Identifying Protein-protein Interaction in Drosophila Adult Heads by Tandem Affinity Purification (TAP)

PubMed Central

Tian, Xiaolin; Zhu, Mingwei; Li, Long; Wu, Chunlai

2013-01-01

Genetic screens conducted using Drosophila melanogaster (fruit fly) have made numerous milestone discoveries in the advance of biological sciences. However, the use of biochemical screens aimed at extending the knowledge gained from genetic analysis was explored only recently. Here we describe a method to purify the protein complex that associates with any protein of interest from adult fly heads. This method takes advantage of the Drosophila GAL4/UAS system to express a bait protein fused with a Tandem Affinity Purification (TAP) tag in fly neurons in vivo, and then implements two rounds of purification using a TAP procedure similar to the one originally established in yeast1 to purify the interacting protein complex. At the end of this procedure, a mixture of multiple protein complexes is obtained whose molecular identities can be determined by mass spectrometry. Validation of the candidate proteins will benefit from the resource and ease of performing loss-of-function studies in flies. Similar approaches can be applied to other fly tissues. We believe that the combination of genetic manipulations and this proteomic approach in the fly model system holds tremendous potential for tackling fundamental problems in the field of neurobiology and beyond. PMID:24335807

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

PubMed Central

Ren, Jun; Zhou, Wei; Wang, Jianxin

2014-01-01

Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes. PMID:25143945

Improvements in the Protein Identifier Cross-Reference service.

PubMed

Wein, Samuel P; Côté, Richard G; Dumousseau, Marine; Reisinger, Florian; Hermjakob, Henning; Vizcaíno, Juan A

2012-07-01

The Protein Identifier Cross-Reference (PICR) service is a tool that allows users to map protein identifiers, protein sequences and gene identifiers across over 100 different source databases. PICR takes input through an interactive website as well as Representational State Transfer (REST) and Simple Object Access Protocol (SOAP) services. It returns the results as HTML pages, XLS and CSV files. It has been in production since 2007 and has been recently enhanced to add new functionality and increase the number of databases it covers. Protein subsequences can be Basic Local Alignment Search Tool (BLAST) against the UniProt Knowledgebase (UniProtKB) to provide an entry point to the standard PICR mapping algorithm. In addition, gene identifiers from UniProtKB and Ensembl can now be submitted as input or mapped to as output from PICR. We have also implemented a 'best-guess' mapping algorithm for UniProt. In this article, we describe the usefulness of PICR, how these changes have been implemented, and the corresponding additions to the web services. Finally, we explain that the number of source databases covered by PICR has increased from the initial 73 to the current 102. New resources include several new species-specific Ensembl databases as well as the Ensembl Genome ones. PICR can be accessed at http://www.ebi.ac.uk/Tools/picr/.

A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data

PubMed Central

Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

2016-01-01

The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew’s Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

An ensemble framework for identifying essential proteins.

PubMed

Zhang, Xue; Xiao, Wangxin; Acencio, Marcio Luis; Lemke, Ney; Wang, Xujing

2016-08-25

Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy, and the number of common predicted essential proteins by different methods is very small. In this paper, an ensemble framework is proposed which integrates gene expression data and protein-protein interaction networks (PINs). It aims to improve the prediction accuracy of basic centrality measures. The idea behind this ensemble framework is that different protein-protein interactions (PPIs) may show different contributions to protein essentiality. Five standard centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and subgraph centrality) are integrated into the ensemble framework respectively. We evaluated the performance of the proposed ensemble framework using yeast PINs and gene expression data. The results show that it can considerably improve the prediction accuracy of the five centrality measures individually. It can also remarkably increase the number of common predicted essential proteins among those predicted by each centrality measure individually and enable each centrality measure to find more low-degree essential proteins. This paper demonstrates that it is valuable to differentiate the contributions of different PPIs for identifying essential proteins based on network topological characteristics. The proposed ensemble framework is a successful paradigm to this end.

Benchmark data for identifying multi-functional types of membrane proteins.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2016-09-01

Identifying membrane proteins and their multi-functional types is an indispensable yet challenging topic in proteomics and bioinformatics. In this article, we provide data that are used for training and testing Mem-ADSVM (Wan et al., 2016. "Mem-ADSVM: a two-layer multi-label predictor for identifying multi-functional types of membrane proteins" [1]), a two-layer multi-label predictor for predicting multi-functional types of membrane proteins.

Identifying Bacterial Immune Evasion Proteins Using Phage Display.

PubMed

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.

A Non-parametric Cutout Index for Robust Evaluation of Identified Proteins*

PubMed Central

Serang, Oliver; Paulo, Joao; Steen, Hanno; Steen, Judith A.

2013-01-01

This paper proposes a novel, automated method for evaluating sets of proteins identified using mass spectrometry. The remaining peptide-spectrum match score distributions of protein sets are compared to an empirical absent peptide-spectrum match score distribution, and a Bayesian non-parametric method reminiscent of the Dirichlet process is presented to accurately perform this comparison. Thus, for a given protein set, the process computes the likelihood that the proteins identified are correctly identified. First, the method is used to evaluate protein sets chosen using different protein-level false discovery rate (FDR) thresholds, assigning each protein set a likelihood. The protein set assigned the highest likelihood is used to choose a non-arbitrary protein-level FDR threshold. Because the method can be used to evaluate any protein identification strategy (and is not limited to mere comparisons of different FDR thresholds), we subsequently use the method to compare and evaluate multiple simple methods for merging peptide evidence over replicate experiments. The general statistical approach can be applied to other types of data (e.g. RNA sequencing) and generalizes to multivariate problems. PMID:23292186

Identifying protein kinase target preferences using mass spectrometry

PubMed Central

Douglass, Jacqueline; Gunaratne, Ruwan; Bradford, Davis; Saeed, Fahad; Hoffert, Jason D.; Steinbach, Peter J.; Pisitkun, Trairak

2012-01-01

A general question in molecular physiology is how to identify candidate protein kinases corresponding to a known or hypothetical phosphorylation site in a protein of interest. It is generally recognized that the amino acid sequence surrounding the phosphorylation site provides information that is relevant to identification of the cognate protein kinase. Here, we present a mass spectrometry-based method for profiling the target specificity of a given protein kinase as well as a computational tool for the calculation and visualization of the target preferences. The mass spectrometry-based method identifies sites phosphorylated in response to in vitro incubation of protein mixtures with active recombinant protein kinases followed by standard phosphoproteomic methodologies. The computational tool, called “PhosphoLogo,” uses an information-theoretic algorithm to calculate position-specific amino acid preferences and anti-preferences from the mass-spectrometry data (http://helixweb.nih.gov/PhosphoLogo/). The method was tested using protein kinase A (catalytic subunit α), revealing the well-known preference for basic amino acids in positions −2 and −3 relative to the phosphorylated amino acid. It also provides evidence for a preference for amino acids with a branched aliphatic side chain in position +1, a finding compatible with known crystal structures of protein kinase A. The method was also employed to profile target preferences and anti-preferences for 15 additional protein kinases with potential roles in regulation of epithelial transport: CK2, p38, AKT1, SGK1, PKCδ, CaMK2δ, DAPK1, MAPKAPK2, PKD3, PIM1, OSR1, STK39/SPAK, GSK3β, Wnk1, and Wnk4. PMID:22723110

Genome-wide RNAi screening identifies protein damage as a regulator of osmoprotective gene expression.

PubMed

Lamitina, Todd; Huang, Chunyi George; Strange, Kevin

2006-08-08

The detection, stabilization, and repair of stress-induced damage are essential requirements for cellular life. All cells respond to osmotic stress-induced water loss with increased expression of genes that mediate accumulation of organic osmolytes, solutes that function as chemical chaperones and restore osmotic homeostasis. The signals and signaling mechanisms that regulate osmoprotective gene expression in animal cells are poorly understood. Here, we show that gpdh-1 and gpdh-2, genes that mediate the accumulation of the organic osmolyte glycerol, are essential for survival of the nematode Caenorhabditis elegans during osmotic stress. Expression of GFP driven by the gpdh-1 promoter (P(gpdh-1)::GFP) is detected only during hypertonic stress but is not induced by other stressors. Using P(gpdh-1)::GFP expression as a phenotype, we screened approximately 16,000 genes by RNAi feeding and identified 122 that cause constitutive activation of gpdh-1 expression and glycerol accumulation. Many of these genes function to regulate protein translation and cotranslational protein folding and to target and degrade denatured proteins, suggesting that the accumulation of misfolded proteins functions as a signal to activate osmoprotective gene expression and organic osmolyte accumulation in animal cells. Consistent with this hypothesis, 73% of these protein-homeostasis genes have been shown to slow age-dependent protein aggregation in C. elegans. Because diverse environmental stressors and numerous disease states result in protein misfolding, mechanisms must exist that discriminate between osmotically induced and other forms of stress-induced protein damage. Our findings provide a foundation for understanding how these damage-selectivity mechanisms function.

Genome-wide RNAi screening identifies protein damage as a regulator of osmoprotective gene expression

PubMed Central

Lamitina, Todd; Huang, Chunyi George; Strange, Kevin

2006-01-01

The detection, stabilization, and repair of stress-induced damage are essential requirements for cellular life. All cells respond to osmotic stress-induced water loss with increased expression of genes that mediate accumulation of organic osmolytes, solutes that function as chemical chaperones and restore osmotic homeostasis. The signals and signaling mechanisms that regulate osmoprotective gene expression in animal cells are poorly understood. Here, we show that gpdh-1 and gpdh-2, genes that mediate the accumulation of the organic osmolyte glycerol, are essential for survival of the nematode Caenorhabditis elegans during osmotic stress. Expression of GFP driven by the gpdh-1 promoter (Pgpdh-1::GFP) is detected only during hypertonic stress but is not induced by other stressors. Using Pgpdh-1::GFP expression as a phenotype, we screened ≈16,000 genes by RNAi feeding and identified 122 that cause constitutive activation of gpdh-1 expression and glycerol accumulation. Many of these genes function to regulate protein translation and cotranslational protein folding and to target and degrade denatured proteins, suggesting that the accumulation of misfolded proteins functions as a signal to activate osmoprotective gene expression and organic osmolyte accumulation in animal cells. Consistent with this hypothesis, 73% of these protein-homeostasis genes have been shown to slow age-dependent protein aggregation in C. elegans. Because diverse environmental stressors and numerous disease states result in protein misfolding, mechanisms must exist that discriminate between osmotically induced and other forms of stress-induced protein damage. Our findings provide a foundation for understanding how these damage-selectivity mechanisms function. PMID:16880390

ORF phage display to identify cellular proteins with different functions.

PubMed

Li, Wei

2012-09-01

Open reading frame (ORF) phage display is a new branch of phage display aimed at improving its efficiency to identify cellular proteins with specific binding or functional activities. Despite the success of phage display with antibody libraries and random peptide libraries, phage display with cDNA libraries of cellular proteins identifies a high percentage of non-ORF clones encoding unnatural short peptides with minimal biological implications. This is mainly because of the uncontrollable reading frames of cellular proteins in conventional cDNA libraries. ORF phage display solves this problem by eliminating non-ORF clones to generate ORF cDNA libraries. Here I summarize the procedures of ORF phage display, discuss the factors influencing its efficiency, present examples of its versatile applications, and highlight evidence of its capability of identifying biologically relevant cellular proteins. ORF phage display coupled with different selection strategies is capable of delineating diverse functions of cellular proteins with unique advantages. Copyright © 2012 Elsevier Inc. All rights reserved.

Profiling Synaptic Proteins Identifies Regulators of Insulin Secretion and Lifespan

PubMed Central

Kaplan, Joshua M.

2008-01-01

Cells are organized into distinct compartments to perform specific tasks with spatial precision. In neurons, presynaptic specializations are biochemically complex subcellular structures dedicated to neurotransmitter secretion. Activity-dependent changes in the abundance of presynaptic proteins are thought to endow synapses with different functional states; however, relatively little is known about the rules that govern changes in the composition of presynaptic terminals. We describe a genetic strategy to systematically analyze protein localization at Caenorhabditis elegans presynaptic specializations. Nine presynaptic proteins were GFP-tagged, allowing visualization of multiple presynaptic structures. Changes in the distribution and abundance of these proteins were quantified in 25 mutants that alter different aspects of neurotransmission. Global analysis of these data identified novel relationships between particular presynaptic components and provides a new method to compare gene functions by identifying shared protein localization phenotypes. Using this strategy, we identified several genes that regulate secretion of insulin-like growth factors (IGFs) and influence lifespan in a manner dependent on insulin/IGF signaling. PMID:19043554

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying Floppy and Rigid Regions in Proteins

NASA Astrophysics Data System (ADS)

Jacobs, D. J.; Thorpe, M. F.; Kuhn, L. A.

1998-03-01

In proteins it is possible to separate hard covalent forces involving bond lengths and bond angles from other weak forces. We model the microstructure of the protein as a generic bar-joint truss framework, where the hard covalent forces and strong hydrogen bonds are regarded as rigid bar constraints. We study the mechanical stability of proteins using FIRST (Floppy Inclusions and Rigid Substructure Topography) based on a recently developed combinatorial constraint counting algorithm (the 3D Pebble Game), which is a generalization of the 2D pebble game (D. J. Jacobs and M. F. Thorpe, ``Generic Rigidity: The Pebble Game'', Phys. Rev. Lett.) 75, 4051-4054 (1995) for the special class of bond-bending networks (D. J. Jacobs, "Generic Rigidity in Three Dimensional Bond-bending Networks", Preprint Aug (1997)). This approach is useful in identifying rigid motifs and flexible linkages in proteins, and thereby determines the essential degrees of freedom. We will show some preliminary results from the FIRST analysis on the myohemerythrin and lyozyme proteins.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

DOE PAGES

Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

2006-01-01

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Proteomic Analysis of the Soybean Symbiosome Identifies New Symbiotic Proteins*

PubMed Central

Clarke, Victoria C.; Loughlin, Patrick C.; Gavrin, Aleksandr; Chen, Chi; Brear, Ella M.; Day, David A.; Smith, Penelope M.C.

2015-01-01

Legumes form a symbiosis with rhizobia in which the plant provides an energy source to the rhizobia bacteria that it uses to fix atmospheric nitrogen. This nitrogen is provided to the legume plant, allowing it to grow without the addition of nitrogen fertilizer. As part of the symbiosis, the bacteria in the infected cells of a new root organ, the nodule, are surrounded by a plant-derived membrane, the symbiosome membrane, which becomes the interface between the symbionts. Fractions containing the symbiosome membrane (SM) and material from the lumen of the symbiosome (peribacteroid space or PBS) were isolated from soybean root nodules and analyzed using nongel proteomic techniques. Bicarbonate stripping and chloroform-methanol extraction of isolated SM were used to reduce complexity of the samples and enrich for hydrophobic integral membrane proteins. One hundred and ninety-seven proteins were identified as components of the SM, with an additional fifteen proteins identified from peripheral membrane and PBS protein fractions. Proteins involved in a range of cellular processes such as metabolism, protein folding and degradation, membrane trafficking, and solute transport were identified. These included a number of proteins previously localized to the SM, such as aquaglyceroporin nodulin 26, sulfate transporters, remorin, and Rab7 homologs. Among the proteome were a number of putative transporters for compounds such as sulfate, calcium, hydrogen ions, peptide/dicarboxylate, and nitrate, as well as transporters for which the substrate is not easy to predict. Analysis of the promoter activity for six genes encoding putative SM proteins showed nodule specific expression, with five showing expression only in infected cells. Localization of two proteins was confirmed using GFP-fusion experiments. The data have been deposited to the ProteomeXchange with identifier PXD001132. This proteome will provide a rich resource for the study of the legume-rhizobium symbiosis. PMID

Identifying cooperative transcriptional regulations using protein–protein interactions

PubMed Central

Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

2005-01-01

Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

Exploiting genomic data to identify proteins involved in abalone reproduction.

PubMed

Mendoza-Porras, Omar; Botwright, Natasha A; McWilliam, Sean M; Cook, Mathew T; Harris, James O; Wijffels, Gene; Colgrave, Michelle L

2014-08-28

Aside from their critical role in reproduction, abalone gonads serve as an indicator of sexual maturity and energy balance, two key considerations for effective abalone culture. Temperate abalone farmers face issues with tank restocking with highly marketable abalone owing to inefficient spawning induction methods. The identification of key proteins in sexually mature abalone will serve as the foundation for a greater understanding of reproductive biology. Addressing this knowledge gap is the first step towards improving abalone aquaculture methods. Proteomic profiling of female and male gonads of greenlip abalone, Haliotis laevigata, was undertaken using liquid chromatography-mass spectrometry. Owing to the incomplete nature of abalone protein databases, in addition to searching against two publicly available databases, a custom database comprising genomic data was used. Overall, 162 and 110 proteins were identified in females and males respectively with 40 proteins common to both sexes. For proteins involved in sexual maturation, sperm and egg structure, motility, acrosomal reaction and fertilization, 23 were identified only in females, 18 only in males and 6 were common. Gene ontology analysis revealed clear differences between the female and male protein profiles reflecting a higher rate of protein synthesis in the ovary and higher metabolic activity in the testis. A comprehensive mass spectrometry-based analysis was performed to profile the abalone gonad proteome providing the foundation for future studies of reproduction in abalone. Key proteins involved in both reproduction and energy balance were identified. Genomic resources were utilised to build a database of molluscan proteins yielding >60% more protein identifications than in a standard workflow employing public protein databases. Copyright © 2014 Elsevier B.V. All rights reserved.

Playing biology's name game: identifying protein names in scientific text.

PubMed

Hanisch, Daniel; Fluck, Juliane; Mevissen, Heinz-Theodor; Zimmer, Ralf

2003-01-01

A growing body of work is devoted to the extraction of protein or gene interaction information from the scientific literature. Yet, the basis for most extraction algorithms, i.e. the specific and sensitive recognition of protein and gene names and their numerous synonyms, has not been adequately addressed. Here we describe the construction of a comprehensive general purpose name dictionary and an accompanying automatic curation procedure based on a simple token model of protein names. We designed an efficient search algorithm to analyze all abstracts in MEDLINE in a reasonable amount of time on standard computers. The parameters of our method are optimized using machine learning techniques. Used in conjunction, these ingredients lead to good search performance. A supplementary web page is available at http://cartan.gmd.de/ProMiner/.

Past Strategies and Future Directions for Identifying AMP-Activated Protein Kinase (AMPK) Modulators

PubMed Central

Sinnett, Sarah E.; Brenman, Jay E.

2014-01-01

AMP-activated protein kinase (AMPK) is a promising therapeutic target for cancer, type II diabetes, and other illnesses characterized by abnormal energy utilization. During the last decade, numerous labs have published a range of methods for identifying novel AMPK modulators. The current understanding of AMPK structure and regulation, however, has propelled a paradigm shift in which many researchers now consider ADP to be an additional regulatory nucleotide of AMPK. How can the AMPK community apply this new understanding of AMPK signaling to translational research? Recent insights into AMPK structure, regulation, and holoenzyme-sensitive signaling may provide the hindsight needed to clearly evaluate the strengths and weaknesses of past AMPK drug discovery efforts. Improving future strategies for AMPK drug discovery will require pairing the current understanding of AMPK signaling with improved experimental designs. PMID:24583089

Gene Unprediction with Spurio: A tool to identify spurious protein sequences.

PubMed

Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

2018-01-01

We now have access to the sequences of tens of millions of proteins. These protein sequences are essential for modern molecular biology and computational biology. The vast majority of protein sequences are derived from gene prediction tools and have no experimental supporting evidence for their translation.  Despite the increasing accuracy of gene prediction tools there likely exists a large number of spurious protein predictions in the sequence databases.  We have developed the Spurio tool to help identify spurious protein predictions in prokaryotes.  Spurio searches the query protein sequence against a prokaryotic nucleotide database using tblastn and identifies homologous sequences. The tblastn matches are used to score the query sequence's likelihood of being a spurious protein prediction using a Gaussian process model. The most informative feature is the appearance of stop codons within the presumed translation of homologous DNA sequences. Benchmarking shows that the Spurio tool is able to distinguish spurious from true proteins. However, transposon proteins are prone to be predicted as spurious because of the frequency of degraded homologs found in the DNA sequence databases. Our initial experiments suggest that less than 1% of the proteins in the UniProtKB sequence database are likely to be spurious and that Spurio is able to identify over 60 times more spurious proteins than the AntiFam resource. The Spurio software and source code is available under an MIT license at the following URL: https://bitbucket.org/bateman-group/spurio.

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

New proteins identified in epididymal fluid from the platypus (Ornithorhynchus anatinus).

PubMed

Dacheux, Jean-Louis; Dacheux, Francoise; Labas, Valerie; Ecroyd, Heath; Nixon, Brett; Jones, Russell C

2009-01-01

The platypus epididymal proteome is being studied because epididymal proteins are essential for male fertility in mammals and it is considered that knowledge of the epididymal proteome in an early mammal would be informative in assessing the convergence and divergence of proteins that are important in the function of the mammalian epididymis. Few of the epididymal proteins that have been identified in eutherian mammals were found in platypus caudal epididymal fluid, and the major epididymal proteins in the platypus (PXN-FBPL, SPARC and E-OR20) have never been identified in the epididymis of any other mammal.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

NASA Astrophysics Data System (ADS)

Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Proteomics-based approach identified differentially expressed proteins with potential roles in endometrial carcinoma.

PubMed

Li, Zhengyu; Min, Wenjiao; Huang, Canhua; Bai, Shujun; Tang, Minghai; Zhao, Xia

2010-01-01

We used proteomic approaches to identify altered expressed proteins in endometrial carcinoma, with the aim of discovering potential biomarkers or therapeutic targets for endometrial carcinoma. The global proteins extracted from endometrial carcinoma and normal endometrial tissues were separated by 2-dimensional electrophoresis and analyzed with PDQuest (Bio-Rad, Hercules, Calif) software. The differentially expressed spots were identified by mass spectrometry and searched against NCBInr protein database. Those proteins with potential roles were confirmed by Western blotting and immunohistochemical assays. Ninety-nine proteins were identified by mass spectrometry, and a cluster diagram analysis indicated that these proteins were involved in metabolism, cell transformation, protein folding, translation and modification, proliferation and apoptosis, signal transduction, cytoskeleton, and so on. In confirmatory immunoblotting and immunohistochemical analyses, overexpressions of epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A were also observed in endometrial carcinoma tissues, which were consistent with the proteomic results. Our results suggested that these identified proteins, including epidermal fatty acid-binding protein, calcyphosine, and cyclophilin A, might be of potential values in the studies of endometrial carcinogenesis or investigations of diagnostic biomarkers or treatment targets for endometrial carcinoma.

Identifying protein domains by global analysis of soluble fragment data.

PubMed

Bulloch, Esther M M; Kingston, Richard L

2014-11-15

The production and analysis of individual structural domains is a common strategy for studying large or complex proteins, which may be experimentally intractable in their full-length form. However, identifying domain boundaries is challenging if there is little structural information concerning the protein target. One experimental procedure for mapping domains is to screen a library of random protein fragments for solubility, since truncation of a domain will typically expose hydrophobic groups, leading to poor fragment solubility. We have coupled fragment solubility screening with global data analysis to develop an effective method for identifying structural domains within a protein. A gene fragment library is generated using mechanical shearing, or by uracil doping of the gene and a uracil-specific enzymatic digest. A split green fluorescent protein (GFP) assay is used to screen the corresponding protein fragments for solubility when expressed in Escherichia coli. The soluble fragment data are then analyzed using two complementary approaches. Fragmentation "hotspots" indicate possible interdomain regions. Clustering algorithms are used to group related fragments, and concomitantly predict domain location. The effectiveness of this Domain Seeking procedure is demonstrated by application to the well-characterized human protein p85α. Copyright © 2014 Elsevier Inc. All rights reserved.

Carboxylator: incorporating solvent-accessible surface area for identifying protein carboxylation sites

NASA Astrophysics Data System (ADS)

Lu, Cheng-Tsung; Chen, Shu-An; Bretaña, Neil Arvin; Cheng, Tzu-Hsiu; Lee, Tzong-Yi

2011-10-01

In proteins, glutamate (Glu) residues are transformed into γ-carboxyglutamate (Gla) residues in a process called carboxylation. The process of protein carboxylation catalyzed by γ-glutamyl carboxylase is deemed to be important due to its involvement in biological processes such as blood clotting cascade and bone growth. There is an increasing interest within the scientific community to identify protein carboxylation sites. However, experimental identification of carboxylation sites via mass spectrometry-based methods is observed to be expensive, time-consuming, and labor-intensive. Thus, we were motivated to design a computational method for identifying protein carboxylation sites. This work aims to investigate the protein carboxylation by considering the composition of amino acids that surround modification sites. With the implication of a modified residue prefers to be accessible on the surface of a protein, the solvent-accessible surface area (ASA) around carboxylation sites is also investigated. Radial basis function network is then employed to build a predictive model using various features for identifying carboxylation sites. Based on a five-fold cross-validation evaluation, a predictive model trained using the combined features of amino acid sequence (AA20D), amino acid composition, and ASA, yields the highest accuracy at 0.874. Furthermore, an independent test done involving data not included in the cross-validation process indicates that in silico identification is a feasible means of preliminary analysis. Additionally, the predictive method presented in this work is implemented as Carboxylator (http://csb.cse.yzu.edu.tw/Carboxylator/), a web-based tool for identifying carboxylated proteins with modification sites in order to help users in investigating γ-glutamyl carboxylation.

Guaifenesin stone matrix proteomics: a protocol for identifying proteins critical to stone formation.

PubMed

Kolbach-Mandel, A M; Mandel, N S; Cohen, S R; Kleinman, J G; Ahmed, F; Mandel, I C; Wesson, J A

2017-04-01

Drug-related kidney stones are a diagnostic problem, since they contain a large matrix (protein) fraction and are frequently incorrectly identified as matrix stones. A urine proteomics study patient produced a guaifenesin stone during her participation, allowing us to both correctly diagnose her disease and identify proteins critical to this drug stone-forming process. The patient provided three random midday urine samples for proteomics studies; one of which contained stone-like sediment with two distinct fractions. These solids were characterized with optical microscopy and Fourier transform infrared spectroscopy. Immunoblotting and quantitative mass spectrometry were used to quantitatively identify the proteins in urine and stone matrix. Infrared spectroscopy showed that the sediment was 60 % protein and 40 % guaifenesin and its metabolite guaiacol. Of the 156 distinct proteins identified in the proteomic studies, 49 were identified in the two stone-components with approximately 50 % of those proteins also found in this patient's urine. Many proteins observed in this drug-related stone have also been reported in proteomic matrix studies of uric acid and calcium containing stones. More importantly, nine proteins were highly enriched and highly abundant in the stone matrix and 8 were reciprocally depleted in urine, suggesting a critical role for these proteins in guaifenesin stone formation. Accurate stone analysis is critical to proper diagnosis and treatment of kidney stones. Many matrix proteins were common to all stone types, but likely not related to disease mechanism. This protocol defined a small set of proteins that were likely critical to guaifenesin stone formation based on their high enrichment and high abundance in stone matrix, and it should be applied to all stone types.

Identifying protein phosphorylation sites with kinase substrate specificity on human viruses.

PubMed

Bretaña, Neil Arvin; Lu, Cheng-Tsung; Chiang, Chiu-Yun; Su, Min-Gang; Huang, Kai-Yao; Lee, Tzong-Yi; Weng, Shun-Long

2012-01-01

Viruses infect humans and progress inside the body leading to various diseases and complications. The phosphorylation of viral proteins catalyzed by host kinases plays crucial regulatory roles in enhancing replication and inhibition of normal host-cell functions. Due to its biological importance, there is a desire to identify the protein phosphorylation sites on human viruses. However, the use of mass spectrometry-based experiments is proven to be expensive and labor-intensive. Furthermore, previous studies which have identified phosphorylation sites in human viruses do not include the investigation of the responsible kinases. Thus, we are motivated to propose a new method to identify protein phosphorylation sites with its kinase substrate specificity on human viruses. The experimentally verified phosphorylation data were extracted from virPTM--a database containing 301 experimentally verified phosphorylation data on 104 human kinase-phosphorylated virus proteins. In an attempt to investigate kinase substrate specificities in viral protein phosphorylation sites, maximal dependence decomposition (MDD) is employed to cluster a large set of phosphorylation data into subgroups containing significantly conserved motifs. The experimental human phosphorylation sites are collected from Phospho.ELM, grouped according to its kinase annotation, and compared with the virus MDD clusters. This investigation identifies human kinases such as CK2, PKB, CDK, and MAPK as potential kinases for catalyzing virus protein substrates as confirmed by published literature. Profile hidden Markov model is then applied to learn a predictive model for each subgroup. A five-fold cross validation evaluation on the MDD-clustered HMMs yields an average accuracy of 84.93% for Serine, and 78.05% for Threonine. Furthermore, an independent testing data collected from UniProtKB and Phospho.ELM is used to make a comparison of predictive performance on three popular kinase-specific phosphorylation site

Identifying Unstable Regions of Proteins Involved in Misfolding Diseases

NASA Astrophysics Data System (ADS)

Guest, Will; Cashman, Neil; Plotkin, Steven

2009-05-01

Protein misfolding is a necessary step in the pathogenesis of many diseases, including Creutzfeldt-Jakob disease (CJD) and familial amyotrophic lateral sclerosis (fALS). Identifying unstable structural elements in their causative proteins elucidates the early events of misfolding and presents targets for inhibition of the disease process. An algorithm was developed to calculate the Gibbs free energy of unfolding for all sequence-contiguous regions of a protein using three methods to parameterize energy changes: a modified G=o model, changes in solvent-accessible surface area, and all-atoms molecular dynamics. The entropic effects of disulfide bonds and post-translational modifications are treated analytically. It incorporates a novel method for finding local dielectric constants inside a protein to accurately handle charge effects. We have predicted the unstable parts of prion protein and superoxide dismutase 1, the proteins involved in CJD and fALS respectively, and have used these regions as epitopes to prepare antibodies that are specific to the misfolded conformation and show promise as therapeutic agents.

Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data

PubMed Central

Toomey, David; Hoppe, Heinrich C.; Brennan, Marian P.; Nolan, Kevin B.; Chubb, Anthony J.

2009-01-01

Background Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. Conclusions/Significance Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under ‘change-of-application’ patents. PMID:19593435

Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems

PubMed Central

MacPherson, Jamie I.; Dickerson, Jonathan E.; Pinney, John W.; Robertson, David L.

2010-01-01

Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection. PMID:20686668

Identifying DNA-binding proteins using structural motifs and the electrostatic potential

PubMed Central

Shanahan, Hugh P.; Garcia, Mario A.; Jones, Susan; Thornton, Janet M.

2004-01-01

Robust methods to detect DNA-binding proteins from structures of unknown function are important for structural biology. This paper describes a method for identifying such proteins that (i) have a solvent accessible structural motif necessary for DNA-binding and (ii) a positive electrostatic potential in the region of the binding region. We focus on three structural motifs: helix–turn-helix (HTH), helix–hairpin–helix (HhH) and helix–loop–helix (HLH). We find that the combination of these variables detect 78% of proteins with an HTH motif, which is a substantial improvement over previous work based purely on structural templates and is comparable to more complex methods of identifying DNA-binding proteins. Similar true positive fractions are achieved for the HhH and HLH motifs. We see evidence of wide evolutionary diversity for DNA-binding proteins with an HTH motif, and much smaller diversity for those with an HhH or HLH motif. PMID:15356290

Unique secreted–surface protein complex of Lactobacillus rhamnosus, identified by phage display

PubMed Central

Gagic, Dragana; Wen, Wesley; Collett, Michael A; Rakonjac, Jasna

2013-01-01

Proteins are the most diverse structures on bacterial surfaces; hence, they are candidates for species- and strain-specific interactions of bacteria with the host, environment, and other microorganisms. Genomics has decoded thousands of bacterial surface and secreted proteins, yet the function of most cannot be predicted because of the enormous variability and a lack of experimental data that would allow deduction of function through homology. Here, we used phage display to identify a pair of interacting extracellular proteins in the probiotic bacterium Lactobacillus rhamnosus HN001. A secreted protein, SpcA, containing two bacterial immunoglobulin-like domains type 3 (Big-3) and a domain distantly related to plant pathogen response domain 1 (PR-1-like) was identified by screening of an L. rhamnosus HN001 library using HN001 cells as bait. The SpcA-“docking” protein, SpcB, was in turn detected by another phage display library screening, using purified SpcA as bait. SpcB is a 3275-residue cell-surface protein that contains general features of large glycosylated Serine-rich adhesins/fibrils from gram-positive bacteria, including the hallmark signal sequence motif KxYKxGKxW. Both proteins are encoded by genes within a L. rhamnosus-unique gene cluster that distinguishes this species from other lactobacilli. To our knowledge, this is the first example of a secreted-docking protein pair identified in lactobacilli. PMID:23233310

G-Jitter Effects in Protein Crystal Growth - A Numerical Study

NASA Technical Reports Server (NTRS)

Ramachandran, N.; Baugher, C. R.

1995-01-01

The impact of spacecraft acceleration environment on Protein Crystal Growth (PCG) is studied. A brief overview of the Space Shuttle acceleration environment is provided followed by a simple scaling procedure used to obtain estimates of the flow and concentration field characteristics in PCG. A detailed two-dimensional numerical model is then used to simulate the PCG system response to different disturbance scenarios; viz. residual g effects, impulse type disturbances and oscillatory inputs. The results show that PCG is susceptible to g-jitter and is a good candidate for vibration isolation.

Multivariate proteomic profiling identifies novel accessory proteins of coated vesicles

PubMed Central

Antrobus, Robin; Hirst, Jennifer; Bhumbra, Gary S.; Kozik, Patrycja; Jackson, Lauren P.; Sahlender, Daniela A.

2012-01-01

Despite recent advances in mass spectrometry, proteomic characterization of transport vesicles remains challenging. Here, we describe a multivariate proteomics approach to analyzing clathrin-coated vesicles (CCVs) from HeLa cells. siRNA knockdown of coat components and different fractionation protocols were used to obtain modified coated vesicle-enriched fractions, which were compared by stable isotope labeling of amino acids in cell culture (SILAC)-based quantitative mass spectrometry. 10 datasets were combined through principal component analysis into a “profiling” cluster analysis. Overall, 136 CCV-associated proteins were predicted, including 36 new proteins. The method identified >93% of established CCV coat proteins and assigned >91% correctly to intracellular or endocytic CCVs. Furthermore, the profiling analysis extends to less well characterized types of coated vesicles, and we identify and characterize the first AP-4 accessory protein, which we have named tepsin. Finally, our data explain how sequestration of TACC3 in cytosolic clathrin cages causes the severe mitotic defects observed in auxilin-depleted cells. The profiling approach can be adapted to address related cell and systems biological questions. PMID:22472443

The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis.

PubMed

Mao, Yimin; Kuo, Su-Wei; Chen, Le; Heckman, C J; Jiang, M C

2017-01-01

Amyotrophic Lateral Sclerosis (ALS) is a devastative neurodegenerative disease characterized by selective loss of motoneurons. While several breakthroughs have been made in identifying ALS genetic defects, the detailed molecular mechanisms are still unclear. These genetic defects involve in numerous biological processes, which converge to a common destiny: motoneuron degeneration. In addition, the common comorbid Frontotemporal Dementia (FTD) further complicates the investigation of ALS etiology. In this study, we aimed to explore the protein-protein interaction network built on known ALS-causative genes to identify essential proteins and common downstream proteins between classical ALS and ALS+FTD (classical ALS + ALS/FTD) groups. The results suggest that classical ALS and ALS+FTD share similar essential protein set (VCP, FUS, TDP-43 and hnRNPA1) but have distinctive functional enrichment profiles. Thus, disruptions to these essential proteins might cause motoneuron susceptible to cellular stresses and eventually vulnerable to proteinopathies. Moreover, we identified a common downstream protein, ubiquitin-C, extensively interconnected with ALS-causative proteins (22 out of 24) which was not linked to ALS previously. Our in silico approach provides the computational background for identifying ALS therapeutic targets, and points out the potential downstream common ground of ALS-causative mutations.

Proteomic analysis identifies insulin-like growth factor-binding protein-related protein-1 as a podocyte product.

PubMed

Matsumoto, Takayuki; Hess, Sonja; Kajiyama, Hiroshi; Sakairi, Toru; Saleem, Moin A; Mathieson, Peter W; Nojima, Yoshihisa; Kopp, Jeffrey B

2010-10-01

The podocyte secretory proteome may influence the phenotype of adjacent podocytes, endothelial cells, parietal epithelial cells, and tubular epithelial cells but has not been systematically characterized. We have initiated studies to characterize this proteome, with the goal of further understanding the podocyte cell biology. We cultured differentiated conditionally immortalized human podocytes and subjected the proteins in conditioned medium to mass spectrometry. At a false discovery rate of <3%, we identified 111 candidates from conditioned medium, including 44 proteins that have signal peptides or are described as secreted proteins in the UniProt database. As validation, we confirmed that one of these proteins, insulin-like growth factor-binding protein-related protein-1 (IGFBP-rP1), was expressed in mRNA and protein of cultured podocytes. In addition, transforming growth factor-β1 stimulation increased IGFBP-rP1 in conditioned medium. We analyzed IGFBP-rP1 glomerular expression in a mouse model of human immunodeficiency virus-associated nephropathy. IGFBP-rP1 was absent from podocytes of normal mice and was expressed in podocytes and pseudocrescents of transgenic mice, where it was coexpressed with desmin, a podocyte injury marker. We conclude that IGFBP-rP1 may be a product of injured podocytes. Further analysis of the podocyte secretory proteome may identify biomarkers of podocyte injury.

Proteomics informed by transcriptomics identifies novel secreted proteins in Dermacentor andersoni saliva

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mudenda, Lwiindi; Aguilar Pierle, Sebastian; Turse, Joshua E.

2014-08-07

Dermacentor andersoni, known as the Rocky Mountain wood tick, is found in the western United States and transmits pathogens that cause diseases of veterinary and public health importance including Rocky Mountain spotted fever, tularemia, Colorado tick fever and bovine anaplasmosis. Tick saliva is known to modulate both innate and acquired immune responses, enabling ticks to feed for several days without detection. During feeding ticks subvert host defences such as hemostasis and inflammation, which would otherwise result in coagulation, wound repair and rejection of the tick. Molecular characterization of the proteins and pharmacological molecules secreted in tick saliva offers an opportunitymore » to develop tick vaccines as an alternative to the use of acaricides, as well as new anti-inflammatory drugs. We performed proteomics informed by transcriptomics to identify D. andersoni saliva proteins that are secreted during feeding. The transcript data generated a database of 21,797 consensus sequences, which we used to identify 677 proteins secreted in the saliva of D. andersoni ticks fed for 2 and 5 days, following proteomic investigations of whole saliva using mass spectrometry. Salivary gland transcript levels of unfed ticks were compared with 2 and 5 day fed ticks to identify genes upregulated early during tick feeding. We cross-referenced the proteomic data with the transcriptomic data to identify 157 proteins of interest for immunomodulation and blood feeding. Proteins of unknown function as well as known immunomodulators were identified.« less

Juvenile hormone-binding proteins of Melanoplus bivittatus identified by EFDA photoaffinity labeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winder, B.S.

1988-01-01

Proteins that bind juvenile hormone in the hemolymph and fat body of the grasshopper, Melanoplus bivittatus were identified by photoaffinity labeling with radiolabeled epoxyfarnesyl diazoacetate ({sup 3}H-EFDA), and were characterized by electrophoretic analysis. A protocol was developed which allowed detection of {sup 3}H-EFDA that was covalently linked to proteins upon exposure to ultraviolet light at 254 nm. Quantification of protein-linked {sup 3}H-EFDA by liquid scintillation spectrometry took advantage of the differential solubility of unlinked {sup 3}H-EFDA in toluene alone, and of the protein-linked {sup 3}H-EFDA in toluene plus the detergent, Triton X-100. Competition between EFDA and juvenile hormone (JH) formore » binding to JH-specific binding sites was measured by hydroxyapatite protein binding assays in the presence of radiolabeled JH or EFDA and competing non-radiolabeled hormone. The protein-linked EFDA was detected on fluorograms of SDS or nondenaturing polyacrylamide gels (PAGE), and by liquid scintillation spectrometry of membranes to which the proteins had been electrophoretically transferred. Proteins which specifically bound JH were identified by photolabeling proteins in the presence and absence of nonlabeled JH-III.« less

A novel approach to identify genes that determine grain protein deviation in cereals.

PubMed

Mosleth, Ellen F; Wan, Yongfang; Lysenko, Artem; Chope, Gemma A; Penson, Simon P; Shewry, Peter R; Hawkesford, Malcolm J

2015-06-01

Grain yield and protein content were determined for six wheat cultivars grown over 3 years at multiple sites and at multiple nitrogen (N) fertilizer inputs. Although grain protein content was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to identify gene transcripts significantly related to GPD across environments. The yield and protein content were initially adjusted for nitrogen fertilizer inputs and then adjusted for yield (to remove the negative correlation with protein content), resulting in a parameter termed corrected GPD. Significant genetic variation in corrected GPD was observed for six cultivars grown over a range of environmental conditions (a total of 584 samples). Gene transcript profiles were determined in a subset of 161 samples of developing grain to identify transcripts contributing to GPD. Principal component analysis (PCA), analysis of variance (ANOVA) and means of scores regression (MSR) were used to identify individual principal components (PCs) correlating with GPD alone. Scores of the selected PCs, which were significantly related to GPD and protein content but not to the yield and significantly affected by cultivar, were identified as reflecting a multivariate pattern of gene expression related to genetic variation in GPD. Transcripts with consistent variation along the selected PCs were identified by an approach hereby called one-block means of scores regression (one-block MSR). © 2014 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.

PubMed

Le, Duc-Hau

2015-01-01

Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2011 CFR

2011-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2013 CFR

2013-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2014 CFR

2014-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2012 CFR

2012-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2010 CFR

2010-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

Dissecting protein function: an efficient protocol for identifying separation-of-function mutations that encode structurally stable proteins.

PubMed

Lubin, Johnathan W; Rao, Timsi; Mandell, Edward K; Wuttke, Deborah S; Lundblad, Victoria

2013-03-01

Mutations that confer the loss of a single biochemical property (separation-of-function mutations) can often uncover a previously unknown role for a protein in a particular biological process. However, most mutations are identified based on loss-of-function phenotypes, which cannot differentiate between separation-of-function alleles vs. mutations that encode unstable/unfolded proteins. An alternative approach is to use overexpression dominant-negative (ODN) phenotypes to identify mutant proteins that disrupt function in an otherwise wild-type strain when overexpressed. This is based on the assumption that such mutant proteins retain an overall structure that is comparable to that of the wild-type protein and are able to compete with the endogenous protein (Herskowitz 1987). To test this, the in vivo phenotypes of mutations in the Est3 telomerase subunit from Saccharomyces cerevisiae were compared with the in vitro secondary structure of these mutant proteins as analyzed by circular-dichroism spectroscopy, which demonstrates that ODN is a more sensitive assessment of protein stability than the commonly used method of monitoring protein levels from extracts. Reverse mutagenesis of EST3, which targeted different categories of amino acids, also showed that mutating highly conserved charged residues to the oppositely charged amino acid had an increased likelihood of generating a severely defective est3(-) mutation, which nevertheless encoded a structurally stable protein. These results suggest that charge-swap mutagenesis directed at a limited subset of highly conserved charged residues, combined with ODN screening to eliminate partially unfolded proteins, may provide a widely applicable and efficient strategy for generating separation-of-function mutations.

Identify High-Quality Protein Structural Models by Enhanced K-Means.

PubMed

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Identify High-Quality Protein Structural Models by Enhanced K-Means

PubMed Central

Li, Haiou; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K-means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K-means clustering (SK-means), whereas the other employs squared distance to optimize the initial centroids (K-means++). Our results showed that SK-means and K-means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K-means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK-means and K-means++ demonstrated substantial improvements relative to results from SPICKER and classical K-means. PMID:28421198

Affinity resins as new tools for identifying target proteins of ascorbic acid.

