison to passive immobilization. The use of biotin-tagged proteins through specific immobilization also allows more efficient selection of binders from a phage-displayed naïve antibody library. In addition, for both these applications, specific immobilization requires much less amount of protein as compared to passive immobilization and can be easily multiplexed. The simplified strategy described here for the production of highly pure biotin-tagged proteins will find use in numerous applications, including those, which may require immobilization of multiple proteins simultaneously on a solid surface.

Pro-HEART - a randomized clinical trial to test the effectiveness of a high protein diet targeting obese individuals with heart failure: rationale, design and baseline characteristics.

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Motie, Marjan; Evangelista, Lorraine S; Horwich, Tamara; Hamilton, Michele; Lombardo, Dawn; Cooper, Dan M; Galassetti, Pietro R; Fonarow, Gregg C

2013-11-01

There is ample research to support the potential benefits of a high protein diet on clinical outcomes in overweight/obese, diabetic subjects. However, nutritional management of overweight/obese individuals with heart failure (HF) and type 2 diabetes mellitus (DM) or metabolic syndrome (MS) is poorly understood and few clinical guidelines related to nutritional approaches exist for this subgroup. This article describes the design, methods, and baseline characteristics of study participants enrolled in Pro-HEART, a randomized clinical trial to determine the short term and long term effects of a high protein diet (30% protein [~110 g/day], 40% carbohydrates [150 g/day], 30% fat [~50 g/day]) versus a standard protein diet (15% protein [~55 g/day], 55% carbohydrates [~200 g/day], 30% fat [~50 g/day]) on body weight and adiposity, cardiac structure and function, functional status, lipid profile, glycemic control, and quality of life. Between August, 2009 and May, 2013, 61 individuals agreed to participate in the study; 52 (85%) - mean age 58.2 ± 9.8 years; 15.4% Blacks; 57.7% Whites; 19.2% Hispanics; 7.7% Asians; 73.1% male; weight 112.0 ± 22.6 kg - were randomized to a 3-month intensive weight management program of either a high protein or standard protein diet; data were collected at baseline, 3 months, and 15 months. This study has the potential to reveal significant details about the role of macronutrients in weight management of overweight/obese individuals with HF and DM or MS. © 2013 Elsevier Inc. All rights reserved.

Proximity Ligation In situ Assay is a Powerful Tool to Monitor Specific ATG Protein Interactions following Autophagy Induction.

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Thierry Gauthier

Full Text Available Macroautophagy is a highly regulated intracellular degradation process which has been extensively studied over the last decade. This pathway has been initially described as a non selective process inducing the degradation of parts of the cytoplasm as well as organelles at random. Nevertheless, over the last few years, new research highlighted the existence of a more selective autophagy pathway specifically recruiting some organelles or aggregates to the autophagosomes in order to induce their degradation. These selective autophagy pathways such as aggrephagy, mitophagy, pexophagy or xenophagy, involve the intervention of a cargo, the material to be degraded, cargo adapters, the molecules allowing the recruitment of the cargo to the autophagosome, and the proteins of the ATG8 family which link the cargo adapters to the autophagosome. One of the main questions which now remain is to develop new techniques and protocols able to discriminate between these different types of induced autophagy. In our work, we studied the possibility to use the P-LISA technique, which has been recently developed to study endogenous in vivo protein interactions, as a new technique to characterize the ATG proteins specifically involved in bulk or selective autophagy. In this manuscript, we indeed demonstrate that this technique allows the study of endogenous ATG protein interactions in cells following autophagy induction, but more interestingly that this technique might be used to characterize the ATG proteins involved in selective autophagy.

Genetic variability and natural selection at the ligand domain of the Duffy binding protein in brazilian Plasmodium vivax populations

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Gil Luiz HS

2010-11-01

Full Text Available Abstract Background Plasmodium vivax malaria is a major public health challenge in Latin America, Asia and Oceania, with 130-435 million clinical cases per year worldwide. Invasion of host blood cells by P. vivax mainly depends on a type I membrane protein called Duffy binding protein (PvDBP. The erythrocyte-binding motif of PvDBP is a 170 amino-acid stretch located in its cysteine-rich region II (PvDBPII, which is the most variable segment of the protein. Methods To test whether diversifying natural selection has shaped the nucleotide diversity of PvDBPII in Brazilian populations, this region was sequenced in 122 isolates from six different geographic areas. A Bayesian method was applied to test for the action of natural selection under a population genetic model that incorporates recombination. The analysis was integrated with a structural model of PvDBPII, and T- and B-cell epitopes were localized on the 3-D structure. Results The results suggest that: (i recombination plays an important role in determining the haplotype structure of PvDBPII, and (ii PvDBPII appears to contain neutrally evolving codons as well as codons evolving under natural selection. Diversifying selection preferentially acts on sites identified as epitopes, particularly on amino acid residues 417, 419, and 424, which show strong linkage disequilibrium. Conclusions This study shows that some polymorphisms of PvDBPII are present near the erythrocyte-binding domain and might serve to elude antibodies that inhibit cell invasion. Therefore, these polymorphisms should be taken into account when designing vaccines aimed at eliciting antibodies to inhibit erythrocyte invasion.