PubMed

Iwaoka, Yuji; Nishino, Kohei; Ishikawa, Takahiro; Ito, Hideyuki; Sawa, Yoshihiro; Tai, Akihiro

2018-02-12

l-Ascorbic acid (AA) has diverse physiological functions, but little is known about the functional mechanisms of AA. In this study, we synthesized two types of affinity resin on which AA is immobilized in a stable form to identify new AA-targeted proteins, which can provide important clues for elucidating unknown functional mechanisms of AA. To our knowledge, an affinity resin on which AA as a ligand is immobilized has not been prepared, because AA is very unstable and rapidly degraded in an aqueous solution. By using the affinity resins, cytochrome c (cyt c) was identified as an AA-targeted protein, and we showed that oxidized cyt c exhibits specific affinity for AA. These results suggest that two kinds of AA-affinity resin can be powerful tools to identify new target proteins of AA.

Identifying protein biomarkers in predicting disease severity of dengue virus infection using immune-related protein microarray.

PubMed

Soe, Hui Jen; Yong, Yean K; Al-Obaidi, Mazen M Jamil; Raju, Chandramathi Samudi; Gudimella, Ranganath; Manikam, Rishya; Sekaran, Shamala Devi

2018-02-01

Dengue virus is one of the most widespread flaviviruses that re-emerged throughout recent decades. The progression from mild dengue to severe dengue (SD) with the complications such as vascular leakage and hemorrhage increases the fatality rate of dengue. The pathophysiology of SD is not entirely clear. To investigate potential biomarkers that are suggestive of pathogenesis of SD, a small panel of serum samples selected from 1 healthy individual, 2 dengue patients without warning signs (DWS-), 2 dengue patients with warning signs (DWS+), and 5 patients with SD were subjected to a pilot analysis using Sengenics Immunome protein array. The overall fold changes of protein expressions and clustering heat map revealed that PFKFB4, TPM1, PDCL3, and PTPN20A were elevated among patients with SD. Differential expression analysis identified that 29 proteins were differentially elevated greater than 2-fold in SD groups than DWS- and DWS+. From the 29 candidate proteins, pathways enrichment analysis also identified insulin signaling and cytoskeleton pathways were involved in SD, suggesting that the insulin pathway may play a pivotal role in the pathogenesis of SD.

Method for early detection of infectious mononucleosis by identifying inmono proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Willard, K. E.

1984-10-02

Early detection of infectious mononucleosis is carried out using a sample of human blood by isolating and identifying the presence of Inmono proteins in the sample from a two-dimensional protein map with the proteins being characterized by having isoelectric banding as measured in urea of about -16 to -17 with respect to certain isoelectric point standards and molecular mass of about 70 to 75 K daltons as measured in the presence of sodium dodecylsulfate containing polyacrylamide gels, the presence of the Inmono proteins being correlated with the existence of infectious mononucleosis.

Method for early detection of infectious mononucleosis by identifying Inmono proteins

DOEpatents

Willard, Karen E.

1984-01-01

Early detection of infectious mononucleosis is carried out using a sample of human blood by isolating and identifying the presence of Inmono proteins in the sample from a two-dimensional protein map with the proteins being characterized by having isoelectric banding as measured in urea of about -16 to -17 with respect to certain isoelectric point standards and molecular mass of about 70 to 75 K daltons as measured in the presence of sodium dodecylsulfate containing polyacrylamide gels, the presence of the Inmono proteins being correlated with the existence of infectious mononucleosis.

Application of identified sensitive physical parameters in reducing the uncertainty of numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2016-04-01

An important source of uncertainty, which then causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. There are many physical parameters in numerical models in the atmospheric and oceanic sciences, and it would cost a great deal to reduce uncertainties in all physical parameters. Therefore, finding a subset of these parameters, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach. The results imply that nonlinear interactions among parameters play a key role in the uncertainty of numerical simulations in arid and semi-arid regions of China compared to those in northern, northeastern and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the

The identification of protein domains that mediate functional interactions between Rab-GTPases and RabGAPs using 3D protein modeling.

PubMed

Davie, Jeremiah J; Faitar, Silviu L

2017-01-01

Currently, time-consuming serial in vitro experimentation involving immunocytochemistry or radiolabeled materials is required to identify which of the numerous Rab-GTPases (Rab) and Rab-GTPase activating proteins (RabGAP) are capable of functional interactions. These interactions are essential for numerous cellular functions, and in silico methods of reducing in vitro trial and error would accelerate the pace of research in cell biology. We have utilized a combination of three-dimensional protein modeling and protein bioinformatics to identify domains present in Rab proteins that are predictive of their functional interaction with a specific RabGAP. The RabF2 and RabSF1 domains appear to play functional roles in mediating the interaction between Rabs and RabGAPs. Moreover, the RabSF1 domain can be used to make in silico predictions of functional Rab/RabGAP pairs. This method is expected to be a broadly applicable tool for predicting protein-protein interactions where existing crystal structures for homologs of the proteins of interest are available.

Identifying Disease Associated miRNAs Based on Protein Domains.

PubMed

Qin, Gui-Min; Li, Rui-Yi; Zhao, Xing-Ming

2016-01-01

MicroRNAs (miRNAs) are a class of small endogenous non-coding genes, acting as regulators in the post-transcriptional processes. Recently, the miRNAs are found to be widely involved in different types of diseases. Therefore, the identification of disease associated miRNAs can help understand the mechanisms that underlie the disease and identify new biomarkers. However, it is not easy to identify the miRNAs related to diseases due to its extensive involvements in various biological processes. In this work, we present a new approach to identify disease associated miRNAs based on domains, the functional and structural blocks of proteins. The results on real datasets demonstrate that our method can effectively identify disease related miRNAs with high precision.

Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development

DTIC Science & Technology

2012-09-01

orientated immobilization of proteins,” Biotechnology Progress, 22(2), 401-405 ( 2006 ). [26] J. M. Kogot, D. A. Sarkes , I. Val-Addo et al...Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development by Joshua M. Kogot, Deborah A. Sarkes ...Peptide-protein Interactions for Smart Reagent Development Joshua M. Kogot, Deborah A. Sarkes , Dimitra N. Stratis-Cullum, and Paul M

Use of Phage Display to Identify Novel Mineralocorticoid Receptor-Interacting Proteins

PubMed Central

Yang, Jun; Fuller, Peter J.; Morgan, James; Shibata, Hirotaka; McDonnell, Donald P.; Clyne, Colin D.

2014-01-01

The mineralocorticoid receptor (MR) plays a central role in salt and water homeostasis via the kidney; however, inappropriate activation of the MR in the heart can lead to heart failure. A selective MR modulator that antagonizes MR signaling in the heart but not the kidney would provide the cardiovascular protection of current MR antagonists but allow for normal electrolyte balance. The development of such a pharmaceutical requires an understanding of coregulators and their tissue-selective interactions with the MR, which is currently limited by the small repertoire of MR coregulators described in the literature. To identify potential novel MR coregulators, we used T7 phage display to screen tissue-selective cDNA libraries for MR-interacting proteins. Thirty MR binding peptides were identified, from which three were chosen for further characterization based on their nuclear localization and their interaction with other MR-interacting proteins or, in the case of x-ray repair cross-complementing protein 6, its known status as an androgen receptor coregulator. Eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 modulated MR-mediated transcription in a ligand-, cell- and/or promoter-specific manner and colocalized with the MR upon agonist treatment when imaged using immunofluorescence microscopy. These results highlight the utility of phage display for rapid and sensitive screening of MR binding proteins and suggest that eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 may be potential MR coactivators whose activity is dependent on the ligand, cellular context, and target gene promoter. PMID:25000480

Proteomic profiling of human plasma exosomes identifies PPAR{gamma} as an exosome-associated protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Looze, Christopher; Yui, David; Leung, Lester

Exosomes are nanovesicles that are released from cells as a mechanism of cell-free intercellular communication. Only a limited number of proteins have been identified from the plasma exosome proteome. Here, we developed a multi-step fractionation scheme incorporating gel exclusion chromatography, rate zonal centrifugation through continuous sucrose gradients, and high-speed centrifugation to purify exosomes from human plasma. Exosome-associated proteins were separated by SDS-PAGE and 66 proteins were identified by LC-MS/MS, which included both cellular and extracellular proteins. Furthermore, we identified and characterized peroxisome proliferator-activated receptor-{gamma} (PPAR{gamma}), a nuclear receptor that regulates adipocyte differentiation and proliferation, as well as immune and inflammatorymore » cell functions, as a novel component of plasma-derived exosomes. Given the important role of exosomes as intercellular messengers, the discovery of PPAR{gamma} as a component of human plasma exosomes identifies a potential new pathway for the paracrine transfer of nuclear receptors.« less

Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.

PubMed

Choong, Wai-Kok; Lih, Tung-Shing Mamie; Chen, Yu-Ju; Sung, Ting-Yi

2017-12-01

To confirm the existence of missing proteins, we need to identify at least two unique peptides with length of 9-40 amino acids of a missing protein in bottom-up mass-spectrometry-based proteomic experiments. However, an identified unique peptide of the missing protein, even identified with high level of confidence, could possibly coincide with a peptide of a commonly observed protein due to isobaric substitutions, mass modifications, alternative splice isoforms, or single amino acid variants (SAAVs). Besides unique peptides of missing proteins, identified variant peptides (SAAV-containing peptides) could also alternatively map to peptides of other proteins due to the aforementioned issues. Therefore, we conducted a thorough comparative analysis on data sets in PeptideAtlas Tiered Human Integrated Search Proteome (THISP, 2017-03 release), including neXtProt (2017-01 release), to systematically investigate the possibility of unique peptides in missing proteins (PE2-4), unique peptides in dubious proteins, and variant peptides affected by isobaric substitutions, causing doubtful identification results. In this study, we considered 11 isobaric substitutions. From our analysis, we found <5% of the unique peptides of missing proteins and >6% of variant peptides became shared with peptides of PE1 proteins after isobaric substitutions.

Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer.

PubMed

Drabik, Anna; Bodzon-Kulakowska, Anna; Suder, Piotr; Silberring, Jerzy; Kulig, Jan; Sierzega, Marek

2017-04-07

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host-pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls.

Theoretical and Numerical Modeling of Transport of Land Use-Specific Fecal Source Identifiers

NASA Astrophysics Data System (ADS)

Bombardelli, F. A.; Sirikanchana, K. J.; Bae, S.; Wuertz, S.

2008-12-01

Microbial contamination in coastal and estuarine waters is of particular concern to public health officials. In this work, we advocate that well-formulated and developed mathematical and numerical transport models can be combined with modern molecular techniques in order to predict continuous concentrations of microbial indicators under diverse scenarios of interest, and that they can help in source identification of fecal pollution. As a proof of concept, we present initially the theory, numerical implementation and validation of one- and two-dimensional numerical models aimed at computing the distribution of fecal source identifiers in water bodies (based on Bacteroidales marker DNA sequences) coming from different land uses such as wildlife, livestock, humans, dogs or cats. These models have been developed to allow for source identification of fecal contamination in large bodies of water. We test the model predictions using diverse velocity fields and boundary conditions. Then, we present some preliminary results of an application of a three-dimensional water quality model to address the source of fecal contamination in the San Pablo Bay (SPB), United States, which constitutes an important sub-embayment of the San Francisco Bay. The transport equations for Bacteroidales include the processes of advection, diffusion, and decay of Bacteroidales. We discuss the validation of the developed models through comparisons of numerical results with field campaigns developed in the SPB. We determine the extent and importance of the contamination in the bay for two decay rates obtained from field observations, corresponding to total host-specific Bacteroidales DNA and host-specific viable Bacteroidales cells, respectively. Finally, we infer transport conditions in the SPB based on the numerical results, characterizing the fate of outflows coming from the Napa, Petaluma and Sonoma rivers.

Proteins related to the functions of fibroblast-like synoviocytes identified by proteomic analysis.

PubMed

Zhang, Hui; Fan, Lie Ying; Zong, Ming; Sun, Li Shan; Lu, Liu

2012-01-01

It is well known that the fibroblast-like synoviocytes (FLS) play a key role in pathogenesis of rheumatoid arthritis (RA). This study was performed to separate the differentially expressed proteins of FLS from the patients with RA or osteoarthritis (OA) by two-dimensional electrophoresis (2-DE), and found proteins associated with the functions of FLS by mass spectrometry (MS). Total proteins were extracted and quantified from the primary cultured FLS from patients of RA (n=8) or OA (n=6). Proteins were separated by high-resolution 2-DE, and identified the differentially expressed proteins by MS. Western blot analyses was used to validated the expression of candidate proteins. The mRNA of these proteins was detected by semi-quantitative fluorescent PCR. There are 1147 protein spots from RA and 1324 protein spots from OA showed on 2-DE graphs, respectively. We have selected 84 protein spots for MS analysis, and 27 protein spots were successfully identified. We have found that protein isoaspartyl methyltransferase (PIMT) and pirin (iron-binding nuclear protein, PIR) with lower expression in RA, and thioredoxin 1(Trx-1) only expressed in RA may be associated with functions of FLS. Western Blot confirmed the expression of PIMT and pirin lower in RA, and Trx-1 expressed only in RA. The results of semi-quantitative fluorescent PCR are also consistent with 2-DE graphs. PIMT, pirin and Trx-1 affect the functions of FLS in some style and can be the drug targets of RA.

Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses.

PubMed

Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

2016-01-01

Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins

PubMed Central

Li, Hui; Wang, Rong; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area. PMID:28744305

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

PubMed

Wang, Xiao; Li, Hui; Wang, Rong; Zhang, Qiuwen; Zhang, Weiwei; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area.

A sequence-based hybrid predictor for identifying conformationally ambivalent regions in proteins.

PubMed

Liu, Yu-Cheng; Yang, Meng-Han; Lin, Win-Li; Huang, Chien-Kang; Oyang, Yen-Jen

2009-12-03

Proteins are dynamic macromolecules which may undergo conformational transitions upon changes in environment. As it has been observed in laboratories that protein flexibility is correlated to essential biological functions, scientists have been designing various types of predictors for identifying structurally flexible regions in proteins. In this respect, there are two major categories of predictors. One category of predictors attempts to identify conformationally flexible regions through analysis of protein tertiary structures. Another category of predictors works completely based on analysis of the polypeptide sequences. As the availability of protein tertiary structures is generally limited, the design of predictors that work completely based on sequence information is crucial for advances of molecular biology research. In this article, we propose a novel approach to design a sequence-based predictor for identifying conformationally ambivalent regions in proteins. The novelty in the design stems from incorporating two classifiers based on two distinctive supervised learning algorithms that provide complementary prediction powers. Experimental results show that the overall performance delivered by the hybrid predictor proposed in this article is superior to the performance delivered by the existing predictors. Furthermore, the case study presented in this article demonstrates that the proposed hybrid predictor is capable of providing the biologists with valuable clues about the functional sites in a protein chain. The proposed hybrid predictor provides the users with two optional modes, namely, the high-sensitivity mode and the high-specificity mode. The experimental results with an independent testing data set show that the proposed hybrid predictor is capable of delivering sensitivity of 0.710 and specificity of 0.608 under the high-sensitivity mode, while delivering sensitivity of 0.451 and specificity of 0.787 under the high-specificity mode. Though

Identifying proteins that bind to specific RNAs - focus on simple repeat expansion diseases

PubMed Central

Jazurek, Magdalena; Ciesiolka, Adam; Starega-Roslan, Julia; Bilinska, Katarzyna; Krzyzosiak, Wlodzimierz J.

2016-01-01

RNA–protein complexes play a central role in the regulation of fundamental cellular processes, such as mRNA splicing, localization, translation and degradation. The misregulation of these interactions can cause a variety of human diseases, including cancer and neurodegenerative disorders. Recently, many strategies have been developed to comprehensively analyze these complex and highly dynamic RNA–protein networks. Extensive efforts have been made to purify in vivo-assembled RNA–protein complexes. In this review, we focused on commonly used RNA-centric approaches that involve mass spectrometry, which are powerful tools for identifying proteins bound to a given RNA. We present various RNA capture strategies that primarily depend on whether the RNA of interest is modified. Moreover, we briefly discuss the advantages and limitations of in vitro and in vivo approaches. Furthermore, we describe recent advances in quantitative proteomics as well as the methods that are most commonly used to validate robust mass spectrometry data. Finally, we present approaches that have successfully identified expanded repeat-binding proteins, which present abnormal RNA–protein interactions that result in the development of many neurological diseases. PMID:27625393

Identifying the missing proteins in human proteome by biological language model.

PubMed

Dong, Qiwen; Wang, Kai; Liu, Xuan

2016-12-23

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Numerical calculation on a two-step subdiffusion behavior of lateral protein movement in plasma membranes

NASA Astrophysics Data System (ADS)

Sumi, Tomonari; Okumoto, Atsushi; Goto, Hitoshi; Sekino, Hideo

2017-10-01

A two-step subdiffusion behavior of lateral movement of transmembrane proteins in plasma membranes has been observed by using single-molecule experiments. A nested double-compartment model where large compartments are divided into several smaller ones has been proposed in order to explain this observation. These compartments are considered to be delimited by membrane-skeleton "fences" and membrane-protein "pickets" bound to the fences. We perform numerical simulations of a master equation using a simple two-dimensional lattice model to investigate the heterogeneous diffusion dynamics behavior of transmembrane proteins within plasma membranes. We show that the experimentally observed two-step subdiffusion process can be described using fence and picket models combined with decreased local diffusivity of transmembrane proteins in the vicinity of the pickets. This allows us to explain the two-step subdiffusion behavior without explicitly introducing nested double compartments.

Identifying protein complexes in PPI network using non-cooperative sequential game.

PubMed

Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta

2017-08-21

Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.

Identifying different transcribed proteins in the newly described Theraphosidae Pamphobeteus verdolaga.

PubMed

Estrada-Gómez, Sebastian; Vargas-Muñoz, Leidy Johana; Saldarriaga-Córdoba, Mónica; Cifuentes, Yeimy; Perafan, Carlos

2017-04-01

Theraphosidae spider venoms are well known for possess a complex mixture of protein and non-protein compounds in their venom. The objective of this study was to report and identify different proteins translated from the venom gland DNA information of the recently described Theraphosidae spider Pamphobeteus verdolaga. Using a venom gland transcriptomic analysis, we reported a set of the first complete sequences of seven different proteins of the recenlty described Theraphosidae spider P. verdolaga. Protein analysis indicates the presence of different proteins on the venom composition of this new spider, some of them uncommon in the Theraphosidae family. MS/MS analysis of P. verdolaga showed different fragments matching sphingomyelinases (sicaritoxin), barytoxins, hexatoxins, latroinsectotoxins, and linear (zadotoxins) peptides. Only four of the MS/MS fragments showed 100% sequence similarity with one of the transcribed proteins. Transcriptomic analysis showed the presence of different groups of proteins like phospholipases, hyaluronidases, inhibitory cysteine knots (ICK) peptides among others. The three database of protein domains used in this study (Pfam, SMART and CDD) showed congruency in the search of unique conserved protein domain for only four of the translated proteins. Those proteins matched with EF-hand proteins, cysteine rich secretory proteins, jingzhaotoxins, theraphotoxins and hexatoxins, from different Mygalomorphae spiders belonging to the families Theraphosidae, Barychelidae and Hexathelidae. None of the analyzed sequences showed a complete 100% similarity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

High-throughput screening identifies Ceefourin 1 and Ceefourin 2 as highly selective inhibitors of multidrug resistance protein 4 (MRP4).

PubMed

Cheung, Leanna; Flemming, Claudia L; Watt, Fujiko; Masada, Nanako; Yu, Denise M T; Huynh, Tony; Conseil, Gwenaëlle; Tivnan, Amanda; Polinsky, Alexander; Gudkov, Andrei V; Munoz, Marcia A; Vishvanath, Anasuya; Cooper, Dermot M F; Henderson, Michelle J; Cole, Susan P C; Fletcher, Jamie I; Haber, Michelle; Norris, Murray D

2014-09-01

Multidrug resistance protein 4 (MRP4/ABCC4), a member of the ATP-binding cassette (ABC) transporter superfamily, is an organic anion transporter capable of effluxing a wide range of physiologically important signalling molecules and drugs. MRP4 has been proposed to contribute to numerous functions in both health and disease; however, in most cases these links remain to be unequivocally established. A major limitation to understanding the physiological and pharmacological roles of MRP4 has been the absence of specific small molecule inhibitors, with the majority of established inhibitors also targeting other ABC transporter family members, or inhibiting the production, function or degradation of important MRP4 substrates. We therefore set out to identify more selective and well tolerated inhibitors of MRP4 that might be used to study the many proposed functions of this transporter. Using high-throughput screening, we identified two chemically distinct small molecules, Ceefourin 1 and Ceefourin 2, that inhibit transport of a broad range of MRP4 substrates, yet are highly selective for MRP4 over other ABC transporters, including P-glycoprotein (P-gp), ABCG2 (Breast Cancer Resistance Protein; BCRP) and MRP1 (multidrug resistance protein 1; ABCC1). Both compounds are more potent MRP4 inhibitors in cellular assays than the most widely used inhibitor, MK-571, requiring lower concentrations to effect a comparable level of inhibition. Furthermore, Ceefourin 1 and Ceefourin 2 have low cellular toxicity, and high microsomal and acid stability. These newly identified inhibitors should be of great value for efforts to better understand the biological roles of MRP4, and may represent classes of compounds with therapeutic application. Copyright © 2014 Elsevier Inc. All rights reserved.

A systematic analysis of the PARP protein family identifies new functions critical for cell physiology

PubMed Central

Vyas, Sejal; Chesarone-Cataldo, Melissa; Todorova, Tanya; Huang, Yun-Han; Chang, Paul

2013-01-01

The poly(ADP-ribose) polymerase (PARP) family of proteins use NAD+ as their substrate to modify acceptor proteins with adenosine diphosphate-ribose (ADPr) modifications. The function of most PARPs under physiological conditions is unknown. Here, to better understand this protein family, we systematically analyze the cell cycle localization of each PARP and of poly(ADP-ribose), a product of PARP activity, then identify the knock-down phenotype of each protein and perform secondary assays to elucidate function. We show that most PARPs are cytoplasmic, identify cell cycle differences in the ratio of nuclear to cytoplasmic poly(ADP-ribose), and identify four phenotypic classes of PARP function. These include the regulation of membrane structures, cell viability, cell division, and the actin cytoskeleton. Further analysis of PARP14 shows that it is a component of focal adhesion complexes required for proper cell motility and focal adhesion function. In total, we show that PARP proteins are critical regulators of eukaryotic physiology. PMID:23917125

A Fluorescent Live Imaging Screening Assay Based on Translocation Criteria Identifies Novel Cytoplasmic Proteins Implicated in G Protein-coupled Receptor Signaling Pathways*

PubMed Central

Lecat, Sandra; Matthes, Hans W.D.; Pepperkok, Rainer; Simpson, Jeremy C.; Galzi, Jean-Luc

2015-01-01

Several cytoplasmic proteins that are involved in G protein-coupled receptor signaling cascades are known to translocate to the plasma membrane upon receptor activation, such as beta-arrestin2. Based on this example and in order to identify new cytoplasmic proteins implicated in the ON-and-OFF cycle of G protein-coupled receptor, a live-imaging screen of fluorescently labeled cytoplasmic proteins was performed using translocation criteria. The screening of 193 fluorescently tagged human proteins identified eight proteins that responded to activation of the tachykinin NK2 receptor by a change in their intracellular localization. Previously we have presented the functional characterization of one of these proteins, REDD1, that translocates to the plasma membrane. Here we report the results of the entire screening. The process of cell activation was recorded on videos at different time points and all the videos can be visualized on a dedicated website. The proteins BAIAP3 and BIN1, partially translocated to the plasma membrane upon activation of NK2 receptors. Proteins ARHGAP12 and PKM2 translocated toward membrane blebs. Three proteins that associate with the cytoskeleton were of particular interest : PLEKHH2 rearranged from individual dots located near the cell-substrate adhesion surface into lines of dots. The speriolin-like protein, SPATC1L, redistributed to cell-cell junctions. The Chloride intracellular Channel protein, CLIC2, translocated from actin-enriched plasma membrane bundles to cell-cell junctions upon activation of NK2 receptors. CLIC2, and one of its close paralogs, CLIC4, were further shown to respond with the same translocation pattern to muscarinic M3 and lysophosphatidic LPA receptors. This screen allowed us to identify potential actors in signaling pathways downstream of G protein-coupled receptors and could be scaled-up for high-content screening. PMID:25759509

A Fluorescent Live Imaging Screening Assay Based on Translocation Criteria Identifies Novel Cytoplasmic Proteins Implicated in G Protein-coupled Receptor Signaling Pathways.

PubMed

Lecat, Sandra; Matthes, Hans W D; Pepperkok, Rainer; Simpson, Jeremy C; Galzi, Jean-Luc

2015-05-01

Several cytoplasmic proteins that are involved in G protein-coupled receptor signaling cascades are known to translocate to the plasma membrane upon receptor activation, such as beta-arrestin2. Based on this example and in order to identify new cytoplasmic proteins implicated in the ON-and-OFF cycle of G protein-coupled receptor, a live-imaging screen of fluorescently labeled cytoplasmic proteins was performed using translocation criteria. The screening of 193 fluorescently tagged human proteins identified eight proteins that responded to activation of the tachykinin NK2 receptor by a change in their intracellular localization. Previously we have presented the functional characterization of one of these proteins, REDD1, that translocates to the plasma membrane. Here we report the results of the entire screening. The process of cell activation was recorded on videos at different time points and all the videos can be visualized on a dedicated website. The proteins BAIAP3 and BIN1, partially translocated to the plasma membrane upon activation of NK2 receptors. Proteins ARHGAP12 and PKM2 translocated toward membrane blebs. Three proteins that associate with the cytoskeleton were of particular interest : PLEKHH2 rearranged from individual dots located near the cell-substrate adhesion surface into lines of dots. The speriolin-like protein, SPATC1L, redistributed to cell-cell junctions. The Chloride intracellular Channel protein, CLIC2, translocated from actin-enriched plasma membrane bundles to cell-cell junctions upon activation of NK2 receptors. CLIC2, and one of its close paralogs, CLIC4, were further shown to respond with the same translocation pattern to muscarinic M3 and lysophosphatidic LPA receptors. This screen allowed us to identify potential actors in signaling pathways downstream of G protein-coupled receptors and could be scaled-up for high-content screening. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

LigSearch: a knowledge-based web server to identify likely ligands for a protein target

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beer, Tjaart A. P. de; Laskowski, Roman A.; Duban, Mark-Eugene

LigSearch is a web server for identifying ligands likely to bind to a given protein. Identifying which ligands might bind to a protein before crystallization trials could provide a significant saving in time and resources. LigSearch, a web server aimed at predicting ligands that might bind to and stabilize a given protein, has been developed. Using a protein sequence and/or structure, the system searches against a variety of databases, combining available knowledge, and provides a clustered and ranked output of possible ligands. LigSearch can be accessed at http://www.ebi.ac.uk/thornton-srv/databases/LigSearch.

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion*

PubMed Central

Hung, Chien-Wen; Klein, Tobias; Cassidy, Liam; Linke, Dennis; Lange, Sabrina; Anders, Uwe; Bureik, Matthias; Heinzle, Elmar; Schneider, Konstantin; Tholey, Andreas

2016-01-01

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe. Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016. PMID:27477394

A new computational strategy for identifying essential proteins based on network topological properties and biological information.

PubMed

Qin, Chao; Sun, Yongqi; Dong, Yadong

2017-01-01

Essential proteins are the proteins that are indispensable to the survival and development of an organism. Deleting a single essential protein will cause lethality or infertility. Identifying and analysing essential proteins are key to understanding the molecular mechanisms of living cells. There are two types of methods for predicting essential proteins: experimental methods, which require considerable time and resources, and computational methods, which overcome the shortcomings of experimental methods. However, the prediction accuracy of computational methods for essential proteins requires further improvement. In this paper, we propose a new computational strategy named CoTB for identifying essential proteins based on a combination of topological properties, subcellular localization information and orthologous protein information. First, we introduce several topological properties of the protein-protein interaction (PPI) network. Second, we propose new methods for measuring orthologous information and subcellular localization and a new computational strategy that uses a random forest prediction model to obtain a probability score for the proteins being essential. Finally, we conduct experiments on four different Saccharomyces cerevisiae datasets. The experimental results demonstrate that our strategy for identifying essential proteins outperforms traditional computational methods and the most recently developed method, SON. In particular, our strategy improves the prediction accuracy to 89, 78, 79, and 85 percent on the YDIP, YMIPS, YMBD and YHQ datasets at the top 100 level, respectively.

Lsa63, a newly identified surface protein of Leptospira interrogans binds laminin and collagen IV.

PubMed

Vieira, Monica L; de Morais, Zenaide M; Gonçales, Amane P; Romero, Eliete C; Vasconcellos, Silvio A; Nascimento, Ana L T O

2010-01-01

Leptospira interrogans is the etiological agent of leptospirosis, a zoonotic disease that affects populations worldwide. We have identified in proteomic studies a protein that is encoded by the gene LIC10314 and expressed in virulent strain of L. interrogans serovar Pomona. This protein was predicted to be surface exposed by PSORT program and contains a p83/100 domain identified by BLAST analysis that is conserved in protein antigens of several strains of Borrelia and Treponema spp. The proteins containing this domain have been claimed antigen candidates for serodiagnosis of Lyme borreliosis. Thus, we have cloned the LIC10314 and expressed the protein in Escherichia coli BL21-SI strain by using the expression vector pAE. The recombinant protein tagged with N-terminal hexahistidine was purified by metal-charged chromatography and characterized by circular dichroism spectroscopy. This protein is conserved among several species of pathogenic Leptospira and absent in the saprophytic strain L. biflexa. We confirm by liquid-phase immunofluorescence assays with living organisms that this protein is most likely a new surface leptospiral protein. The ability of the protein to mediate attachment to ECM components was evaluated by binding assays. The leptospiral protein encoded by LIC10314, named Lsa63 (Leptospiral surface adhesin of 63kDa), binds strongly to laminin and collagen IV in a dose-dependent and saturable fashion. In addition, Lsa63 is probably expressed during infection since it was recognized by antibodies of serum samples of confirmed-leptospirosis patients in convalescent phase of the disease. Altogether, the data suggests that this novel identified surface protein may be involved in leptospiral pathogenesis. 2009 The British Infection Society. Published by Elsevier Ltd. All rights reserved.

Identifying paths of allosteric communication in the protein BirA through simulations

NASA Astrophysics Data System (ADS)

Custer, Gregory; Beckett, Dorothy; Matysiak, Silvina

Biotin ligase/repressor (BirA) is a bifunctional enzyme which adenylates biotin and transfers the product, biotinyl-5'-AMP (bio-5'-AMP) to biotin carboxyl carrier protein (BCCP). In the absence of BCCP, bio-5'-AMP promotes the dimerization of BirA. In dimer form, the BirA.bio-5'-AMP complex is able to bind to the biotin operator and prevents further synthesis of biotin. The bio-5'-AMP binds away from the dimer interface, so it is acting as an allosteric activator. We perform all-atom molecular dynamics simulations with BirA to look at fluctuations within the protein at equilibrium. We simulate apoBirA, liganded BirA, as well as two mutants, M211A and V219A. In agreement with experimental observations, several loops of the protein become stabilized for the liganded BirA when compared to the apo protein. In addition, changes in the dimer interface are observed for the M211A and V219A mutations, which are located in the ligand binding region. Using inter-residue correlation coefficients and pair energies a communication network through the protein is constructed. With this network we have identified paths which have the potential to be important in allosteric activation of BirA. These paths and the methods we use to identify them will be presented.

In-situ Click Reaction Coupled with Quantitative Proteomics for Identifying Protein Targets of Catechol Estrogens.

PubMed

Liang, Huei-Chen; Liu, Yi-Chen; Chen, Hsin; Ku, Ming Chun; Do, Quynh-Trang; Wang, Chih-Yen; Tzeng, Shun-Fen; Chen, Shu-Hui

2018-06-13

Catechol estrogens (CEs) are metabolic electrophiles that actively undergo covalent interaction with cellular proteins, influencing molecular function. There is no feasible method to identify their binders in a living system. Herein, we developed a click chemistry-based approach using ethinylestradiol (EE2) as the precursor probe coupled with quantitative proteomics to identify protein targets of CEs and classify their binding strengths. Using in-situ metabolic conversion and click reaction in liver microsomes, CEs-protein complex was captured by the probe, digested by trypsin, stable isotope labeled via reductive amination, and analyzed by liquid chromatography-mass spectrometry (LC-MS). A total of 334 liver proteins were repeatedly identified (n  2); 274 identified proteins were classified as strong binders based on precursor mass mapping. The binding strength was further scaled by D/H ratio (activity probe/solvent): 259 strong binders had D/H > 5.25; 46 weak binders had 5.25 > D/H > 1; 5 non-specific binders (keratins) had D/H < 1. These results were confirmed using spiked covalent control (strong binder) and noncovalent control (weak binder), as well as in vitro testing of cytochrome c (D/H = 5.9) which showed covalent conjugation with CEs. Many identified strong binders, such as glutathione transferase, catechol-O-methyl transferase, superoxide dismutase, catalase, glutathione peroxidase, and cytochrome c, are involved in cellular redox processes or detoxification activities. CE conjugation was shown to suppress the superoxide oxidase activity of cytochrome c, suggesting that CEs modification may alter the redox action of cellular proteins. Due to structural similarity and inert alkyne group, EE2 probe is very likely to capture protein targets of CEs in general. Thus, this strategy can be adopted to explore the biological impact of CEs modification in living systems.

CoMoDo: identifying dynamic protein domains based on covariances of motion.

PubMed

Wieninger, Silke A; Ullmann, G Matthias

2015-06-09

Most large proteins are built of several domains, compact units which enable functional protein motions. Different domain assignment approaches exist, which mostly rely on concepts of stability, folding, and evolution. We describe the automatic assignment method CoMoDo, which identifies domains based on protein dynamics. Covariances of atomic fluctuations, here calculated by an Elastic Network Model, are used to group residues into domains of different hierarchical levels. The so-called dynamic domains facilitate the study of functional protein motions involved in biological processes like ligand binding and signal transduction. By applying CoMoDo to a large number of proteins, we demonstrate that dynamic domains exhibit features absent in the commonly assigned structural domains, which can deliver insight into the interactions between domains and between subunits of multimeric proteins. CoMoDo is distributed as free open source software at www.bisb.uni-bayreuth.de/CoMoDo.html .

Probabilistic analysis for identifying the driving force of protein folding

NASA Astrophysics Data System (ADS)

Tokunaga, Yoshihiko; Yamamori, Yu; Matubayasi, Nobuyuki

2018-03-01

Toward identifying the driving force of protein folding, energetics was analyzed in water for Trp-cage (20 residues), protein G (56 residues), and ubiquitin (76 residues) at their native (folded) and heat-denatured (unfolded) states. All-atom molecular dynamics simulation was conducted, and the hydration effect was quantified by the solvation free energy. The free-energy calculation was done by employing the solution theory in the energy representation, and it was seen that the sum of the protein intramolecular (structural) energy and the solvation free energy is more favorable for a folded structure than for an unfolded one generated by heat. Probabilistic arguments were then developed to determine which of the electrostatic, van der Waals, and excluded-volume components of the interactions in the protein-water system governs the relative stabilities between the folded and unfolded structures. It was found that the electrostatic interaction does not correspond to the preference order of the two structures. The van der Waals and excluded-volume components were shown, on the other hand, to provide the right order of preference at probabilities of almost unity, and it is argued that a useful modeling of protein folding is possible on the basis of the excluded-volume effect.

Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles.

PubMed

Zheng, Wu; Blake, Catherine

2015-10-01

Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts. Copyright © 2015 Elsevier Inc. All rights reserved.

A novel assay to identify the trafficking proteins that bind to specific vesicle populations

PubMed Central

Bentley, Marvin; Banker, Gary

2016-01-01

Here we describe a method capable of identifying interactions between candidate trafficking proteins and a defined vesicle population in intact cells. The assay involves the expression of an FKBP12-rapamycin–binding domain (FRB)–tagged candidate vesicle-binding protein that can be inducibly linked to an FKBP-tagged molecular motor. If the FRB-tagged candidate protein binds the labeled vesicles, then linking the FRB and FKBP domains recruits motors to the vesicles and causes a predictable, highly distinctive change in vesicle trafficking. We describe two versions of the assay: a general protocol for use in cells with a typical microtubule-organizing center and a specialized protocol designed to detect protein-vesicle interactions in cultured neurons. We have successfully used this assay to identify kinesins and Rabs that bind to a variety of different vesicle populations. In principle, this assay could be used to investigate interactions between any category of vesicle trafficking proteins and any vesicle population that can be specifically labeled. PMID:26621371

Deformation and Failure of Protein Materials in Physiologically Extreme Conditions and Disease

DTIC Science & Technology

2009-03-01

resonance (NMR) spectroscopy and X- ray crystallography have advanced our ability to identify 3D protein structures57. Site-specific studies using NMR, a... ray crystallography, providing structural and temporal information about mechanisms of deformation and assembly (for example in intermediate...tens of thousands of 3D atomistic protein structures, identifying the structure of numerous proteins from varying species sources60. X- ray

Proteomic analysis identifies differentially expressed proteins after red propolis treatment in Hep-2 cells.

PubMed

Frozza, Caroline Olivieri da Silva; Ribeiro, Tanara da Silva; Gambato, Gabriela; Menti, Caroline; Moura, Sidnei; Pinto, Paulo Marcos; Staats, Charley Christian; Padilha, Francine Ferreira; Begnini, Karine Rech; de Leon, Priscila Marques Moura; Borsuk, Sibele; Savegnago, Lucielli; Dellagostin, Odir; Collares, Tiago; Seixas, Fabiana Kömmling; Henriques, João Antonio Pêgas; Roesch-Ely, Mariana

2014-01-01

Here we investigated alterations in the protein profile of Hep-2 treated with red propolis using two-dimensional electrophoresis associated to mass spectrometry and apoptotic rates of cells treated with and without red propolis extracts through TUNEL and Annexin-V assays. A total of 325 spots were manually excised from the two-dimensional gel electrophoresis and 177 proteins were identified using LC-MS-MS. Among all proteins identified that presented differential expression, most were down-regulated in presence of red propolis extract at a concentration of 120 μg/mL (IC50): GRP78, PRDX2, LDHB, VIM and TUBA1A. Only two up-regulated proteins were identified in this study in the non-cytotoxic (6 μg/mL) red propolis treated group: RPLP0 and RAD23B. TUNEL staining assay showed a markedly increase in the mid- to late-stage apoptosis of Hep-2 cells induced by red propolis at concentrations of 60 and 120 μg/mL when compared with non-treated cells. The increase of late apoptosis was confirmed by in situ Annexin-V analysis in which red propolis extract induced late apoptosis in a dose-dependent manner. The differences in tumor cell protein profiles warrant further investigations including isolation of major bioactive compounds of red propolis in different cell lines using proteomics and molecular tests to validate the protein expression here observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

A cherry protein and its gene, abundantly expressed in ripening fruit, have been identified as thaumatin-like.

PubMed

Fils-Lycaon, B R; Wiersma, P A; Eastwell, K C; Sautiere, P

1996-05-01

A 29-kD polypeptide is the most abundant soluble protein in ripe cherry fruit (Prunus avium L); accumulation begins at the onset of ripening as the fruit turns from yellow to red. This protein was extracted from ripe cherries and purified by size-exclusion and ion-exchange chromatography. Antibodies to the purified protein were used to screen a cDNA library from ripe cherries. Numerous recombinant plaques reacted positively with the antibodies; the DNA sequence of representative clones encoded a polypeptide of 245 amino acid residues. A signal peptide was indicated, and the predicted mature protein corresponded to the purified protein in size (23.3 kD, by mass spectrometry) and isoelectric point (4.2). A search of known protein sequences revealed a strong similarity between this polypeptide and the thaumatin family of pathogenesis-related proteins. The cherry thaumatin-like protein does not have a sweet taste, and no antifungal activity was seen in preliminary assays. Expression of the protein appears to be regulated at the gene level, with mRNA levels at their highest in the ripe fruit.

A cherry protein and its gene, abundantly expressed in ripening fruit, have been identified as thaumatin-like.

PubMed Central

Fils-Lycaon, B R; Wiersma, P A; Eastwell, K C; Sautiere, P

1996-01-01

A 29-kD polypeptide is the most abundant soluble protein in ripe cherry fruit (Prunus avium L); accumulation begins at the onset of ripening as the fruit turns from yellow to red. This protein was extracted from ripe cherries and purified by size-exclusion and ion-exchange chromatography. Antibodies to the purified protein were used to screen a cDNA library from ripe cherries. Numerous recombinant plaques reacted positively with the antibodies; the DNA sequence of representative clones encoded a polypeptide of 245 amino acid residues. A signal peptide was indicated, and the predicted mature protein corresponded to the purified protein in size (23.3 kD, by mass spectrometry) and isoelectric point (4.2). A search of known protein sequences revealed a strong similarity between this polypeptide and the thaumatin family of pathogenesis-related proteins. The cherry thaumatin-like protein does not have a sweet taste, and no antifungal activity was seen in preliminary assays. Expression of the protein appears to be regulated at the gene level, with mRNA levels at their highest in the ripe fruit. PMID:8685266

Z2Pack: Numerical implementation of hybrid Wannier centers for identifying topological materials

NASA Astrophysics Data System (ADS)

Gresch, Dominik; Autès, Gabriel; Yazyev, Oleg V.; Troyer, Matthias; Vanderbilt, David; Bernevig, B. Andrei; Soluyanov, Alexey A.

2017-02-01

The intense theoretical and experimental interest in topological insulators and semimetals has established band structure topology as a fundamental material property. Consequently, identifying band topologies has become an important, but often challenging, problem, with no exhaustive solution at the present time. In this work we compile a series of techniques, some previously known, that allow for a solution to this problem for a large set of the possible band topologies. The method is based on tracking hybrid Wannier charge centers computed for relevant Bloch states, and it works at all levels of materials modeling: continuous k .p models, tight-binding models, and ab initio calculations. We apply the method to compute and identify Chern, Z2, and crystalline topological insulators, as well as topological semimetal phases, using real material examples. Moreover, we provide a numerical implementation of this technique (the Z2Pack software package) that is ideally suited for high-throughput screening of materials databases for compounds with nontrivial topologies. We expect that our work will allow researchers to (a) identify topological materials optimal for experimental probes, (b) classify existing compounds, and (c) reveal materials that host novel, not yet described, topological states.

mom identifies a receptor for the Drosophila JAK/STAT signal transduction pathway and encodes a protein distantly related to the mammalian cytokine receptor family

PubMed Central

Chen, Hua-Wei; Chen, Xiu; Oh, Su-Wan; Marinissen, Maria J.; Gutkind, J. Silvio; Hou, Steven X.

2002-01-01

The JAK/STAT signal transduction pathway controls numerous events in Drosophila melanogaster development. Receptors for the pathway have yet to be identified. Here we have identified a Drosophila gene that shows embryonic mutant phenotypes identical to those in the hopscotch (hop)/JAK kinase and marelle (mrl)/Stat92e mutations. We named this gene master of marelle (mom). Genetic analyses place mom's function between upd (the ligand) and hop. We further show that cultured cells transfected with the mom gene bind UPD and activate the HOP/STAT92E signal transduction pathway. mom encodes a protein distantly related to the mammalian cytokine receptor family. These data show that mom functions as a receptor of the Drosophila JAK/STAT signal transduction pathway. PMID:11825879

Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast.

PubMed

Huang, Mingtao; Bai, Yunpeng; Sjostrom, Staffan L; Hallström, Björn M; Liu, Zihe; Petranovic, Dina; Uhlén, Mathias; Joensson, Haakan N; Andersson-Svahn, Helene; Nielsen, Jens

2015-08-25

There is an increasing demand for biotech-based production of recombinant proteins for use as pharmaceuticals in the food and feed industry and in industrial applications. Yeast Saccharomyces cerevisiae is among preferred cell factories for recombinant protein production, and there is increasing interest in improving its protein secretion capacity. Due to the complexity of the secretory machinery in eukaryotic cells, it is difficult to apply rational engineering for construction of improved strains. Here we used high-throughput microfluidics for the screening of yeast libraries, generated by UV mutagenesis. Several screening and sorting rounds resulted in the selection of eight yeast clones with significantly improved secretion of recombinant α-amylase. Efficient secretion was genetically stable in the selected clones. We performed whole-genome sequencing of the eight clones and identified 330 mutations in total. Gene ontology analysis of mutated genes revealed many biological processes, including some that have not been identified before in the context of protein secretion. Mutated genes identified in this study can be potentially used for reverse metabolic engineering, with the objective to construct efficient cell factories for protein secretion. The combined use of microfluidics screening and whole-genome sequencing to map the mutations associated with the improved phenotype can easily be adapted for other products and cell types to identify novel engineering targets, and this approach could broadly facilitate design of novel cell factories.

Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.

PubMed

Le, Nguyen-Quoc-Khanh; Nguyen, Trinh-Trung-Duong; Ou, Yu-Yen

2017-05-01

The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

DOEpatents

Apel, William A.; Thompson, Vicki S; Lacey, Jeffrey A.; Gentillon, Cynthia A.

2016-08-09

A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

DOEpatents

Thompson, Vicki S; Lacey, Jeffrey A; Gentillon, Cynthia A; Apel, William A

2015-03-03

A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

Proteomic Analysis of Pigeonpea (Cajanus cajan) Seeds Reveals the Accumulation of Numerous Stress-Related Proteins.

PubMed

Krishnan, Hari B; Natarajan, Savithiry S; Oehrle, Nathan W; Garrett, Wesley M; Darwish, Omar

2017-06-14

Pigeonpea is one of the major sources of dietary protein for more than a billion people living in South Asia. This hardy legume is often grown in low-input and risk-prone marginal environments. Considerable research effort has been devoted by a global research consortium to develop genomic resources for the improvement of this legume crop. These efforts have resulted in the elucidation of the complete genome sequence of pigeonpea. Despite these developments, little is known about the seed proteome of this important crop. Here, we report the proteome of pigeonpea seed. To enable the isolation of maximum number of seed proteins, including those that are present in very low amounts, three different protein fractions were obtained by employing different extraction media. High-resolution two-dimensional (2-D) electrophoresis followed by MALDI-TOF-TOF-MS/MS analysis of these protein fractions resulted in the identification of 373 pigeonpea seed proteins. Consistent with the reported high degree of synteny between the pigeonpea and soybean genomes, a large number of pigeonpea seed proteins exhibited significant amino acid homology with soybean seed proteins. Our proteomic analysis identified a large number of stress-related proteins, presumably due to its adaptation to drought-prone environments. The availability of a pigeonpea seed proteome reference map should shed light on the roles of these identified proteins in various biological processes and facilitate the improvement of seed composition.

A Novel Proteomics Approach to Identify SUMOylated Proteins and Their Modification Sites in Human Cells*

PubMed Central

Galisson, Frederic; Mahrouche, Louiza; Courcelles, Mathieu; Bonneil, Eric; Meloche, Sylvain; Chelbi-Alix, Mounira K.; Thibault, Pierre

2011-01-01

The small ubiquitin-related modifier (SUMO) is a small group of proteins that are reversibly attached to protein substrates to modify their functions. The large scale identification of protein SUMOylation and their modification sites in mammalian cells represents a significant challenge because of the relatively small number of in vivo substrates and the dynamic nature of this modification. We report here a novel proteomics approach to selectively enrich and identify SUMO conjugates from human cells. We stably expressed different SUMO paralogs in HEK293 cells, each containing a His6 tag and a strategically located tryptic cleavage site at the C terminus to facilitate the recovery and identification of SUMOylated peptides by affinity enrichment and mass spectrometry. Tryptic peptides with short SUMO remnants offer significant advantages in large scale SUMOylome experiments including the generation of paralog-specific fragment ions following CID and ETD activation, and the identification of modified peptides using conventional database search engines such as Mascot. We identified 205 unique protein substrates together with 17 precise SUMOylation sites present in 12 SUMO protein conjugates including three new sites (Lys-380, Lys-400, and Lys-497) on the protein promyelocytic leukemia. Label-free quantitative proteomics analyses on purified nuclear extracts from untreated and arsenic trioxide-treated cells revealed that all identified SUMOylated sites of promyelocytic leukemia were differentially SUMOylated upon stimulation. PMID:21098080

Pathogen effector protein screening in yeast identifies Legionella factors that interfere with membrane trafficking.

PubMed

Shohdy, Nadim; Efe, Jem A; Emr, Scott D; Shuman, Howard A

2005-03-29

Legionella pneumophila invades and replicates intracellularly in human and protozoan hosts. The bacteria use the Icm/Dot type IVB secretion system to translocate effectors that inhibit phagosome maturation and modulate host vesicle trafficking pathways. To understand how L. pneumophila modulates organelle trafficking in host cells, we carried out pathogen effector protein screening in yeast, identifying L. pneumophila genes that produced membrane trafficking [vacuole protein sorting (VPS)] defects in yeast. We identified four L. pneumophila DNA fragments that perturb sorting of vacuolar proteins. Three encode ORFs of unknown function that are translocated via the Icm/Dot transporter from Legionella into macrophages. VPS inhibitor protein (Vip) A is a coiled-coil protein, VipD is a patatin domain-containing protein, and VipF contains an acetyltransferase domain. Processing studies in yeast indicate that VipA, VipD, and VipF inhibit lysosomal protein trafficking by different mechanisms; overexpressing VipA has an effect on carboxypeptidase Y trafficking, whereas VipD interferes with multivesicular body formation at the late endosome and endoplasmic reticulum-to-Golgi body transport. Such differences highlight the multiple strategies L. pneumophila effectors use to subvert host trafficking processes. Using yeast as an effector gene discovery tool allows for a powerful, genetic approach to both the identification of virulence factors and the study of their function.

Mapping the membrane proteome of anaerobic gut fungi identifies a wealth of carbohydrate binding proteins and transporters.

PubMed

Seppälä, Susanna; Solomon, Kevin V; Gilmore, Sean P; Henske, John K; O'Malley, Michelle A

2016-12-20

Engineered cell factories that convert biomass into value-added compounds are emerging as a timely alternative to petroleum-based industries. Although often overlooked, integral membrane proteins such as solute transporters are pivotal for engineering efficient microbial chassis. Anaerobic gut fungi, adapted to degrade raw plant biomass in the intestines of herbivores, are a potential source of valuable transporters for biotechnology, yet very little is known about the membrane constituents of these non-conventional organisms. Here, we mined the transcriptome of three recently isolated strains of anaerobic fungi to identify membrane proteins responsible for sensing and transporting biomass hydrolysates within a competitive and rather extreme environment. Using sequence analyses and homology, we identified membrane protein-coding sequences from assembled transcriptomes from three strains of anaerobic gut fungi: Neocallimastix californiae, Anaeromyces robustus, and Piromyces finnis. We identified nearly 2000 transporter components: about half of these are involved in the general secretory pathway and intracellular sorting of proteins; the rest are predicted to be small-solute transporters. Unexpectedly, we found a number of putative sugar binding proteins that are associated with prokaryotic uptake systems; and approximately 100 class C G-protein coupled receptors (GPCRs) with non-canonical putative sugar binding domains. We report the first comprehensive characterization of the membrane protein machinery of biotechnologically relevant anaerobic gut fungi. Apart from identifying conserved machinery for protein sorting and secretion, we identify a large number of putative solute transporters that are of interest for biotechnological applications. Notably, our data suggests that the fungi display a plethora of carbohydrate binding domains at their surface, perhaps as a means to sense and sequester some of the sugars that their biomass degrading, extracellular enzymes

A yeast-based genetic screening to identify human proteins that increase homologous recombination.

PubMed

Collavoli, Anita; Comelli, Laura; Rainaldi, Giuseppe; Galli, Alvaro

2008-05-01

To identify new human proteins implicated in homologous recombination (HR), we set up 'a papillae assay' to screen a human cDNA library using the RS112 strain of Saccharomyces cerevisiae containing an intrachromosomal recombination substrate. We isolated 23 cDNAs, 11 coding for complete proteins and 12 for partially deleted proteins that increased HR when overexpressed in yeast. We characterized the effect induced by the overexpression of the complete human proteasome subunit beta 2, the partially deleted proteasome subunits alpha 3 and beta 8, the ribosomal protein L12, the brain abundant membrane signal protein (BASP1) and the human homologue to v-Ha-RAS (HRAS), which elevated HR by 2-6.5-fold over the control. We found that deletion of the RAD52 gene, which has a key role in most HR events, abolished the increase of HR induced by the proteasome subunits and HRAS; by contrast, the RAD52 deletion did not affect the high level of HR due to BASP1 and RPL12. This suggests that the proteins stimulated yeast HR via different mechanisms. Overexpression of the complete beta 2 human proteasome subunit or the partially deleted alpha 3 and beta 8 subunits increased methyl methanesulphonate (MMS) resistance much more in the rad52 Delta mutant than in the wild-type. Overexpression of RPL12 and BASP1 did not affect MMS resistance in both the wild-type and the rad52 Delta mutant, whereas HRAS decreased MMS resistance in the rad52 Delta mutant. The results indicate that these proteins may interfere with the pathway(s) involved in the repair of MMS-induced DNA damage. Finally, we provide further evidence that yeast is a helpful tool to identify human proteins that may have a regulatory role in HR.

Proteome analysis of Aspergillus fumigatus identifies glycosylphosphatidylinositol-anchored proteins associated to the cell wall biosynthesis.

PubMed

Bruneau, J M; Magnin, T; Tagat, E; Legrand, R; Bernard, M; Diaquin, M; Fudali, C; Latgé, J P

2001-08-01

Previous studies in Aspergillus fumigatus (Mouyna I., Fontaine T., Vai M., Monod M., Fonzi W. A., Diaquin M., Popolo L., Hartland R. P., Latgé J.-P, J. Biol. Chem. 2000, 275, 14882-14889) have shown that a glucanosyltransferase playing an important role in fungal cell wall biosynthesis is glycosylphosphatidylinositol (GPI) anchored to the membrane. To identify other GPI-anchored proteins putatively involved in cell wall biogenesis, a proteomic analysis has been undertaken in A. fumigatus and the protein data were matched with the yeast genomic data. GPI-anchored proteins of A. fumigatus were released from membrane preparation by an endogenous GPI-phospholipase C, purified by liquid chromatography and separated by two-dimensional electrophoresis. They were characterized by their peptide mass fingerprint through matrix-assisted laser desorption/ionization-time of flight-(MALDI-TOF)-mass spectrometry and by internal amino acid sequencing. Nine GPI-anchored proteins were identified in A. fumigatus. Five of them were homologs of putatively GPI-anchored yeast proteins (Csa1p, Crh1p, Crh2p, Ecm33p, Gas1p) of unknown function but shown by gene disruption analysis to play a role in cell wall morphogenesis. In addition, a comparative study performed with chitin synthase and glucanosyl transferase mutants of A. fumigatus showed that a modification of the growth phenotype seen in these mutants was associated to an alteration of the pattern of GPI-anchored proteins. These results suggest that GPI-anchored proteins identified in this study are involved in A. fumigatus cell wall organization.

Identifying biological concepts from a protein-related corpus with a probabilistic topic model

PubMed Central

Zheng, Bin; McLean, David C; Lu, Xinghua

2006-01-01

Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA) model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO) terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text. PMID:16466569

Endothelial cell palmitoylproteomics identifies novel lipid modified targets and potential substrates for protein acyl transferases

PubMed Central

Marin, Ethan P.; Derakhshan, Behrad; Lam, TuKiet T.; Davalos, Alberto; Sessa, William C.

2012-01-01

Rationale Protein S-palmitoylation is the post-translational attachment of a saturated 16-carbon palmitic acid to a cysteine side chain via a thioester bond. Palmitoylation can affect protein localization, trafficking, stability, and function. The extent and roles of palmitoylation in endothelial cell (EC) biology is not well understood, in part due to technological limits on palmitoylprotein detection. Objective To develop a method using acyl-biotinyl exchange (ABE) technology coupled with mass spectrometry to globally isolate and identify palmitoylproteins in EC. Methods and Results More than 150 putative palmitoyl proteins were identified in EC using ABE and mass spectrometry. Among the novel palmitoylproteins identified is superoxide dismutase 1 (SOD1), an intensively studied enzyme that protects all cells from oxidative damage. Mutation of cysteine 6 prevents palmitoylation, leads to reduction in SOD1 activity in vivo and in vitro, and inhibits nuclear localization, thereby supporting a functional role for SOD1 palmitoylation. Moreover, we used ABE to search for substrates of particular protein acyl transferases in EC. We found that palmitoylation of the cell adhesion protein PECAM1 is dependent on the protein acyl transferase ZDHHC21. We show that knockdown of ZDHHC21 leads to reduced levels of PECAM1 at the cell surface. Conclusions Our data demonstrate the utility of EC palmitoylproteomics to reveal new insights into the role of this important post-translational lipid modification in EC biology. PMID:22496122

Prolonged Fasting Identifies Heat Shock Protein 10 as a Sirtuin 3 Substrate

PubMed Central

Lu, Zhongping; Chen, Yong; Aponte, Angel M.; Battaglia, Valentina; Gucek, Marjan; Sack, Michael N.

2015-01-01

Although Sirtuin 3 (SIRT3), a mitochondrially enriched deacetylase and activator of fat oxidation, is down-regulated in response to high fat feeding, the rate of fatty acid oxidation and mitochondrial protein acetylation are invariably enhanced in this dietary milieu. These paradoxical data implicate that additional acetylation modification-dependent levels of regulation may be operational under nutrient excess conditions. Because the heat shock protein (Hsp) Hsp10-Hsp60 chaperone complex mediates folding of the fatty acid oxidation enzyme medium-chain acyl-CoA dehydrogenase, we tested whether acetylation-dependent mitochondrial protein folding contributes to this regulatory discrepancy. We demonstrate that Hsp10 is a functional SIRT3 substrate and that, in response to prolonged fasting, SIRT3 levels modulate mitochondrial protein folding. Acetyl mutagenesis of Hsp10 lysine 56 alters Hsp10-Hsp60 binding, conformation, and protein folding. Consistent with Hsp10-Hsp60 regulation of fatty acid oxidation enzyme integrity, medium-chain acyl-CoA dehydrogenase activity and fat oxidation are elevated by Hsp10 acetylation. These data identify acetyl modification of Hsp10 as a nutrient-sensing regulatory node controlling mitochondrial protein folding and metabolic function. PMID:25505263

An RNAi Screen To Identify Protein Phosphatases That Function Within the Drosophila Circadian Clock.

PubMed

Agrawal, Parul; Hardin, Paul E

2016-12-07

Circadian clocks in eukaryotes keep time via cell-autonomous transcriptional feedback loops. A well-characterized example of such a transcriptional feedback loop is in Drosophila, where CLOCK-CYCLE (CLK-CYC) complexes activate transcription of period (per) and timeless (tim) genes, rising levels of PER-TIM complexes feed-back to repress CLK-CYC activity, and degradation of PER and TIM permits the next cycle of CLK-CYC transcription. The timing of CLK-CYC activation and PER-TIM repression is regulated posttranslationally, in part through rhythmic phosphorylation of CLK, PER, and TIM. Previous behavioral screens identified several kinases that control CLK, PER, and TIM levels, subcellular localization, and/or activity, but two phosphatases that function within the clock were identified through the analysis of candidate genes from other pathways or model systems. To identify phosphatases that play a role in the clock, we screened clock cell-specific RNA interference (RNAi) knockdowns of all annotated protein phosphatases and protein phosphatase regulators in Drosophila for altered activity rhythms. This screen identified 19 protein phosphatases that lengthened or shortened the circadian period by ≥1 hr (p ≤ 0.05 compared to controls) or were arrhythmic. Additional RNAi lines, transposon inserts, overexpression, and loss-of-function mutants were tested to independently confirm these RNAi phenotypes. Based on genetic validation and molecular analysis, 15 viable protein phosphatases remain for future studies. These candidates are expected to reveal novel features of the circadian timekeeping mechanism in Drosophila that are likely to be conserved in all animals including humans. Copyright © 2016 Agrawal and Hardin.

UDoNC: An Algorithm for Identifying Essential Proteins Based on Protein Domains and Protein-Protein Interaction Networks.

PubMed

Peng, Wei; Wang, Jianxin; Cheng, Yingjiao; Lu, Yu; Wu, Fangxiang; Pan, Yi

2015-01-01

Prediction of essential proteins which are crucial to an organism's survival is important for disease analysis and drug design, as well as the understanding of cellular life. The majority of prediction methods infer the possibility of proteins to be essential by using the network topology. However, these methods are limited to the completeness of available protein-protein interaction (PPI) data and depend on the network accuracy. To overcome these limitations, some computational methods have been proposed. However, seldom of them solve this problem by taking consideration of protein domains. In this work, we first analyze the correlation between the essentiality of proteins and their domain features based on data of 13 species. We find that the proteins containing more protein domain types which rarely occur in other proteins tend to be essential. Accordingly, we propose a new prediction method, named UDoNC, by combining the domain features of proteins with their topological properties in PPI network. In UDoNC, the essentiality of proteins is decided by the number and the frequency of their protein domain types, as well as the essentiality of their adjacent edges measured by edge clustering coefficient. The experimental results on S. cerevisiae data show that UDoNC outperforms other existing methods in terms of area under the curve (AUC). Additionally, UDoNC can also perform well in predicting essential proteins on data of E. coli.

Mapping the membrane proteome of anaerobic gut fungi identifies a wealth of carbohydrate binding proteins and transporters

DOE PAGES

Seppala, Susanna; Solomon, Kevin V.; Gilmore, Sean P.; ...

2016-12-20

Here, engineered cell factories that convert biomass into value-added compounds are emerging as a timely alternative to petroleum-based industries. Although often overlooked, integral membrane proteins such as solute transporters are pivotal for engineering efficient microbial chassis. Anaerobic gut fungi, adapted to degrade raw plant biomass in the intestines of herbivores, are a potential source of valuable transporters for biotechnology, yet very little is known about the membrane constituents of these non-conventional organisms. Here, we mined the transcriptome of three recently isolated strains of anaerobic fungi to identify membrane proteins responsible for sensing and transporting biomass hydrolysates within a competitive andmore » rather extreme environment. Using sequence analyses and homology, we identified membrane protein-coding sequences from assembled transcriptomes from three strains of anaerobic gut fungi: Neocallimastix californiae, Anaeromyces robustus, and Piromyces finnis. We identified nearly 2000 transporter components: about half of these are involved in the general secretory pathway and intracellular sorting of proteins; the rest are predicted to be small-solute transporters. Unexpectedly, we found a number of putative sugar binding proteins that are associated with prokaryotic uptake systems; and approximately 100 class C G-protein coupled receptors (GPCRs) with non-canonical putative sugar binding domains. In conclusion, we report the first comprehensive characterization of the membrane protein machinery of biotechnologically relevant anaerobic gut fungi. Apart from identifying conserved machinery for protein sorting and secretion, we identify a large number of putative solute transporters that are of interest for biotechnological applications. Notably, our data suggests that the fungi display a plethora of carbohydrate binding domains at their surface, perhaps as a means to sense and sequester some of the sugars that their biomass

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identifying three-dimensional structures of autophosphorylation complexes in crystals of protein kinases

PubMed Central

Xu, Qifang; Malecka, Kimberly L.; Fink, Lauren; Jordan, E. Joseph; Duffy, Erin; Kolander, Samuel; Peterson, Jeffrey; Dunbrack, Roland L.

2016-01-01

Protein kinase autophosphorylation is a common regulatory mechanism in cell signaling pathways. Crystal structures of several homomeric protein kinase complexes have a serine, threonine, or tyrosine autophosphorylation site of one kinase monomer located in the active site of another monomer, a structural complex that we call an “autophosphorylation complex.” We developed and applied a structural bioinformatics method to identify all such autophosphorylation kinase complexes in X-ray crystallographic structures in the Protein Data Bank (PDB). We identified 15 autophosphorylation complexes in the PDB, of which 5 complexes had not previously been described in the publications describing the crystal structures. These 5 consist of tyrosine residues in the N-terminal juxtamembrane regions of colony stimulating factor 1 receptor (CSF1R, Tyr561) and EPH receptor A2 (EPHA2, Tyr594), tyrosine residues in the activation loops of the SRC kinase family member LCK (Tyr394) and insulin-like growth factor 1 receptor (IGF1R, Tyr1166), and a serine in a nuclear localization signal region of CDC-like kinase 2 (CLK2, Ser142). Mutations in the complex interface may alter autophosphorylation activity and contribute to disease; therefore we mutated residues in the autophosphorylation complex interface of LCK and found that two mutations impaired autophosphorylation (T445V and N446A) and mutation of Pro447 to Ala, Gly, or Leu increased autophosphorylation. The identified autophosphorylation sites are conserved in many kinases, suggesting that, by homology, these complexes may provide insight into autophosphorylation complex interfaces of kinases that are relevant drug targets. PMID:26628682

Miscellaneous vitreous-derived IgM antibodies target numerous retinal proteins in equine recurrent uveitis.

PubMed

Zipplies, Johanna K; Hauck, Stefanie M; Eberhardt, Christina; Hirmer, Sieglinde; Amann, Barbara; Stangassinger, Manfred; Ueffing, Marius; Deeg, Cornelia A

2012-09-01

In equine recurrent uveitis (ERU), immune reactions are directed toward known antigens like S-antigen, interphotoreceptor retinoid-binding protein, and cellular retinalaldehyde-binding protein, and anti-retinal antibodies were detected in vitreous samples. The aim of this study was the investigation of intraocular immunoglobulin M (IgM) reactivities to retinal proteome. Retina was separated by one- and two-dimensional gel electrophoresis and blotted semidry on PVDF membranes. To identify intraocular IgM antibody responses to retinal tissue, blots were incubated with vitreous samples of ERU-diseased horses (n = 50) and healthy controls (n = 30), followed by an HRP-labeled secondary antibody specific for equine IgM. Noticeable 2D western blot signals were aligned on a 2D gel of retinal proteome, excised, and subsequently identified by tandem mass spectrometry. Interestingly, frequent and very miscellaneous IgM response patterns to the retinal proteome in 68% of ERU vitreous samples were detected. Binding of IgM antibodies was localized at 17 different molecular weights. The most frequently detected signal, in 21 of the 50 samples, was located at 49 kDa. Comparing the samples interindividually between one and up to nine different signals in one sample could be observed. All healthy vitreous samples were devoid of IgM antibodies. Analysis of targeted spots with mass spectrometry led to the clear identification of 11 different proteins (corresponding to 16 different spots). One candidate could not be discovered so far. The considerable IgM response to retinal proteins demonstrates an ongoing immune response, which might contribute to the remitting relapsing character of ERU. Novel identified target proteins point to a diverse response pattern of individual ERU cases. © 2012 American College of Veterinary Ophthalmologists.

Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis.

PubMed

Bakkar, Nadine; Kovalik, Tina; Lorenzini, Ileana; Spangler, Scott; Lacoste, Alix; Sponaugle, Kyle; Ferrante, Philip; Argentinis, Elenee; Sattler, Rita; Bowser, Robert

2018-02-01

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with no effective treatments. Numerous RNA-binding proteins (RBPs) have been shown to be altered in ALS, with mutations in 11 RBPs causing familial forms of the disease, and 6 more RBPs showing abnormal expression/distribution in ALS albeit without any known mutations. RBP dysregulation is widely accepted as a contributing factor in ALS pathobiology. There are at least 1542 RBPs in the human genome; therefore, other unidentified RBPs may also be linked to the pathogenesis of ALS. We used IBM Watson ® to sieve through all RBPs in the genome and identify new RBPs linked to ALS (ALS-RBPs). IBM Watson extracted features from published literature to create semantic similarities and identify new connections between entities of interest. IBM Watson analyzed all published abstracts of previously known ALS-RBPs, and applied that text-based knowledge to all RBPs in the genome, ranking them by semantic similarity to the known set. We then validated the Watson top-ten-ranked RBPs at the protein and RNA levels in tissues from ALS and non-neurological disease controls, as well as in patient-derived induced pluripotent stem cells. 5 RBPs previously unlinked to ALS, hnRNPU, Syncrip, RBMS3, Caprin-1 and NUPL2, showed significant alterations in ALS compared to controls. Overall, we successfully used IBM Watson to help identify additional RBPs altered in ALS, highlighting the use of artificial intelligence tools to accelerate scientific discovery in ALS and possibly other complex neurological disorders.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

PubMed

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Novel seminal fluid proteins in the seed beetle Callosobruchus maculatus identified by a proteomic and transcriptomic approach.

PubMed

Bayram, H; Sayadi, A; Goenaga, J; Immonen, E; Arnqvist, G

2017-02-01

The seed beetle Callosobruchus maculatus is a significant agricultural pest and increasingly studied model of sexual conflict. Males possess genital spines that increase the transfer of seminal fluid proteins (SFPs) into the female body. As SFPs alter female behaviour and physiology, they are likely to modulate reproduction and sexual conflict in this species. Here, we identified SFPs using proteomics combined with a de novo transcriptome. A prior 2D-sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis identified male accessory gland protein spots that were probably transferred to the female at mating. Proteomic analysis of these spots identified 98 proteins, a majority of which were also present within ejaculates collected from females. Standard annotation workflows revealed common functional groups for SFPs, including proteases and metabolic proteins. Transcriptomic analysis found 84 transcripts differentially expressed between the sexes. Notably, genes encoding 15 proteins were highly expressed in male abdomens and only negligibly expressed within females. Most of these sequences corresponded to 'unknown' proteins (nine of 15) and may represent rapidly evolving SFPs novel to seed beetles. Our combined analyses highlight 44 proteins for which there is strong evidence that they are SFPs. These results can inform further investigation, to better understand the molecular mechanisms of sexual conflict in seed beetles. © 2016 The Royal Entomological Society.

A newly identified protein of Leptospira interrogans mediates binding to laminin.

PubMed

Longhi, Mariana T; Oliveira, Tatiane R; Romero, Eliete C; Gonçales, Amane P; de Morais, Zenaide M; Vasconcellos, Silvio A; Nascimento, Ana L T O

2009-10-01

Pathogenic Leptospira is the aetiological agent of leptospirosis, a life-threatening disease that affects populations worldwide. The search for novel antigens that could be relevant in host-pathogen interactions is being pursued. These antigens have the potential to elicit several activities, including adhesion. This study focused on a hypothetical predicted lipoprotein of Leptospira, encoded by the gene LIC12895, thought to mediate attachment to extracellular matrix (ECM) components. The gene was cloned and expressed in Escherichia coli BL21 Star (DE3)pLys by using the expression vector pAE. The recombinant protein tagged with N-terminal hexahistidine was purified by metal-charged chromatography and characterized by circular dichroism spectroscopy. The capacity of the protein to mediate attachment to ECM components was evaluated by binding assays. The leptospiral protein encoded by LIC12895, named Lsa27 (leptospiral surface adhesin, 27 kDa), bound strongly to laminin in a dose-dependent and saturable fashion. Moreover, Lsa27 was recognized by antibodies from serum samples of confirmed leptospirosis specimens in both the initial and the convalescent phases of the disease. Lsa27 is most likely a surface protein of Leptospira as revealed in liquid-phase immunofluorescence assays with living organisms. Taken together, these data indicate that this newly identified membrane protein is expressed during natural infection and may play a role in mediating adhesion of L. interrogans to its host.

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome.

PubMed

Higuera, Clara; Gardiner, Katheleen J; Cios, Krzysztof J

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets.

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

PubMed Central

Higuera, Clara; Gardiner, Katheleen J.; Cios, Krzysztof J.

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets. PMID:26111164

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

PubMed Central

2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

PubMed

DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

2015-06-01

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A numerical identifiability test for state-space models--application to optimal experimental design.

PubMed

Hidalgo, M E; Ayesa, E

2001-01-01

This paper describes a mathematical tool for identifiability analysis, easily applicable to high order non-linear systems modelled in state-space and implementable in simulators with a time-discrete approach. This procedure also permits a rigorous analysis of the expected estimation errors (average and maximum) in calibration experiments. The methodology is based on the recursive numerical evaluation of the information matrix during the simulation of a calibration experiment and in the setting-up of a group of information parameters based on geometric interpretations of this matrix. As an example of the utility of the proposed test, the paper presents its application to an optimal experimental design of ASM Model No. 1 calibration, in order to estimate the maximum specific growth rate microH and the concentration of heterotrophic biomass XBH.

A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi

PubMed Central

2013-01-01

Background Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes. Results We take advantage of the availability of sequenced fungal genomes and present an unbiased method for finding putative pathogen proteins and secreted effectors in a query genome via comparative hidden Markov model analyses followed by unsupervised protein clustering. Our method returns experimentally validated fungal effectors in Stagonospora nodorum and Fusarium oxysporum as well as the N-terminal Y/F/WxC-motif from the barley powdery mildew pathogen. Application to the cereal pathogen Fusarium graminearum reveals a secreted phosphorylcholine phosphatase that is characteristic of hemibiotrophic and necrotrophic cereal pathogens and shares an ancient selection process with bacterial plant pathogens. Three F. graminearum protein clusters are found with an enriched secretion signal. One of these putative effector clusters contains proteins that share a [SG]-P-C-[KR]-P sequence motif in the N-terminal and show features not commonly associated with fungal effectors. This motif is conserved in secreted pathogenic Fusarium proteins and a prime candidate for functional testing. Conclusions Our pipeline has successfully uncovered conservation patterns, putative effectors and motifs of fungal pathogens that would have been overlooked by existing approaches that identify effectors as small, secreted, cysteine-rich peptides. It can be applied to any pathogenic proteome data, such as microbial pathogen data of plants and other organisms. PMID:24252298

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

Identifying and engineering promoters for high level and sustainable therapeutic recombinant protein production in cultured mammalian cells.

PubMed

Ho, Steven C L; Yang, Yuansheng

2014-08-01

Promoters are essential on plasmid vectors to initiate transcription of the transgenes when generating therapeutic recombinant proteins expressing mammalian cell lines. High and sustained levels of gene expression are desired during therapeutic protein production while gene expression is useful for cell engineering. As many finely controlled promoters exhibit cell and product specificity, new promoters need to be identified, optimized and carefully evaluated before use. Suitable promoters can be identified using techniques ranging from simple molecular biology methods to modern high-throughput omics screenings. Promoter engineering is often required after identification to either obtain high and sustained expression or to provide a wider range of gene expression. This review discusses some of the available methods to identify and engineer promoters for therapeutic recombinant protein expression in mammalian cells.

Network-Based Methods for Identifying Key Active Proteins in the Extracellular Electron Transfer Process in Shewanella oneidensis MR-1.

PubMed

Ding, Dewu; Sun, Xiao

2018-01-16

Shewanella oneidensis MR-1 can transfer electrons from the intracellular environment to the extracellular space of the cells to reduce the extracellular insoluble electron acceptors (Extracellular Electron Transfer, EET). Benefiting from this EET capability, Shewanella has been widely used in different areas, such as energy production, wastewater treatment, and bioremediation. Genome-wide proteomics data was used to determine the active proteins involved in activating the EET process. We identified 1012 proteins with decreased expression and 811 proteins with increased expression when the EET process changed from inactivation to activation. We then networked these proteins to construct the active protein networks, and identified the top 20 key active proteins by network centralization analysis, including metabolism- and energy-related proteins, signal and transcriptional regulatory proteins, translation-related proteins, and the EET-related proteins. We also constructed the integrated protein interaction and transcriptional regulatory networks for the active proteins, then found three exclusive active network motifs involved in activating the EET process-Bi-feedforward Loop, Regulatory Cascade with a Feedback, and Feedback with a Protein-Protein Interaction (PPI)-and identified the active proteins involved in these motifs. Both enrichment analysis and comparative analysis to the whole-genome data implicated the multiheme c -type cytochromes and multiple signal processing proteins involved in the process. Furthermore, the interactions of these motif-guided active proteins and the involved functional modules were discussed. Collectively, by using network-based methods, this work reported a proteome-wide search for the key active proteins that potentially activate the EET process.

Hidden Markov model approach for identifying the modular framework of the protein backbone.

PubMed

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

High throughput atmospheric pressure plasma-induced graft polymerization for identifying protein-resistant surfaces.

PubMed

Gu, Minghao; Kilduff, James E; Belfort, Georges

2012-02-01

Three critical aspects of searching for and understanding how to find highly resistant surfaces to protein adhesion are addressed here with specific application to synthetic membrane filtration. They include the (i) discovery of a series of previously unreported monomers from a large library of monomers with high protein resistance and subsequent low fouling characteristics for membrane ultrafiltration of protein-containing fluids, (ii) development of a new approach to investigate protein-resistant mechanisms from structure-property relationships, and (iii) adaptation of a new surface modification method, called atmospheric pressure plasma-induced graft polymerization (APP), together with a high throughput platform (HTP), for low cost vacuum-free synthesis of anti-fouling membranes. Several new high-performing chemistries comprising two polyethylene glycol (PEG), two amines and one zwitterionic monomers were identified from a library (44 commercial monomers) of five different classes of monomers as strong protein-resistant monomers. Combining our analysis here, using the Hansen solubility parameters (HSP) approach, and data from the literature, we conclude that strong interactions with water (hydrogen bonding) and surface flexibility are necessary for producing the highest protein resistance. Superior protein-resistant surfaces and subsequent anti-fouling performance was obtained with the HTP-APP as compared with our earlier HTP-photo graft-induced polymerization (PGP). Copyright © 2011 Elsevier Ltd. All rights reserved.

A reverse-phase protein microarray-based screen identifies host signaling dynamics upon Burkholderia spp. infection

PubMed Central

Chiang, Chih-Yuan; Uzoma, Ijeoma; Lane, Douglas J.; Memišević, Vesna; Alem, Farhang; Yao, Kuan; Kota, Krishna P.; Bavari, Sina; Wallqvist, Anders; Hakami, Ramin M.; Panchal, Rekha G.

2015-01-01

Burkholderia is a diverse genus of gram-negative bacteria that causes high mortality rate in humans, equines and cattle. The lack of effective therapeutic treatments poses serious public health threats. Developing insights toward host-Burkholderia spp. interaction is critical for understanding the pathogenesis of infection as well as identifying therapeutic targets for drug development. Reverse-phase protein microarray technology was previously proven to identify and characterize novel biomarkers and molecular signatures associated with infectious disease and cancer. In the present study, this technology was utilized to interrogate changes in host protein expression and phosphorylation events in macrophages infected with a collection of geographically diverse strains of Burkholderia spp. The expression or phosphorylation state of 25 proteins was altered during Burkholderia spp. infections of which eight proteins were selected for further characterization by immunoblotting. Increased phosphorylation of AMPK-α1, Src, and GSK3β suggested the importance of their roles in regulating Burkholderia spp. mediated innate immune response. Modulating the inflammatory response by perturbing their activities may provide therapeutic routes for future treatments. PMID:26284031

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

PubMed

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

Bioinformatics analysis identifies several intrinsically disordered human E3 ubiquitin-protein ligases.

PubMed

Boomsma, Wouter; Nielsen, Sofie V; Lindorff-Larsen, Kresten; Hartmann-Petersen, Rasmus; Ellgaard, Lars

2016-01-01

The ubiquitin-proteasome system targets misfolded proteins for degradation. Since the accumulation of such proteins is potentially harmful for the cell, their prompt removal is important. E3 ubiquitin-protein ligases mediate substrate ubiquitination by bringing together the substrate with an E2 ubiquitin-conjugating enzyme, which transfers ubiquitin to the substrate. For misfolded proteins, substrate recognition is generally delegated to molecular chaperones that subsequently interact with specific E3 ligases. An important exception is San1, a yeast E3 ligase. San1 harbors extensive regions of intrinsic disorder, which provide both conformational flexibility and sites for direct recognition of misfolded targets of vastly different conformations. So far, no mammalian ortholog of San1 is known, nor is it clear whether other E3 ligases utilize disordered regions for substrate recognition. Here, we conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology of their ordered regions, and did not capture the unique disorder patterns that encode the functional mechanism of San1. However, by searching specifically for key features of the San1 sequence, such as long regions of intrinsic disorder embedded with short stretches predicted to be suitable for substrate interaction, we identified several E3 ligases with these characteristics. Our initial analysis revealed that another remarkable trait of San1 is shared with several candidate E3 ligases: long stretches of complete lysine suppression, which in San1 limits auto-ubiquitination. We encode these characteristic features into a San1 similarity-score, and present a set of proteins that are plausible candidates as San1 counterparts in humans. In conclusion, our work indicates that San1 is

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes.

PubMed

Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

2016-05-26

Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes.

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes

PubMed Central

Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

2016-01-01

Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes. PMID:27225414

Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach.

PubMed

Núñez-Vivanco, Gabriel; Valdés-Jiménez, Alejandro; Besoaín, Felipe; Reyes-Parada, Miguel

2016-01-01

Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures. Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility

Time-dependent changes in protein expression in rainbow trout muscle following hypoxia.

PubMed

Wulff, Tune; Jokumsen, Alfred; Højrup, Peter; Jessen, Flemming

2012-04-18

Adaptation to hypoxia is a complex process, and individual proteins will be up- or down-regulated in order to address the main challenges at any given time. To investigate the dynamics of the adaptation, rainbow trout (Oncorhynchus mykiss) was exposed to 30% of normal oxygen tension for 1, 2, 5 and 24 h respectively, after which muscle samples were taken. The successful investigation of numerous proteins in a single study was achieved by selectively separating the sarcoplasmic proteins using 2-DE. In total 46 protein spots were identified as changing in abundance in response to hypoxia using one-way ANOVA and multivariate data analysis. Proteins of interest were subsequently identified by MS/MS following tryptic digestion. The observed regulation following hypoxia in skeletal muscle was determined to be time specific, as only a limited number of proteins were regulated in response to more than one time point. The cellular response to hypoxia included regulation of proteins involved in maintaining iron homeostasis, energy levels and muscle structure. In conclusion, this proteome-based study presents a comprehensive investigation of the expression profiles of numerous proteins at four different time points. This increases our understanding of timed changes in protein expression in rainbow trout muscle following hypoxia. Copyright © 2012 Elsevier B.V. All rights reserved.

Deep Coverage Proteomics Identifies More Low-Abundance Missing Proteins in Human Testis Tissue with Q-Exactive HF Mass Spectrometer.

PubMed

Wei, Wei; Luo, Weijia; Wu, Feilin; Peng, Xuehui; Zhang, Yao; Zhang, Manli; Zhao, Yan; Su, Na; Qi, YingZi; Chen, Lingsheng; Zhang, Yangjun; Wen, Bo; He, Fuchu; Xu, Ping

2016-11-04

Since 2012, missing proteins (MPs) investigation has been one of the critical missions of Chromosome-Centric Human Proteome Project (C-HPP) through various biochemical strategies. On the basis of our previous testis MPs study, faster scanning and higher resolution mass-spectrometry-based proteomics might be conducive to MPs exploration, especially for low-abundance proteins. In this study, Q-Exactive HF (HF) was used to survey proteins from the same testis tissues separated by two separating methods (tricine- and glycine-SDS-PAGE), as previously described. A total of 8526 proteins were identified, of which more low-abundance proteins were uniquely detected in HF data but not in our previous LTQ Orbitrap Velos (Velos) reanalysis data. Further transcriptomics analysis showed that these uniquely identified proteins by HF also had lower expression at the mRNA level. Of the 81 total identified MPs, 74 and 39 proteins were listed as MPs in HF and Velos data sets, respectively. Among the above MPs, 47 proteins (43 neXtProt PE2 and 4 PE3) were ranked as confirmed MPs after verifying with the stringent spectra match and isobaric and single amino acid variants filtering. Functional investigation of these 47 MPs revealed that 11 MPs were testis-specific proteins and 7 MPs were involved in spermatogenesis process. Therefore, we concluded that higher scanning speed and resolution of HF might be factors for improving the low-abundance MP identification in future C-HPP studies. All mass-spectrometry data from this study have been deposited in the ProteomeXchange with identifier PXD004092.

The protein expression landscape of the Arabidopsis root

PubMed Central

Petricka, Jalean J.; Schauer, Monica A.; Megraw, Molly; Breakfield, Natalie W.; Thompson, J. Will; Georgiev, Stoyan; Soderblom, Erik J.; Ohler, Uwe; Moseley, Martin Arthur; Grossniklaus, Ueli; Benfey, Philip N.

2012-01-01

Because proteins are the major functional components of cells, knowledge of their cellular localization is crucial to gaining an understanding of the biology of multicellular organisms. We have generated a protein expression map of the Arabidopsis root providing the identity and cell type-specific localization of nearly 2,000 proteins. Grouping proteins into functional categories revealed unique cellular functions and identified cell type-specific biomarkers. Cellular colocalization provided support for numerous protein–protein interactions. With a binary comparison, we found that RNA and protein expression profiles are weakly correlated. We then performed peak integration at cell type-specific resolution and found an improved correlation with transcriptome data using continuous values. We performed GeLC-MS/MS (in-gel tryptic digestion followed by liquid chromatography-tandem mass spectrometry) proteomic experiments on mutants with ectopic and no root hairs, providing complementary proteomic data. Finally, among our root hair-specific proteins we identified two unique regulators of root hair development. PMID:22447775

Analysis of evolutionary conservation patterns and their influence on identifying protein functional sites.

PubMed

Fang, Chun; Noguchi, Tamotsu; Yamana, Hayato

2014-10-01

Evolutionary conservation information included in position-specific scoring matrix (PSSM) has been widely adopted by sequence-based methods for identifying protein functional sites, because all functional sites, whether in ordered or disordered proteins, are found to be conserved at some extent. However, different functional sites have different conservation patterns, some of them are linear contextual, some of them are mingled with highly variable residues, and some others seem to be conserved independently. Every value in PSSMs is calculated independently of each other, without carrying the contextual information of residues in the sequence. Therefore, adopting the direct output of PSSM for prediction fails to consider the relationship between conservation patterns of residues and the distribution of conservation scores in PSSMs. In order to demonstrate the importance of combining PSSMs with the specific conservation patterns of functional sites for prediction, three different PSSM-based methods for identifying three kinds of functional sites have been analyzed. Results suggest that, different PSSM-based methods differ in their capability to identify different patterns of functional sites, and better combining PSSMs with the specific conservation patterns of residues would largely facilitate the prediction.

Identifying relationships between unrelated pharmaceutical target proteins on the basis of shared active compounds.

PubMed

Miljković, Filip; Kunimoto, Ryo; Bajorath, Jürgen

2017-08-01

Computational exploration of small-molecule-based relationships between target proteins from different families. Target annotations of drugs and other bioactive compounds were systematically analyzed on the basis of high-confidence activity data. A total of 286 novel chemical links were established between distantly related or unrelated target proteins. These relationships involved a total of 1859 bioactive compounds including 147 drugs and 141 targets. Computational analysis of large amounts of compounds and activity data has revealed unexpected relationships between diverse target proteins on the basis of compounds they share. These relationships are relevant for drug discovery efforts. Target pairs that we have identified and associated compound information are made freely available.

Peptides identified in soybean protein increase plasma cholesterol in mice on hypercholesterolemic diets

USDA-ARS?s Scientific Manuscript database

The in vitro micellar cholesterol displacement assay has been used to identify peptides that may potentially reduce cholesterol in vivo. We tested two of these peptides, LPYPR and WGAPSI, derived from soybean protein (SP) that have been reported to displace cholesterol from micelles by feeding them...

Identifying Key Proteins in Hg Methylation Pathways of Desulfovibrio by Global Proteomics, Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Summers, Anne O.; Miller, Susan M.; Wall, Judy

2016-06-18

Elemental mercury, Hg(0) is a contaminant at many DOE sites, especially at Oak Ridge National Laboratory (ORNL) where the spread of spilled Hg and its effects on microbial populations have been monitored for decades. To explore the microbial interactions with Hg, we have devised a global proteomic approach capable of directly detecting Hg-adducts of proteins. This technique developed in the facultative anaerobe, Escherichia coli, allows us to identify the proteins most vulnerable to acute exposure to organomercurials phenyl- and ethyl-mercury (as surrogates for the highly neurotoxic methyl-Hg) (Polacco, et al, 2011). We have found >300 such proteins in all metabolicmore » functional groups and cellular compartments; most are highly conserved and can serve as markers for acute Hg exposure (Zink, et al. 2016, in preparation). We have also discovered that acute Hg exposure severely disrupts thiol, iron and redox homeostases, and electrolyte balance (LaVoie, et al., 2015) Thus, we proposed to bring these techniques to bear on the central problem of identifying the cellular proteins involved in bacterial uptake and methylation of mercury and its release from the cell.« less

The antibacterial protein lysozyme identified as the termite egg recognition pheromone.