Tailoring of the Nanotexture of Mesoporous Silica Films and their Functionalized Derivatives for Selectively Harvesting Low Molecular Weight Protein

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Hu, Ye; Bouamrani, Ali; Tasciotti, Ennio; Li, Li; Liu, Xuewu; Ferrari, Mauro

2010-01-01

We present a fast, efficient and reliable system based on mesoporous silica chips to specifically fractionate and enrich the low molecular weight proteome. Mesoporous silica thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different templates and concentrations in the precursor solution, various pore size distributions, pore structures and connectivity were obtained and applied for selective recovery of low mass proteins. In combination with mass spectrometry and statistic analysis, we demonstrated the correlation between the nanophase characteristics of the mesoporous silica thin films and the specificity and efficacy of low mass proteome harvesting. In addition, to overcome the limitations of the pre-functionalization method in polymer selection, plasma ashing was used for the first time for the treatment of the mesoporous silica surface prior to chemical modification. Surface charge modifications by different functional groups resulted in a selective capture of the low molecular weight proteins from serum sample. In conclusion our study demonstrates that the ability to tune the physico-chemical properties of mesoporous silica surfaces, for a selective enrichment of the low molecular weight proteome from complex biological fluids, has the potential to promote proteomic biomarker discovery. PMID:20014864

Native whey protein with high levels of leucine results in similar post-exercise muscular anabolic responses as regular whey protein: a randomized controlled trial.

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Hamarsland, Håvard; Nordengen, Anne Lene; Nyvik Aas, Sigve; Holte, Kristin; Garthe, Ina; Paulsen, Gøran; Cotter, Matthew; Børsheim, Elisabet; Benestad, Haakon B; Raastad, Truls

2017-01-01

Protein intake is essential to maximally stimulate muscle protein synthesis, and the amino acid leucine seems to possess a superior effect on muscle protein synthesis compared to other amino acids. Native whey has higher leucine content and thus a potentially greater anabolic effect on muscle than regular whey (WPC-80). This study compared the acute anabolic effects of ingesting 2 × 20 g of native whey protein, WPC-80 or milk protein after a resistance exercise session. A total of 24 young resistance trained men and women took part in this double blind, randomized, partial crossover, controlled study. Participants received either WPC-80 and native whey ( n  = 10), in a crossover design, or milk ( n  = 12). Supplements were ingested immediately (20 g) and two hours after (20 g) a bout of heavy-load lower body resistance exercise. Blood samples and muscle biopsies were collected to measure plasma concentrations of amino acids by gas-chromatography mass spectrometry, muscle phosphorylation of p70S6K, 4E-BP1 and eEF-2 by immunoblotting, and mixed muscle protein synthesis by use of [ 2 H 5 ]phenylalanine-infusion, gas-chromatography mass spectrometry and isotope-ratio mass spectrometry. Being the main comparison, differences between native whey and WPC-80 were analysed by a one-way ANOVA and comparisons between the whey supplements and milk were analysed by a two-way ANOVA. Native whey increased blood leucine concentrations more than WPC-80 and milk ( P  whey ingestion induced a greater phosphorylation of p70S6K than milk 180 min after exercise ( P  = 0.03). Muscle protein synthesis rates increased 1-3 h hours after exercise with WPC-80 (0.119%), and 1-5 h after exercise with native whey (0.112%). Muscle protein synthesis rates were higher 1-5 h after exercise with native whey than with milk (0.112% vs. 0.064, P  = 0.023). Despite higher-magnitude increases in blood leucine concentrations with native whey, it was not superior to WPC-80

Net protein and metabolizable protein requirements for maintenance and growth of early-weaned Dorper crossbred male lambs

Institute of Scientific and Technical Information of China (English)

Tao Ma; Kaidong Deng; Yan Tu; Naifeng Zhang; Bingwen Si; Guishan Xu; Qiyu Diao

2017-01-01

Background:Dorper is an important breed for meat purpose and widely used in the livestock industry of the world.However,the protein requirement of Dorper crossbred has not been investigated.The current paper reports the net protein (NP) and metabolizable protein (MP) requirements of Dorper crossbred ram lambs from 20 to 35 kg BW.Methods:Thirty-five Dorper × thin-tailed Han crossbred lambs weaned at approximately 50 d of age (20.3 ± 2.15 kg of BW) were used.Seven lambs of 25 kg BW were slaughtered as the baseline animals at the start of the trial.An intermediate group of seven randomly selected lambs fed ad libitum was slaughtered at 28.6 kg BW.The remaining 21 lambs were randomly divided into three levels of dry matter intake:ad libitum or 70％ or 40％ of ad libitum intake.Those lambs were slaughtered when the lambs fed ad libitum reached 35 kg BW.Total body N and N retention were measured.Results:The daily NP and MP requirements for maintenance were 1.89 and 4.52 g/kg metabolic shrunk BW (SBW0.75).The partial efficiency of MP utilization for maintenance was 0.42.The NP requirement for growth ranged from 12.1 to 43.5 g/d,for the lambs gaining 100 to 350 g/d,and the partial efficiency of MP utilization for growth was 0.86.Conclusions:The NP and MP requirements for the maintenance and growth of Dorper crossbred male lambs were lower than the recommendations of American and British nutritional systems.