PubMed

Matsuura, Kenji; Tamura, Takashi; Kobayashi, Norimasa; Yashiro, Toshihisa; Tatsumi, Shingo

2007-08-29

Social insects rely heavily on pheromone communication to maintain their sociality. Egg protection is one of the most fundamental social behaviours in social insects. The recent discovery of the termite-egg mimicking fungus 'termite-ball' and subsequent studies on termite egg protection behaviour have shown that termites can be manipulated by using the termite egg recognition pheromone (TERP), which strongly evokes the egg-carrying and -grooming behaviours of workers. Despite the great scientific and economic importance, TERP has not been identified because of practical difficulties. Herein we identified the antibacterial protein lysozyme as the TERP. We isolated the target protein using ion-exchange and hydrophobic interaction chromatography, and the MALDI-TOF MS analysis showed a molecular size of 14.5 kDa. We found that the TERP provided antibacterial activity against a gram-positive bacterium. Among the currently known antimicrobial proteins, the molecular size of 14.5 kDa limits the target to lysozyme. Termite lysozymes obtained from eggs and salivary glands, and even hen egg lysozyme, showed a strong termite egg recognition activity. Besides eggs themselves, workers also supply lysozyme to eggs through frequent egg-grooming, by which egg surfaces are coated with saliva containing lysozyme. Reverse transcript PCR analysis showed that mRNA of termite lysozyme was expressed in both salivary glands and eggs. Western blot analysis confirmed that lysozyme production begins in immature eggs in queen ovaries. This is the first identification of proteinaceous pheromone in social insects. Researchers have focused almost exclusively on hydrocarbons when searching for recognition pheromones in social insects. The present finding of a proteinaceous pheromone represents a major step forward in, and result in the broadening of, the search for recognition pheromones. This novel function of lysozyme as a termite pheromone illuminates the profound influence of pathogenic

The Antibacterial Protein Lysozyme Identified as the Termite Egg Recognition Pheromone

PubMed Central

Matsuura, Kenji; Tamura, Takashi; Kobayashi, Norimasa; Yashiro, Toshihisa; Tatsumi, Shingo

2007-01-01

Social insects rely heavily on pheromone communication to maintain their sociality. Egg protection is one of the most fundamental social behaviours in social insects. The recent discovery of the termite-egg mimicking fungus ‘termite-ball’ and subsequent studies on termite egg protection behaviour have shown that termites can be manipulated by using the termite egg recognition pheromone (TERP), which strongly evokes the egg-carrying and -grooming behaviours of workers. Despite the great scientific and economic importance, TERP has not been identified because of practical difficulties. Herein we identified the antibacterial protein lysozyme as the TERP. We isolated the target protein using ion-exchange and hydrophobic interaction chromatography, and the MALDI-TOF MS analysis showed a molecular size of 14.5 kDa. We found that the TERP provided antibacterial activity against a gram-positive bacterium. Among the currently known antimicrobial proteins, the molecular size of 14.5 kDa limits the target to lysozyme. Termite lysozymes obtained from eggs and salivary glands, and even hen egg lysozyme, showed a strong termite egg recognition activity. Besides eggs themselves, workers also supply lysozyme to eggs through frequent egg-grooming, by which egg surfaces are coated with saliva containing lysozyme. Reverse transcript PCR analysis showed that mRNA of termite lysozyme was expressed in both salivary glands and eggs. Western blot analysis confirmed that lysozyme production begins in immature eggs in queen ovaries. This is the first identification of proteinaceous pheromone in social insects. Researchers have focused almost exclusively on hydrocarbons when searching for recognition pheromones in social insects. The present finding of a proteinaceous pheromone represents a major step forward in, and result in the broadening of, the search for recognition pheromones. This novel function of lysozyme as a termite pheromone illuminates the profound influence of pathogenic

Beta Atomic Contacts: Identifying Critical Specific Contacts in Protein Binding Interfaces

PubMed Central

Liu, Qian; Kwoh, Chee Keong; Hoi, Steven C. H.

2013-01-01

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the β-skeletons in computational geometry, requires that there is no other atom in the contact spheres defined by two contact atoms; this sphere is similar to the van der Waals spheres of atoms. The statistical analysis on a large dataset shows that β contacts are only a small fraction of conventional distance-based contacts. To empirically quantify the importance of β contacts, we design βACV, an SVM classifier with β contacts as input, to classify homodimers from crystal packing. We found that our βACV is able to achieve the state-of-the-art classification performance superior to SVM classifiers with distance-based contacts as input. Our βACV also outperforms several existing methods when being evaluated on several datasets in previous works. The promising empirical performance suggests that β contacts can truly identify critical specific contacts in protein binding interfaces. β contacts thus provide a new model for more precise description of atomic organization in protein quaternary structures than distance-based contacts. PMID:23630569

High confidence proteomic analysis of yeast LDs identifies additional droplet proteins and reveals connections to dolichol synthesis and sterol acetylation.

PubMed

Currie, Erin; Guo, Xiuling; Christiano, Romain; Chitraju, Chandramohan; Kory, Nora; Harrison, Kenneth; Haas, Joel; Walther, Tobias C; Farese, Robert V

2014-07-01

Accurate protein inventories are essential for understanding an organelle's functions. The lipid droplet (LD) is a ubiquitous intracellular organelle with major functions in lipid storage and metabolism. LDs differ from other organelles because they are bounded by a surface monolayer, presenting unique features for protein targeting to LDs. Many proteins of varied functions have been found in purified LD fractions by proteomics. While these studies have become increasingly sensitive, it is often unclear which of the identified proteins are specific to LDs. Here we used protein correlation profiling to identify 35 proteins that specifically enrich with LD fractions of Saccharomyces cerevisiae Of these candidates, 30 fluorophore-tagged proteins localize to LDs by microscopy, including six proteins, several with human orthologs linked to diseases, which we newly identify as LD proteins (Cab5, Rer2, Say1, Tsc10, YKL047W, and YPR147C). Two of these proteins, Say1, a sterol deacetylase, and Rer2, a cis-isoprenyl transferase, are enzymes involved in sterol and polyprenol metabolism, respectively, and we show their activities are present in LD fractions. Our results provide a highly specific list of yeast LD proteins and reveal that the vast majority of these proteins are involved in lipid metabolism. Copyright © 2014 by the American Society for Biochemistry and Molecular Biology, Inc.

Identifying mRNA sequence elements for target recognition by human Argonaute proteins

PubMed Central

Li, Jingjing; Kim, TaeHyung; Nutiu, Razvan; Ray, Debashish; Hughes, Timothy R.; Zhang, Zhaolei

2014-01-01

It is commonly known that mammalian microRNAs (miRNAs) guide the RNA-induced silencing complex (RISC) to target mRNAs through the seed-pairing rule. However, recent experiments that coimmunoprecipitate the Argonaute proteins (AGOs), the central catalytic component of RISC, have consistently revealed extensive AGO-associated mRNAs that lack seed complementarity with miRNAs. We herein test the hypothesis that AGO has its own binding preference within target mRNAs, independent of guide miRNAs. By systematically analyzing the data from in vivo cross-linking experiments with human AGOs, we have identified a structurally accessible and evolutionarily conserved region (∼10 nucleotides in length) that alone can accurately predict AGO–mRNA associations, independent of the presence of miRNA binding sites. Within this region, we further identified an enriched motif that was replicable on independent AGO-immunoprecipitation data sets. We used RNAcompete to enumerate the RNA-binding preference of human AGO2 to all possible 7-mer RNA sequences and validated the AGO motif in vitro. These findings reveal a novel function of AGOs as sequence-specific RNA-binding proteins, which may aid miRNAs in recognizing their targets with high specificity. PMID:24663241

Diverse structures, functions and uses of FK506 binding proteins.

PubMed

Bonner, Julia Maeve; Boulianne, Gabrielle L

2017-10-01

FK506 (Tacrolimus), isolated from Streptomyces tsukubaenis is a powerful immunosuppressant shown to inhibit T cell activation. FK506 mediated immunosuppression requires the formation of a complex between FK506, a FK506 binding protein (FKBP) and calcineurin. Numerous FKBPs have been identified in a wide range of species, from single celled organisms to humans. FKBPs show peptidylprolyl cis/trans isomerase (PPIase) activity and have been shown to affect a wide range of cellular processes including protein folding, receptor signaling and apoptosis. FKBPs also affect numerous biological functions in addition to immunosuppression including regulation of cardiac function, neuronal function and development and have been implicated in several diseases including cardiac disease, cancer and neurodegenerative diseases such as Alzheimer's disease. More recently, FKBPs have proven useful as molecular tools for studying protein interactions, localization and functions. This review provides an overview of the current state of knowledge of FKBPs and their numerous biological functions and uses. Copyright © 2017 Elsevier Inc. All rights reserved.

A Human Proteome Array Approach to Identifying Key Host Proteins Targeted by Toxoplasma Kinase ROP18*

PubMed Central

Yang, Zhaoshou; Hou, Yongheng; Hao, Taofang; Rho, Hee-Sool; Wan, Jun; Luan, Yizhao; Gao, Xin; Yao, Jianping; Pan, Aihua; Xie, Zhi; Qian, Jiang; Liao, Wanqin; Zhu, Heng; Zhou, Xingwang

2017-01-01

Toxoplasma kinase ROP18 is a key molecule responsible for the virulence of Toxoplasma gondii; however, the mechanisms by which ROP18 exerts parasite virulence via interaction with host proteins remain limited to a small number of identified substrates. To identify a broader array of ROP18 substrates, we successfully purified bioactive mature ROP18 and used it to probe a human proteome array. Sixty eight new putative host targets were identified. Functional annotation analysis suggested that these proteins have a variety of functions, including metabolic process, kinase activity and phosphorylation, cell growth, apoptosis and cell death, and immunity, indicating a pleiotropic role of ROP18 kinase. Among these proteins, four candidates, p53, p38, UBE2N, and Smad1, were further validated. We demonstrated that ROP18 targets p53, p38, UBE2N, and Smad1 for degradation. Importantly, we demonstrated that ROP18 phosphorylates Smad1 Ser-187 to trigger its proteasome-dependent degradation. Further functional characterization of the substrates of ROP18 may enhance understanding of the pathogenesis of Toxoplasma infection and provide new therapeutic targets. Similar strategies could be used to identify novel host targets for other microbial kinases functioning at the pathogen-host interface. PMID:28087594

Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

NASA Astrophysics Data System (ADS)

Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

2016-05-01

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

Numerical classification of coding sequences

NASA Technical Reports Server (NTRS)

Collins, D. W.; Liu, C. C.; Jukes, T. H.

1992-01-01

DNA sequences coding for protein may be represented by counts of nucleotides or codons. A complete reading frame may be abbreviated by its base count, e.g. A76C158G121T74, or with the corresponding codon table, e.g. (AAA)0(AAC)1(AAG)9 ... (TTT)0. We propose that these numerical designations be used to augment current methods of sequence annotation. Because base counts and codon tables do not require revision as knowledge of function evolves, they are well-suited to act as cross-references, for example to identify redundant GenBank entries. These descriptors may be compared, in place of DNA sequences, to extract homologous genes from large databases. This approach permits rapid searching with good selectivity.

Computational Framework for Analysis of Prey–Prey Associations in Interaction Proteomics Identifies Novel Human Protein–Protein Interactions and Networks

PubMed Central

Saha, Sudipto; Dazard, Jean-Eudes; Xu, Hua; Ewing, Rob M.

2013-01-01

Large-scale protein–protein interaction data sets have been generated for several species including yeast and human and have enabled the identification, quantification, and prediction of cellular molecular networks. Affinity purification-mass spectrometry (AP-MS) is the preeminent methodology for large-scale analysis of protein complexes, performed by immunopurifying a specific “bait” protein and its associated “prey” proteins. The analysis and interpretation of AP-MS data sets is, however, not straightforward. In addition, although yeast AP-MS data sets are relatively comprehensive, current human AP-MS data sets only sparsely cover the human interactome. Here we develop a framework for analysis of AP-MS data sets that addresses the issues of noise, missing data, and sparsity of coverage in the context of a current, real world human AP-MS data set. Our goal is to extend and increase the density of the known human interactome by integrating bait–prey and cocomplexed preys (prey–prey associations) into networks. Our framework incorporates a score for each identified protein, as well as elements of signal processing to improve the confidence of identified protein–protein interactions. We identify many protein networks enriched in known biological processes and functions. In addition, we show that integrated bait–prey and prey–prey interactions can be used to refine network topology and extend known protein networks. PMID:22845868

A cohort of new adhesive proteins identified from transcriptomic analysis of mussel foot glands.

PubMed

DeMartini, Daniel G; Errico, John M; Sjoestroem, Sebastian; Fenster, April; Waite, J Herbert

2017-06-01

The adaptive attachment of marine mussels to a wide range of substrates in a high-energy, saline environment has been explored for decades and is a significant driver of bioinspired wet adhesion research. Mussel attachment relies on a fibrous holdfast known as the byssus, which is made by a specialized appendage called the foot. Multiple adhesive and structural proteins are rapidly synthesized, secreted and moulded by the foot into holdfast threads. About 10 well-characterized proteins, namely the mussel foot proteins (Mfps), the preCols and the thread matrix proteins, are reported as representing the bulk of these structures. To explore how robust this proposition is, we sequenced the transcriptome of the glandular tissues that produce and secrete the various holdfast components using next-generation sequencing methods. Surprisingly, we found around 15 highly expressed genes that have not previously been characterized, but bear key similarities to the previously defined mussel foot proteins, suggesting additional contribution to byssal function. We verified the validity of these transcripts by polymerase chain reaction, cloning and Sanger sequencing as well as confirming their presence as proteins in the byssus. These newly identified proteins greatly expand the palette of mussel holdfast biochemistry and provide new targets for investigation into bioinspired wet adhesion. © 2017 The Author(s).

Proteomic profiling identifies the inorganic pyrophosphatase (PPA1) protein as a potential biomarker of metastasis in laryngeal squamous cell carcinoma.

PubMed

Bodnar, Magdalena; Luczak, Magdalena; Bednarek, Kinga; Szylberg, Lukasz; Marszalek, Andrzej; Grenman, Reidar; Szyfter, Krzysztof; Jarmuz-Szymczak, Malgorzata; Giefing, Maciej

2016-06-01

Relapse and metastasis are the main causes of unfavorable outcome in head and neck cancers. Whereas, understanding of the molecular background of these processes is far from being complete. Therefore, in this study we aimed to identify potential biomarker candidates of relapse and metastasis in laryngeal squamous cell carcinoma (LSCC) by combining the 2D electrophoresis based protein screen and immunohistochemical analysis of candidate proteins. We screened three groups of LSCC cell lines derived from primary tumors, recurrent tumors and metastases and identified seven proteins that differed significantly in relative abundance between the analyzed groups. Among the identified proteins were the heat shock proteins HSP60 and HSP70 that were significantly downregulated both in recurrences- and metastases-derived cell lines but not in primary tumor-derived cell lines. Moreover, we identified significant upregulation of the annexin V, calreticulin and the inorganic pyrophosphatase (PPA1) exclusively in the metastases-derived cell lines. As these upregulated proteins could potentially become novel biomarkers of metastasis, we have compared their abundance in primary tumor LSCC N(0) cases, primary tumor LSCC N(+) cases as well as in LSCC metastases N(+). Our results show an intense increase of cytoplasmic PPA1 abundance in the N(+) (p = 0.000042) compared to the N(0) group. In summary, we show a group of proteins deregulated in recurrences and metastases of LSCC. Moreover, we suggest the PPA1 protein as a potential new biomarker for metastasis in this cancer.

Strategy to Identify and Test Putative Light-Sensitive Non-Opsin G-Protein-Coupled Receptors: A Case Study.

PubMed

Faggionato, Davide; Serb, Jeanne M

2017-08-01

The rise of high-throughput RNA sequencing (RNA-seq) and de novo transcriptome assembly has had a transformative impact on how we identify and study genes in the phototransduction cascade of non-model organisms. But the advantage provided by the nearly automated annotation of RNA-seq transcriptomes may at the same time hinder the possibility for gene discovery and the discovery of new gene functions. For example, standard functional annotation based on domain homology to known protein families can only confirm group membership, not identify the emergence of new biochemical function. In this study, we show the importance of developing a strategy that circumvents the limitations of semiautomated annotation and apply this workflow to photosensitivity as a means to discover non-opsin photoreceptors. We hypothesize that non-opsin G-protein-coupled receptor (GPCR) proteins may have chromophore-binding lysines in locations that differ from opsin. Here, we provide the first case study describing non-opsin light-sensitive GPCRs based on tissue-specific RNA-seq data of the common bay scallop Argopecten irradians (Lamarck, 1819). Using a combination of sequence analysis and three-dimensional protein modeling, we identified two candidate proteins. We tested their photochemical properties and provide evidence showing that these two proteins incorporate 11-cis and/or all-trans retinal and react to light photochemically. Based on this case study, we demonstrate that there is potential for the discovery of new light-sensitive GPCRs, and we have developed a workflow that starts from RNA-seq assemblies to the discovery of new non-opsin, GPCR-based photopigments.

Motility screen identifies Drosophila IGF-II mRNA-binding protein--zipcode-binding protein acting in oogenesis and synaptogenesis.

PubMed

Boylan, Kristin L M; Mische, Sarah; Li, Mingang; Marqués, Guillermo; Morin, Xavier; Chia, William; Hays, Thomas S

2008-02-01

The localization of specific mRNAs can establish local protein gradients that generate and control the development of cellular asymmetries. While all evidence underscores the importance of the cytoskeleton in the transport and localization of RNAs, we have limited knowledge of how these events are regulated. Using a visual screen for motile proteins in a collection of GFP protein trap lines, we identified the Drosophila IGF-II mRNA-binding protein (Imp), an ortholog of Xenopus Vg1 RNA binding protein and chicken zipcode-binding protein. In Drosophila, Imp is part of a large, RNase-sensitive complex that is enriched in two polarized cell types, the developing oocyte and the neuron. Using time-lapse confocal microscopy, we establish that both dynein and kinesin contribute to the transport of GFP-Imp particles, and that regulation of transport in egg chambers appears to differ from that in neurons. In Drosophila, loss-of-function Imp mutations are zygotic lethal, and mutants die late as pharate adults. Imp has a function in Drosophila oogenesis that is not essential, as well as functions that are essential during embryogenesis and later development. Germline clones of Imp mutations do not block maternal mRNA localization or oocyte development, but overexpression of a specific Imp isoform disrupts dorsal/ventral polarity. We report here that loss-of-function Imp mutations, as well as Imp overexpression, can alter synaptic terminal growth. Our data show that Imp is transported to the neuromuscular junction, where it may modulate the translation of mRNA targets. In oocytes, where Imp function is not essential, we implicate a specific Imp domain in the establishment of dorsoventral polarity.

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Poly-Small Ubiquitin-like Modifier (PolySUMO)-binding Proteins Identified through a String Search*

PubMed Central

Sun, Huaiyu; Hunter, Tony

2012-01-01

Polysumoylation is a crucial cellular response to stresses against genomic integrity or proteostasis. Like the small ubiquitin-like modifier (SUMO)-targeted ubiquitin ligase RNF4, proteins with clustered SUMO-interacting motifs (SIMs) can be important signal transducers downstream of polysumoylation. To identify novel polySUMO-binding proteins, we conducted a computational string search with a custom Python script. We found clustered SIMs in another RING domain protein Arkadia/RNF111. Detailed biochemical analysis of the Arkadia SIMs revealed that dominant SIMs in a SIM cluster often contain a pentameric VIDLT ((V/I/L/F/Y)(V/I)DLT) core sequence that is also found in the SIMs in PIAS family E3s and is likely the best-fitted structure for SUMO recognition. This idea led to the identification of additional novel SIM clusters in FLASH/CASP8AP2, C5orf25, and SOBP/JXC1. We suggest that the clustered SIMs in these proteins form distinct SUMO binding domains to recognize diverse forms of protein sumoylation. PMID:23086935

Immunoproteomic Analysis To Identify Shiga Toxin-Producing Escherichia coli Outer Membrane Proteins Expressed during Human Infection

PubMed Central

Montero, David; Orellana, Paz; Gutiérrez, Daniela; Araya, Daniela; Salazar, Juan Carlos; Prado, Valeria; Oñate, Ángel; del Canto, Felipe

2014-01-01

Shiga-toxin producing Escherichia coli (STEC) is the etiologic agent of acute diarrhea, dysentery, and hemolytic-uremic syndrome (HUS). There is no approved vaccine for STEC infection in humans, and antibiotic use is contraindicated, as it promotes Shiga toxin production. In order to identify STEC-associated antigens and immunogenic proteins, outer membrane proteins (OMPs) were extracted from STEC O26:H11, O103, O113:H21, and O157:H7 strains, and commensal E. coli strain HS was used as a control. SDS-PAGE, two-dimensional-PAGE analysis, Western blot assays using sera from pediatric HUS patients and controls, and matrix-assisted laser desorption ionization–tandem time of flight analyses were used to identify 12 immunogenic OMPs, some of which were not reactive with control sera. Importantly, seven of these proteins have not been previously reported to be immunogenic in STEC strains. Among these seven proteins, OmpT and Cah displayed IgG and IgA reactivity with sera from HUS patients. Genes encoding these two proteins were present in a majority of STEC strains. Knowledge of the antigens produced during infection of the host and the immune response to those antigens will be important for future vaccine development. PMID:25156722

An approach to large scale identification of non-obvious structural similarities between proteins

PubMed Central

Cherkasov, Artem; Jones, Steven JM

2004-01-01

Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence. PMID:15147578

Discovery Proteomics Identifies a Molecular Link between the Coatomer Protein Complex I and Androgen Receptor-dependent Transcription*

PubMed Central

Hsiao, Jordy J.; Smits, Melinda M.; Ng, Brandon H.; Lee, Jinhee; Wright, Michael E.

2016-01-01

Aberrant androgen receptor (AR)-dependent transcription is a hallmark of human prostate cancers. At the molecular level, ligand-mediated AR activation is coordinated through spatial and temporal protein-protein interactions involving AR-interacting proteins, which we designate the “AR-interactome.” Despite many years of research, the ligand-sensitive protein complexes involved in ligand-mediated AR activation in prostate tumor cells have not been clearly defined. Here, we describe the development, characterization, and utilization of a novel human LNCaP prostate tumor cell line, N-AR, which stably expresses wild-type AR tagged at its N terminus with the streptavidin-binding peptide epitope (streptavidin-binding peptide-tagged wild-type androgen receptor; SBP-AR). A bioanalytical workflow involving streptavidin chromatography and label-free quantitative mass spectrometry was used to identify SBP-AR and associated ligand-sensitive cytosolic proteins/protein complexes linked to AR activation in prostate tumor cells. Functional studies verified that ligand-sensitive proteins identified in the proteomic screen encoded modulators of AR-mediated transcription, suggesting that these novel proteins were putative SBP-AR-interacting proteins in N-AR cells. This was supported by biochemical associations between recombinant SBP-AR and the ligand-sensitive coatomer protein complex I (COPI) retrograde trafficking complex in vitro. Extensive biochemical and molecular experiments showed that the COPI retrograde complex regulates ligand-mediated AR transcriptional activation, which correlated with the mobilization of the Golgi-localized ARA160 coactivator to the nuclear compartment of prostate tumor cells. Collectively, this study provides a bioanalytical strategy to validate the AR-interactome and define novel AR-interacting proteins involved in ligand-mediated AR activation in prostate tumor cells. Moreover, we describe a cellular system to study how compartment-specific AR

The cellular prion protein identifies bipotential cardiomyogenic progenitors.

PubMed

Hidaka, Kyoko; Shirai, Manabu; Lee, Jong-Kook; Wakayama, Takanari; Kodama, Itsuo; Schneider, Michael D; Morisaki, Takayuki

2010-01-08

The paucity of specific surface markers for cardiomyocytes and their progenitors has impeded the development of embryonic or pluripotent stem cell-based transplantation therapy. Identification of relevant surface markers may also enhance our understanding of the mechanisms underlying differentiation. Here, we show that cellular prion protein (PrP) serves as an effective surface marker for isolating nascent cardiomyocytes as well as cardiomyogenic progenitors. Embryonic stem (or embryo-derived) cells were analyzed using flow cytometry to detect surface expression of PrP and intracellular myosin heavy chain (Myhc) proteins. Sorted cells were then analyzed for their differentiation potential. PrP+ cells from beating embryoid bodies (EBs) frequently included nascent Myhc+ cardiomyocytes. Cultured PrP+ cells further differentiated, giving rise to cardiac troponin I+ definitive cardiomyocytes with either an atrial or a ventricular identity. These cells were electrophysiologically functional and able to survive in vivo after transplantation. Combining PrP with a second marker, platelet-derived growth factor receptor (PDGFR)alpha, enabled us to identify an earlier cardiomyogenic population from prebeating EBs, the PrP+PDGFRalpha+ (PRa) cells. The Myhc- PRa cells expressed cardiac transcription factors, such as Nkx2.5, T-box transcription factor 5, and Isl1 (islet LIM homeobox 1), although they were not completely committed. In mouse embryos, PRa cells in cardiac crescent at the 1 to 2 somite stage were Myhc+, whereas they were Myhc- at headfold stages. PRa cells clonally expanded in methlycellulose cultures. Furthermore, single Myhc- PRa cell-derived colonies contained both cardiac and smooth muscle cells. Thus, PrP demarcates a population of bipotential cardiomyogenic progenitor cells that can differentiate into cardiac or smooth muscle cells.

Comparative genome analysis to identify SNPs associated with high oleic acid and elevated protein content in soybean.

PubMed

Kulkarni, Krishnanand P; Patil, Gunvant; Valliyodan, Babu; Vuong, Tri D; Shannon, J Grover; Nguyen, Henry T; Lee, Jeong-Dong

2018-03-01

The objective of this study was to determine the genetic relationship between the oleic acid and protein content. The genotypes having high oleic acid and elevated protein (HOEP) content were crossed with five elite lines having normal oleic acid and average protein (NOAP) content. The selected accessions were grown at six environments in three different locations and phenotyped for protein, oil, and fatty acid components. The mean protein content of parents, HOEP, and NOAP lines was 34.6%, 38%, and 34.9%, respectively. The oleic acid concentration of parents, HOEP, and NOAP lines was 21.7%, 80.5%, and 20.8%, respectively. The HOEP plants carried both FAD2-1A (S117N) and FAD2-1B (P137R) mutant alleles contributing to the high oleic acid phenotype. Comparative genome analysis using whole-genome resequencing data identified six genes having single nucleotide polymorphism (SNP) significantly associated with the traits analyzed. A single SNP in the putative gene Glyma.10G275800 was associated with the elevated protein content, and palmitic, oleic, and linoleic acids. The genes from the marker intervals of previously identified QTL did not carry SNPs associated with protein content and fatty acid composition in the lines used in this study, indicating that all the genes except Glyma.10G278000 may be the new genes associated with the respective traits.

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics.

PubMed

Omasits, Ulrich; Varadarajan, Adithi R; Schmid, Michael; Goetze, Sandra; Melidis, Damianos; Bourqui, Marc; Nikolayeva, Olga; Québatte, Maxime; Patrignani, Andrea; Dehio, Christoph; Frey, Juerg E; Robinson, Mark D; Wollscheid, Bernd; Ahrens, Christian H

2017-12-01

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae , Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote. © 2017 Omasits et al.; Published by Cold Spring Harbor Laboratory Press.

Application of M13 phage display for identifying immunogenic proteins from tick (Ixodes scapularis) saliva.

PubMed

Becker, Martin; Felsberger, André; Frenzel, André; Shattuck, Wendy M C; Dyer, Megan; Kügler, Jonas; Zantow, Jonas; Mather, Thomas N; Hust, Michael

2015-05-30

Ticks act as vectors for a large number of different pathogens, perhaps most notably Borrelia burgdorferi, the causative agent of Lyme disease. The most prominent tick vector in the United States is the blacklegged tick, Ixodes scapularis. Tick bites are of special public health concern since there are no vaccines available against most tick-transmitted pathogens. Based on the observation that certain non-natural host animals such as guinea pigs or humans can develop adaptive immune responses to tick bites, anti-tick vaccination is a potential approach to tackle health risks associated with tick bites. The aim of this study was to use an oligopeptide phage display strategy to identify immunogenic salivary gland proteins from I. scapularis that are recognized by human immune sera. Oligopeptide libraries were generated from salivary gland mRNA of 18 h fed nymphal I. scapularis. Eight immunogenic oligopeptides were selected using human immune sera. Three selected immunogenic oligopeptides were cloned and produced as recombinant proteins. The immunogenic character of an identified metalloprotease (MP1) was validated with human sera. This enzyme has been described previously and was hypothesized as immunogenic which was confirmed in this study. Interestingly, it also has close homologs in other Ixodes species. An immunogenic protein of I. scapularis was identified by oligopeptide phage display. MP1 is a potential candidate for vaccine development.

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread.

PubMed

Spreafico, Filippo; Bongarzone, Italia; Pizzamiglio, Sara; Magni, Ruben; Taverna, Elena; De Bortoli, Maida; Ciniselli, Chiara M; Barzanò, Elena; Biassoni, Veronica; Luchini, Alessandra; Liotta, Lance A; Zhou, Weidong; Signore, Michele; Verderio, Paolo; Massimino, Maura

2017-07-11

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

Identifying intrinsically disordered protein regions likely to undergo binding-induced helical transitions.

PubMed

Glover, Karen; Mei, Yang; Sinha, Sangita C

2016-10-01

Many proteins contain intrinsically disordered regions (IDRs) lacking stable secondary and ordered tertiary structure. IDRs are often implicated in macromolecular interactions, and may undergo structural transitions upon binding to interaction partners. However, as binding partners of many protein IDRs are unknown, these structural transitions are difficult to verify and often are poorly understood. In this study we describe a method to identify IDRs that are likely to undergo helical transitions upon binding. This method combines bioinformatics analyses followed by circular dichroism spectroscopy to monitor 2,2,2-trifluoroethanol (TFE)-induced changes in secondary structure content of these IDRs. Our results demonstrate that there is no significant change in the helicity of IDRs that are not predicted to fold upon binding. IDRs that are predicted to fold fall into two groups: one group does not become helical in the presence of TFE and includes examples of IDRs that form β-strands upon binding, while the other group becomes more helical and includes examples that are known to fold into helices upon binding. Therefore, we propose that bioinformatics analyses combined with experimental evaluation using TFE may provide a general method to identify IDRs that undergo binding-induced disorder-to-helix transitions. Copyright © 2016 Elsevier B.V. All rights reserved.

Gastric Cancer-Specific Protein Profile Identified Using Endoscopic Biopsy Samples via MALDI Mass Spectrometry

PubMed Central

Kim, Hark Kyun; Reyzer, Michelle L.; Choi, Il Ju; Kim, Chan Gyoo; Kim, Hee Sung; Oshima, Akira; Chertov, Oleg; Colantonio, Simona; Fisher, Robert J.; Allen, Jamie L.; Caprioli, Richard M.; Green, Jeffrey E.

2012-01-01

To date, proteomic analyses on gastrointestinal cancer tissue samples have been performed using surgical specimens only, which are obtained after a diagnosis is made. To determine if a proteomic signature obtained from endoscopic biopsy samples could be found to assist with diagnosis, frozen endoscopic biopsy samples collected from 63 gastric cancer patients and 43 healthy volunteers were analyzed using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. A statistical classification model was developed to distinguish tumor from normal tissues using half the samples and validated with the other half. A protein profile was discovered consisting of 73 signals that could classify 32 cancer and 22 normal samples in the validation set with high predictive values (positive and negative predictive values for cancer, 96.8% and 91.3%; sensitivity, 93.8%; specificity, 95.5%). Signals overexpressed in tumors were identified as α-defensin-1, α-defensin-2, calgranulin A, and calgranulin B. A protein profile was also found to distinguish pathologic stage Ia (pT1N0M0) samples (n = 10) from more advanced stage (Ib or higher) tumors (n = 48). Thus, protein profiles obtained from endoscopic biopsy samples may be useful in assisting with the diagnosis of gastric cancer and, possibly, in identifying early stage disease. PMID:20557134

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions.

PubMed

Agarwal, Shashank; Liu, Feifan; Yu, Hong

2011-10-03

Protein-protein interaction (PPI) is an important biomedical phenomenon. Automatically detecting PPI-relevant articles and identifying methods that are used to study PPI are important text mining tasks. In this study, we have explored domain independent features to develop two open source machine learning frameworks. One performs binary classification to determine whether the given article is PPI relevant or not, named "Simple Classifier", and the other one maps the PPI relevant articles with corresponding interaction method nodes in a standardized PSI-MI (Proteomics Standards Initiative-Molecular Interactions) ontology, named "OntoNorm". We evaluated our system in the context of BioCreative challenge competition using the standardized data set. Our systems are amongst the top systems reported by the organizers, attaining 60.8% F1-score for identifying relevant documents, and 52.3% F1-score for mapping articles to interaction method ontology. Our results show that domain-independent machine learning frameworks can perform competitively well at the tasks of detecting PPI relevant articles and identifying the methods that were used to study the interaction in such articles. Simple Classifier is available at http://sourceforge.net/p/simpleclassify/home/ and OntoNorm at http://sourceforge.net/p/ontonorm/home/.

NetCoffee: a fast and accurate global alignment approach to identify functionally conserved proteins in multiple networks.

PubMed

Hu, Jialu; Kehr, Birte; Reinert, Knut

2014-02-15

Owing to recent advancements in high-throughput technologies, protein-protein interaction networks of more and more species become available in public databases. The question of how to identify functionally conserved proteins across species attracts a lot of attention in computational biology. Network alignments provide a systematic way to solve this problem. However, most existing alignment tools encounter limitations in tackling this problem. Therefore, the demand for faster and more efficient alignment tools is growing. We present a fast and accurate algorithm, NetCoffee, which allows to find a global alignment of multiple protein-protein interaction networks. NetCoffee searches for a global alignment by maximizing a target function using simulated annealing on a set of weighted bipartite graphs that are constructed using a triplet approach similar to T-Coffee. To assess its performance, NetCoffee was applied to four real datasets. Our results suggest that NetCoffee remedies several limitations of previous algorithms, outperforms all existing alignment tools in terms of speed and nevertheless identifies biologically meaningful alignments. The source code and data are freely available for download under the GNU GPL v3 license at https://code.google.com/p/netcoffee/.

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

PubMed

Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

2011-05-01

Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

PubMed

Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Quantitative proteomics identifies 38 proteins that are differentially expressed in cucumber in response to cucumber green mottle mosaic virus infection.

PubMed

Liu, Hua-Wei; Liang, Chao-Qiong; Liu, Peng-Fei; Luo, Lai-Xin; Li, Jian-Qiang

2015-12-15

Since it was first reported in 1935, Cucumber green mottle mosaic virus (CGMMV) has become a serious pathogen in a range of cucurbit crops. The virus is generally transmitted by propagation materials, and to date no effective chemical or cultural methods of control have been developed to combat its spread. The current study presents a preliminary analysis of the pathogenic mechanisms from the perspective of protein expression levels in an infected cucumber host, with the objective of elucidating the infection process and potential strategies to reduce both the economic and yield losses associated with CGMMV. Isobaric tags for relative and absolute quantitation (iTRAQ) technology coupled with liquid chromatography-tandem mass spectrometric (LC-MS/MS) were used to identify the differentially expressed proteins in cucumber plants infected with CGMMV compared with mock-inoculated plants. The functions of the proteins were deduced by functional annotation and their involvement in metabolic processes explored by KEGG pathway analysis to identify their interactions during CGMMV infection, while their in vivo expression was further verified by qPCR. Infection by CGMMV altered both the expression level and absolute quantity of 38 proteins (fold change >0.6) in cucumber hosts. Of these, 23 were found to be up-regulated, while 15 were down-regulated. Gene ontology (GO) analysis revealed that 22 of the proteins had a combined function and were associated with molecular function (MF), biological process (BP) and cellular component (CC). Several other proteins had a dual function with 1, 7, and 2 proteins being associated with BP/CC, BP/MF, CC/MF, respectively. The remaining 3 proteins were only involved in MF. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 18 proteins that were involved in 13 separate metabolic pathways. These pathways were subsequently merged to generate three network diagrams illustrating the interactions between the different

Structural genomics analysis of uncharacterized protein families overrepresented in human gut bacteria identifies a novel glycoside hydrolase

PubMed Central

2014-01-01

Background Bacteroides spp. form a significant part of our gut microbiome and are well known for optimized metabolism of diverse polysaccharides. Initial analysis of the archetypal Bacteroides thetaiotaomicron genome identified 172 glycosyl hydrolases and a large number of uncharacterized proteins associated with polysaccharide metabolism. Results BT_1012 from Bacteroides thetaiotaomicron VPI-5482 is a protein of unknown function and a member of a large protein family consisting entirely of uncharacterized proteins. Initial sequence analysis predicted that this protein has two domains, one on the N- and one on the C-terminal. A PSI-BLAST search found over 150 full length and over 90 half size homologs consisting only of the N-terminal domain. The experimentally determined three-dimensional structure of the BT_1012 protein confirms its two-domain architecture and structural analysis of both domains suggests their specific functions. The N-terminal domain is a putative catalytic domain with significant similarity to known glycoside hydrolases, the C-terminal domain has a beta-sandwich fold typically found in C-terminal domains of other glycosyl hydrolases, however these domains are typically involved in substrate binding. We describe the structure of the BT_1012 protein and discuss its sequence-structure relationship and their possible functional implications. Conclusions Structural and sequence analyses of the BT_1012 protein identifies it as a glycosyl hydrolase, expanding an already impressive catalog of enzymes involved in polysaccharide metabolism in Bacteroides spp. Based on this we have renamed the Pfam families representing the two domains found in the BT_1012 protein, PF13204 and PF12904, as putative glycoside hydrolase and glycoside hydrolase-associated C-terminal domain respectively. PMID:24742328

An Approach to Identify and Characterize a Subunit Candidate Shigella Vaccine Antigen.

PubMed

Pore, Debasis; Chakrabarti, Manoj K

2016-01-01

Shigellosis remains a serious issue throughout the developing countries, particularly in children under the age of 5. Numerous strategies have been tested to develop vaccines targeting shigellosis; unfortunately despite several years of extensive research, no safe, effective, and inexpensive vaccine against shigellosis is available so far. Here, we illustrate in detail an approach to identify and establish immunogenic outer membrane proteins from Shigella flexneri 2a as subunit vaccine candidates.

A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

PubMed Central

Musungu, Bryan; Bhatnagar, Deepak; Brown, Robert L.; Fakhoury, Ahmad M.; Geisler, Matt

2015-01-01

Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize. PMID:26089837

A New Scheme to Characterize and Identify Protein Ubiquitination Sites.

PubMed

Nguyen, Van-Nui; Huang, Kai-Yao; Huang, Chien-Hsun; Lai, K Robert; Lee, Tzong-Yi

2017-01-01

Protein ubiquitination, involving the conjugation of ubiquitin on lysine residue, serves as an important modulator of many cellular functions in eukaryotes. Recent advancements in proteomic technology have stimulated increasing interest in identifying ubiquitination sites. However, most computational tools for predicting ubiquitination sites are focused on small-scale data. With an increasing number of experimentally verified ubiquitination sites, we were motivated to design a predictive model for identifying lysine ubiquitination sites for large-scale proteome dataset. This work assessed not only single features, such as amino acid composition (AAC), amino acid pair composition (AAPC) and evolutionary information, but also the effectiveness of incorporating two or more features into a hybrid approach to model construction. The support vector machine (SVM) was applied to generate the prediction models for ubiquitination site identification. Evaluation by five-fold cross-validation showed that the SVM models learned from the combination of hybrid features delivered a better prediction performance. Additionally, a motif discovery tool, MDDLogo, was adopted to characterize the potential substrate motifs of ubiquitination sites. The SVM models integrating the MDDLogo-identified substrate motifs could yield an average accuracy of 68.70 percent. Furthermore, the independent testing result showed that the MDDLogo-clustered SVM models could provide a promising accuracy (78.50 percent) and perform better than other prediction tools. Two cases have demonstrated the effective prediction of ubiquitination sites with corresponding substrate motifs.

Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

PubMed

Meckes, David G

2014-01-01

The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

Comparative Proteomics Identifies Host Immune System Proteins Affected by Infection with Mycobacterium bovis

PubMed Central

López, Vladimir; Villar, Margarita; Queirós, João; Vicente, Joaquín; Mateos-Hernández, Lourdes; Díez-Delgado, Iratxe; Contreras, Marinela; Alves, Paulo C.; Alberdi, Pilar; Gortázar, Christian; de la Fuente, José

2016-01-01

Mycobacteria of the Mycobacterium tuberculosis complex (MTBC) greatly impact human and animal health worldwide. The mycobacterial life cycle is complex, and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood. Eurasian wild boar (Sus scrofa) are natural reservoir hosts for MTBC and a model for mycobacterial infection and tuberculosis (TB). In the wild boar TB model, mycobacterial infection affects the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils, and biomarkers have been proposed as correlates with resistance to natural infection. However, the mechanisms used by mycobacteria to manipulate host immune response are not fully characterized. Our hypothesis is that the immune system proteins under-represented in infected animals, when compared to uninfected controls, are used by mycobacteria to guarantee pathogen infection and transmission. To address this hypothesis, a comparative proteomics approach was used to compare host response between uninfected (TB-) and M. bovis-infected young (TB+) and adult animals with different infection status [TB lesions localized in the head (TB+) or affecting multiple organs (TB++)]. The results identified host immune system proteins that play an important role in host response to mycobacteria. Calcium binding protein A9, Heme peroxidase, Lactotransferrin, Cathelicidin and Peptidoglycan-recognition protein were under-represented in TB+ animals when compared to uninfected TB- controls, but protein levels were higher as infection progressed in TB++ animals when compared to TB- and/or TB+ adult wild boar. MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls. The results reported here suggest that M. bovis manipulates host immune response by reducing the production of immune system proteins. However, as infection progresses, wild boar immune response recovers to limit pathogen

Evaluation of chemical labeling methods for identifying functional arginine residues of proteins by mass spectrometry.

PubMed

Wanigasekara, Maheshika S K; Chowdhury, Saiful M

2016-09-07

Arginine residues undergo several kinds of post-translational modifications (PTMs). These PTMs are associated with several inflammatory diseases, such as rheumatoid arthritis, atherosclerosis, and diabetes. Mass spectrometric studies of arginine modified proteins and peptides are very important, not only to identify the reactive arginine residues but also to understand the tandem mass spectrometry behavior of these peptides for assigning the sequences unambiguously. Herein, we utilize tandem mass spectrometry to report the performance of two widely used arginine labeling reagents, 1,2-cyclohexanedione (CHD) and phenylglyoxal (PG) with several arginine containing peptides and proteins. Time course labeling studies were performed to demonstrate the selectivity of the reagents in proteins or protein digests. Structural studies on the proteins were also explored to better understand the reaction sites and position of arginine residues. We found CHD showed better labeling efficiencies compared to phenylglyoxal. Reactive arginine profiling on a purified albumin protein clearly pointed out the cellular glycation modification site for this protein with high confidence. We believe these detailed mass-spectrometric studies will provide significant input to profile reactive arginine residues in large-scale studies; therefore, targeted proteomics can be performed to the short listed reactive sites for cellular arginine modifications. Copyright © 2016 Elsevier B.V. All rights reserved.

Protein - Which is Best?

PubMed

Hoffman, Jay R; Falvo, Michael J

2004-09-01

Protein intake that exceeds the recommended daily allowance is widely accepted for both endurance and power athletes. However, considering the variety of proteins that are available much less is known concerning the benefits of consuming one protein versus another. The purpose of this paper is to identify and analyze key factors in order to make responsible recommendations to both the general and athletic populations. Evaluation of a protein is fundamental in determining its appropriateness in the human diet. Proteins that are of inferior content and digestibility are important to recognize and restrict or limit in the diet. Similarly, such knowledge will provide an ability to identify proteins that provide the greatest benefit and should be consumed. The various techniques utilized to rate protein will be discussed. Traditionally, sources of dietary protein are seen as either being of animal or vegetable origin. Animal sources provide a complete source of protein (i.e. containing all essential amino acids), whereas vegetable sources generally lack one or more of the essential amino acids. Animal sources of dietary protein, despite providing a complete protein and numerous vitamins and minerals, have some health professionals concerned about the amount of saturated fat common in these foods compared to vegetable sources. The advent of processing techniques has shifted some of this attention and ignited the sports supplement marketplace with derivative products such as whey, casein and soy. Individually, these products vary in quality and applicability to certain populations. The benefits that these particular proteins possess are discussed. In addition, the impact that elevated protein consumption has on health and safety issues (i.e. bone health, renal function) are also reviewed. Key PointsHigher protein needs are seen in athletic populations.Animal proteins is an important source of protein, however potential health concerns do exist from a diet of protein

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Inflammatory and fibrotic proteins proteomically identified as key protein constituents in urine and stone matrix of patients with kidney calculi.

PubMed

Boonla, Chanchai; Tosukhowong, Piyaratana; Spittau, Björn; Schlosser, Andreas; Pimratana, Chaowat; Krieglstein, Kerstin

2014-02-15

To uncover whether urinary proteins are incorporated into stones, the proteomic profiles of kidney stones and urine collected from the same patients have to be explored. We employed 1D-PAGE and nanoHPLC-ESI-MS/MS to analyze the proteomes of kidney stone matrix (n=16), nephrolithiatic urine (n=14) and healthy urine (n=3). We identified 62, 66 and 22 proteins in stone matrix, nephrolithiatic urine and healthy urine, respectively. Inflammation- and fibrosis-associated proteins were frequently detected in the stone matrix and nephrolithiatic urine. Eighteen proteins were exclusively found in the stone matrix and nephrolithiatic urine, considered as candidate biomarkers for kidney stone formation. S100A8 and fibronectin, representatives of inflammation and fibrosis, respectively, were up-regulated in nephrolithiasis renal tissues. S100A8 was strongly expressed in infiltrated leukocytes. Fibronectin was over-expressed in renal tubular cells. S100A8 and fibronectin were immunologically confirmed to exist in nephrolithiatic urine and stone matrix, but in healthy urine they were undetectable. Conclusion, both kidney stones and urine obtained from the same patients greatly contained inflammatory and fibrotic proteins. S100A8 and fibronectin were up-regulated in stone-baring kidneys and nephrolithiatic urine. Therefore, inflammation and fibrosis are suggested to be involved in the formation of kidney calculi. Copyright © 2013 Elsevier B.V. All rights reserved.

Phenotypic Screening Identifies Protein Synthesis Inhibitors as H-Ras-Nanocluster-Increasing Tumor Growth Inducers.

PubMed

Najumudeen, Arafath K; Posada, Itziar M D; Lectez, Benoit; Zhou, Yong; Landor, Sebastian K-J; Fallarero, Adyary; Vuorela, Pia; Hancock, John; Abankwa, Daniel

2015-12-15

Ras isoforms H-, N-, and K-ras are each mutated in specific cancer types at varying frequencies and have different activities in cell fate control. On the plasma membrane, Ras proteins are laterally segregated into isoform-specific nanoscale signaling hubs, termed nanoclusters. As Ras nanoclusters are required for Ras signaling, chemical modulators of nanoclusters represent ideal candidates for the specific modulation of Ras activity in cancer drug development. We therefore conducted a chemical screen with commercial and in-house natural product libraries using a cell-based H-ras-nanoclustering FRET assay. Next to established Ras inhibitors, such as a statin and farnesyl-transferase inhibitor, we surprisingly identified five protein synthesis inhibitors as positive regulators. Using commonly employed cycloheximide as a representative compound, we show that protein synthesis inhibition increased nanoclustering and effector recruitment specifically of active H-ras but not of K-ras. Consistent with these data, cycloheximide treatment activated both Erk and Akt kinases and specifically promoted H-rasG12V-induced, but not K-rasG12V-induced, PC12 cell differentiation. Intriguingly, cycloheximide increased the number of mammospheres, which are enriched for cancer stem cells. Depletion of H-ras in combination with cycloheximide significantly reduced mammosphere formation, suggesting an exquisite synthetic lethality. The potential of cycloheximide to promote tumor cell growth was also reflected in its ability to increase breast cancer cell tumors grown in ovo. These results illustrate the possibility of identifying Ras-isoform-specific modulators using nanocluster-directed screening. They also suggest an unexpected feedback from protein synthesis inhibition to Ras signaling, which might present a vulnerability in certain tumor cell types.

Coupling genetics and proteomics to identify aphid proteins associated with vector-specific transmission of polerovirus (luteoviridae).

PubMed

Yang, Xiaolong; Thannhauser, T W; Burrows, Mary; Cox-Foster, Diana; Gildow, Fred E; Gray, Stewart M

2008-01-01

Cereal yellow dwarf virus-RPV (CYDV-RPV) is transmitted specifically by the aphids Rhopalosiphum padi and Schizaphis graminum in a circulative nonpropagative manner. The high level of vector specificity results from the vector aphids having the functional components of the receptor-mediated endocytotic pathways to allow virus to transverse the gut and salivary tissues. Studies of F(2) progeny from crosses of vector and nonvector genotypes of S. graminum showed that virus transmission efficiency is a heritable trait regulated by multiple genes acting in an additive fashion and that gut- and salivary gland-associated factors are not genetically linked. Utilizing two-dimensional difference gel electrophoresis to compare the proteomes of vector and nonvector parental and F(2) genotypes, four aphid proteins (S4, S8, S29, and S405) were specifically associated with the ability of S. graminum to transmit CYDV-RPV. The four proteins were coimmunoprecipitated with purified RPV, indicating that the aphid proteins are capable of binding to virus. Analysis by mass spectrometry identified S4 as a luciferase and S29 as a cyclophilin, both of which have been implicated in macromolecular transport. Proteins S8 and S405 were not identified from available databases. Study of this unique genetic system coupled with proteomic analysis indicated that these four virus-binding aphid proteins were specifically inherited and conserved in different generations of vector genotypes and suggests that they play a major role in regulating polerovirus transmission.

Discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is a novel biomarker of myxofibrosarcoma invasion identified by global protein expression profiling.

PubMed

Kikuta, Kazutaka; Kubota, Daisuke; Yoshida, Akihiko; Qiao, Zhiwei; Morioka, Hideo; Nakamura, Masaya; Matsumoto, Morio; Chuman, Hirokazu; Kawai, Akira; Kondo, Tadashi

2017-09-01

Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application. Copyright © 2017 Elsevier B.V. All rights reserved.

The use of functional chemical-protein associations to identify multi-pathway renoprotectants.

PubMed

Xu, Jia; Meng, Kexin; Zhang, Rui; Yang, He; Liao, Chang; Zhu, Wenliang; Jiao, Jundong

2014-01-01

Typically, most nephropathies can be categorized as complex human diseases in which the cumulative effect of multiple minor genes, combined with environmental and lifestyle factors, determines the disease phenotype. Thus, multi-target drugs would be more likely to facilitate comprehensive renoprotection than single-target agents. In this study, functional chemical-protein association analysis was performed to retrieve multi-target drugs of high pathway wideness from the STITCH 3.1 database. Pathway wideness of a drug evaluated the efficiency of regulation of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in quantity. We identified nine experimentally validated renoprotectants that exerted remarkable impact on KEGG pathways by targeting a limited number of proteins. We selected curcumin as an illustrative compound to display the advantage of multi-pathway drugs on renoprotection. We compared curcumin with hemin, an agonist of heme oxygenase-1 (HO-1), which significantly affects only one KEGG pathway, porphyrin and chlorophyll metabolism (adjusted p = 1.5×10-5). At the same concentration (10 µM), both curcumin and hemin equivalently mitigated oxidative stress in H2O2-treated glomerular mesangial cells. The benefit of using hemin was derived from its agonistic effect on HO-1, providing relief from oxidative stress. Selective inhibition of HO-1 completely blocked the action of hemin but not that of curcumin, suggesting simultaneous multi-pathway intervention by curcumin. Curcumin also increased cellular autophagy levels, enhancing its protective effect; however, hemin had no effects. Based on the fact that the dysregulation of multiple pathways is implicated in the etiology of complex diseases, we proposed a feasible method for identifying multi-pathway drugs from compounds with validated targets. Our efforts will help identify multi-pathway agents capable of providing comprehensive protection against renal injuries.

iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition.

PubMed

Feng, Peng-Mian; Chen, Wei; Lin, Hao; Chou, Kuo-Chen

2013-11-01

Heat shock proteins (HSPs) are a type of functionally related proteins present in all living organisms, both prokaryotes and eukaryotes. They play essential roles in protein-protein interactions such as folding and assisting in the establishment of proper protein conformation and prevention of unwanted protein aggregation. Their dysfunction may cause various life-threatening disorders, such as Parkinson's, Alzheimer's, and cardiovascular diseases. Based on their functions, HSPs are usually classified into six families: (i) HSP20 or sHSP, (ii) HSP40 or J-class proteins, (iii) HSP60 or GroEL/ES, (iv) HSP70, (v) HSP90, and (vi) HSP100. Although considerable progress has been achieved in discriminating HSPs from other proteins, it is still a big challenge to identify HSPs among their six different functional types according to their sequence information alone. With the avalanche of protein sequences generated in the post-genomic age, it is highly desirable to develop a high-throughput computational tool in this regard. To take up such a challenge, a predictor called iHSP-PseRAAAC has been developed by incorporating the reduced amino acid alphabet information into the general form of pseudo amino acid composition. One of the remarkable advantages of introducing the reduced amino acid alphabet is being able to avoid the notorious dimension disaster or overfitting problem in statistical prediction. It was observed that the overall success rate achieved by iHSP-PseRAAAC in identifying the functional types of HSPs among the aforementioned six types was more than 87%, which was derived by the jackknife test on a stringent benchmark dataset in which none of HSPs included has ≥40% pairwise sequence identity to any other in the same subset. It has not escaped our notice that the reduced amino acid alphabet approach can also be used to investigate other protein classification problems. As a user-friendly web server, iHSP-PseRAAAC is accessible to the public at http

Quantitative proteomics identifies altered O-GlcNAcylation of structural, synaptic and memory-associated proteins in Alzheimer's disease: Brain protein O-GlcNAcylation in Alzheimer's disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Sheng; Yang, Feng; Petyuk, Vladislav A.

Protein modification by O-linked beta-N-acetylglucosamine (O-GlcNAc) is emerging as an important factor in the pathogenesis of sporadic Alzheimer’s disease. Herein we report the most comprehensive, quantitative proteomics analysis for protein O-GlcNAcylation in post-mortem human brains with and without Alzheimer’s using isobaric tandem mass tags labeling, chemoenzymatic photocleavage enrichment and liquid chromatography coupled to mass spectrometry. A total of 1,850 O-GlcNAc peptides covering 1,094 O-GlcNAcylation sites were identified from 530 proteins in the human brain. 128 O-GlcNAc peptides covering 78 proteins were altered significantly in Alzheimer’s brain as compared to controls (q<0.05). Moreover, alteration of the O-GlcNAc peptide abundance could bemore » attributed more to O-GlcNAcylation level than to protein level changes. The altered O-GlcNAcylated proteins belong to several structural and functional categories, including synaptic proteins, cytoskeleton proteins, and memory-associated proteins. These findings suggest that dysregulation of O-GlcNAcylation of multiple brain proteins may be involved in the development of sporadic Alzheimer’s disease.« less

Small-molecule inhibitors of phosphatidylcholine transfer protein/StarD2 identified by high-throughput screening.

PubMed

Wagle, Neil; Xian, Jun; Shishova, Ekaterina Y; Wei, Jie; Glicksman, Marcie A; Cuny, Gregory D; Stein, Ross L; Cohen, David E

2008-12-01

Phosphatidylcholine transfer protein (PC-TP, also referred to as StarD2) is a highly specific intracellular lipid-binding protein that catalyzes the transfer of phosphatidylcholines between membranes in vitro. Recent studies have suggested that PC-TP in vivo functions to regulate fatty acid and glucose metabolism, possibly via interactions with selected other proteins. To begin to address the relationship between activity in vitro and biological function, we undertook a high-throughput screen to identify small-molecule inhibitors of the phosphatidylcholine transfer activity of PC-TP. After adapting a fluorescence quench assay to measure phosphatidylcholine transfer activity, we screened 114,752 compounds of a small-molecule library. The high-throughput screen identified 14 potential PC-TP inhibitors. Of these, 6 compounds exhibited characteristics consistent with specific inhibition of PC-TP activity, with IC(50) values that ranged from 4.1 to 95.0muM under conditions of the in vitro assay. These compounds should serve as valuable reagents to elucidate the biological function of PC-TP. Because mice with homozygous disruption of the PC-TP gene (Pctp) are sensitized to insulin action and relatively resistant to the development of atherosclerosis, these inhibitors may also prove to be of value in the management of diabetes and atherosclerotic cardiovascular diseases.

Cell cycle, oncogenic and tumor suppressor pathways regulate numerous long and macro non-protein-coding RNAs

PubMed Central

2014-01-01

Background The genome is pervasively transcribed but most transcripts do not code for proteins, constituting non-protein-coding RNAs. Despite increasing numbers of functional reports of individual long non-coding RNAs (lncRNAs), assessing the extent of functionality among the non-coding transcriptional output of mammalian cells remains intricate. In the protein-coding world, transcripts differentially expressed in the context of processes essential for the survival of multicellular organisms have been instrumental in the discovery of functionally relevant proteins and their deregulation is frequently associated with diseases. We therefore systematically identified lncRNAs expressed differentially in response to oncologically relevant processes and cell-cycle, p53 and STAT3 pathways, using tiling arrays. Results We found that up to 80% of the pathway-triggered transcriptional responses are non-coding. Among these we identified very large macroRNAs with pathway-specific expression patterns and demonstrated that these are likely continuous transcripts. MacroRNAs contain elements conserved in mammals and sauropsids, which in part exhibit conserved RNA secondary structure. Comparing evolutionary rates of a macroRNA to adjacent protein-coding genes suggests a local action of the transcript. Finally, in different grades of astrocytoma, a tumor disease unrelated to the initially used cell lines, macroRNAs are differentially expressed. Conclusions It has been shown previously that the majority of expressed non-ribosomal transcripts are non-coding. We now conclude that differential expression triggered by signaling pathways gives rise to a similar abundance of non-coding content. It is thus unlikely that the prevalence of non-coding transcripts in the cell is a trivial consequence of leaky or random transcription events. PMID:24594072

Quantitative phosphoproteomics identifies SnRK2 protein kinase substrates and reveals the effectors of abscisic acid action.

PubMed

Wang, Pengcheng; Xue, Liang; Batelli, Giorgia; Lee, Shinyoung; Hou, Yueh-Ju; Van Oosten, Michael J; Zhang, Huiming; Tao, W Andy; Zhu, Jian-Kang

2013-07-02

Sucrose nonfermenting 1 (SNF1)-related protein kinase 2s (SnRK2s) are central components of abscisic acid (ABA) signaling pathways. The snrk2.2/2.3/2.6 triple-mutant plants are nearly completely insensitive to ABA, suggesting that most of the molecular actions of ABA are triggered by the SnRK2s-mediated phosphorylation of substrate proteins. Only a few substrate proteins of the SnRK2s are known. To identify additional substrate proteins of the SnRK2s and provide insight into the molecular actions of ABA, we used quantitative phosphoproteomics to compare the global changes in phosphopeptides in WT and snrk2.2/2.3/2.6 triple mutant seedlings in response to ABA treatment. Among the 5,386 unique phosphorylated peptides identified in this study, we found that ABA can increase the phosphorylation of 166 peptides and decrease the phosphorylation of 117 peptides in WT seedlings. In the snrk2.2/2.3/2.6 triple mutant, 84 of the 166 peptides, representing 58 proteins, could not be phosphorylated, or phosphorylation was not increased under ABA treatment. In vitro kinase assays suggest that most of the 58 proteins can serve as substrates of the SnRK2s. The SnRK2 substrates include proteins involved in flowering time regulation, RNA and DNA binding, miRNA and epigenetic regulation, signal transduction, chloroplast function, and many other cellular processes. Consistent with the SnRK2 phosphorylation of flowering time regulators, the snrk2.2/2.3/2.6 triple mutant flowered significantly earlier than WT. These results shed new light on the role of the SnRK2 protein kinases and on the downstream effectors of ABA action, and improve our understanding of plant responses to adverse environments.

Novel Mitochondria-Targeted Heat-Soluble Proteins Identified in the Anhydrobiotic Tardigrade Improve Osmotic Tolerance of Human Cells

PubMed Central

Tanaka, Sae; Tanaka, Junko; Miwa, Yoshihiro; Horikawa, Daiki D.; Katayama, Toshiaki; Arakawa, Kazuharu; Toyoda, Atsushi; Kubo, Takeo; Kunieda, Takekazu

2015-01-01

Tardigrades are able to tolerate almost complete dehydration through transition to a metabolically inactive state, called “anhydrobiosis”. Late Embryogenesis Abundant (LEA) proteins are heat-soluble proteins involved in the desiccation tolerance of many anhydrobiotic organisms. Tardigrades, Ramazzottius varieornatus, however, express predominantly tardigrade-unique heat-soluble proteins: CAHS (Cytoplasmic Abundant Heat Soluble) and SAHS (Secretory Abundant Heat Soluble) proteins, which are secreted or localized in most intracellular compartments, except the mitochondria. Although mitochondrial integrity is crucial to ensure cellular survival, protective molecules for mitochondria have remained elusive. Here, we identified two novel mitochondrial heat-soluble proteins, RvLEAM and MAHS (Mitochondrial Abundant Heat Soluble), as potent mitochondrial protectants from Ramazzottius varieornatus. RvLEAM is a group3 LEA protein and immunohistochemistry confirmed its mitochondrial localization in tardigrade cells. MAHS-green fluorescent protein fusion protein localized in human mitochondria and was heat-soluble in vitro, though no sequence similarity with other known proteins was found, and one region was conserved among tardigrades. Furthermore, we demonstrated that RvLEAM protein as well as MAHS protein improved the hyperosmotic tolerance of human cells. The findings of the present study revealed that tardigrade mitochondria contain at least two types of heat-soluble proteins that might have protective roles in water-deficient environments. PMID:25675104

Novel mitochondria-targeted heat-soluble proteins identified in the anhydrobiotic Tardigrade improve osmotic tolerance of human cells.

PubMed

Tanaka, Sae; Tanaka, Junko; Miwa, Yoshihiro; Horikawa, Daiki D; Katayama, Toshiaki; Arakawa, Kazuharu; Toyoda, Atsushi; Kubo, Takeo; Kunieda, Takekazu

2015-01-01

Tardigrades are able to tolerate almost complete dehydration through transition to a metabolically inactive state, called "anhydrobiosis". Late Embryogenesis Abundant (LEA) proteins are heat-soluble proteins involved in the desiccation tolerance of many anhydrobiotic organisms. Tardigrades, Ramazzottius varieornatus, however, express predominantly tardigrade-unique heat-soluble proteins: CAHS (Cytoplasmic Abundant Heat Soluble) and SAHS (Secretory Abundant Heat Soluble) proteins, which are secreted or localized in most intracellular compartments, except the mitochondria. Although mitochondrial integrity is crucial to ensure cellular survival, protective molecules for mitochondria have remained elusive. Here, we identified two novel mitochondrial heat-soluble proteins, RvLEAM and MAHS (Mitochondrial Abundant Heat Soluble), as potent mitochondrial protectants from Ramazzottius varieornatus. RvLEAM is a group3 LEA protein and immunohistochemistry confirmed its mitochondrial localization in tardigrade cells. MAHS-green fluorescent protein fusion protein localized in human mitochondria and was heat-soluble in vitro, though no sequence similarity with other known proteins was found, and one region was conserved among tardigrades. Furthermore, we demonstrated that RvLEAM protein as well as MAHS protein improved the hyperosmotic tolerance of human cells. The findings of the present study revealed that tardigrade mitochondria contain at least two types of heat-soluble proteins that might have protective roles in water-deficient environments.

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

PubMed Central

Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

2016-01-01

The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

Application of a proteomic approach to identify proteins associated with primary graft non-function after liver transplantation.

PubMed

Kornasiewicz, Oskar; Bojarczuk, Kamil; Bugajski, Marek; Golab, Jakub; Krawczyk, Marek

2012-10-01

Primary graft non-function (PNF) is a rare, life-threatening complication of liver transplantation. Increasing use of extended criteria donor pools and high-risk recipients seem to influence the incidence of PNF. Primary failure is associated with high patient morbidity and inferior graft survival. The only available treatment for PNF is emergency hepatic retransplantation, which is also correlated with significant morbidity and mortality. Therefore, researchers are working to identify risk factors of diagnostic value to prevent PNF. The current study attempted to explore liver proteomic patterns in patients with PNF. Using two-dimensional gel electrophoresis and liquid chromatography-mass spectrometry (LC-MS), we compared liver protein homogenates from 3 patients with PNF to those obtained from 6 healthy liver samples to identify potential new biomarkers of PNF. Our comparisons revealed 21 proteins with differential expression (13 upregulated and 8 downregulated). Most of these proteins are involved in energy metabolism, lipid metabolism, peptide cleavage, cell differentiation, and apoptosis. Although none of these proteins appeared more than once in separate analyses, this preliminary study shows that two-dimensional gel electrophoresis and LC-MS may allow identification of characteristic proteins to be used as biomarkers of a life-threatening complication of liver transplantation. Larger-scale analyses could improve patient care by finding suitable prognostic and therapeutic options. These data represent the first global proteomic approach to study PNF.

Systematic prediction of control proteins and their DNA binding sites

PubMed Central

Sorokin, Valeriy; Severinov, Konstantin; Gelfand, Mikhail S.

2009-01-01

We present here the results of a systematic bioinformatics analysis of control (C) proteins, a class of DNA-binding regulators that control time-delayed transcription of their own genes as well as restriction endonuclease genes in many type II restriction-modification systems. More than 290 C protein homologs were identified and DNA-binding sites for ∼70% of new and previously known C proteins were predicted by a combination of phylogenetic footprinting and motif searches in DNA upstream of C protein genes. Additional analysis revealed that a large proportion of C protein genes are translated from leaderless RNA, which may contribute to time-delayed nature of genetic switches operated by these proteins. Analysis of genetic contexts of newly identified C protein genes revealed that they are not exclusively associated with restriction-modification genes; numerous instances of associations with genes originating from mobile genetic elements were observed. These instances might be vestiges of ancient horizontal transfers and indicate that during evolution ancestral restriction-modification system genes were the sites of mobile elements insertions. PMID:19056824

Inducible gene expression and protein translocation using nontoxic ligands identified by a mammalian three-hybrid screen

PubMed Central

Liberles, Stephen D.; Diver, Steven T.; Austin, David J.; Schreiber, Stuart L.

1997-01-01

The natural product rapamycin has been used to provide temporal and quantitative control of gene expression in animals through its ability to interact with two proteins simultaneously. A shortcoming of this approach is that rapamycin is an inhibitor of cell proliferation, the result of binding to FKBP12–rapamycin-associated protein (FRAP). To overcome this limitation, nontoxic derivatives of rapamycin bearing bulky substituents at its C16-position were synthesized, each in a single step. The isosteric isopropoxy and methallyl substituents with the nonnatural C16-configuration abolish both binding to FRAP and inhibition of T cell proliferation. Binding proteins for these derivatives were identified from libraries of cDNAs encoding mutants of the FKBP12–rapamycin-binding (FRB) domain of FRAP by using a mammalian three-hybrid transcription assay. Targeting of the mutations was guided by the structure of the FKBP12-rapamycin–FRB ternary complex. Three compensatory mutations in the FRB domain, all along one face of an α-helix in a rapamycin-binding pocket, were identified that together restore binding of the rapamycin derivatives. Using this mutant FRB domain, one of the nontoxic rapamycin derivatives induced targeted gene expression in Jurkat T cells with an EC50 below 10 nM. Another derivative was used to recruit a cytosolic protein to the plasma membrane, mimicking a process involved in many signaling pathways. PMID:9223271

A screen of cell-surface molecules identifies leucine-rich repeat proteins as key mediators of synaptic target selection in the Drosophila neuromuscular system

PubMed Central

Kurusu, Mitsuhiko; Cording, Amy; Taniguchi, Misako; Menon, Kaushiki; Suzuki, Emiko; Zinn, Kai

2008-01-01

Summary In Drosophila embryos and larvae, a small number of identified motor neurons innervate body wall muscles in a highly stereotyped pattern. Although genetic screens have identified many proteins that are required for axon guidance and synaptogenesis in this system, little is known about the mechanisms by which muscle fibers are defined as targets for specific motor axons. To identify potential target labels, we screened 410 genes encoding cell-surface and secreted proteins, searching for those whose overexpression on all muscle fibers causes motor axons to make targeting errors. Thirty such genes were identified, and a number of these were members of a large gene family encoding proteins whose extracellular domains contain leucine-rich repeat (LRR) sequences, which are protein interaction modules. By manipulating gene expression in muscle 12, we showed that four LRR proteins participate in the selection of this muscle as the appropriate synaptic target for the RP5 motor neuron. PMID:18817735

A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115

Protein arginine methylation/demethylation and cancer

PubMed Central

Poulard, Coralie; Corbo, Laura; Le Romancer, Muriel

2016-01-01

Protein arginine methylation is a common post-translational modification involved in numerous cellular processes including transcription, DNA repair, mRNA splicing and signal transduction. Currently, there are nine known members of the protein arginine methyltransferase (PRMT) family, but only one arginine demethylase has been identified, namely the Jumonji domain-containing 6 (JMJD6). Although its demethylase activity was initially challenged, its dual activity as an arginine demethylase and a lysine hydroxylase is now recognized. Interestingly, a growing number of substrates for arginine methylation and demethylation play key roles in tumorigenesis. Though alterations in the sequence of these enzymes have not been identified in cancer, their overexpression is associated with various cancers, suggesting that they could constitute targets for therapeutic strategies. In this review, we present the recent knowledge of the involvement of PRMTs and JMJD6 in tumorigenesis. PMID:27556302

Proteomics approach to identify unique xylem sap proteins in Pierce's disease-tolerant Vitis species.

PubMed

Basha, Sheikh M; Mazhar, Hifza; Vasanthaiah, Hemanth K N

2010-03-01

Pierce's disease (PD) is a destructive bacterial disease of grapes caused by Xylella fastidiosa which is xylem-confined. The tolerance level to this disease varies among Vitis species. Our research was aimed at identifying unique xylem sap proteins present in PD-tolerant Vitis species. The results showed wide variation in the xylem sap protein composition, where a set of polypeptides with pI between 4.5 and 4.7 and M(r) of 31 kDa were present in abundant amount in muscadine (Vitis rotundifolia, PD-tolerant), in reduced levels in Florida hybrid bunch (Vitis spp., PD-tolerant) and absent in bunch grapes (Vitis vinifera, PD-susceptible). Liquid chromatography/mass spectrometry/mass spectrometry analysis of these proteins revealed their similarity to beta-1, 3-glucanase, peroxidase, and a subunit of oxygen-evolving enhancer protein 1, which are known to play role in defense and oxygen generation. In addition, the amount of free amino acids and soluble sugars was found to be significantly lower in xylem sap of muscadine genotypes compared to V. vinifera genotypes, indicating that the higher nutritional value of bunch grape sap may be more suitable for Xylella growth. These data suggest that the presence of these unique proteins in xylem sap is vital for PD tolerance in muscadine and Florida hybrid bunch grapes.

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

PubMed

Rawat, Puneet; Kumar, Sandeep; Michael Gromiha, M

2018-06-24

Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protein aggregates, amyloid fibrils and plaques. In-vitro experiments have shown that even single amino acid substitutions can drastically enhance or mitigate protein aggregation kinetics. In this work, we have collected a dataset of 220 unique mutations in 25 proteins and classified them as enhancers or mitigators on the basis of their effect on protein aggregation rate. The data were analyzed via machine learning to identify features capable of distinguishing between aggregation rate enhancers and mitigators. Our initial Support Vector Machine (SVM) model separated such mutations with an overall accuracy of 69%. When local secondary structures at the mutation sites were considered, the accuracies further improved by 13-15%. The machine-learnt features are distinct for each secondary structure class at mutation sites. Protein stability and flexibility changes are important features for mutations in α-helices. β-strand propensity, polarity and charge become important when mutations occur in β-strands and ability to form secondary structure, helical tendency and aggregation propensity are important for mutations lying in coils. These results have been incorporated into a sequence-based algorithm (available at http://www.iitm.ac.in/bioinfo/aggrerate-disc/) capable of predicting whether a mutation will enhance or mitigate a protein's aggregation rate. This algorithm will find several applications towards understanding protein aggregation in human diseases, enable in-silico optimization of biopharmaceuticals and enzymes for improved biophysical attributes and de novo design of bio-nanomaterials. Copyright © 2018. Published by Elsevier B.V.

Comparative genomic analysis identified a mutation related to enhanced heterologous protein production in the filamentous fungus Aspergillus oryzae.

PubMed

Jin, Feng-Jie; Katayama, Takuya; Maruyama, Jun-Ichi; Kitamoto, Katsuhiko

2016-11-01

Genomic mapping of mutations using next-generation sequencing technologies has facilitated the identification of genes contributing to fundamental biological processes, including human diseases. However, few studies have used this approach to identify mutations contributing to heterologous protein production in industrial strains of filamentous fungi, such as Aspergillus oryzae. In a screening of A. oryzae strains that hyper-produce human lysozyme (HLY), we previously isolated an AUT1 mutant that showed higher production of various heterologous proteins; however, the underlying factors contributing to the increased heterologous protein production remained unclear. Here, using a comparative genomic approach performed with whole-genome sequences, we attempted to identify the genes responsible for the high-level production of heterologous proteins in the AUT1 mutant. The comparative sequence analysis led to the detection of a gene (AO090120000003), designated autA, which was predicted to encode an unknown cytoplasmic protein containing an alpha/beta-hydrolase fold domain. Mutation or deletion of autA was associated with higher production levels of HLY. Specifically, the HLY yields of the autA mutant and deletion strains were twofold higher than that of the control strain during the early stages of cultivation. Taken together, these results indicate that combining classical mutagenesis approaches with comparative genomic analysis facilitates the identification of novel genes involved in heterologous protein production in filamentous fungi.

A Comparative Quantitative Proteomic Study Identifies New Proteins Relevant for Sulfur Oxidation in the Purple Sulfur Bacterium Allochromatium vinosum

PubMed Central

Weissgerber, Thomas; Sylvester, Marc; Kröninger, Lena

2014-01-01

In the present study, we compared the proteome response of Allochromatium vinosum when growing photoautotrophically in the presence of sulfide, thiosulfate, and elemental sulfur with the proteome response when the organism was growing photoheterotrophically on malate. Applying tandem mass tag analysis as well as two-dimensional (2D) PAGE, we detected 1,955 of the 3,302 predicted proteins by identification of at least two peptides (59.2%) and quantified 1,848 of the identified proteins. Altered relative protein amounts (≥1.5-fold) were observed for 385 proteins, corresponding to 20.8% of the quantified A. vinosum proteome. A significant number of the proteins exhibiting strongly enhanced relative protein levels in the presence of reduced sulfur compounds are well documented essential players during oxidative sulfur metabolism, e.g., the dissimilatory sulfite reductase DsrAB. Changes in protein levels generally matched those observed for the respective relative mRNA levels in a previous study and allowed identification of new genes/proteins participating in oxidative sulfur metabolism. One gene cluster (hyd; Alvin_2036-Alvin_2040) and one hypothetical protein (Alvin_2107) exhibiting strong responses on both the transcriptome and proteome levels were chosen for gene inactivation and phenotypic analyses of the respective mutant strains, which verified the importance of the so-called Isp hydrogenase supercomplex for efficient oxidation of sulfide and a crucial role of Alvin_2107 for the oxidation of sulfur stored in sulfur globules to sulfite. In addition, we analyzed the sulfur globule proteome and identified a new sulfur globule protein (SgpD; Alvin_2515). PMID:24487535

Integrated web visualizations for protein-protein interaction databases.

PubMed

Jeanquartier, Fleur; Jean-Quartier, Claire; Holzinger, Andreas

2015-06-16

Understanding living systems is crucial for curing diseases. To achieve this task we have to understand biological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of databases and tools that support analysts in exploring protein-protein interactions on an integrated level for knowledge discovery. They provide predictions and correlations, indicate possibilities for future experimental research and fill the gaps to complete the picture of biochemical processes. There are numerous and huge databases of protein-protein interactions used to gain insights into answering some of the many questions of systems biology. Many computational resources integrate interaction data with additional information on molecular background. However, the vast number of diverse Bioinformatics resources poses an obstacle to the goal of understanding. We present a survey of databases that enable the visual analysis of protein networks. We selected M=10 out of N=53 resources supporting visualization, and we tested against the following set of criteria: interoperability, data integration, quantity of possible interactions, data visualization quality and data coverage. The study reveals differences in usability, visualization features and quality as well as the quantity of interactions. StringDB is the recommended first choice. CPDB presents a comprehensive dataset and IntAct lets the user change the network layout. A comprehensive comparison table is available via web. The supplementary table can be accessed on http://tinyurl.com/PPI-DB-Comparison-2015. Only some web resources featuring graph visualization can be successfully applied to interactive visual analysis of protein-protein interaction. Study results underline the necessity for further enhancements of visualization integration in biochemical analysis tools. Identified challenges are data comprehensiveness, confidence, interactive feature and visualization maturing.

Protein – Which is Best?

PubMed Central

Hoffman, Jay R.; Falvo, Michael J.

2004-01-01

Protein intake that exceeds the recommended daily allowance is widely accepted for both endurance and power athletes. However, considering the variety of proteins that are available much less is known concerning the benefits of consuming one protein versus another. The purpose of this paper is to identify and analyze key factors in order to make responsible recommendations to both the general and athletic populations. Evaluation of a protein is fundamental in determining its appropriateness in the human diet. Proteins that are of inferior content and digestibility are important to recognize and restrict or limit in the diet. Similarly, such knowledge will provide an ability to identify proteins that provide the greatest benefit and should be consumed. The various techniques utilized to rate protein will be discussed. Traditionally, sources of dietary protein are seen as either being of animal or vegetable origin. Animal sources provide a complete source of protein (i.e. containing all essential amino acids), whereas vegetable sources generally lack one or more of the essential amino acids. Animal sources of dietary protein, despite providing a complete protein and numerous vitamins and minerals, have some health professionals concerned about the amount of saturated fat common in these foods compared to vegetable sources. The advent of processing techniques has shifted some of this attention and ignited the sports supplement marketplace with derivative products such as whey, casein and soy. Individually, these products vary in quality and applicability to certain populations. The benefits that these particular proteins possess are discussed. In addition, the impact that elevated protein consumption has on health and safety issues (i.e. bone health, renal function) are also reviewed. Key Points Higher protein needs are seen in athletic populations. Animal proteins is an important source of protein, however potential health concerns do exist from a diet of protein

CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts

PubMed Central

Hafsa, Noor E.; Arndt, David; Wishart, David S.

2015-01-01

The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I′, II′ and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0. PMID:25979265

CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts.

PubMed

Hafsa, Noor E; Arndt, David; Wishart, David S

2015-07-01

The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I', II' and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

Evaluation of the protective efficacy of four novel identified membrane associated proteins of Streptococcus suis serotype 2.

PubMed

Zhou, Yang; Wang, Yan; Deng, Limei; Zheng, Chengkun; Yuan, Fangyan; Chen, Huanchun; Bei, Weicheng; Li, Jinquan

2015-05-05

Streptococcus suis serotype 2 (S. suis 2) is an important zoonotic pathogen that can also cause epidemics of life-threatening infections in humans. Surface proteins of pathogens play a critical role in the interaction with host system or environment, as they take part in processes like virulence, cytotoxicity, adhesion, signaling or transport, etc. Thus, surface proteins identified by the screening of immunoproteomic techniques are promising vaccine candidates or diagnostic markers. In this study, four membrane associated proteins (MAP) identified by immunoproteomic method were cloned and expressed as recombinant proteins with his-tag. Screening for vaccine candidates were firstly performed by protection assay in vivo and immunization with Sbp markedly protected mice against systemic S. suis 2 infection. The immune responses and protective of Sbp were further evaluated. The results showed that Sbp could elicit a strong humoral antibody response and protect mice from lethal challenge with S. suis 2. The antiserum against Sbp could efficiently impede survival of bacterial in whole blood killing assay and conferred significant protection against S. suis 2 infection in passive immunization assays. The findings indicate that Sbp may serve as an important factor in the pathogenesis of S. suis 2 and would be a promising subunit vaccine candidate. Copyright © 2015 Elsevier Ltd. All rights reserved.

sc-PDB: a database for identifying variations and multiplicity of 'druggable' binding sites in proteins.

PubMed

Meslamani, Jamel; Rognan, Didier; Kellenberger, Esther

2011-05-01

The sc-PDB database is an annotated archive of druggable binding sites extracted from the Protein Data Bank. It contains all-atoms coordinates for 8166 protein-ligand complexes, chosen for their geometrical and physico-chemical properties. The sc-PDB provides a functional annotation for proteins, a chemical description for ligands and the detailed intermolecular interactions for complexes. The sc-PDB now includes a hierarchical classification of all the binding sites within a functional class. The sc-PDB entries were first clustered according to the protein name indifferent of the species. For each cluster, we identified dissimilar sites (e.g. catalytic and allosteric sites of an enzyme). SCOPE AND APPLICATIONS: The classification of sc-PDB targets by binding site diversity was intended to facilitate chemogenomics approaches to drug design. In ligand-based approaches, it avoids comparing ligands that do not share the same binding site. In structure-based approaches, it permits to quantitatively evaluate the diversity of the binding site definition (variations in size, sequence and/or structure). The sc-PDB database is freely available at: http://bioinfo-pharma.u-strasbg.fr/scPDB.

Coupling Genetics and Proteomics To Identify Aphid Proteins Associated with Vector-Specific Transmission of Polerovirus (Luteoviridae)▿

PubMed Central

Yang, Xiaolong; Thannhauser, T. W.; Burrows, Mary; Cox-Foster, Diana; Gildow, Fred E.; Gray, Stewart M.

2008-01-01

Cereal yellow dwarf virus-RPV (CYDV-RPV) is transmitted specifically by the aphids Rhopalosiphum padi and Schizaphis graminum in a circulative nonpropagative manner. The high level of vector specificity results from the vector aphids having the functional components of the receptor-mediated endocytotic pathways to allow virus to transverse the gut and salivary tissues. Studies of F2 progeny from crosses of vector and nonvector genotypes of S. graminum showed that virus transmission efficiency is a heritable trait regulated by multiple genes acting in an additive fashion and that gut- and salivary gland-associated factors are not genetically linked. Utilizing two-dimensional difference gel electrophoresis to compare the proteomes of vector and nonvector parental and F2 genotypes, four aphid proteins (S4, S8, S29, and S405) were specifically associated with the ability of S. graminum to transmit CYDV-RPV. The four proteins were coimmunoprecipitated with purified RPV, indicating that the aphid proteins are capable of binding to virus. Analysis by mass spectrometry identified S4 as a luciferase and S29 as a cyclophilin, both of which have been implicated in macromolecular transport. Proteins S8 and S405 were not identified from available databases. Study of this unique genetic system coupled with proteomic analysis indicated that these four virus-binding aphid proteins were specifically inherited and conserved in different generations of vector genotypes and suggests that they play a major role in regulating polerovirus transmission. PMID:17959668

Identifying Ca2+-Binding Sites in Proteins by Liquid Chromatography-Mass Spectrometry Using Ca2+-Directed Dissociations

PubMed Central

Jamalian, Azadeh; Sneekes, Evert-Jan; Wienk, Hans; Dekker, Lennard J. M.; Ruttink, Paul J. A.; Ursem, Mario; Luider, Theo M.; Burgers, Peter C.

2014-01-01

Here we describe a new method to identify calcium-binding sites in proteins using high-resolution liquid chromatography-mass spectrometry in concert with calcium-directed collision-induced dissociations. Our method does not require any modifications to the liquid chromatography-mass spectrometry apparatus, uses standard digestion protocols, and can be applied to existing high-resolution MS data files. In contrast to NMR, our method is applicable to very small amounts of complex protein mixtures (femtomole level). Calcium-bound peptides can be identified using three criteria: (1) the calculated exact mass of the calcium containing peptide; (2) specific dissociations of the calcium-containing peptide from threonine and serine residues; and (3) the very similar retention times of the calcium-containing peptide and the free peptide. PMID:25023127

Mapping of Chikungunya Virus Interactions with Host Proteins Identified nsP2 as a Highly Connected Viral Component

PubMed Central

Bouraï, Mehdi; Lucas-Hourani, Marianne; Gad, Hans Henrik; Drosten, Christian; Jacob, Yves; Tafforeau, Lionel; Cassonnet, Patricia; Jones, Louis M.; Judith, Delphine; Couderc, Thérèse; Lecuit, Marc; André, Patrice; Kümmerer, Beate Mareike; Lotteau, Vincent; Desprès, Philippe; Vidalain, Pierre-Olivier

2012-01-01

Chikungunya virus (CHIKV) is a mosquito-transmitted alphavirus that has been responsible for an epidemic outbreak of unprecedented magnitude in recent years. Since then, significant efforts have been made to better understand the biology of this virus, but we still have poor knowledge of CHIKV interactions with host cell components at the molecular level. Here we describe the extensive use of high-throughput yeast two-hybrid (HT-Y2H) assays to characterize interactions between CHIKV and human proteins. A total of 22 high-confidence interactions, which essentially involved the viral nonstructural protein nsP2, were identified and further validated in protein complementation assay (PCA). These results were integrated to a larger network obtained by extensive mining of the literature for reports on alphavirus-host interactions. To investigate the role of cellular proteins interacting with nsP2, gene silencing experiments were performed in cells infected by a recombinant CHIKV expressing Renilla luciferase as a reporter. Collected data showed that heterogeneous nuclear ribonucleoprotein K (hnRNP-K) and ubiquilin 4 (UBQLN4) participate in CHIKV replication in vitro. In addition, we showed that CHIKV nsP2 induces a cellular shutoff, as previously reported for other Old World alphaviruses, and determined that among binding partners identified by yeast two-hybrid methods, the tetratricopeptide repeat protein 7B (TTC7B) plays a significant role in this activity. Altogether, this report provides the first interaction map between CHIKV and human proteins and describes new host cell proteins involved in the replication cycle of this virus. PMID:22258240

Quantitative Proteomic Analysis of the Influenza A Virus Nonstructural Proteins NS1 and NS2 during Natural Cell Infection Identifies PACT as an NS1 Target Protein and Antiviral Host Factor

PubMed Central

Tawaratsumida, Kazuki; Phan, Van; Hrincius, Eike R.; High, Anthony A.; Webby, Richard; Redecke, Vanessa

2014-01-01

ABSTRACT Influenza A virus (IAV) replication depends on the interaction of virus proteins with host factors. The viral nonstructural protein 1 (NS1) is essential in this process by targeting diverse cellular functions, including mRNA splicing and translation, cell survival, and immune defense, in particular the type I interferon (IFN-I) response. In order to identify host proteins targeted by NS1, we established a replication-competent recombinant IAV that expresses epitope-tagged forms of NS1 and NS2, which are encoded by the same gene segment, allowing purification of NS proteins during natural cell infection and analysis of interacting proteins by quantitative mass spectrometry. We identified known NS1- and NS2-interacting proteins but also uncharacterized proteins, including PACT, an important cofactor for the IFN-I response triggered by the viral RNA-sensor RIG-I. We show here that NS1 binds PACT during virus replication and blocks PACT/RIG-I-mediated activation of IFN-I, which represents a critical event for the host defense. Protein interaction and interference with IFN-I activation depended on the functional integrity of the highly conserved RNA binding domain of NS1. A mutant virus with deletion of NS1 induced high levels of IFN-I in control cells, as expected; in contrast, shRNA-mediated knockdown of PACT compromised IFN-I activation by the mutant virus, but not wild-type virus, a finding consistent with the interpretation that PACT (i) is essential for IAV recognition and (ii) is functionally compromised by NS1. Together, our data describe a novel approach to identify virus-host protein interactions and demonstrate that NS1 interferes with PACT, whose function is critical for robust IFN-I production. IMPORTANCE Influenza A virus (IAV) is an important human pathogen that is responsible for annual epidemics and occasional devastating pandemics. Viral replication and pathogenicity depends on the interference of viral factors with components of the host

Whole Wiskott‑Aldrich syndrome protein gene deletion identified by high throughput sequencing.