Protein degradation and protection against misfolded or damaged proteins

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Goldberg, Alfred L.

2003-12-01

The ultimate mechanism that cells use to ensure the quality of intracellular proteins is the selective destruction of misfolded or damaged polypeptides. In eukaryotic cells, the large ATP-dependent proteolytic machine, the 26S proteasome, prevents the accumulation of non-functional, potentially toxic proteins. This process is of particular importance in protecting cells against harsh conditions (for example, heat shock or oxidative stress) and in a variety of diseases (for example, cystic fibrosis and the major neurodegenerative diseases). A full understanding of the pathogenesis of the protein-folding diseases will require greater knowledge of how misfolded proteins are recognized and selectively degraded.

Milk protein intake, the metabolic-endocrine response, and growth in infancy: data from a randomized clinical trial.

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Socha, Piotr; Grote, Veit; Gruszfeld, Dariusz; Janas, Roman; Demmelmair, Hans; Closa-Monasterolo, Ricardo; Subías, Joaquín Escribano; Scaglioni, Silvia; Verduci, Elvira; Dain, Elena; Langhendries, Jean-Paul; Perrin, Emmanuel; Koletzko, Berthold

2011-12-01

Protein intake in early infancy has been suggested to be an important risk factor for later obesity, but information on potential mechanisms is very limited. This study examined the influence of protein intake in infancy on serum amino acids, insulin, and the insulin-like growth factor I (IGF-I) axis and its possible relation to growth in the first 2 y of life. In a multicenter European study, 1138 healthy, formula-fed infants were randomly assigned to receive cow-milk-based infant and follow-on formulas with lower protein (LP; 1.77 and 2.2 g protein/100 kcal) or higher protein (HP; 2.9 and 4.4 g protein/100 kcal) contents for the first year. Biochemical variables were measured at age 6 mo in 339 infants receiving LP formula and 333 infants receiving HP formula and in 237 breastfed infants. Essential amino acids, especially branched-chain amino acids, IGF-I, and urinary C-peptide:creatinine ratio, were significantly (P < 0.001) higher in the HP group than in the LP group, whereas IGF-binding protein (IGF-BP) 2 was lower and IGF-BP3 did not differ significantly. The median IGF-I total serum concentration was 48.4 ng/mL (25th, 75th percentile: 27.2, 81.8 ng/mL) in the HP group and 34.7 ng/mL (17.7, 57.5 ng/mL) in the LP group; the urine C-peptide:creatinine ratios were 140.6 ng/mg (80.0, 203.8 ng/mg) and 107.3 ng/mg (65.2, 194.7 ng/mg), respectively. Most essential amino acids, IGF-I, C-peptide, and urea increased significantly in both the LP and HP groups compared with the breastfed group. Total IGF-I was significantly associated with growth until 6 mo but not thereafter. HP intake stimulates the IGF-I axis and insulin release in infancy. IGF-I enhances growth during the first 6 mo of life. This trial was registered at clinicaltrials.gov as NCT00338689.

Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

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Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

2010-01-01

Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

A novel medium for expression of proteins selectively labeled with 15N-amino acids in Spodoptera frugiperda (Sf9) insect cells

International Nuclear Information System (INIS)

Brueggert, Michael; Rehm, Till; Shanker, Sreejesh; Georgescu, Julia; Holak, Tad A.

2003-01-01

Whereas bacterial expression systems are widely used for production of uniformly or selectively 15 N-labeled proteins the usage of the baculovirus expression system for labeling is limited to very few examples in the literature. Here we present the complete formulations of the two insect media, IML406 and 455, for the high-yield production of selectively 15 N-labeled proteins in insect cells. The quantities of 15 N-amino acids utilized in the production of labeled GST were similar in the case of bacterial and viral expression. For the most studied amino acids essential for insect cells the 15 N-HSQC spectra, recorded with GST labeled in insect cells, showed no cross labeling and provided therefore spectra of better quality compared to NMR spectra of GST expressed in E. coli. Also in the case of amino acids not essential for Sf9 cells we were able to label a defined number of amino acid species. Therefore the selective labeling using the baculovirus expression vector system represents a complement or even an alternative to the bacterial expression system. Based on these findings we can provide a first simple overview of the network of the amino acid metabolism in E. coli and insect cells focused on nitrogen. For some amino acids the expression of labeled proteins in insect cells can replace the cell-free protein expression

ORGANIC MATTER AND CRUDE PROTEIN DEGRADATION SYNCHRONY IN DIETS SELECTED BY RANGE GOATS.

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Rafael Ramírez Orduña