PubMed

He, Xiangling; Zou, Runying; Zhang, Bing; You, Yalan; Yang, Yang; Tian, Xin

2017-11-01

Wiskott‑Aldrich syndrome (WAS) is a rare X‑linked recessive immunodeficiency disorder, characterized by thrombocytopenia, small platelets, eczema and recurrent infections associated with increased risk of autoimmunity and malignancy disorders. Mutations in the WAS protein (WASP) gene are responsible for WAS. To date, WASP mutations, including missense/nonsense, splicing, small deletions, small insertions, gross deletions, and gross insertions have been identified in patients with WAS. In addition, WASP‑interacting proteins are suspected in patients with clinical features of WAS, in whom the WASP gene sequence and mRNA levels are normal. The present study aimed to investigate the application of next generation sequencing in definitive diagnosis and clinical therapy for WAS. A 5 month‑old child with WAS who displayed symptoms of thrombocytopenia was examined. Whole exome sequence analysis of genomic DNA showed that the coverage and depth of WASP were extremely low. Quantitative polymerase chain reaction indicated total WASP gene deletion in the proband. In conclusion, high throughput sequencing is useful for the verification of WAS on the genetic profile, and has implications for family planning guidance and establishment of clinical programs.

β-Filagenin, a Newly Identified Protein Coassembling with Myosin and Paramyosin in Caenorhabditis elegans

PubMed Central

Liu, Feizhou; Bauer, Christopher C.; Ortiz, Irving; Cook, Richard G.; Schmid, Michael F.; Epstein, Henry F.

1998-01-01

Muscle thick filaments are stable assemblies of myosin and associated proteins whose dimensions are precisely regulated. The mechanisms underlying the stability and regulation of the assembly are not understood. As an approach to these problems, we have studied the core proteins that, together with paramyosin, form the core structure of the thick filament backbone in the nematode Caenorhabditis elegans. We obtained partial peptide sequences from one of the core proteins, β-filagenin, and then identified a gene that encodes a novel protein of 201–amino acid residues from databases using these sequences. β-Filagenin has a calculated isoelectric point at 10.61 and a high percentage of aromatic amino acids. Secondary structure algorithms predict that it consists of four β-strands but no α-helices. Western blotting using an affinity-purified antibody showed that β-filagenin was associated with the cores. β-Filagenin was localized by immunofluorescence microscopy to the A bands of body–wall muscles, but not the pharynx. β-filagenin assembled with the myosin homologue paramyosin into the tubular cores of wild-type nematodes at a periodicity matching the 72-nm repeats of paramyosin, as revealed by immunoelectron microscopy. In CB1214 mutants where paramyosin is absent, β-filagenin assembled with myosin to form abnormal tubular filaments with a periodicity identical to wild type. These results verify that β-filagenin is a core protein that coassembles with either myosin or paramyosin in C. elegans to form tubular filaments. PMID:9442110

Molecular characterization and functional analysis of PR-1-like proteins identified from the wheat head blight fungus Fusarium graminearum

USDA-ARS?s Scientific Manuscript database

The group 1 pathogenesis-related (PR-1) proteins originally identified from plants and their homologues are also found in other eukaryotic kingdoms. Studies on non-plant PR-1-like (PR-1L) proteins have been pursued widely in humans/animals but rarely in filamentous ascomycetes. Here we report the ch...

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer.

PubMed

Bhuripanyo, Karan; Wang, Yiyang; Liu, Xianpeng; Zhou, Li; Liu, Ruochuan; Duong, Duc; Zhao, Bo; Bi, Yingtao; Zhou, Han; Chen, Geng; Seyfried, Nicholas T; Chazin, Walter J; Kiyokawa, Hiroaki; Yin, Jun

2018-01-01

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct "orthogonal UB transfer (OUT)" cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N -methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and β-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress.

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer

PubMed Central

Bhuripanyo, Karan; Wang, Yiyang; Liu, Xianpeng; Zhou, Li; Liu, Ruochuan; Duong, Duc; Zhao, Bo; Bi, Yingtao; Zhou, Han; Chen, Geng; Seyfried, Nicholas T.; Chazin, Walter J.; Kiyokawa, Hiroaki; Yin, Jun

2018-01-01

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct “orthogonal UB transfer (OUT)” cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N-methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and β-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress. PMID:29326975

A Modified MuDPIT Separation Identified 4,488 Proteins in a System Wide Analysis of Quiescence in Yeast

PubMed Central

Webb, Kristofor J.; Xu, Tao; Park, Sung Kyu; Yates, John R.

2013-01-01

A modified multidimensional protein identification technology (MudPIT) separation was coupled to an LTQ Orbitrap Velos mass spectrometer and used to rapidly identify the near complete yeast proteome from a whole cell tryptic digest. This modified on-line two dimensional liquid chromatography separation consists of 39 strong cation exchange steps followed by a short 18.5 min reversed-phase (RP) gradient. A total of 4,269 protein identifications were made from 4,189 distinguishable protein families from yeast during log phase growth. The “Micro” MudPIT separation performed as well as a standard MudPIT separation in 40% less gradient time. The majority of the yeast proteome can now be routinely covered in less than a days’ time with high reproducibility and sensitivity. The newly devised separation method was used to detect changes in protein expression during cellular quiescence in yeast. An enrichment in the GO annotations ‘oxidation reduction’, ‘catabolic processing’ and ‘cellular response to oxidative stress’ was seen in the quiescent cellular fraction, consistent with their long lived stress resistant phenotypes. Heterogeneity was observed in the stationary phase fraction with a less dense cell population showing reductions in KEGG pathway categories of ‘Ribosome’ and ‘Proteasome’, further defining the complex nature of yeast populations present during stationary phase growth. In total 4,488 distinguishable protein families were identified in all cellular conditions tested. PMID:23540446

A Matter of Timing: Identifying Significant Multi-Dose Radiotherapy Improvements by Numerical Simulation and Genetic Algorithm Search

PubMed Central

Angus, Simon D.; Piotrowska, Monika Joanna

2014-01-01

Multi-dose radiotherapy protocols (fraction dose and timing) currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA) techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5%) and 7.1% (13.3%) improvement (reduction) on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h), leading to the discovery that the performance of the GA search candidates could be replicated by 17–18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost

A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

PubMed

Angus, Simon D; Piotrowska, Monika Joanna

2014-01-01

Multi-dose radiotherapy protocols (fraction dose and timing) currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA) techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5%) and 7.1% (13.3%) improvement (reduction) on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h), leading to the discovery that the performance of the GA search candidates could be replicated by 17-18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost-effecitive means

Quantitative proteomics identifies altered O-GlcNAcylation of structural, synaptic and memory-associated proteins in Alzheimer's disease.

PubMed

Wang, Sheng; Yang, Feng; Petyuk, Vladislav A; Shukla, Anil K; Monroe, Matthew E; Gritsenko, Marina A; Rodland, Karin D; Smith, Richard D; Qian, Wei-Jun; Gong, Cheng-Xin; Liu, Tao

2017-09-01

Protein modification by O-linked β-N-acetylglucosamine (O-GlcNAc) is emerging as an important factor in the pathogenesis of sporadic Alzheimer's disease (AD); however, detailed molecular characterization of this important protein post-translational modification at the proteome level has been highly challenging, owing to its low stoichiometry and labile nature. Herein, we report the most comprehensive, quantitative proteomics analysis for protein O-GlcNAcylation in postmortem human brain tissues with and without AD by the use of isobaric tandem mass tag labelling, chemoenzymatic photocleavage enrichment, and liquid chromatography coupled to mass spectrometry. A total of 1850 O-GlcNAc peptides covering 1094 O-GlcNAcylation sites were identified from 530 proteins in the human brain. One hundred and thirty-one O-GlcNAc peptides covering 81 proteins were altered in AD brains as compared with controls (q < 0.05). Moreover, alteration of O-GlcNAc peptide abundance could be attributed more to O-GlcNAcylation level than to protein level changes. The altered O-GlcNAcylated proteins belong to several structural and functional categories, including synaptic proteins, cytoskeleton proteins, and memory-associated proteins. These findings suggest that dysregulation of O-GlcNAcylation of multiple brain proteins may be involved in the development of sporadic AD. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Identifying reliable predictors of protein-energy malnutrition in hospitalized frail older adults: A prospective longitudinal study.

PubMed

Sanson, Gianfranco; Bertocchi, Luca; Dal Bo, Eugenia; Di Pasquale, Carmen Luisa; Zanetti, Michela

2018-06-01

Decreased food intake is a risk factor for relevant complications (e.g. infections, pressure ulcers), longer hospital stays, higher readmission rates, greater health care costs and increased patient mortality, particularly in frail hospitalized older adults who are malnourished or at risk of malnutrition. Nurses are called to improve this criticality, starting from accurately identifying malnourished patients at hospital admission and effectively monitoring their food intake. The primary aim was to identify reliable predictive indicators of reduced food intake at hospital admission. The secondary aims were to assess the adequacy of daily energy and protein intake and the impact of nutrient intake on patient outcomes. Prospective observational longitudinal study. Internal Medicine Ward of an Academic Teaching University Hospital. Acute older adults who were malnourished or at risk of malnutrition (Nutritional Risk Score-2002 ≥ 3, middle-upper arm circumference <23.5 cm or impaired self-feeding ability) at admission. The effective energy and protein intake was monitored during the first 5 days of hospital stay by a photographic method and compared to the daily energy and protein requirement calculated by specific equations. Data on anthropometry, inflammation/malnutrition laboratory data and body composition (phase angle calculated using bioelectrical impedance analysis) were collected. Eighty-one subjects (age 81.5 ± 11.5 years) were enrolled. Mean energy intake was 669.0 ± 573.9 kcal/day, and mean protein intake was 30.7 ± 25.8 g/day. Over 60% of patients ingested ≤50% of their calculated energy and protein requirements: these patients were older (p = 0.026), had a lower middle-upper arm circumference (p = 0.022) and total arm area (p = 0.038), a higher C-reactive protein/albumin ratio and Instant Nutritional Assessment score (p < 0.01), and experienced longer hospital stays (p ≤ 0.04) and higher in

Proteomic Analysis of Rhizoctonia solani Identifies Infection-specific, Redox Associated Proteins and Insight into Adaptation to Different Plant Hosts*

PubMed Central

Anderson, Jonathan P.; Hane, James K.; Stoll, Thomas; Pain, Nicholas; Hastie, Marcus L.; Kaur, Parwinder; Hoogland, Christine; Gorman, Jeffrey J.; Singh, Karam B.

2016-01-01

Rhizoctonia solani is an important root infecting pathogen of a range of food staples worldwide including wheat, rice, maize, soybean, potato and others. Conventional resistance breeding strategies are hindered by the absence of tractable genetic resistance in any crop host. Understanding the biology and pathogenicity mechanisms of this fungus is important for addressing these disease issues, however, little is known about how R. solani causes disease. This study capitalizes on recent genomic studies by applying mass spectrometry based proteomics to identify soluble, membrane-bound and culture filtrate proteins produced under wheat infection and vegetative growth conditions. Many of the proteins found in the culture filtrate had predicted functions relating to modification of the plant cell wall, a major activity required for pathogenesis on the plant host, including a number found only under infection conditions. Other infection related proteins included a high proportion of proteins with redox associated functions and many novel proteins without functional classification. The majority of infection only proteins tested were confirmed to show transcript up-regulation during infection including a thaumatin which increased susceptibility to R. solani when expressed in Nicotiana benthamiana. In addition, analysis of expression during infection of different plant hosts highlighted how the infection strategy of this broad host range pathogen can be adapted to the particular host being encountered. Data are available via ProteomeXchange with identifier PXD002806. PMID:26811357

Evaluation of Protein Profiles From Treated Xenograft Tumor Models Identifies an Antibody Panel for Formalin-fixed and Paraffin-embedded (FFPE) Tissue Analysis by Reverse Phase Protein Arrays (RPPA)*

PubMed Central

Bader, Sabine; Zajac, Magdalena; Friess, Thomas; Ruge, Elisabeth; Rieder, Natascha; Gierke, Berthold; Heubach, Yvonne; Thomas, Marlene; Pawlak, Michael

2015-01-01

Reverse phase protein arrays (RPPA) are an established tool for measuring the expression and activation status of multiple proteins in parallel using only very small amounts of tissue. Several studies have demonstrated the value of this technique for signaling pathway analysis using proteins extracted from fresh frozen (FF) tissue in line with validated antibodies for this tissue type; however, formalin fixation and paraffin embedding (FFPE) is the standard method for tissue preservation in the clinical setting. Hence, we performed RPPA to measure profiles for a set of 300 protein markers using matched FF and FFPE tissue specimens to identify which markers performed similarly using the RPPA technique in fixed and unfixed tissues. Protein lysates were prepared from matched FF and FFPE tissue specimens of individual tumors taken from three different xenograft models of human cancer. Materials from both untreated mice and mice treated with either anti-HER3 or bispecific anti-IGF-1R/EGFR monoclonal antibodies were analyzed. Correlations between signals from FF and FFPE tissue samples were investigated. Overall, 60 markers were identified that produced comparable profiles between FF and FFPE tissues, demonstrating significant correlation between the two sample types. The top 25 markers also showed significance after correction for multiple testing. The panel of markers covered several clinically relevant tumor signaling pathways and both phosphorylated and nonphosphorylated proteins were represented. Biologically relevant changes in marker expression were noted when RPPA profiles from treated and untreated xenografts were compared. These data demonstrate that, using appropriately selected antibodies, RPPA analysis from FFPE tissue is well feasible and generates biologically meaningful information. The identified panel of markers that generate similar profiles in matched fixed and unfixed tissue samples may be clinically useful for pharmacodynamic studies of drug effect

Prediction of Protein-Protein Interaction Sites by Random Forest Algorithm with mRMR and IFS

PubMed Central

Li, Bi-Qing; Feng, Kai-Yan; Chen, Lei; Huang, Tao; Cai, Yu-Dong

2012-01-01

Prediction of protein-protein interaction (PPI) sites is one of the most challenging problems in computational biology. Although great progress has been made by employing various machine learning approaches with numerous characteristic features, the problem is still far from being solved. In this study, we developed a novel predictor based on Random Forest (RF) algorithm with the Minimum Redundancy Maximal Relevance (mRMR) method followed by incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility. We also included five 3D structural features to predict protein-protein interaction sites and achieved an overall accuracy of 0.672997 and MCC of 0.347977. Feature analysis showed that 3D structural features such as Depth Index (DPX) and surface curvature (SC) contributed most to the prediction of protein-protein interaction sites. It was also shown via site-specific feature analysis that the features of individual residues from PPI sites contribute most to the determination of protein-protein interaction sites. It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction. PMID:22937126

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice.

PubMed

Robinson, Matthew M; Dasari, Surendra; Karakelides, Helen; Bergen, H Robert; Nair, K Sreekumaran

2016-09-01

Insulin regulates skeletal muscle protein degradation, but the types of proteins being degraded in vivo remain to be determined due to methodological limitations. We present a method to assess the types of skeletal muscle proteins that are degraded by extracting their degradation products as low-molecular weight (LMW) peptides from muscle samples. High-resolution mass spectrometry was used to identify the original intact proteins that generated the LMW peptides, which we validated in rodents and then applied to humans. We deprived insulin from insulin-treated streptozotocin (STZ) diabetic mice for 6 and 96 h and for 8 h in type 1 diabetic humans (T1D) for comparison with insulin-treated conditions. Protein degradation was measured using activation of autophagy and proteasome pathways, stable isotope tracers, and LMW approaches. In mice, insulin deprivation activated proteasome pathways and autophagy in muscle homogenates and isolated mitochondria. Reproducibility analysis of LMW extracts revealed that ∼80% of proteins were detected consistently. As expected, insulin deprivation increased whole body protein turnover in T1D. Individual protein degradation increased with insulin deprivation, including those involved in mitochondrial function, proteome homeostasis, nDNA support, and contractile/cytoskeleton. Individual mitochondrial proteins that generated more LMW fragment with insulin deprivation included ATP synthase subunit-γ (+0.5-fold, P = 0.007) and cytochrome c oxidase subunit 6 (+0.305-fold, P = 0.03). In conclusion, identifying LMW peptide fragments offers an approach to determine the degradation of individual proteins. Insulin deprivation increases degradation of select proteins and provides insight into the regulatory role of insulin in maintaining proteome homeostasis, especially of mitochondria. Copyright © 2016 the American Physiological Society.

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice

PubMed Central

Robinson, Matthew M.; Dasari, Surendra; Karakelides, Helen; Bergen, H. Robert

2016-01-01

Insulin regulates skeletal muscle protein degradation, but the types of proteins being degraded in vivo remain to be determined due to methodological limitations. We present a method to assess the types of skeletal muscle proteins that are degraded by extracting their degradation products as low-molecular weight (LMW) peptides from muscle samples. High-resolution mass spectrometry was used to identify the original intact proteins that generated the LMW peptides, which we validated in rodents and then applied to humans. We deprived insulin from insulin-treated streptozotocin (STZ) diabetic mice for 6 and 96 h and for 8 h in type 1 diabetic humans (T1D) for comparison with insulin-treated conditions. Protein degradation was measured using activation of autophagy and proteasome pathways, stable isotope tracers, and LMW approaches. In mice, insulin deprivation activated proteasome pathways and autophagy in muscle homogenates and isolated mitochondria. Reproducibility analysis of LMW extracts revealed that ∼80% of proteins were detected consistently. As expected, insulin deprivation increased whole body protein turnover in T1D. Individual protein degradation increased with insulin deprivation, including those involved in mitochondrial function, proteome homeostasis, nDNA support, and contractile/cytoskeleton. Individual mitochondrial proteins that generated more LMW fragment with insulin deprivation included ATP synthase subunit-γ (+0.5-fold, P = 0.007) and cytochrome c oxidase subunit 6 (+0.305-fold, P = 0.03). In conclusion, identifying LMW peptide fragments offers an approach to determine the degradation of individual proteins. Insulin deprivation increases degradation of select proteins and provides insight into the regulatory role of insulin in maintaining proteome homeostasis, especially of mitochondria. PMID:27436610

Unbiased screen identifies aripiprazole as a modulator of abundance of the polyglutamine disease protein, ataxin-3

PubMed Central

Costa, Maria do Carmo; Ashraf, Naila S.; Fischer, Svetlana; Yang, Yemen; Schapka, Emily; Joshi, Gnanada; McQuade, Thomas J.; Dharia, Rahil M.; Dulchavsky, Mark; Ouyang, Michelle; Cook, David; Sun, Duxin; Larsen, Martha J.; Gestwicki, Jason E.; Todi, Sokol V.; Ivanova, Magdalena I.; Paulson, Henry L.

2016-01-01

No disease-modifying treatment exists for the fatal neurodegenerative polyglutamine disease known both as Machado-Joseph disease and spinocerebellar ataxia type 3. As a potential route to therapy, we identified small molecules that reduce levels of the mutant disease protein, ATXN3. Screens of a small molecule collection, including 1250 Food and Drug Administration-approved drugs, in a novel cell-based assay, followed by secondary screens in brain slice cultures from transgenic mice expressing the human disease gene, identified the atypical antipsychotic aripiprazole as one of the hits. Aripiprazole increased longevity in a Drosophila model of Machado-Joseph disease and effectively reduced aggregated ATXN3 species in flies and in brains of transgenic mice treated for 10 days. The aripiprazole-mediated decrease in ATXN3 abundance may reflect a complex response culminating in the modulation of specific components of cellular protein homeostasis. Aripiprazole represents a potentially promising therapeutic drug for Machado-Joseph disease and possibly other neurological proteinopathies. PMID:27645800

Absolute Quantification of Selected Proteins in the Human Osteoarthritic Secretome

PubMed Central

Peffers, Mandy J.; Beynon, Robert J.; Clegg, Peter D.

2013-01-01

Osteoarthritis (OA) is characterized by a loss of extracellular matrix which is driven by catabolic cytokines. Proteomic analysis of the OA cartilage secretome enables the global study of secreted proteins. These are an important class of molecules with roles in numerous pathological mechanisms. Although cartilage studies have identified profiles of secreted proteins, quantitative proteomics techniques have been implemented that would enable further biological questions to be addressed. To overcome this limitation, we used the secretome from human OA cartilage explants stimulated with IL-1β and compared proteins released into the media using a label-free LC-MS/MS-based strategy. We employed QconCAT technology to quantify specific proteins using selected reaction monitoring. A total of 252 proteins were identified, nine were differentially expressed by IL-1 β stimulation. Selected protein candidates were quantified in absolute amounts using QconCAT. These findings confirmed a significant reduction in TIMP-1 in the secretome following IL-1β stimulation. Label-free and QconCAT analysis produced equivocal results indicating no effect of cytokine stimulation on aggrecan, cartilage oligomeric matrix protein, fibromodulin, matrix metalloproteinases 1 and 3 or plasminogen release. This study enabled comparative protein profiling and absolute quantification of proteins involved in molecular pathways pertinent to understanding the pathogenesis of OA. PMID:24132152

Smooth muscle-protein translocation and tissue function.

PubMed

Eddinger, Thomas J

2014-09-01

Smooth muscle (SM) tissue is a complex organization of multiple cell types and is regulated by numerous signaling molecules (neurotransmitters, hormones, cytokines, etc.). SM contractile function can be regulated via expression and distribution of the contractile and cytoskeletal proteins, and activation of any of the second messenger pathways that regulate them. Spatial-temporal changes in the contractile, cytoskeletal or regulatory components of SM cells (SMCs) have been proposed to alter SM contractile activity. Ca(2+) sensitization/desensitization can occur as a result of changes at any of these levels, and specific pathways have been identified at all of these levels. Understanding when and how proteins can translocate within the cytoplasm, or to-and-from the plasmalemma and the cytoplasm to alter contractile activity is critical. Numerous studies have reported translocation of proteins associated with the adherens junction and G protein-coupled receptor activation pathways in isolated SMC systems. Specific examples of translocation of vinculin to and from the adherens junction and protein kinase C (PKC) and 17 kDa PKC-potentiated inhibitor of myosin light chain phosphatase (CPI-17) to and from the plasmalemma in isolated SMC systems but not in intact SM tissues are discussed. Using both isolated SMC systems and SM tissues in parallel to pursue these studies will advance our understanding of both the role and mechanism of these pathways as well as their possible significance for Ca(2+) sensitization in intact SM tissues and organ systems. © 2014 Wiley Periodicals, Inc.

Redox Proteomics of the Inflammatory Secretome Identifies a Common Set of Redoxins and Other Glutathionylated Proteins Released in Inflammation, Influenza Virus Infection and Oxidative Stress

PubMed Central

Checconi, Paola; Salzano, Sonia; Bowler, Lucas; Mullen, Lisa; Mengozzi, Manuela; Hanschmann, Eva-Maria; Lillig, Christopher Horst; Sgarbanti, Rossella; Panella, Simona; Nencioni, Lucia; Palamara, Anna Teresa; Ghezzi, Pietro

2015-01-01

Protein cysteines can form transient disulfides with glutathione (GSH), resulting in the production of glutathionylated proteins, and this process is regarded as a mechanism by which the redox state of the cell can regulate protein function. Most studies on redox regulation of immunity have focused on intracellular proteins. In this study we have used redox proteomics to identify those proteins released in glutathionylated form by macrophages stimulated with lipopolysaccharide (LPS) after pre-loading the cells with biotinylated GSH. Of the several proteins identified in the redox secretome, we have selected a number for validation. Proteomic analysis indicated that LPS stimulated the release of peroxiredoxin (PRDX) 1, PRDX2, vimentin (VIM), profilin1 (PFN1) and thioredoxin 1 (TXN1). For PRDX1 and TXN1, we were able to confirm that the released protein is glutathionylated. PRDX1, PRDX2 and TXN1 were also released by the human pulmonary epithelial cell line, A549, infected with influenza virus. The release of the proteins identified was inhibited by the anti-inflammatory glucocorticoid, dexamethasone (DEX), which also inhibited tumor necrosis factor (TNF)-α release, and by thiol antioxidants (N-butanoyl GSH derivative, GSH-C4, and N-acetylcysteine (NAC), which did not affect TNF-α production. The proteins identified could be useful as biomarkers of oxidative stress associated with inflammation, and further studies will be required to investigate if the extracellular forms of these proteins has immunoregulatory functions. PMID:25985305

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

PubMed

Dilley, Kari A; Voorhies, Alexander A; Luthra, Priya; Puri, Vinita; Stockwell, Timothy B; Lorenzi, Hernan; Basler, Christopher F; Shabman, Reed S

2017-01-01

Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN) response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV), and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA) or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI) RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV). Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR) activation.

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing

PubMed Central

Voorhies, Alexander A.; Luthra, Priya; Puri, Vinita; Stockwell, Timothy B.; Lorenzi, Hernan; Basler, Christopher F.; Shabman, Reed S.

2017-01-01

Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN) response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV), and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA) or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI) RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV). Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR) activation. PMID:28636653

Whole Exome Sequencing Identifies Rare Protein-Coding Variants in Behçet's Disease.

PubMed

Ognenovski, Mikhail; Renauer, Paul; Gensterblum, Elizabeth; Kötter, Ina; Xenitidis, Theodoros; Henes, Jörg C; Casali, Bruno; Salvarani, Carlo; Direskeneli, Haner; Kaufman, Kenneth M; Sawalha, Amr H

2016-05-01

Behçet's disease (BD) is a systemic inflammatory disease with an incompletely understood etiology. Despite the identification of multiple common genetic variants associated with BD, rare genetic variants have been less explored. We undertook this study to investigate the role of rare variants in BD by performing whole exome sequencing in BD patients of European descent. Whole exome sequencing was performed in a discovery set comprising 14 German BD patients of European descent. For replication and validation, Sanger sequencing and Sequenom genotyping were performed in the discovery set and in 2 additional independent sets of 49 German BD patients and 129 Italian BD patients of European descent. Genetic association analysis was then performed in BD patients and 503 controls of European descent. Functional effects of associated genetic variants were assessed using bioinformatic approaches. Using whole exome sequencing, we identified 77 rare variants (in 74 genes) with predicted protein-damaging effects in BD. These variants were genotyped in 2 additional patient sets and then analyzed to reveal significant associations with BD at 2 genetic variants detected in all 3 patient sets that remained significant after Bonferroni correction. We detected genetic association between BD and LIMK2 (rs149034313), involved in regulating cytoskeletal reorganization, and between BD and NEIL1 (rs5745908), involved in base excision DNA repair (P = 3.22 × 10(-4) and P = 5.16 × 10(-4) , respectively). The LIMK2 association is a missense variant with predicted protein damage that may influence functional interactions with proteins involved in cytoskeletal regulation by Rho GTPase, inflammation mediated by chemokine and cytokine signaling pathways, T cell activation, and angiogenesis (Bonferroni-corrected P = 5.63 × 10(-14) , P = 7.29 × 10(-6) , P = 1.15 × 10(-5) , and P = 6.40 × 10(-3) , respectively). The genetic association in NEIL1 is a predicted splice

Identifying interacting proteins of a Caenorhabditis elegans voltage-gated chloride channel CLH-1 using GFP-Trap and mass spectrometry.

PubMed

Zhou, Zi-Liang; Jiang, Jing; Yin, Jiang-An; Cai, Shi-Qing

2014-06-25

Chloride channels belong to a superfamily of ion channels that permit passive passage of anions, mainly chloride, across cell membrane. They play a variety of important physiological roles in regulation of cytosolic pH, cell volume homeostasis, organic solute transport, cell migration, cell proliferation, and differentiation. However, little is known about the functional regulation of these channels. In this study, we generated an integrated transgenic worm strain expressing green fluorescence protein (GFP) fused CLC-type chloride channel 1 (CLH-1::GFP), a voltage-gated chloride channel in Caenorhabditis elegans (C. elegans). CLH-1::GFP was expressed in some unidentified head neurons and posterior intestinal cells of C. elegans. Interacting proteins of CLH-1::GFP were purified by GFP-Trap, a novel system for efficient isolation of GFP fusion proteins and their interacting factors. Mass spectrometry (MS) analysis revealed that a total of 27 high probability interacting proteins were co-trapped with CLHp-1::GFP. Biochemical evidence showed that eukaryotic translation elongation factor 1 (EEF-1), one of these co-trapped proteins identified by MS, physically interacted with CLH-1, in consistent with GFP-Trap experiments. Further immunostaining data revealed that the protein level of CLH-1 was significantly increased upon co-expression with EEF-1. These results suggest that the combination of GFP-Trap purification with MS is an excellent tool to identify novel interacting proteins of voltage-gated chloride channels in C. elegans. Our data also show that EEF-1 is a regulator of voltage-gated chloride channel CLH-1.

[Numeric alterations in the dys gene and their association with clinical features].

PubMed

Mampel, Alejandra; Echeverría, María Inés; Vargas, Ana Lía; Roque, María

2011-01-01

The Duchenne/Becker muscular dystrophy is a hereditary miopathy with a recessive sex-linked pattern. The related gene is called DYS and the coded protein plays a crucial role in the anchorage between the cytoskeleton and the cellular membrane in muscle cells. Different clinical manifestations are observed depending on the impact of the genetic alteration on the protein. The global register of mutations reveals an enhanced frequency for deletions/duplications of one or more exons affecting the DYS gene. In the present work, numeric alterations have been studied in the 79 exons of the DYS gene. The study has been performed on 59 individuals, including 31 independent cases and 28 cases with a familial link. The applied methodology was Multiplex Ligation Dependent Probe Amplification (MLPA). In the 31 independent cases clinical data were established: i.e. the clinical score, the Raven test percentiles, and the creatininphosphokinase (CPK) blood values. Our results reveal a 61.3% frequency of numeric alterations affecting the DYS gene in our population, provoking all of them a reading frame shift. The rate for de novo mutations was identified as 35.2%. Alterations involving a specific region of one exon were observed with high frequency, affecting a specific region. A significant association was found between numeric alterations and a low percentile for the Raven test. These data contribute to the local knowledge of genetic alterations and their phenotypic impact for the Duchenne/Becker disease.

Storage proteins of common bean identified with 2D-PAGE

USDA-ARS?s Scientific Manuscript database

The common bean is a significant source of protein, complex carbohydrates, fiber, and minerals. Seeds of most dry beans contain 15 to 25% protein and are rich in lysine but low in the sulfur containing amino acids cysteine and methionine. Knowledge of common bean proteins is important for research a...

Identification of new intrinsic proteins in Arabidopsis plasma membrane proteome.

PubMed

Marmagne, Anne; Rouet, Marie-Aude; Ferro, Myriam; Rolland, Norbert; Alcon, Carine; Joyard, Jacques; Garin, Jérome; Barbier-Brygoo, Hélène; Ephritikhine, Geneviève

2004-07-01

Identification and characterization of anion channel genes in plants represent a goal for a better understanding of their central role in cell signaling, osmoregulation, nutrition, and metabolism. Though channel activities have been well characterized in plasma membrane by electrophysiology, the corresponding molecular entities are little documented. Indeed, the hydrophobic protein equipment of plant plasma membrane still remains largely unknown, though several proteomic approaches have been reported. To identify new putative transport systems, we developed a new proteomic strategy based on mass spectrometry analyses of a plasma membrane fraction enriched in hydrophobic proteins. We produced from Arabidopsis cell suspensions a highly purified plasma membrane fraction and characterized it in detail by immunological and enzymatic tests. Using complementary methods for the extraction of hydrophobic proteins and mass spectrometry analyses on mono-dimensional gels, about 100 proteins have been identified, 95% of which had never been found in previous proteomic studies. The inventory of the plasma membrane proteome generated by this approach contains numerous plasma membrane integral proteins, one-third displaying at least four transmembrane segments. The plasma membrane localization was confirmed for several proteins, therefore validating such proteomic strategy. An in silico analysis shows a correlation between the putative functions of the identified proteins and the expected roles for plasma membrane in transport, signaling, cellular traffic, and metabolism. This analysis also reveals 10 proteins that display structural properties compatible with transport functions and will constitute interesting targets for further functional studies.

IBT-based quantitative proteomics identifies potential regulatory proteins involved in pigmentation of purple sea cucumber, Apostichopus japonicus.

PubMed

Xing, Lili; Sun, Lina; Liu, Shilin; Li, Xiaoni; Zhang, Libin; Yang, Hongsheng

2017-09-01

Sea cucumbers are an important economic species and exhibit high yield value among aquaculture animals. Purple sea cucumbers are very rare and beautiful and have stable hereditary patterns. In this study, isobaric tags (IBT) were first used to reveal the molecular mechanism of pigmentation in the body wall of the purple sea cucumber. We analyzed the proteomes of purple sea cucumber in early pigmentation stage (Pa), mid pigmentation stage (Pb) and late pigmentation stage (Pc), resulting in the identification of 5580 proteins, including 1099 differentially expressed proteins in Pb: Pa and 339 differentially expressed proteins in Pc: Pb. GO and KEGG analyses revealed possible differentially expressed proteins, including"melanogenesis", "melanosome", "melanoma", "pigment-biosynthetic process", "Epidermis development", "Ras-signaling pathway", "Wnt-signaling pathway", "response to UV light", and "tyrosine metabolism", involved in pigment synthesis and regulation in purple sea cucumbers. The large number of differentially expressed proteins identified here should be highly useful in further elucidating the mechanisms underlying pigmentation in sea cucumbers. Furthermore, these results may also provide the base for further identification of proteins involved in resistance mechanisms against melanoma, albinism, UV damage, and other diseases in sea cucumbers. Copyright © 2017. Published by Elsevier Inc.

Complex network theory for the identification and assessment of candidate protein targets.

PubMed

McGarry, Ken; McDonald, Sharon

2018-06-01

In this work we use complex network theory to provide a statistical model of the connectivity patterns of human proteins and their interaction partners. Our intention is to identify important proteins that may be predisposed to be potential candidates as drug targets for therapeutic interventions. Target proteins usually have more interaction partners than non-target proteins, but there are no hard-and-fast rules for defining the actual number of interactions. We devise a statistical measure for identifying hub proteins, we score our target proteins with gene ontology annotations. The important druggable protein targets are likely to have similar biological functions that can be assessed for their potential therapeutic value. Our system provides a statistical analysis of the local and distant neighborhood protein interactions of the potential targets using complex network measures. This approach builds a more accurate model of drug-to-target activity and therefore the likely impact on treating diseases. We integrate high quality protein interaction data from the HINT database and disease associated proteins from the DrugTarget database. Other sources include biological knowledge from Gene Ontology and drug information from DrugBank. The problem is a very challenging one since the data is highly imbalanced between target proteins and the more numerous nontargets. We use undersampling on the training data and build Random Forest classifier models which are used to identify previously unclassified target proteins. We validate and corroborate these findings from the available literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ankyrin-repeat containing proteins of microbes: a conserved structure with functional diversity

PubMed Central

Al-Khodor, Souhaila; Price, Christopher T.; Kalia, Awdhesh; Kwaik, Yousef Abu

2009-01-01

Summary The ankyrin repeat (ANK) is the most common protein-protein interaction motif in nature and predominantly found in eukaryotic proteins. The genome sequencing of various pathogenic or symbiotic bacteria and eukaryotic viruses identified numerous genes encoding ANK-containing proteins that were proposed to have been acquired from eukaryotes by horizontal gene transfer. However, the recent discovery of additional ANK-containing proteins encoded in the genomes of archaea and free-living bacteria suggests either a more ancient origin of the ANK motif or multiple convergent evolution events. Many bacterial pathogens employ various types of secretion systems to deliver ANK-containing proteins into eukaryotic cells where they mimic or manipulate various host functions. Understanding the molecular and biochemical functions of this family of proteins will enhance our understanding of important host-microbe interactions. PMID:19962898

Biosensor-based approach identifies four distinct calmodulin-binding domains in the G protein-coupled estrogen receptor 1.

PubMed

Tran, Quang-Kim; Vermeer, Mark

2014-01-01

The G protein-coupled estrogen receptor 1 (GPER) has been demonstrated to participate in many cellular functions, but its regulatory inputs are not clearly understood. Here we describe a new approach that identifies GPER as a calmodulin-binding protein, locates interaction sites, and characterizes their binding properties. GPER coimmunoprecipitates with calmodulin in primary vascular smooth muscle cells under resting conditions, which is enhanced upon acute treatment with either specific ligands or a Ca(2+)-elevating agent. To confirm direct interaction and locate the calmodulin-binding domain(s), we designed a series of FRET biosensors that consist of enhanced cyan and yellow fluorescent proteins flanking each of GPER's submembrane domains (SMDs). Responses of these biosensors showed that all four submembrane domains directly bind calmodulin. Modifications of biosensor linker identified domains that display the strongest calmodulin-binding affinities and largest biosensor dynamics, including a.a. 83-93, 150-175, 242-259, 330-351, corresponding respectively to SMDs 1, 2, 3, and the juxta-membranous section of SMD4. These biosensors bind calmodulin in a strictly Ca(2+)-dependent fashion and with disparate affinities in the order SMD2>SMD4>SMD3>SMD1, apparent K d values being 0.44 ± 0.03, 1.40 ± 0.16, 8.01 ± 0.29, and 136.62 ± 6.56 µM, respectively. Interestingly, simultaneous determinations of biosensor responses and suitable Ca(2+) indicators identified separate Ca(2+) sensitivities for their interactions with calmodulin. SMD1-CaM complexes display a biphasic Ca(2+) response, representing two distinct species (SMD1 sp1 and SMD1 sp2) with drastically different Ca(2+) sensitivities. The Ca(2+) sensitivities of CaM-SMDs interactions follow the order SMD1sp1>SMD4>SMD2>SMD1sp2>SMD3, EC50(Ca(2+)) values being 0.13 ± 0.02, 0.75 ± 0.05, 2.38 ± 0.13, 3.71 ± 0.13, and 5.15 ± 0.25 µM, respectively. These data indicate that calmodulin may regulate GPER

Identifying Functional Mechanisms of Gene and Protein Regulatory Networks in Response to a Broader Range of Environmental Stresses

PubMed Central

Li, Cheng-Wei; Chen, Bor-Sen

2010-01-01

Cellular responses to sudden environmental stresses or physiological changes provide living organisms with the opportunity for final survival and further development. Therefore, it is an important topic to understand protective mechanisms against environmental stresses from the viewpoint of gene and protein networks. We propose two coupled nonlinear stochastic dynamic models to reconstruct stress-activated gene and protein regulatory networks via microarray data in response to environmental stresses. According to the reconstructed gene/protein networks, some possible mutual interactions, feedforward and feedback loops are found for accelerating response and filtering noises in these signaling pathways. A bow-tie core network is also identified to coordinate mutual interactions and feedforward loops, feedback inhibitions, feedback activations, and cross talks to cope efficiently with a broader range of environmental stresses with limited proteins and pathways. PMID:20454442

Structural basis of O-GlcNAc recognition by mammalian 14-3-3 proteins.

PubMed

Toleman, Clifford A; Schumacher, Maria A; Yu, Seok-Ho; Zeng, Wenjie; Cox, Nathan J; Smith, Timothy J; Soderblom, Erik J; Wands, Amberlyn M; Kohler, Jennifer J; Boyce, Michael

2018-06-05

O-GlcNAc is an intracellular posttranslational modification that governs myriad cell biological processes and is dysregulated in human diseases. Despite this broad pathophysiological significance, the biochemical effects of most O-GlcNAcylation events remain uncharacterized. One prevalent hypothesis is that O-GlcNAc moieties may be recognized by "reader" proteins to effect downstream signaling. However, no general O-GlcNAc readers have been identified, leaving a considerable gap in the field. To elucidate O-GlcNAc signaling mechanisms, we devised a biochemical screen for candidate O-GlcNAc reader proteins. We identified several human proteins, including 14-3-3 isoforms, that bind O-GlcNAc directly and selectively. We demonstrate that 14-3-3 proteins bind O-GlcNAc moieties in human cells, and we present the structures of 14-3-3β/α and γ bound to glycopeptides, providing biophysical insights into O-GlcNAc-mediated protein-protein interactions. Because 14-3-3 proteins also bind to phospho-serine and phospho-threonine, they may integrate information from O-GlcNAc and O-phosphate signaling pathways to regulate numerous physiological functions.

Temporal Profiling and Pulsed SILAC Labeling Identify Novel Secreted Proteins During Ex Vivo Osteoblast Differentiation of Human Stromal Stem Cells*

PubMed Central

Kristensen, Lars P.; Chen, Li; Nielsen, Maria Overbeck; Qanie, Diyako W.; Kratchmarova, Irina; Kassem, Moustapha; Andersen, Jens S.

2012-01-01

It is well established that bone forming cells (osteoblasts) secrete proteins with autocrine, paracrine, and endocrine function. However, the identity and functional role for the majority of these secreted and differentially expressed proteins during the osteoblast (OB) differentiation process, is not fully established. To address these questions, we quantified the temporal dynamics of the human stromal (mesenchymal, skeletal) stem cell (hMSC) secretome during ex vivo OB differentiation using stable isotope labeling by amino acids in cell culture (SILAC). In addition, we employed pulsed SILAC labeling to distinguish genuine secreted proteins from intracellular contaminants. We identified 466 potentially secreted proteins that were quantified at 5 time-points during 14-days ex vivo OB differentiation including 41 proteins known to be involved in OB functions. Among these, 315 proteins exhibited more than 2-fold up or down-regulation. The pulsed SILAC method revealed a strong correlation between the fraction of isotope labeling and the subset of proteins known to be secreted and involved in OB differentiation. We verified SILAC data using qRT-PCR analysis of 9 identified potential novel regulators of OB differentiation. Furthermore, we studied the biological effects of one of these proteins, the hormone stanniocalcin 2 (STC2) and demonstrated its autocrine effects in enhancing osteoblastic differentiation of hMSC. In conclusion, combining complete and pulsed SILAC labeling facilitated the identification of novel factors produced by hMSC with potential role in OB differentiation. Our study demonstrates that the secretome of osteoblastic cells is more complex than previously reported and supports the emerging evidence that osteoblastic cells secrete proteins with endocrine functions and regulate cellular processes beyond bone formation. PMID:22801418

Integrating multiple ‘omics’ analyses identifies serological protein biomarkers for preeclampsia

PubMed Central

2013-01-01

Background Preeclampsia (PE) is a pregnancy-related vascular disorder which is the leading cause of maternal morbidity and mortality. We sought to identify novel serological protein markers to diagnose PE with a multi-’omics’ based discovery approach. Methods Seven previous placental expression studies were combined for a multiplex analysis, and in parallel, two-dimensional gel electrophoresis was performed to compare serum proteomes in PE and control subjects. The combined biomarker candidates were validated with available ELISA assays using gestational age-matched PE (n=32) and control (n=32) samples. With the validated biomarkers, a genetic algorithm was then used to construct and optimize biomarker panels in PE assessment. Results In addition to the previously identified biomarkers, the angiogenic and antiangiogenic factors (soluble fms-like tyrosine kinase (sFlt-1) and placental growth factor (PIGF)), we found 3 up-regulated and 6 down-regulated biomakers in PE sera. Two optimal biomarker panels were developed for early and late onset PE assessment, respectively. Conclusions Both early and late onset PE diagnostic panels, constructed with our PE biomarkers, were superior over sFlt-1/PIGF ratio in PE discrimination. The functional significance of these PE biomarkers and their associated pathways were analyzed which may provide new insights into the pathogenesis of PE. PMID:24195779

Preserved Proteins from Extinct Bison latifrons Identified by Tandem Mass Spectrometry; Hydroxylysine Glycosides are a Common Feature of Ancient Collagen*

PubMed Central

Hill, Ryan C.; Wither, Matthew J.; Nemkov, Travis; Barrett, Alexander; D'Alessandro, Angelo; Dzieciatkowska, Monika; Hansen, Kirk C.

2015-01-01

Bone samples from several vertebrates were collected from the Ziegler Reservoir fossil site, in Snowmass Village, Colorado, and processed for proteomics analysis. The specimens come from Pleistocene megafauna Bison latifrons, dating back ∼120,000 years. Proteomics analysis using a simplified sample preparation procedure and tandem mass spectrometry (MS/MS) was applied to obtain protein identifications. Several bioinformatics resources were used to obtain peptide identifications based on sequence homology to extant species with annotated genomes. With the exception of soil sample controls, all samples resulted in confident peptide identifications that mapped to type I collagen. In addition, we analyzed a specimen from the extinct B. latifrons that yielded peptide identifications mapping to over 33 bovine proteins. Our analysis resulted in extensive fibrillar collagen sequence coverage, including the identification of posttranslational modifications. Hydroxylysine glucosylgalactosylation, a modification thought to be involved in collagen fiber formation and bone mineralization, was identified for the first time in an ancient protein dataset. Meta-analysis of data from other studies indicates that this modification may be common in well-preserved prehistoric samples. Additional peptide sequences from extracellular matrix (ECM) and non-ECM proteins have also been identified for the first time in ancient tissue samples. These data provide a framework for analyzing ancient protein signatures in well-preserved fossil specimens, while also contributing novel insights into the molecular basis of organic matter preservation. As such, this analysis has unearthed common posttranslational modifications of collagen that may assist in its preservation over time. The data are available via ProteomeXchange with identifier PXD001827. PMID:25948757

Ecto-Fc MS identifies ligand-receptor interactions through extracellular domain Fc fusion protein baits and shotgun proteomic analysis

PubMed Central

Savas, Jeffrey N.; De Wit, Joris; Comoletti, Davide; Zemla, Roland; Ghosh, Anirvan

2015-01-01

Ligand-receptor interactions represent essential biological triggers which regulate many diverse and important cellular processes. We have developed a discovery-based proteomic biochemical protocol which couples affinity purification with multidimensional liquid chromatographic tandem mass spectrometry (LCLC-MS/MS) and bioinformatic analysis. Compared to previous approaches, our analysis increases sensitivity, shortens analysis duration, and boosts comprehensiveness. In this protocol, receptor extracellular domains are fused with the Fc region of IgG to generate fusion proteins that are purified from transfected HEK293T cells. These “ecto-Fcs” are coupled to protein A beads and serve as baits for binding assays with prey proteins extracted from rodent brain. After capture, the affinity purified proteins are digested into peptides and comprehensively analyzed by LCLC-MS/MS with ion trap mass spectrometers. In four working days, this protocol can generate shortlists of candidate ligand-receptor protein-protein interactions. Our “Ecto-Fc MS” approach outperforms antibody-based approaches and provides a reproducible and robust framework to identify extracellular ligand – receptor interactions. PMID:25101821

Quantitative Profiling Identifies Potential Regulatory Proteins Involved in Development from Dauer Stage to L4 Stage in Caenorhabditis elegans.

PubMed

Kim, Sunhee; Lee, Hyoung-Joo; Hahm, Jeong-Hoon; Jeong, Seul-Ki; Park, Don-Ha; Hancock, William S; Paik, Young-Ki

2016-02-05

When Caenorhabditis elegans encounters unfavorable growth conditions, it enters the dauer stage, an alternative L3 developmental period. A dauer larva resumes larval development to the normal L4 stage by uncharacterized postdauer reprogramming (PDR) when growth conditions become more favorable. During this transition period, certain heterochronic genes involved in controlling the proper sequence of developmental events are known to act, with their mutations suppressing the Muv (multivulva) phenotype in C. elegans. To identify the specific proteins in which the Muv phenotype is highly suppressed, quantitative proteomic analysis with iTRAQ labeling of samples obtained from worms at L1 + 30 h (for continuous development [CD]) and dauer recovery +3 h (for postdauer development [PD]) was carried out to detect changes in protein abundance in the CD and PD states of both N2 and lin-28(n719). Of the 1661 unique proteins identified with a < 1% false discovery rate at the peptide level, we selected 58 proteins exhibiting ≥2-fold up-regulation or ≥2-fold down-regulation in the PD state and analyzed the Gene Ontology terms. RNAi assays against 15 selected up-regulated genes showed that seven genes were predicted to be involved in higher Muv phenotype (p < 0.05) in lin-28(n791), which is not seen in N2. Specifically, two genes, K08H10.1 and W05H9.1, displayed not only the highest rate (%) of Muv phenotype in the RNAi assay but also the dauer-specific mRNA expression, indicating that these genes may be required for PDR, leading to the very early onset of dauer recovery. Thus, our proteomic approach identifies and quantitates the regulatory proteins potentially involved in PDR in C. elegans, which safeguards the overall lifecycle in response to environmental changes.

Comparative quantitative proteomic analysis of disease stratified laser captured microdissected human islets identifies proteins and pathways potentially related to type 1 diabetes.

PubMed

Nyalwidhe, Julius O; Grzesik, Wojciech J; Burch, Tanya C; Semeraro, Michele L; Waseem, Tayab; Gerling, Ivan C; Mirmira, Raghavendra G; Morris, Margaret A; Nadler, Jerry L

2017-01-01

Type 1 diabetes (T1D) is a chronic inflammatory disease that is characterized by autoimmune destruction of insulin-producing pancreatic beta cells. The goal of this study was to identify novel protein signatures that distinguish Islets from patients with T1D, patients who are autoantibody positive without symptoms of diabetes, and from individuals with no evidence of disease. High resolution high mass accuracy label free quantitative mass spectrometry analysis was applied to islets isolated by laser capture microdissection from disease stratified human pancreata from the Network for Pancreatic Organ Donors with Diabetes (nPOD), these included donors without diabetes, donors with T1D-associated autoantibodies in the absence of diabetes, and donors with T1D. Thirty-nine proteins were found to be differentially regulated in autoantibody positive cases compared to the no-disease group, with 25 upregulated and 14 downregulated proteins. For the T1D cases, 63 proteins were differentially expressed, with 24 upregulated and 39 downregulated, compared to the no disease controls. We have identified functional annotated enriched gene families and multiple protein-protein interaction clusters of proteins are involved in biological and molecular processes that may have a role in T1D. The proteins that are upregulated in T1D cases include S100A9, S100A8, REG1B, REG3A and C9 amongst others. These proteins have important biological functions, such as inflammation, metabolic regulation, and autoimmunity, all of which are pathways linked to the pathogenesis of T1D. The identified proteins may be involved in T1D development and pathogenesis. Our findings of novel proteins uniquely upregulated in T1D pancreas provides impetus for further investigations focusing on their expression profiles in beta cells/ islets to evaluate their role in the disease pathogenesis. Some of these molecules may be novel therapeutic targets T1D.

Global Proteomic Analysis in Trypanosomes Reveals Unique Proteins and Conserved Cellular Processes Impacted by Arginine Methylation

PubMed Central

Lott, Kaylen; Li, Jun; Fisk, John C.; Wang, Hao; Aletta, John M.; Qu, Jun; Read, Laurie K.

2013-01-01

Arginine methylation is a common posttranslational modification with reported functions in transcription, RNA processing and translation, and DNA repair. Trypanosomes encode five protein arginine methyltransferases, suggesting that arginine methylation exerts widespread impacts on the biology of these organisms. Here, we performed a global proteomic analysis of T. brucei to identify arginine methylated proteins and their sites of modification. Using an approach entailing two-dimensional chromatographic separation, and alternating electron transfer dissociation and collision induced dissociation, we identified 1332 methylarginines in 676 proteins. The resulting data set represents the largest compilation of arginine methylated proteins in any organism to date. Functional classification revealed numerous arginine methylated proteins involved in flagellar function, RNA metabolism, DNA replication and repair, and intracellular protein trafficking. Thus, arginine methylation has the potential to impact aspects of T. brucei gene expression, cell biology, and pathogenesis. Interestingly, pathways with known methylated proteins in higher eukaryotes were identified in this study, but often different components of the pathway were methylated in trypanosomes. Methylarginines were often identified in glycine rich contexts, although exceptions to this rule were detected. Collectively, these data inform on a multitude of aspects of trypanosome biology and serve as a guide for the identification of homologous arginine methylated proteins in higher eukaryotes. PMID:23872088

Tick receptor for outer surface protein A from Ixodes ricinus — the first intrinsically disordered protein involved in vector-microbe recognition

NASA Astrophysics Data System (ADS)

Urbanowicz, Anna; Lewandowski, Dominik; Szpotkowski, Kamil; Figlerowicz, Marek

2016-04-01

The tick receptor for outer surface protein A (TROSPA) is the only identified factor involved in tick gut colonization by various Borrelia species. TROSPA is localized in the gut epithelium and can recognize and bind the outer surface bacterial protein OspA via an unknown mechanism. Based on earlier reports and our latest observations, we considered that TROSPA would be the first identified intrinsically disordered protein (IDP) involved in the interaction between a vector and a pathogenic microbe. To verify this hypothesis, we performed structural studies of a TROSPA mutant from Ixodes ricinus using both computational and experimental approaches. Irrespective of the method used, we observed that the secondary structure content of the TROSPA polypeptide chain is low. In addition, the collected SAXS data indicated that this protein is highly extended and exists in solution as a set of numerous conformers. These features are all commonly considered hallmarks of IDPs. Taking advantage of our SAXS data, we created structural models of TROSPA and proposed a putative mechanism for the TROSPA-OspA interaction. The disordered nature of TROSPA may explain the ability of a wide spectrum of Borrelia species to colonize the tick gut.

Identifying equivalent sound sources from aeroacoustic simulations using a numerical phased array

NASA Astrophysics Data System (ADS)

Pignier, Nicolas J.; O'Reilly, Ciarán J.; Boij, Susann

2017-04-01

An application of phased array methods to numerical data is presented, aimed at identifying equivalent flow sound sources from aeroacoustic simulations. Based on phased array data extracted from compressible flow simulations, sound source strengths are computed on a set of points in the source region using phased array techniques assuming monopole propagation. Two phased array techniques are used to compute the source strengths: an approach using a Moore-Penrose pseudo-inverse and a beamforming approach using dual linear programming (dual-LP) deconvolution. The first approach gives a model of correlated sources for the acoustic field generated from the flow expressed in a matrix of cross- and auto-power spectral values, whereas the second approach results in a model of uncorrelated sources expressed in a vector of auto-power spectral values. The accuracy of the equivalent source model is estimated by computing the acoustic spectrum at a far-field observer. The approach is tested first on an analytical case with known point sources. It is then applied to the example of the flow around a submerged air inlet. The far-field spectra obtained from the source models for two different flow conditions are in good agreement with the spectra obtained with a Ffowcs Williams-Hawkings integral, showing the accuracy of the source model from the observer's standpoint. Various configurations for the phased array and for the sources are used. The dual-LP beamforming approach shows better robustness to changes in the number of probes and sources than the pseudo-inverse approach. The good results obtained with this simulation case demonstrate the potential of the phased array approach as a modelling tool for aeroacoustic simulations.

Gel-based and gel-free proteomic analysis of Nicotiana tabacum trichomes identifies proteins involved in secondary metabolism and in the (a)biotic stress response.

PubMed

Van Cutsem, Emmanuel; Simonart, Géraldine; Degand, Hervé; Faber, Anne-Marie; Morsomme, Pierre; Boutry, Marc

2011-02-01

Nicotiana tabacum leaves are covered by trichomes involved in the secretion of large amounts of secondary metabolites, some of which play a major role in plant defense. However, little is known about the metabolic pathways that operate in these structures. We undertook a proteomic analysis of N. tabacum trichomes in order to identify their protein complement. Efficient trichome isolation was obtained by abrading frozen leaves. After homogenization, soluble proteins and a microsomal fraction were prepared by centrifugation. Gel-based and gel-free proteomic analyses were then performed. 2-DE analysis of soluble proteins led to the identification of 1373 protein spots, which were digested and analyzed by MS/MS, leading to 680 unique identifications. Both soluble proteins and microsomal fraction were analyzed by LC MALDI-MS/MS after trypsin digestion, leading to 858 identifications, many of which had not been identified after 2-DE, indicating that the two methods complement each other. Many enzymes putatively involved in secondary metabolism were identified, including enzymes involved in the synthesis of terpenoid precursors and in acyl sugar production. Several transporters were also identified, some of which might be involved in secondary metabolite transport. Various (a)biotic stress response proteins were also detected, supporting the role of trichomes in plant defense. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Kinome-Wide Small Interfering RNA Screen Identifies Proviral and Antiviral Host Factors in Severe Acute Respiratory Syndrome Coronavirus Replication, Including Double-Stranded RNA-Activated Protein Kinase and Early Secretory Pathway Proteins

PubMed Central

de Wilde, Adriaan H.; Wannee, Kazimier F.; Scholte, Florine E. M.; Goeman, Jelle J.; ten Dijke, Peter; Snijder, Eric J.

2015-01-01

ABSTRACT To identify host factors relevant for severe acute respiratory syndrome-coronavirus (SARS-CoV) replication, we performed a small interfering RNA (siRNA) library screen targeting the human kinome. Protein kinases are key regulators of many cellular functions, and the systematic knockdown of their expression should provide a broad perspective on factors and pathways promoting or antagonizing coronavirus replication. In addition to 40 proteins that promote SARS-CoV replication, our study identified 90 factors exhibiting an antiviral effect. Pathway analysis grouped subsets of these factors in specific cellular processes, including the innate immune response and the metabolism of complex lipids, which appear to play a role in SARS-CoV infection. Several factors were selected for in-depth validation in follow-up experiments. In cells depleted for the β2 subunit of the coatomer protein complex (COPB2), the strongest proviral hit, we observed reduced SARS-CoV protein expression and a >2-log reduction in virus yield. Knockdown of the COPB2-related proteins COPB1 and Golgi-specific brefeldin A-resistant guanine nucleotide exchange factor 1 (GBF1) also suggested that COPI-coated vesicles and/or the early secretory pathway are important for SARS-CoV replication. Depletion of the antiviral double-stranded RNA-activated protein kinase (PKR) enhanced virus replication in the primary screen, and validation experiments confirmed increased SARS-CoV protein expression and virus production upon PKR depletion. In addition, cyclin-dependent kinase 6 (CDK6) was identified as a novel antiviral host factor in SARS-CoV replication. The inventory of pro- and antiviral host factors and pathways described here substantiates and expands our understanding of SARS-CoV replication and may contribute to the identification of novel targets for antiviral therapy. IMPORTANCE Replication of all viruses, including SARS-CoV, depends on and is influenced by cellular pathways. Although

Interaction entropy for protein-protein binding

NASA Astrophysics Data System (ADS)

Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.

2017-03-01

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

Interaction entropy for protein-protein binding.

PubMed

Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H

2017-03-28

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

The association of 83 plasma proteins with CHD mortality, BMI, HDL-, and total-cholesterol in men: applying multivariate statistics to identify proteins with prognostic value and biological relevance.

PubMed

Heidema, A Geert; Thissen, Uwe; Boer, Jolanda M A; Bouwman, Freek G; Feskens, Edith J M; Mariman, Edwin C M

2009-06-01

In this study, we applied the multivariate statistical tool Partial Least Squares (PLS) to analyze the relative importance of 83 plasma proteins in relation to coronary heart disease (CHD) mortality and the intermediate end points body mass index, HDL-cholesterol and total cholesterol. From a Dutch monitoring project for cardiovascular disease risk factors, men who died of CHD between initial participation (1987-1991) and end of follow-up (January 1, 2000) (N = 44) and matched controls (N = 44) were selected. Baseline plasma concentrations of proteins were measured by a multiplex immunoassay. With the use of PLS, we identified 15 proteins with prognostic value for CHD mortality and sets of proteins associated with the intermediate end points. Subsequently, sets of proteins and intermediate end points were analyzed together by Principal Components Analysis, indicating that proteins involved in inflammation explained most of the variance, followed by proteins involved in metabolism and proteins associated with total-C. This study is one of the first in which the association of a large number of plasma proteins with CHD mortality and intermediate end points is investigated by applying multivariate statistics, providing insight in the relationships among proteins, intermediate end points and CHD mortality, and a set of proteins with prognostic value.

The Identification and Functional Characterization of WxL Proteins from Enterococcus faecium Reveal Surface Proteins Involved in Extracellular Matrix Interactions

PubMed Central

Galloway-Peña, Jessica R.; Liang, Xiaowen; Singh, Kavindra V.; Yadav, Puja; Chang, Chungyu; La Rosa, Sabina Leanti; Shelburne, Samuel; Ton-That, Hung; Höök, Magnus

2014-01-01

The WxL domain recently has been identified as a novel cell wall binding domain found in numerous predicted proteins within multiple Gram-positive bacterial species. However, little is known about the function of proteins containing this novel domain. Here, we identify and characterize 6 Enterococcus faecium proteins containing the WxL domain which, by reverse transcription-PCR (RT-PCR) and genomic analyses, are located in three similarly organized operons, deemed WxL loci A, B, and C. Western blotting, electron microscopy, and enzyme-linked immunosorbent assays (ELISAs) determined that genes of WxL loci A and C encode antigenic, cell surface proteins exposed at higher levels in clinical isolates than in commensal isolates. Secondary structural analyses of locus A recombinant WxL domain-containing proteins found they are rich in β-sheet structure and disordered segments. Using Biacore analyses, we discovered that recombinant WxL proteins from locus A bind human extracellular matrix proteins, specifically type I collagen and fibronectin. Proteins encoded by locus A also were found to bind to each other, suggesting a novel cell surface complex. Furthermore, bile salt survival assays and animal models using a mutant from which all three WxL loci were deleted revealed the involvement of WxL operons in bile salt stress and endocarditis pathogenesis. In summary, these studies extend our understanding of proteins containing the WxL domain and their potential impact on colonization and virulence in E. faecium and possibly other Gram-positive bacterial species. PMID:25512313

Novel proteins associated with risk for coronary heart disease or stroke among postmenopausal women identified by in-depth plasma proteome profiling

PubMed Central

2010-01-01

Background Coronary heart disease (CHD) and stroke were key outcomes in the Women's Health Initiative (WHI) randomized trials of postmenopausal estrogen and estrogen plus progestin therapy. We recently reported a large number of changes in blood protein concentrations in the first year following randomization in these trials using an in-depth quantitative proteomics approach. However, even though many affected proteins are in pathways relevant to the observed clinical effects, the relationships of these proteins to CHD and stroke risk among postmenopausal women remains substantially unknown. Methods The same in-depth proteomics platform was applied to plasma samples, obtained at enrollment in the WHI Observational Study, from 800 women who developed CHD and 800 women who developed stroke during cohort follow-up, and from 1-1 matched controls. A plasma pooling strategy, followed by extensive fractionation prior to mass spectrometry, was used to identify proteins related to disease incidence, and the overlap of these proteins with those affected by hormone therapy was examined. Replication studies, using enzyme-linked-immunosorbent assay (ELISA), were carried out in the WHI hormone therapy trial cohorts. Results Case versus control concentration differences were suggested for 37 proteins (nominal P < 0.05) for CHD, with three proteins, beta-2 microglobulin (B2M), alpha-1-acid glycoprotein 1 (ORM1), and insulin-like growth factor binding protein acid labile subunit (IGFALS) having a false discovery rate < 0.05. Corresponding numbers for stroke were 47 proteins with nominal P < 0.05, three of which, apolipoprotein A-II precursor (APOA2), peptidyl-prolyl isomerase A (PPIA), and insulin-like growth factor binding protein 4 (IGFBP4), have a false discovery rate < 0.05. Other proteins involved in insulin-like growth factor signaling were also highly ranked. The associations of B2M with CHD (P < 0.001) and IGFBP4 with stroke (P = 0.005) were confirmed using ELISA in

Genomic and protein expression profiling identifies CDK6 as novel independent prognostic marker in medulloblastoma.

PubMed

Mendrzyk, Frank; Radlwimmer, Bernhard; Joos, Stefan; Kokocinski, Felix; Benner, Axel; Stange, Daniel E; Neben, Kai; Fiegler, Heike; Carter, Nigel P; Reifenberger, Guido; Korshunov, Andrey; Lichter, Peter

2005-12-01

Medulloblastoma is the most common malignant brain tumor in children. Despite multimodal aggressive treatment, nearly half of the patients die as a result of this tumor. Identification of molecular markers for prognosis and development of novel pathogenesis-based therapies depends crucially on a better understanding of medulloblastoma pathomechanisms. We performed genome-wide analysis of DNA copy number imbalances in 47 medulloblastomas using comparative genomic hybridization to large insert DNA microarrays (matrix-CGH). The expression of selected candidate genes identified by matrix-CGH was analyzed immunohistochemically on tissue microarrays representing medulloblastomas from 189 clinically well-documented patients. To identify novel prognostic markers, genomic findings and protein expression data were correlated to patient survival. Matrix-CGH analysis revealed frequent DNA copy number alterations of several novel candidate regions. Among these, gains at 17q23.2-qter (P < .01) and losses at 17p13.1 to 17p13.3 (P = .04) were significantly correlated to poor prognosis. Within 17q23.2-qter and 7q21.2, two of the most frequently gained chromosomal regions, confined amplicons were identified that contained the PPM1D and CDK6 genes, respectively. Immunohistochemistry revealed strong expression of PPM1D in 148 (88%) of 168 and CDK6 in 50 (30%) of 169 medulloblastomas. Overexpression of CDK6 correlated significantly with poor prognosis (P < .01) and represented an independent prognostic marker of overall survival on multivariate analysis (P = .02). We identified CDK6 as a novel molecular marker that can be determined by immunohistochemistry on routinely processed tissue specimens and may facilitate the prognostic assessment of medulloblastoma patients. Furthermore, increased protein-levels of PPM1D and CDK6 may link the TP53 and RB1 tumor suppressor pathways to medulloblastoma pathomechanisms.

Human monoclonal antibodies to West Nile virus identify epitopes on the prM protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calvert, Amanda E., E-mail: zpz0@cdc.go; Kalantarov, Gavreel F.; Chang, Gwong-Jen J.

2011-02-05

Hybridoma cell lines (2E8, 8G8 and 5G12) producing fully human monoclonal antibodies (hMAbs) specific for the pre-membrane (prM) protein of West Nile virus (WNV) were prepared using a human fusion partner cell line, MFP-2, and human peripheral blood lymphocytes from a blood donor diagnosed with WNV fever in 2004. Using site-directed mutagenesis of a WNV-like particle (VLP) we identified 4 amino acid residues in the prM protein unique to WNV and important in the binding of these hMAbs to the VLP. Residues V19 and L33 are important epitopes for the binding of all three hMAbs. Mutations at residue, T20 andmore » T24 affected the binding of hMAbs, 8G8 and 5G12 only. These hMAbs did not significantly protect AG129 interferon-deficient mice or Swiss Webster outbred mice from WNV infection.« less

How many proteins can be identified in a 2DE gel spot within an analysis of a complex human cancer tissue proteome?

PubMed

Zhan, Xianquan; Yang, Haiyan; Peng, Fang; Li, Jianglin; Mu, Yun; Long, Ying; Cheng, Tingting; Huang, Yuda; Li, Zhao; Lu, Miaolong; Li, Na; Li, Maoyu; Liu, Jianping; Jungblut, Peter R

2018-04-01

Two-dimensional gel electrophoresis (2DE) in proteomics is traditionally assumed to contain only one or two proteins in each 2DE spot. However, 2DE resolution is being complemented by the rapid development of high sensitivity mass spectrometers. Here we compared MALDI-MS, LC-Q-TOF MS and LC-Orbitrap Velos MS for the identification of proteins within one spot. With LC-Orbitrap Velos MS each Coomassie Blue-stained 2DE spot contained an average of at least 42 and 63 proteins/spot in an analysis of a human glioblastoma proteome and a human pituitary adenoma proteome, respectively, if a single gel spot was analyzed. If a pool of three matched gel spots was analyzed this number further increased up to an average of 230 and 118 proteins/spot for glioblastoma and pituitary adenoma proteome, respectively. Multiple proteins per spot confirm the necessity of isotopic labeling in large-scale quantification of different protein species in a proteome. Furthermore, a protein abundance analysis revealed that most of the identified proteins in each analyzed 2DE spot were low-abundance proteins. Many proteins were present in several of the analyzed spots showing the ability of 2DE-MS to separate at the protein species level. Therefore, 2DE coupled with high-sensitivity LC-MS has a clearly higher sensitivity as expected until now to detect, identify and quantify low abundance proteins in a complex human proteome with an estimated resolution of about 500 000 protein species. This clearly exceeds the resolution power of bottom-up LC-MS investigations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic identification and purification of seed proteins from native Amazonian species displaying antifungal activity.

PubMed

Ramos, Márcio V; Brito, Daniel; Freitas, Cléverson D T; Gonçalves, José Francisco C; Porfirio, Camila T M N; Lobo, Marina D P; Monteiro-Moreira, Ana Cristina O; Souza, Luiz A C; Fernandes, Andreia V

2018-04-19

Seeds of native species from the rain forest (Amazon) are source of chitinases and their protein extracts exhibited strong and broad antifungal activity. Numerous plant species native to the Amazon have not yet been chemically studied. Studies of seeds are scarcer, since adversities in accessing study areas and seasonality pose constant hurdles to systematic research. In this study, proteins were extracted from seeds belonging to endemic Amazon species and were investigated for the first time. Proteolytic activity, peptidase inhibitors, and chitinases were identified, but chitinolytic activity predominated. Four proteins were purified through chromatography and identified as lectin and chitinases by MS/MS analyses. The proteins were examined for inhibition of a phytopathogen (Fusarium oxysporum). Analyses by fluorescence microscopy suggested binding of propidium iodide to DNA of fungal spores, revealing that spore integrity was lost when accessed by the proteins. Further structural and functional analyses of defensive proteins belonging to species facing highly complex ecosystems such as Amazonia should be conducted, since these could provide new insights into specificity and synergism involving defense proteins of plants submitted to a very complex ecosystem.

A functional cancer genomics screen identifies a druggable synthetic lethal interaction between MSH3 and PRKDC.

PubMed

Dietlein, Felix; Thelen, Lisa; Jokic, Mladen; Jachimowicz, Ron D; Ivan, Laura; Knittel, Gero; Leeser, Uschi; van Oers, Johanna; Edelmann, Winfried; Heukamp, Lukas C; Reinhardt, H Christian

2014-05-01

Here, we use a large-scale cell line-based approach to identify cancer cell-specific mutations that are associated with DNA-dependent protein kinase catalytic subunit (DNA-PKcs) dependence. For this purpose, we profiled the mutational landscape across 1,319 cancer-associated genes of 67 distinct cell lines and identified numerous genes involved in homologous recombination-mediated DNA repair, including BRCA1, BRCA2, ATM, PAXIP, and RAD50, as being associated with non-oncogene addiction to DNA-PKcs. Mutations in the mismatch repair gene MSH3, which have been reported to occur recurrently in numerous human cancer entities, emerged as the most significant predictors of DNA-PKcs addiction. Concordantly, DNA-PKcs inhibition robustly induced apoptosis in MSH3-mutant cell lines in vitro and displayed remarkable single-agent efficacy against MSH3-mutant tumors in vivo. Thus, we here identify a therapeutically actionable synthetic lethal interaction between MSH3 and the non-homologous end joining kinase DNA-PKcs. Our observations recommend DNA-PKcs inhibition as a therapeutic concept for the treatment of human cancers displaying homologous recombination defects.

The Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection

USDA-ARS?s Scientific Manuscript database

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a non-incorporated protein in concert with numerous insect and plant proteins to regulate virus movem...

Preliminary study on plasma proteins in pregnant and non-pregnant female dogs.

PubMed

Szczubiał, Marek; Wawrzykowski, Jacek; Dąbrowski, Roman; Krawczyk, Magdalena; Kankofer, Marta

2017-07-15

In this study, we used a combined approach based on 2-dimensional electrophoresis (2-DE), difference in gel electrophoresis (DIGE), and mass spectrometry (MS) to identify the plasma protein composition in pregnant female dogs and compared it with non-pregnant female dogs. We used the plasma samples obtained from four female dogs during I, II, and III thirds of pregnancy, three days after parturition, as well as from four non-pregnant female dogs in diestrus phase. Analysis of 2-DE gel image exhibited of 249 protein spots. The intensity of staining of 35 spots differed significantly (P < 0.05) between the non-pregnant and pregnant female dogs. We used matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI TOF MS) to identify 47 spots corresponding to 52 different proteins. Five identified protein spots, including zinc finger BED domain-containing protein 5, hemoglobin subunit beta-2, integrator complex subunit 7, apolipoprotein A-I, and glutamyl aminopeptidase were differentially presented in the plasma of pregnant and non-pregnant female dogs. To the best of our knowledge, this is the first report on the plasma protein profile of pregnant and non-pregnant female dogs. In this study, we identified proteins that have not been previously identified in dogs. Our findings showed that numerous protein spots were differentially presented in the plasma of female dogs during normal pregnancy. Although we identified only a limited number of differentially presented proteins, our study demonstrated that the plasma protein profile changed during pregnancy in female dogs, which suggests its importance in maintaining pregnancy. Further studies are necessary to define complete plasma protein profile of pregnant female dogs and to identify all proteins that are differentially presented in the pregnant animals compared with the non-pregnant ones. In addition, studies are warranted to explain the role of those proteins in maintaining the pregnancy and

Exploiting three kinds of interface propensities to identify protein binding sites.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2009-08-01

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. In this study, we present a building block of proteins called order profiles to use the evolutionary information of the protein sequence frequency profiles and apply this building block to produce a class of propensities called order profile interface propensities. For comparisons, we revisit the usage of residue interface propensities and binary profile interface propensities for protein binding site prediction. Each kind of propensities combined with sequence profiles and accessible surface areas are inputted into SVM. When tested on four types of complexes (hetero-permanent complexes, hetero-transient complexes, homo-permanent complexes and homo-transient complexes), experimental results show that the order profile interface propensities are better than residue interface propensities and binary profile interface propensities. Therefore, order profile is a suitable profile-level building block of the protein sequences and can be widely used in many tasks of computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the protein remote homology detection.

A parallel genome-wide RNAi screening strategy to identify host proteins important for entry of Marburg virus and H5N1 influenza virus.

PubMed

Cheng, Han; Koning, Katie; O'Hearn, Aileen; Wang, Minxiu; Rumschlag-Booms, Emily; Varhegyi, Elizabeth; Rong, Lijun

2015-11-24

Genome-wide RNAi screening has been widely used to identify host proteins involved in replication and infection of different viruses, and numerous host factors are implicated in the replication cycles of these viruses, demonstrating the power of this approach. However, discrepancies on target identification of the same viruses by different groups suggest that high throughput RNAi screening strategies need to be carefully designed, developed and optimized prior to the large scale screening. Two genome-wide RNAi screens were performed in parallel against the entry of pseudotyped Marburg viruses and avian influenza virus H5N1 utilizing an HIV-1 based surrogate system, to identify host factors which are important for virus entry. A comparative analysis approach was employed in data analysis, which alleviated systematic positional effects and reduced the false positive number of virus-specific hits. The parallel nature of the strategy allows us to easily identify the host factors for a specific virus with a greatly reduced number of false positives in the initial screen, which is one of the major problems with high throughput screening. The power of this strategy is illustrated by a genome-wide RNAi screen for identifying the host factors important for Marburg virus and/or avian influenza virus H5N1 as described in this study. This strategy is particularly useful for highly pathogenic viruses since pseudotyping allows us to perform high throughput screens in the biosafety level 2 (BSL-2) containment instead of the BSL-3 or BSL-4 for the infectious viruses, with alleviated safety concerns. The screening strategy together with the unique comparative analysis approach makes the data more suitable for hit selection and enables us to identify virus-specific hits with a much lower false positive rate.

Immunoreactive Coxiella burnetii Nine Mile proteins separated by 2D electrophoresis and identified by tandem mass spectrometry

PubMed Central

Deringer, James R.; Chen, Chen; Samuel, James E.; Brown, Wendy C.

2011-01-01

Coxiella burnetii is a Gram-negative obligate intracellular pathogen and the causative agent of Q fever in humans. Q fever causes acute flu-like symptoms and may develop into a chronic disease leading to endocarditis. Its potential as a bioweapon has led to its classification as a category B select agent. An effective inactivated whole-cell vaccine (WCV) currently exists but causes severe granulomatous/necrotizing reactions in individuals with prior exposure, and is not licensed for use in most countries. Current efforts to reduce or eliminate the deleterious reactions associated with WCVs have focused on identifying potential subunit vaccine candidates. Both humoral and T cell-mediated responses are required for protection in animal models. In this study, nine novel immunogenic C. burnetii proteins were identified in extracted whole-cell lysates using 2D electrophoresis, immunoblotting with immune guinea pig sera, and tandem MS. The immunogenic C. burnetii proteins elicited antigen-specific IgG in guinea pigs vaccinated with whole-cell killed Nine Mile phase I vaccine, suggesting a T cell-dependent response. Eleven additional proteins previously shown to react with immune human sera were also antigenic in guinea pigs, showing the relevance of the guinea pig immunization model for antigen discovery. The antigens described here warrant further investigation to validate their potential use as subunit vaccine candidates. PMID:21030434

Proteomic Analysis of Intact Flagella of Procyclic Trypanosoma brucei Cells Identifies Novel Flagellar Proteins with Unique Sub-localization and Dynamics*

PubMed Central

Subota, Ines; Julkowska, Daria; Vincensini, Laetitia; Reeg, Nele; Buisson, Johanna; Blisnick, Thierry; Huet, Diego; Perrot, Sylvie; Santi-Rocca, Julien; Duchateau, Magalie; Hourdel, Véronique; Rousselle, Jean-Claude; Cayet, Nadège; Namane, Abdelkader; Chamot-Rooke, Julia; Bastin, Philippe

2014-01-01

Cilia and flagella are complex organelles made of hundreds of proteins of highly variable structures and functions. Here we report the purification of intact flagella from the procyclic stage of Trypanosoma brucei using mechanical shearing. Structural preservation was confirmed by transmission electron microscopy that showed that flagella still contained typical elements such as the membrane, the axoneme, the paraflagellar rod, and the intraflagellar transport particles. It also revealed that flagella severed below the basal body, and were not contaminated by other cytoskeletal structures such as the flagellar pocket collar or the adhesion zone filament. Mass spectrometry analysis identified a total of 751 proteins with high confidence, including 88% of known flagellar components. Comparison with the cell debris fraction revealed that more than half of the flagellum markers were enriched in flagella and this enrichment criterion was taken into account to identify 212 proteins not previously reported to be associated to flagella. Nine of these were experimentally validated including a 14-3-3 protein not yet reported to be associated to flagella and eight novel proteins termed FLAM (FLAgellar Member). Remarkably, they localized to five different subdomains of the flagellum. For example, FLAM6 is restricted to the proximal half of the axoneme, no matter its length. In contrast, FLAM8 is progressively accumulating at the distal tip of growing flagella and half of it still needs to be added after cell division. A combination of RNA interference and Fluorescence Recovery After Photobleaching approaches demonstrated very different dynamics from one protein to the other, but also according to the stage of construction and the age of the flagellum. Structural proteins are added to the distal tip of the elongating flagellum and exhibit slow turnover whereas membrane proteins such as the arginine kinase show rapid turnover without a detectible polarity. PMID:24741115

Identifying the influential aquifer heterogeneity factor on nitrate reduction processes by numerical simulation

NASA Astrophysics Data System (ADS)

Jang, E.; He, W.; Savoy, H.; Dietrich, P.; Kolditz, O.; Rubin, Y.; Schüth, C.; Kalbacher, T.

2017-01-01

Nitrate reduction reactions in groundwater systems are strongly influenced by various aquifer heterogeneity factors that affect the transport of chemical species, spatial distribution of redox reactive substances and, as a result, the overall nitrate reduction efficiency. In this study, we investigated the influence of physical and chemical aquifer heterogeneity, with a focus on nitrate transport and redox transformation processes. A numerical modeling study for simulating coupled hydrological-geochemical aquifer heterogeneity was conducted in order to improve our understanding of the influence of the aquifer heterogeneity on the nitrate reduction reactions and to identify the most influential aquifer heterogeneity factors throughout the simulation. Results show that the most influential aquifer heterogeneity factors could change over time. With abundant presence of electron donors in the high permeable zones (initial stage), physical aquifer heterogeneity significantly influences the nitrate reduction since it enables the preferential transport of nitrate to these zones and enhances mixing of reactive partners. Chemical aquifer heterogeneity plays a comparatively minor role. Increasing the spatial variability of the hydraulic conductivity also increases the nitrate removal efficiency of the system. However, ignoring chemical aquifer heterogeneity can lead to an underestimation of nitrate removals in long-term behavior. With the increase of the spatial variability of the electron donor, i.e. chemical heterogeneity, the number of the ;hot spots; i.e. zones with comparably higher reactivity, should also increase. Hence, nitrate removal efficiencies will also be spatially variable but overall removal efficiency will be sustained if longer time scales are considered and nitrate fronts reach these high reactivity zones.

Protein kinase inhibitor peptide (PKI): a family of endogenous neuropeptides that modulate neuronal cAMP-dependent protein kinase function.

PubMed

Dalton, George D; Dewey, William L

2006-02-01

Signal transduction cascades involving cAMP-dependent protein kinase are highly conserved among a wide variety of organisms. Given the universal nature of this enzyme it is not surprising that cAMP-dependent protein kinase plays a critical role in numerous cellular processes. This is particularly evident in the nervous system where cAMP-dependent protein kinase is involved in neurotransmitter release, gene transcription, and synaptic plasticity. Protein kinase inhibitor peptide (PKI) is an endogenous thermostable peptide that modulates cAMP-dependent protein kinase function. PKI contains two distinct functional domains within its amino acid sequence that allow it to: (1) potently and specifically inhibit the activity of the free catalytic subunit of cAMP-dependent protein kinase and (2) export the free catalytic subunit of cAMP-dependent protein kinase from the nucleus. Three distinct PKI isoforms (PKIalpha, PKIbeta, PKIgamma) have been identified and each isoform is expressed in the brain. PKI modulates neuronal synaptic activity, while PKI also is involved in morphogenesis and symmetrical left-right axis formation. In addition, PKI also plays a role in regulating gene expression induced by cAMP-dependent protein kinase. Future studies should identify novel physiological functions for endogenous PKI both in the nervous system and throughout the body. Most interesting will be the determination whether functional differences exist between individual PKI isoforms which is an intriguing possibility since these isoforms exhibit: (1) cell-type specific tissue expression patterns, (2) different potencies for the inhibition of cAMP-dependent protein kinase activity, and (3) expression patterns that are hormonally, developmentally and cell-cycle regulated. Finally, synthetic peptide analogs of endogenous PKI will continue to be invaluable tools that are used to elucidate the role of cAMP-dependent protein kinase in a variety of cellular processes throughout the nervous

Comparative gene expression profiling of in vitro differentiated megakaryocytes and erythroblasts identifies novel activatory and inhibitory platelet membrane proteins.

PubMed

Macaulay, Iain C; Tijssen, Marloes R; Thijssen-Timmer, Daphne C; Gusnanto, Arief; Steward, Michael; Burns, Philippa; Langford, Cordelia F; Ellis, Peter D; Dudbridge, Frank; Zwaginga, Jaap-Jan; Watkins, Nicholas A; van der Schoot, C Ellen; Ouwehand, Willem H

2007-04-15

To identify previously unknown platelet receptors we compared the transcriptomes of in vitro differentiated megakaryocytes (MKs) and erythroblasts (EBs). RNA was obtained from purified, biologically paired MK and EB cultures and compared using cDNA microarrays. Bioinformatical analysis of MK-up-regulated genes identified 151 transcripts encoding transmembrane domain-containing proteins. Although many of these were known platelet genes, a number of previously unidentified or poorly characterized transcripts were also detected. Many of these transcripts, including G6b, G6f, LRRC32, LAT2, and the G protein-coupled receptor SUCNR1, encode proteins with structural features or functions that suggest they may be involved in the modulation of platelet function. Immunoblotting on platelets confirmed the presence of the encoded proteins, and flow cytometric analysis confirmed the expression of G6b, G6f, and LRRC32 on the surface of platelets. Through comparative analysis of expression in platelets and other blood cells we demonstrated that G6b, G6f, and LRRC32 are restricted to the platelet lineage, whereas LAT2 and SUCNR1 were also detected in other blood cells. The identification of the succinate receptor SUCNR1 in platelets is of particular interest, because physiologically relevant concentrations of succinate were shown to potentiate the effect of low doses of a variety of platelet agonists.

Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity.

PubMed

Wang, Guan-Feng; Ji, Jiabing; El-Kasmi, Farid; Dangl, Jeffery L; Johal, Guri; Balint-Kurti, Peter J

2015-02-01

Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR) proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR). Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC), a nucleotide binding (NB-ARC) and a leucine rich repeat (LRR) domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.

Whole-genome resequencing identifies the molecular genetic cause for the absence of a Gy5 glycinin protein in soybean PI 603408

USDA-ARS?s Scientific Manuscript database

During ongoing proteomic analysis of the soybean (Glycine max (L.) Merr) germplasm collection, PI 603408 was identified as a landrace whose seeds lack accumulation of one of the major seed storage glycinin protein subunits. Whole genomic resequencing was used to identify a two-base deletion affectin...

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

PubMed

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.

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

PubMed Central

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

2016-01-01

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 R2 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. PMID:27172185

Urine protein profiling identified alpha-1-microglobulin and haptoglobin as biomarkers for early diagnosis of acute allograft rejection following kidney transplantation.

PubMed

Stubendorff, Beatrice; Finke, Stephanie; Walter, Martina; Kniemeyer, Olaf; von Eggeling, Ferdinand; Gruschwitz, Torsten; Steiner, Thomas; Ott, Undine; Wolf, Gunter; Wunderlich, Heiko; Junker, Kerstin

2014-12-01

Early diagnosis of acute rejection and effective immunosuppressive therapy lead to improvement in graft survival following kidney transplantation. In this study, we aimed to establish a urinary protein profile suitable to distinguish between patients with rejection and stable graft function and to predict acute rejection based on postoperatively collected urine samples. A further objective was to identify candidate proteins for the use as biomarkers in clinical practice. Urine samples of 116 kidney recipients were included. Rejection was proven by biopsy (n = 58), and stable transplant function was monitored for at least 2 years (n = 58). Postoperative urine samples were collected between 3rd and 10th day following transplantation. Urinary protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Protein identification and validation were performed using multiplex fluorescence 2DE, peptide mass fingerprinting and enzyme-linked immunosorbent assay. A protein profile including four mass peaks differentiated acute rejection from stable transplants at the time point of rejection and at the postoperative state with 73 % sensitivity and 88 % specificity. Alpha-1-microglobulin (A1MG) and Haptoglobin (Hp) were identified as putative rejection biomarkers. Protein levels were significantly higher in postoperative urine from patients with rejection (A1MG 29.13 vs. 22.06 μg/ml, p = 0.001; Hp 628.34 vs. 248.57 ng/ml, p = 0.003). The combination of both proteins enabled the diagnosis of early rejection with 85 % sensitivity and 80 % specificity. Protein profiling using mass spectrometry is suitable for noninvasive detection of rejection-specific changes following kidney transplantation. A specific protein profile enables the prediction of early acute allograft rejection in the immediate postoperative period. A1MG and Hp appear to be reliable rejection biomarkers.

Library Screen Identifies Enterococcus faecalis CcpA, the Catabolite Control Protein A, as an Effector of Ace, a Collagen Adhesion Protein Linked to Virulence

PubMed Central

Gao, Peng; Pinkston, Kenneth L.; Bourgogne, Agathe; Cruz, Melissa R.; Garsin, Danielle A.; Murray, Barbara E.

2013-01-01

The Enterococcus faecalis cell wall-anchored protein Ace is an important virulence factor involved in cell adhesion and infection. Expression of Ace on the cell surface is affected by many factors, including stage of growth, culture temperature, and environmental components, such as serum, urine, and collagen. However, the mechanisms that regulate or modulate Ace display are not well understood. With interest in identifying genes associated with Ace expression, we utilized a whole-cell enzyme-linked immunosorbent assay (ELISA)-based screening method to identify mutants from a transposon insertion mutant library which exhibited distinct Ace surface expression profiles. We identified a ccpA insertion mutant which showed significantly decreased levels of Ace surface expression at early growth phase versus those of wild-type OG1RF. Confirmation of the observation was achieved through flow cytometry and complementation analysis. Compared to the wild type, the E. faecalis ccpA mutant had an impaired ability to adhere to collagen when grown to early exponential phase, consistent with the lack of Ace expression in the early growth phase. As a key component of carbon catabolite regulation, CcpA has been previously reported to play a critical role in regulating expression of proteins involved in E. faecalis carbohydrate uptake and utilization. Our discovery is the first to associate CcpA with the production of a major E. faecalis virulence factor, providing new insights into the regulation of E. faecalis pathogenesis. PMID:23974022

Protein expression profiling identifies molecular targets of quercetin as a major dietary flavonoid in human colon cancer cells.

PubMed

Wenzel, Uwe; Herzog, Angelika; Kuntz, Sabine; Daniel, Hannelore

2004-07-01

A high dietary intake of plant foods is thought to contribute to the prevention of colorectal cancers in humans and flavonoids as part of such a diet are considered to contribute to those protective effects. Quercetin is a major dietary flavonoid consumed with a diet rich in onions, tea, and apples. We used HT-29 human colon cancer cells and investigated the effects of quercetin on proliferation, apoptosis, and differentiation as processes shown to be disregulated during cancer development. To identify the cellular targets of quercetin action, two-dimensional gel electrophoresis was performed and proteins altered in expression level after quercetin exposure of cells were identified by mass spectrometry of peptide fragments generated by tryptic digestion. Quercetin inhibited the proliferation of HT-29 cells with an IC(50)-value of 81.2 +/- 6.6 microM. Cell differentiation based on surface expression of alkaline phosphatase was enhanced 4-fold and the activity of the pro-apoptotic effector caspase-3 increased 3-fold. Those effects were associated with the regulation of heat-shock proteins and annexins shown to both play a crucial role in the process of apoptosis. Cytoskeletal caspase substrates were found as regulated as well and various proteins involved in intermediary metabolism and in gene regulation showed altered steady-state expression levels upon quercetin treatment of cells. In conclusion, quercetin alters the levels of a variety of proteins involved in growth, differentiation, and apoptosis of colon cancer cells. Their identification as molecular targets of quercetin may explain the anti-cancer activities of this flavonoid.

Adhesion, invasion and evasion: the many functions of the surface proteins of Staphylococcus aureus

PubMed Central

Foster, Timothy J.; Geoghegan, Joan A.; Ganesh, Vannakambadi K.; Höök, Magnus

2014-01-01

Staphylococcus aureus is an important opportunistic pathogen and persistently colonizes about 20% of the human population. Its surface is ‘decorated’ with proteins that are covalently anchored to the cell wall peptidoglycan. Structural and functional analysis has identified four distinct classes of surface proteins, of which microbial surface component recognizing adhesive matrix molecules (MSCRAMMs) are the largest class. These surface proteins have numerous functions, including adhesion to and invasion of host cells and tissues, evasion of immune responses and biofilm formation. Thus, cell wall-anchored proteins are essential virulence factors for the survival of S. aureus in the commensal state and during invasive infections, and targeting them with vaccines could combat S. aureus infections. PMID:24336184

Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

PubMed

Nath, Anjali K; Krauthammer, Michael; Li, Puyao; Davidov, Eugene; Butler, Lucas C; Copel, Joshua; Katajamaa, Mikko; Oresic, Matej; Buhimschi, Irina; Buhimschi, Catalin; Snyder, Michael; Madri, Joseph A

2009-01-01

Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs). However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies. Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others) were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B) was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1) as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF) samples from women carrying normal fetuses and those with CHDs. The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs.

Proteomic-Based Detection of a Protein Cluster Dysregulated during Cardiovascular Development Identifies Biomarkers of Congenital Heart Defects

PubMed Central

Nath, Anjali K.; Krauthammer, Michael; Li, Puyao; Davidov, Eugene; Butler, Lucas C.; Copel, Joshua; Katajamaa, Mikko; Oresic, Matej; Buhimschi, Irina; Buhimschi, Catalin; Snyder, Michael; Madri, Joseph A.

2009-01-01

Background Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs). However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies. Methodology/Principal Findings Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others) were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B) was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1) as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF) samples from women carrying normal fetuses and those with CHDs. Conclusions/Significance The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs. PMID:19156209

RIP-seq analysis of eukaryotic Sm proteins identifies three major categories of Sm-containing ribonucleoproteins

PubMed Central

2014-01-01

Background Sm proteins are multimeric RNA-binding factors, found in all three domains of life. Eukaryotic Sm proteins, together with their associated RNAs, form small ribonucleoprotein (RNP) complexes important in multiple aspects of gene regulation. Comprehensive knowledge of the RNA components of Sm RNPs is critical for understanding their functions. Results We developed a multi-targeting RNA-immunoprecipitation sequencing (RIP-seq) strategy to reliably identify Sm-associated RNAs from Drosophila ovaries and cultured human cells. Using this method, we discovered three major categories of Sm-associated transcripts: small nuclear (sn)RNAs, small Cajal body (sca)RNAs and mRNAs. Additional RIP-PCR analysis showed both ubiquitous and tissue-specific interactions. We provide evidence that the mRNA-Sm interactions are mediated by snRNPs, and that one of the mechanisms of interaction is via base pairing. Moreover, the Sm-associated mRNAs are mature, indicating a splicing-independent function for Sm RNPs. Conclusions This study represents the first comprehensive analysis of eukaryotic Sm-containing RNPs, and provides a basis for additional functional analyses of Sm proteins and their associated snRNPs outside of the context of pre-mRNA splicing. Our findings expand the repertoire of eukaryotic Sm-containing RNPs and suggest new functions for snRNPs in mRNA metabolism. PMID:24393626

Altered Protein S-Glutathionylation Identifies a Potential Mechanism of Resistance to Acetaminophen-Induced Hepatotoxicity

PubMed Central

McGarry, David J.; Chakravarty, Probir; Wolf, C. Roland

2015-01-01

Acetaminophen (APAP) is the most commonly used over-the-counter analgesic. However, hepatotoxicity induced by APAP is a major clinical issue, and the factors that define sensitivity to APAP remain unclear. We have previously demonstrated that mice nulled for glutathione S-transferase Pi (GSTP) are resistant to APAP-induced hepatotoxicity. This study aims to exploit this difference to delineate pathways of importance in APAP toxicity. We used mice nulled for GSTP and heme oxygenase-1 oxidative stress reporter mice, together with a novel nanoflow liquid chromatography–tandem mass spectrometry methodology to investigate the role of oxidative stress, cell signaling, and protein S-glutathionylation in APAP hepatotoxicity. We provide evidence that the sensitivity difference between wild-type and Gstp1/2−/− mice is unrelated to the ability of APAP to induce oxidative stress, despite observing significant increases in c-Jun N-terminal kinase and extracellular signal-regulated kinase phosphorylation in wild-type mice. The major difference in response to APAP was in the levels of protein S-glutathionylation: Gstp1/2−/− mice exhibited a significant increase in the number of S-glutathionylated proteins compared with wild-type animals. Remarkably, these S-glutathionylated proteins are involved in oxidative phosphorylation, respiratory complexes, drug metabolism, and mitochondrial apoptosis. Furthermore, we found that S-glutathionylation of the rate-limiting glutathione-synthesizing enzyme, glutamate cysteine ligase, was markedly increased in Gstp1/2−/− mice in response to APAP. The data demonstrate that S-glutathionylation provides an adaptive response to APAP and, as a consequence, suggest that this is an important determinant in APAP hepatotoxicity. This work identifies potential novel avenues associated with cell survival for the treatment of chemical-induced hepatotoxicity. PMID:26311813

Differential Protein Expression Marks the Transition From Infection With Opisthorchis viverrini to Cholangiocarcinoma*

PubMed Central

Khoontawad, Jarinya; Pairojkul, Chawalit; Rucksaken, Rucksak; Pinlaor, Porntip; Wongkham, Chaisiri; Yongvanit, Puangrat; Pugkhem, Ake; Jones, Alun; Plieskatt, Jordan; Potriquet, Jeremy; Bethony, Jeffery; Pinlaor, Somchai; Mulvenna, Jason

2017-01-01

Parts of Southeast Asia have the highest incidence of intrahepatic cholangiocarcinoma (CCA) in the world because of infection by the liver fluke Opisthorchis viverrini (Ov). Ov-associated CCA is the culmination of chronic Ov-infection, with the persistent production of the growth factors and cytokines associated with persistent inflammation, which can endure for years in Ov-infected individuals prior to transitioning to CCA. Isobaric labeling and tandem mass spectrometry of liver tissue from a hamster model of CCA was used to compare protein expression profiles from inflammed tissue (Ovinfected but not cancerous) versus cancerous tissue (Ov-induced CCA). Immunohistochemistry and immunoblotting were used to verify dysregulated proteins in the animal model and in human tissue. We identified 154 dysregulated proteins that marked the transition from Ov-infection to Ov-induced CCA, i.e. proteins dysregulated during carcinogenesis but not Ov-infection. The verification of dysregulated proteins in resected liver tissue from humans with Ov-associated CCA showed the numerous parallels in protein dysregulation between human and animal models of Ov-induced CCA. To identify potential circulating markers for CCA, dysregulated proteins were compared with proteins isolated from exosomes secreted by a human CCA cell line (KKU055) and 27 proteins were identified as dysregulated in CCA and present in exosomes. These data form the basis of potential diagnostic biomarkers for human Ov-associated CCA. The profile of protein dysregulation observed during chronic Ovinfection and then in Ov-induced CCA provides insight into the etiology of an infection-induced inflammation-related cancer. PMID:28232516

Overlooked Short Toxin-Like Proteins: A Shortcut to Drug Design

PubMed Central

Linial, Michal

2017-01-01

Short stable peptides have huge potential for novel therapies and biosimilars. Cysteine-rich short proteins are characterized by multiple disulfide bridges in a compact structure. Many of these metazoan proteins are processed, folded, and secreted as soluble stable folds. These properties are shared by both marine and terrestrial animal toxins. These stable short proteins are promising sources for new drug development. We developed ClanTox (classifier of animal toxins) to identify toxin-like proteins (TOLIPs) using machine learning models trained on a large-scale proteomic database. Insects proteomes provide a rich source for protein innovations. Therefore, we seek overlooked toxin-like proteins from insects (coined iTOLIPs). Out of 4180 short (<75 amino acids) secreted proteins, 379 were predicted as iTOLIPs with high confidence, with as many as 30% of the genes marked as uncharacterized. Based on bioinformatics, structure modeling, and data-mining methods, we found that the most significant group of predicted iTOLIPs carry antimicrobial activity. Among the top predicted sequences were 120 termicin genes from termites with antifungal properties. Structural variations of insect antimicrobial peptides illustrate the similarity to a short version of the defensin fold with antifungal specificity. We also identified 9 proteins that strongly resemble ion channel inhibitors from scorpion and conus toxins. Furthermore, we assigned functional fold to numerous uncharacterized iTOLIPs. We conclude that a systematic approach for finding iTOLIPs provides a rich source of peptides for drug design and innovative therapeutic discoveries. PMID:29109389

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

PubMed Central

He, Hao; Zhang, Lei; Li, Jian; Wang, Yu-Ping; Zhang, Ji-Gang; Shen, Jie; Guo, Yan-Fang

2014-01-01

Context: To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods: First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results: In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion: We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis. PMID:25119315

HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1*

PubMed Central

Hernandez, Anna; Buch, Anna; Sodeik, Beate; Cristea, Ileana Mihaela

2016-01-01

Human herpesviruses are widespread human pathogens with a remarkable impact on worldwide public health. Despite intense decades of research, the molecular details in many aspects of their function remain to be fully characterized. To unravel the details of how these viruses operate, a thorough understanding of the relationships between the involved components is key. Here, we present HVint, a novel protein-protein intraviral interaction resource for herpes simplex virus type 1 (HSV-1) integrating data from five external sources. To assess each interaction, we used a scoring scheme that takes into consideration aspects such as the type of detection method and the number of lines of evidence. The coverage of the initial interactome was further increased using evolutionary information, by importing interactions reported for other human herpesviruses. These latter interactions constitute, therefore, computational predictions for potential novel interactions in HSV-1. An independent experimental analysis was performed to confirm a subset of our predicted interactions. This subset covers proteins that contribute to nuclear egress and primary envelopment events, including VP26, pUL31, pUL40, and the recently characterized pUL32 and pUL21. Our findings support a coordinated crosstalk between VP26 and proteins such as pUL31, pUS9, and the CSVC complex, contributing to the development of a model describing the nuclear egress and primary envelopment pathways of newly synthesized HSV-1 capsids. The results are also consistent with recent findings on the involvement of pUL32 in capsid maturation and early tegumentation events. Further, they open the door to new hypotheses on virus-specific regulators of pUS9-dependent transport. To make this repository of interactions readily accessible for the scientific community, we also developed a user-friendly and interactive web interface. Our approach demonstrates the power of computational predictions to assist in the design of

Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations.

PubMed

Suratanee, Apichat; Plaimas, Kitiporn

2017-01-01

The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k -nearest neighbor (R k NN) search. The R k NN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the R k NN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases.

Differential proteomic analysis to identify proteins associated with quality traits of frozen mud shrimp (Solenocera melantho) using an iTRAQ-based strategy.

PubMed

Shi, Jing; Zhang, Longteng; Lei, Yutian; Shen, Huixing; Yu, Xunpei; Luo, Yongkang

2018-06-15

An iTRAQ-based strategy was applied to investigate proteome changes in mud shrimp during long-term frozen storage under different conditions. A total of 226 proteins was identified as differential abundance proteins (DAPs) in mud shrimp from two frozen treatment groups (-20 °C and -40 °C) compared with the fresh control group. The proteome changes in mud shrimp muscle stored under -20 °C was much greater than that under -40 °C. Correlation analysis between DAPs and quality traits of mud shrimp muscle showed that 12 proteins were correlated closely with color (L ∗ , a ∗ , and b ∗ value) and texture (hardness, elasticity, and chewiness). Bioinformatic analysis revealed that most of these proteins were involved in protein structure, metabolic enzymes, and protein turnover. Among them, several proteins might be potential protein markers for color, and some proteins are good candidate predictors for textural properties of mud shrimp muscle. Copyright © 2018 Elsevier Ltd. All rights reserved.

Quantitative study of protein-protein interactions by quartz nanopipettes

NASA Astrophysics Data System (ADS)

Tiwari, Purushottam Babu; Astudillo, Luisana; Miksovska, Jaroslava; Wang, Xuewen; Li, Wenzhi; Darici, Yesim; He, Jin

2014-08-01

In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions.In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with

The 1.1 Å resolution structure of a periplasmic phosphate-binding protein from Stenotrophomonas maltophilia: a crystallization contaminant identified by molecular replacement using the entire Protein Data Bank.

PubMed

Keegan, Ronan; Waterman, David G; Hopper, David J; Coates, Leighton; Taylor, Graham; Guo, Jingxu; Coker, Alun R; Erskine, Peter T; Wood, Steve P; Cooper, Jonathan B

2016-08-01

During efforts to crystallize the enzyme 2,4-dihydroxyacetophenone dioxygenase (DAD) from Alcaligenes sp. 4HAP, a small number of strongly diffracting protein crystals were obtained after two years of crystal growth in one condition. The crystals diffracted synchrotron radiation to almost 1.0 Å resolution and were, until recently, assumed to be formed by the DAD protein. However, when another crystal form of this enzyme was eventually solved at lower resolution, molecular replacement using this new structure as the search model did not give a convincing solution with the original atomic resolution data set. Hence, it was considered that these crystals might have arisen from a protein impurity, although molecular replacement using the structures of common crystallization contaminants as search models again failed. A script to perform molecular replacement using MOLREP in which the first chain of every structure in the PDB was used as a search model was run on a multi-core cluster. This identified a number of prokaryotic phosphate-binding proteins as scoring highly in the MOLREP peak lists. Calculation of an electron-density map at 1.1 Å resolution based on the solution obtained with PDB entry 2q9t allowed most of the amino acids to be identified visually and built into the model. A BLAST search then indicated that the molecule was most probably a phosphate-binding protein from Stenotrophomonas maltophilia (UniProt ID B4SL31; gene ID Smal_2208), and fitting of the corresponding sequence to the atomic resolution map fully corroborated this. Proteins in this family have been linked to the virulence of antibiotic-resistant strains of pathogenic bacteria and with biofilm formation. The structure of the S. maltophilia protein has been refined to an R factor of 10.15% and an Rfree of 12.46% at 1.1 Å resolution. The molecule adopts the type II periplasmic binding protein (PBP) fold with a number of extensively elaborated loop regions. A fully dehydrated phosphate

Antibody screening identifies 78 putative host proteins involved in Cyprinid herpesvirus 3 infection or propagation in common carp, Cyprinus carpio L.

PubMed Central

Gotesman, M; Soliman, H; El-Matbouli, M

2014-01-01

Cyprinid herpesvirus 3 (CyHV-3) is the aetiological agent of a serious and notifiable disease afflicting common and koi carp, Cyprinus carpio L., termed koi herpesvirus disease (KHVD). Significant progress has been achieved in the last 15 years, since the initial reports surfaced from Germany, USA and Israel of the CyHV-3 virus, in terms of pathology and detection. However, relatively few studies have been carried out in understanding viral replication and propagation. Antibody-based affinity has been used for detection of CyHV-3 in enzyme-linked immunosorbent assay and PCR-based techniques, and immunohistological assays have been used to describe a CyHV-3 membrane protein, termed ORF81. In this study, monoclonal antibodies linked to N-hydroxysuccinimide (NHS)-activated spin columns were used to purify CyHV-3 and host proteins from tissue samples originating in either CyHV-3 symptomatic or asymptomatic fish. The samples were next analysed either by polyacrylamide gel electrophoresis (PAGE) and subsequently by electrospray ionization coupled to mass spectrometry (ESI-MS) or by ESI-MS analysis directly after purification. A total of 78 host proteins and five CyHV-3 proteins were identified in the two analyses. These data can be used to develop novel control methods for CyHV-3, based on pathways or proteins identified in this study. PMID:23347276

Application of wide selected-ion monitoring data-independent acquisition to identify tomato fruit proteins regulated by the CUTIN DEFICIENT2 transcription factor.

PubMed

Martin, Laetitia B B; Sherwood, Robert W; Nicklay, Joshua J; Yang, Yong; Muratore-Schroeder, Tara L; Anderson, Elizabeth T; Thannhauser, Theodore W; Rose, Jocelyn K C; Zhang, Sheng

2016-08-01

We describe here the use of label-free wide selected-ion monitoring data-independent acquisition (WiSIM-DIA) to identify proteins that are involved in the formation of tomato (Solanum lycopersicum) fruit cuticles and that are regulated by the transcription factor CUTIN DEFICIENT2 (CD2). A spectral library consisting of 11 753 unique peptides, corresponding to 2338 tomato protein groups, was used and the DIA analysis was performed at the MS1 level utilizing narrow mass windows for extraction with Skyline 2.6 software. We identified a total of 1140 proteins, 67 of which had expression levels that differed significantly between the cd2 tomato mutant and the wild-type cultivar M82. Differentially expressed proteins including a key protein involved in cutin biosynthesis, were selected for validation by target SRM/MRM and by Western blot analysis. In addition to confirming a role for CD2 in regulating cuticle formation, the results also revealed that CD2 influences pathways associated with cell wall biology, anthocyanin biosynthesis, plant development, and responses to stress, which complements findings of earlier RNA-Seq experiments. Our results provide new insights into molecular processes and aspects of fruit biology associated with CD2 function, and demonstrate that the WiSIM-DIA is an effective quantitative approach for global protein identifications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of wide selected-ion monitoring data-independent acquisition to identify tomato fruit proteins regulated by the CUTIN DEFICIENT2 transcription factor

PubMed Central

Martin, Laetitia B. B.; Sherwood, Robert W.; Nicklay, Joshua J.; Yang, Yong; Muratore-Schroeder, Tara L.; Anderson, Elizabeth T.; Thannhauser, Theodore W.; Rose, Jocelyn K. C.; Zhang, Sheng

2017-01-01

We describe here the use of label-free wide selected-ion monitoring data-independent acquisition (WiSIM-DIA) to identify proteins that are involved in the formation of tomato (Solanum lycopersicum) fruit cuticles and that are regulated by the transcription factor CUTIN DEFICIENT2 (CD2). A spectral library consisting of 11 753 unique peptides, corresponding to 2338 tomato protein groups, was used and the DIA analysis was performed at the MS1 level utilizing narrow mass windows for extraction with Skyline 2.6 software. We identified a total of 1140 proteins, 67 of which had expression levels that differed significantly between the cd2 tomato mutant and the wild-type cultivar M82. Differentially expressed proteins including a key protein involved in cutin biosynthesis, were selected for validation by target SRM/MRM and by Western blot analysis. In addition to confirming a role for CD2 in regulating cuticle formation, the results also revealed that CD2 influences pathways associated with cell wall biology, anthocyanin biosynthesis, plant development, and responses to stress, which complements findings of earlier RNA-Seq experiments. Our results provide new insights into molecular processes and aspects of fruit biology associated with CD2 function, and demonstrate that the WiSIM-DIA is an effective quantitative approach for global protein identifications. PMID:27089858

Eukaryotic elongation factor 2 kinase regulates the synthesis of microtubule-related proteins in neurons.

PubMed

Kenney, Justin W; Genheden, Maja; Moon, Kyung-Mee; Wang, Xuemin; Foster, Leonard J; Proud, Christopher G

2016-01-01

Modulation of the elongation phase of protein synthesis is important for numerous physiological processes in both neurons and other cell types. Elongation is primarily regulated via eukaryotic elongation factor 2 kinase (eEF2K). However, the consequence of altering eEF2K activity on the synthesis of specific proteins is largely unknown. Using both pharmacological and genetic manipulations of eEF2K combined with two protein-labeling techniques, stable isotope labeling of amino acids in cell culture and bio-orthogonal non-canonical amino acid tagging, we identified a subset of proteins whose synthesis is sensitive to inhibition of eEF2K in murine primary cortical neurons. Gene ontology (GO) analyses indicated that processes related to microtubules are particularly sensitive to eEF2K inhibition. Our findings suggest that eEF2K likely contributes to neuronal function by regulating the synthesis of microtubule-related proteins. Modulation of the elongation phase of protein synthesis is important for numerous physiological processes in neurons. Here, using labeling of new proteins coupled with proteomic techniques in primary cortical neurons, we find that the synthesis of microtubule-related proteins is up-regulated by inhibition of elongation. This suggests that translation elongation is a key regulator of cytoskeletal dynamics in neurons. © 2015 The Authors. Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of International Society for Neurochemistry.

Deciphering mRNA Sequence Determinants of Protein Production Rate

NASA Astrophysics Data System (ADS)

Szavits-Nossan, Juraj; Ciandrini, Luca; Romano, M. Carmen

2018-03-01

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons' choice for regulating translation rates and ribosome densities.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

PubMed

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions

PubMed Central

Banks, Charles A. S.; Boanca, Gina; Lee, Zachary T.; Florens, Laurence; Washburn, Michael P.

2015-01-01

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine “cloning scar” present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected. PMID:25704442

Membrane-associated proteomics of chickpea identifies Sad1/UNC-84 protein (CaSUN1), a novel component of dehydration signaling

NASA Astrophysics Data System (ADS)

Jaiswal, Dinesh Kumar; Mishra, Poonam; Subba, Pratigya; Rathi, Divya; Chakraborty, Subhra; Chakraborty, Niranjan

2014-02-01

Dehydration affects almost all the physiological processes including those that result in the accumulation of misfolded proteins in the endoplasmic reticulum (ER), which in turn elicits a highly conserved signaling, the unfolded protein response (UPR). We investigated the dehydration-responsive membrane-associated proteome of a legume, chickpea, by 2-DE coupled with mass spectrometry. A total of 184 protein spots were significantly altered over a dehydration treatment of 120 h. Among the differentially expressed proteins, a non-canonical SUN domain protein, designated CaSUN1 (Cicer arietinum Sad1/UNC-84), was identified. CaSUN1 localized to the nuclear membrane and ER, besides small vacuolar vesicles. The transcripts were downregulated by both abiotic and biotic stresses, but not by abscisic acid treatment. Overexpression of CaSUN1 conferred stress tolerance in transgenic Arabidopsis. Furthermore, functional complementation of the yeast mutant, slp1, could rescue its growth defects. We propose that the function of CaSUN1 in stress response might be regulated via UPR signaling.

Energy Landscape and Transition State of Protein-Protein Association

NASA Astrophysics Data System (ADS)

Alsallaq, Ramzi; Zhou, Huan-Xiang

2006-11-01

Formation of a stereospecific protein complex is favored by specific interactions between two proteins but disfavored by the loss of translational and rotational freedom. Echoing the protein folding process, we have previously proposed a transition state for protein-protein association. Here we clarify the specification of the transition state by working with two toy models for protein association. The models demonstrate that a sharp transition between the bound state with numerous short-range interactions but restricted translation and rotational freedom and the unbound state with at most a small number of interactions but expanded configurational freedom. This transition sets the outer boundary of the bound state as well as the transition state for association. The energy landscape is funnel-like, with the deep well of the bound state surrounded by a broad shallow basin. This formalism of protein-protein association is applied to four protein-protein complexes, and is found to give accurate predictions for the effects of charge mutations and ionic strength on the association rates.

Juvenile Hormone Prevents 20-Hydroxyecdysone-induced Metamorphosis by Regulating the Phosphorylation of a Newly Identified Broad Protein*

PubMed Central

Cai, Mei-Juan; Liu, Wen; Pei, Xu-Yang; Li, Xiang-Ru; He, Hong-Juan; Wang, Jin-Xing; Zhao, Xiao-Fan

2014-01-01

The steroid hormone 20-hydroxyecdysone (20E) initiates insect molting and metamorphosis. By contrast, juvenile hormone (JH) prevents metamorphosis. However, the mechanism by which JH inhibits metamorphosis remains unclear. In this study, we propose that JH induces the phosphorylation of Broad isoform Z7 (BrZ7), a newly identified protein, to inhibit 20E-mediated metamorphosis in the lepidopteran insect Helicoverpa armigera. The knockdown of BrZ7 in larvae inhibited metamorphosis by repressing the expression of the 20E response gene. BrZ7 was weakly expressed and phosphorylated during larval growth but highly expressed and non-phosphorylated during metamorphosis. JH regulated the rapid phosphorylation of BrZ7 via a G-protein-coupled receptor-, phospholipase C-, and protein kinase C-triggered pathway. The phosphorylated BrZ7 bound to the 5′-regulatory region of calponin to regulate its expression in the JH pathway. Exogenous JH induced BrZ7 phosphorylation to prevent metamorphosis by suppressing 20E-related gene transcription. JH promoted non-phosphorylated calponin interacting with ultraspiracle protein to activate the JH pathway and antagonize the 20E pathway. This study reveals one of the possible mechanisms by which JH counteracts 20E-regulated metamorphosis by inducing the phosphorylation of BrZ7. PMID:25096576

An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

PubMed

Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through

Differential proteomics analysis to identify proteins and pathways associated with male sterility of soybean using iTRAQ-based strategy.

PubMed

Li, Jiajia; Ding, Xianlong; Han, Shaohuai; He, Tingting; Zhang, Hao; Yang, Longshu; Yang, Shouping; Gai, Junyi

2016-04-14

To further elucidate the molecular mechanism of cytoplasmic male sterility (CMS) in soybean, a differential proteomic analysis was completed between the CMS line NJCMS1A and its maintainer NJCMS1B using iTRAQ-based strategy. As a result, 180 differential abundance proteins (DAPs) were identified, of which, 60 were down-regulated and 120 were up-regulated in NJCMS1A compared with NJCMS1B. Bioinformatic analysis showed that 167 DAPs were annotated in 41 Gene Ontology functional groups, 106 DAPs were classified into 20 clusters of orthologous groups of protein categories, and 128 DAPs were enrichment in 53 KEGG pathways. Fifteen differential level proteins/genes with the same expression pattern were identified in the further conjoint analysis of DAPs and the previously reported differential expression genes. Moreover, multiple reaction monitoring test, qRT-PCR analysis and enzyme activity assay validated that the iTRAQ results were reliable. Based on functional analysis of DAPs, we concluded that male sterility in NJCMS1A might be related to insufficiencies in energy supply, unbalance of protein synthesis and degradation, disruption of flavonoid synthesis, programmed cell death, abnormalities of substance metabolism, etc. These results might facilitate our understanding of the molecular mechanisms behind CMS in soybean. Soybean is an important global crop that provides protein and oil. Heterosis is a significantly potential approach to increase the yield of soybean. Cytoplasmic male sterility (CMS) plays a vital role in the production of hybrid seeds. However, the genetic and molecular mechanisms of male sterility in soybean still need to be further elucidated. In the present paper, a differential proteomic analysis was carried out and the results showed that several key proteins involved in key pathways were associated with male sterility in soybean. This work provides a new insight to understand the genetic and molecular mechanisms underlying CMS in soybean

Combination of Multiple Spectral Libraries Improves the Current Search Methods Used to Identify Missing Proteins in the Chromosome-Centric Human Proteome Project.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Kim, Kwang-Youl; Kwon, Kyung-Hoon; Yoo, Jong Shin; Omenn, Gilbert S; Baker, Mark S; Hancock, William S; Paik, Young-Ki

2015-12-04

Approximately 2.9 billion long base-pair human reference genome sequences are known to encode some 20 000 representative proteins. However, 3000 proteins, that is, ~15% of all proteins, have no or very weak proteomic evidence and are still missing. Missing proteins may be present in rare samples in very low abundance or be only temporarily expressed, causing problems in their detection and protein profiling. In particular, some technical limitations cause missing proteins to remain unassigned. For example, current mass spectrometry techniques have high limits and error rates for the detection of complex biological samples. An insufficient proteome coverage in a reference sequence database and spectral library also raises major issues. Thus, the development of a better strategy that results in greater sensitivity and accuracy in the search for missing proteins is necessary. To this end, we used a new strategy, which combines a reference spectral library search and a simulated spectral library search, to identify missing proteins. We built the human iRefSPL, which contains the original human reference spectral library and additional peptide sequence-spectrum match entries from other species. We also constructed the human simSPL, which contains the simulated spectra of 173 907 human tryptic peptides determined by MassAnalyzer (version 2.3.1). To prove the enhanced analytical performance of the combination of the human iRefSPL and simSPL methods for the identification of missing proteins, we attempted to reanalyze the placental tissue data set (PXD000754). The data from each experiment were analyzed using PeptideProphet, and the results were combined using iProphet. For the quality control, we applied the class-specific false-discovery rate filtering method. All of the results were filtered at a false-discovery rate of <1% at the peptide and protein levels. The quality-controlled results were then cross-checked with the neXtProt DB (2014-09-19 release). The two

Quantifying protein-protein interactions in high throughput using protein domain microarrays.

PubMed

Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

2010-04-01

Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

Seed protein variations of Salicornia L. and allied taxa in Turkey.

PubMed

Yaprak, A E; Yurdakulol, E

2007-06-01

Electrophoretic seed protein patterns of a number of accessions of Salicornia europaea L. sl., S. prostrata Palas, S. fragilis P.W. Ball and Tutin, Sarcocornia fruticosa (L.) A. J. Scott, Sarcocornia perennis (Miller.) A. J. Scott, Arthrocnemum glaucum (Del.) Ung.-Sternb., Microcnemum coralloides (Loscos and Pardo) subsp. anatolicum Wagenitz and Halocnemum strobilaceum (Pall.) Bieb. were electrophoretically analysed on SDS-PAGE. In total 48 different bands were identified. The obtained data have been treated numerically using the cluster analysis method of unweighted pair group (UPGMA). Finally it was determined that all species separated according to seed protein profiles. And the cladogram obtained studied taxa have been given.

Ugene, a newly identified protein that is commonly over-expressed in cancer, and that binds uracil DNA-glycosylase

PubMed Central

Guo, Chunguang; Zhang, Xiaodong; Fink, Stephen P; Platzer, Petra; Wilson, Keith; Willson, James K. V.; Wang, Zhenghe; Markowitz, Sanford D

2008-01-01

Expression microarrays identified a novel transcript, designated as Ugene, whose expression is absent in normal colon and colon adenomas, but that is commonly induced in malignant colon cancers. These findings were validated by real-time PCR and Northern blot analysis in an independent panel of colon cancer cases. In addition, Ugene expression was found to be elevated in many other common cancer types, including, breast, lung, uterus, and ovary. Immunofluorescence of V5-tagged Ugene revealed it to have a nuclear localization. In a pull-down assay, uracil DNA-glycosylase 2 (UNG2), an important enzyme in the base excision repair pathway, was identified as a partner protein that binds to Ugene. Co-immunoprecipitation and Western blot analysis confirmed the binding between the endogenous Ugene and UNG2 proteins. Using deletion constructs, we find that Ugene binds to the first 25 amino acids of the UNG2 NH2-terminus. We suggest Ugene induction in cancer may contribute to the cancer phenotype by interacting with the base excision repair pathway. PMID:18676834

Lack of beta-arrestin signaling in the absence of active G proteins.

PubMed

Grundmann, Manuel; Merten, Nicole; Malfacini, Davide; Inoue, Asuka; Preis, Philip; Simon, Katharina; Rüttiger, Nelly; Ziegler, Nicole; Benkel, Tobias; Schmitt, Nina Katharina; Ishida, Satoru; Müller, Ines; Reher, Raphael; Kawakami, Kouki; Inoue, Ayumi; Rick, Ulrike; Kühl, Toni; Imhof, Diana; Aoki, Junken; König, Gabriele M; Hoffmann, Carsten; Gomeza, Jesus; Wess, Jürgen; Kostenis, Evi

2018-01-23

G protein-independent, arrestin-dependent signaling is a paradigm that broadens the signaling scope of G protein-coupled receptors (GPCRs) beyond G proteins for numerous biological processes. However, arrestin signaling in the collective absence of functional G proteins has never been demonstrated. Here we achieve a state of "zero functional G" at the cellular level using HEK293 cells depleted by CRISPR/Cas9 technology of the Gs/q/12 families of Gα proteins, along with pertussis toxin-mediated inactivation of Gi/o. Together with HEK293 cells lacking β-arrestins ("zero arrestin"), we systematically dissect G protein- from arrestin-driven signaling outcomes for a broad set of GPCRs. We use biochemical, biophysical, label-free whole-cell biosensing and ERK phosphorylation to identify four salient features for all receptors at "zero functional G": arrestin recruitment and internalization, but-unexpectedly-complete failure to activate ERK and whole-cell responses. These findings change our understanding of how GPCRs function and in particular of how they activate ERK1/2.

The Primary Role of Fibrinogen-Related Proteins in Invertebrates Is Defense, Not Coagulation

PubMed Central

Hanington, Patrick C.; Zhang, Si-Ming

2010-01-01

In vertebrates, the conversion of fibrinogen into fibrin is an essential process that underlies the establishment of the supporting protein framework required for coagulation. In invertebrates, fibrinogen-domain-containing proteins play a role in the defense response generated against pathogens; however, they do not function in coagulation, suggesting that this role has been recently acquired. Molecules containing fibrinogen motifs have been identified in numerous invertebrate organisms, and most of these molecules known to date have been linked to defense. Moreover, recent genome projects of invertebrate animals have revealed surprisingly high numbers of fibrinogen-like loci in their genomes, suggesting important and perhaps diverse functions of fibrinogen-like proteins in invertebrates. The ancestral role of molecules containing fibrinogen-related domains (FReDs) with immunity is the focus of this review, with emphasis on specific FReDs called fibrinogen-related proteins (FREPs) identified from the schistosome-transmitting mollusc Biomphalaria glabrata. Herein, we outline the range of invertebrate organisms FREPs can be found in, and detail the roles these molecules play in defense and protection against infection. PMID:21063081

Analysis of Proteins That Rapidly Change Upon Mechanistic/Mammalian Target of Rapamycin Complex 1 (mTORC1) Repression Identifies Parkinson Protein 7 (PARK7) as a Novel Protein Aberrantly Expressed in Tuberous Sclerosis Complex (TSC).

PubMed

Niere, Farr; Namjoshi, Sanjeev; Song, Ehwang; Dilly, Geoffrey A; Schoenhard, Grant; Zemelman, Boris V; Mechref, Yehia; Raab-Graham, Kimberly F

2016-02-01

Many biological processes involve the mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Thus, the challenge of deciphering mTORC1-mediated functions during normal and pathological states in the central nervous system is challenging. Because mTORC1 is at the core of translation, we have investigated mTORC1 function in global and regional protein expression. Activation of mTORC1 has been generally regarded to promote translation. Few but recent works have shown that suppression of mTORC1 can also promote local protein synthesis. Moreover, excessive mTORC1 activation during diseased states represses basal and activity-induced protein synthesis. To determine the role of mTORC1 activation in protein expression, we have used an unbiased, large-scale proteomic approach. We provide evidence that a brief repression of mTORC1 activity in vivo by rapamycin has little effect globally, yet leads to a significant remodeling of synaptic proteins, in particular those proteins that reside in the postsynaptic density. We have also found that curtailing the activity of mTORC1 bidirectionally alters the expression of proteins associated with epilepsy, Alzheimer's disease, and autism spectrum disorder-neurological disorders that exhibit elevated mTORC1 activity. Through a protein-protein interaction network analysis, we have identified common proteins shared among these mTORC1-related diseases. One such protein is Parkinson protein 7, which has been implicated in Parkinson's disease, yet not associated with epilepsy, Alzheimers disease, or autism spectrum disorder. To verify our finding, we provide evidence that the protein expression of Parkinson protein 7, including new protein synthesis, is sensitive to mTORC1 inhibition. Using a mouse model of tuberous sclerosis complex, a disease that displays both epilepsy and autism spectrum disorder phenotypes and has overactive mTORC1 signaling, we show that Parkinson protein 7 protein is elevated in the dendrites and colocalizes

Computational prediction of host-pathogen protein-protein interactions.

PubMed

Dyer, Matthew D; Murali, T M; Sobral, Bruno W

2007-07-01

Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein-protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens-Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions. Supplementary data are available at http://staff.vbi.vt.edu/dyermd/publications/dyer2007a.html. Supplementary data are available at Bioinformatics online.

HIP1-ALK, a novel fusion protein identified in lung adenocarcinoma.

PubMed

Hong, Mineui; Kim, Ryong Nam; Song, Ji-Young; Choi, So-Jung; Oh, Ensel; Lira, Maruja E; Mao, Mao; Takeuchi, Kengo; Han, Joungho; Kim, Jhingook; Choi, Yoon-La

2014-03-01

The most common mechanism underlying overexpression and activation of anaplastic lymphoma kinase (ALK) in non-small-cell lung carcinoma could be attributed to the formation of a fusion protein. To date, five fusion partners of ALK have been reported, namely, echinoderm microtubule associated protein like 4, tropomyosin-related kinase-fused gene, kinesin family member 5B, kinesin light chain 1, and protein tyrosine phosphatase, nonreceptor type 3. In this article, we report a novel fusion gene huntingtin interacting protein 1 (HIP1)-ALK, which is conjoined between the huntingtin-interacting protein 1 gene HIP1 and ALK. Reverse-transcriptase polymerase chain reaction and immunohistochemical analysis were used to detect this fusion gene's transcript and protein expression, respectively. We had amplified the full-length cDNA sequence of this novel fusion gene by using 5'-rapid amplification of cDNA ends. The causative genomic translocation t(2;7)(p23;q11.23) for generating this novel fusion gene was verified by using genomic sequencing. The examined adenocarcinoma showed predominant acinar pattern, and ALK immunostaining was localized to the cytoplasm, with intense staining in the submembrane region. In break-apart, fluorescence in situ hybridization analysis for ALK, split of the 5' and 3' probe signals, and isolated 3' signals were observed. Reverse-transcriptase polymerase chain reaction revealed that the tumor harbored a novel fusion transcript in which exon 21 of HIP1 was fused to exon 20 of ALK in-frame. The novel fusion gene and its protein HIP1-ALK harboring epsin N-terminal homology, coiled-coil, juxtamembrane, and kinase domains, which could play a role in carcinogenesis, could become diagnostic and therapeutic target of the lung adenocarcinoma and deserve a further study in the future.

Sperm and Spermatids Contain Different Proteins and Bind Distinct Egg Factors

PubMed Central

Teperek, Marta; Miyamoto, Kei; Simeone, Angela; Feret, Renata; Deery, Michael J.; Gurdon, John B.; Jullien, Jerome

2014-01-01

Spermatozoa are more efficient at supporting normal embryonic development than spermatids, their immature, immediate precursors. This suggests that the sperm acquires the ability to support embryonic development during spermiogenesis (spermatid to sperm maturation). Here, using Xenopus laevis as a model organism, we performed 2-D Fluorescence Difference Gel Electrophoresis (2D-DIGE) and mass spectrometry analysis of differentially expressed proteins between sperm and spermatids in order to identify factors that could be responsible for the efficiency of the sperm to support embryonic development. Furthermore, benefiting from the availability of egg extracts in Xenopus, we also tested whether the chromatin of sperm could attract different egg factors compared to the chromatin of spermatids. Our analysis identified: (1) several proteins which were present exclusively in sperm; but not in spermatid nuclei and (2) numerous egg proteins binding to the sperm (but not to the spermatid chromatin) after incubation in egg extracts. Amongst these factors we identified many chromatin-associated proteins and transcriptional repressors. Presence of transcriptional repressors binding specifically to sperm chromatin could suggest its preparation for the early embryonic cell cycles, during which no transcription is observed and suggests that sperm chromatin has a unique protein composition, which facilitates the recruitment of egg chromatin remodelling factors. It is therefore likely that the acquisition of these sperm-specific factors during spermiogenesis makes the sperm chromatin suitable to interact with the maternal factors and, as a consequence, to support efficient embryonic development. PMID:25244019

Solid-phase synthesis and screening of N-acylated polyamine (NAPA) combinatorial libraries for protein binding.

PubMed

Iera, Jaclyn A; Jenkins, Lisa M Miller; Kajiyama, Hiroshi; Kopp, Jeffrey B; Appella, Daniel H

2010-11-15

Inhibitors for protein-protein interactions are challenging to design, in part due to the unique and complex architectures of each protein's interaction domain. Most approaches to develop inhibitors for these interactions rely on rational design, which requires prior structural knowledge of the target and its ligands. In the absence of structural information, a combinatorial approach may be the best alternative to finding inhibitors of a protein-protein interaction. Current chemical libraries, however, consist mostly of molecules designed to inhibit enzymes. In this manuscript, we report the synthesis and screening of a library based on an N-acylated polyamine (NAPA) scaffold that we designed to have specific molecular features necessary to inhibit protein-protein interactions. Screens of the library identified a member with favorable binding properties to the HIV viral protein R (Vpr), a regulatory protein from HIV, that is involved in numerous interactions with other proteins critical for viral replication. Published by Elsevier Ltd.

Modelling of DNA-Mediated of Two- and -Three dimensional Protein-Protein and Protein-Nanoparticle Self-Assembly

NASA Astrophysics Data System (ADS)

Millan, Jaime; McMillan, Janet; Brodin, Jeff; Lee, Byeongdu; Mirkin, Chad; Olvera de La Cruz, Monica

Programmable DNA interactions represent a robust scheme to self-assemble a rich variety of tunable superlattices, where intrinsic and in some cases non-desirable nano-scale building blocks interactions are substituted for DNA hybridization events. Recent advances in synthesis has allowed the extension of this successful scheme to proteins, where DNA distribution can be tuned independently of protein shape by selectively addressing surface residues, giving rise to assembly properties in three dimensional protein-nanoparticle superlattices dependent on DNA distribution. In parallel to this advances, we introduced a scalable coarse-grained model that faithfully reproduces the previously observed co-assemblies from nanoparticles and proteins conjugates. Herein, we implement this numerical model to explain the stability of complex protein-nanoparticle binary superlattices and to elucidate experimentally inaccessible features such as protein orientation. Also, we will discuss systematic studies that highlight the role of DNA distribution and sequence on two-dimensional protein-protein and protein-nanoparticle superlattices.

Analysis of Proteins That Rapidly Change Upon Mechanistic/Mammalian Target of Rapamycin Complex 1 (mTORC1) Repression Identifies Parkinson Protein 7 (PARK7) as a Novel Protein Aberrantly Expressed in Tuberous Sclerosis Complex (TSC)*

PubMed Central

Niere, Farr; Namjoshi, Sanjeev; Song, Ehwang; Dilly, Geoffrey A.; Schoenhard, Grant; Zemelman, Boris V.; Mechref, Yehia; Raab-Graham, Kimberly F.

2016-01-01

Many biological processes involve the mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Thus, the challenge of deciphering mTORC1-mediated functions during normal and pathological states in the central nervous system is challenging. Because mTORC1 is at the core of translation, we have investigated mTORC1 function in global and regional protein expression. Activation of mTORC1 has been generally regarded to promote translation. Few but recent works have shown that suppression of mTORC1 can also promote local protein synthesis. Moreover, excessive mTORC1 activation during diseased states represses basal and activity-induced protein synthesis. To determine the role of mTORC1 activation in protein expression, we have used an unbiased, large-scale proteomic approach. We provide evidence that a brief repression of mTORC1 activity in vivo by rapamycin has little effect globally, yet leads to a significant remodeling of synaptic proteins, in particular those proteins that reside in the postsynaptic density. We have also found that curtailing the activity of mTORC1 bidirectionally alters the expression of proteins associated with epilepsy, Alzheimer's disease, and autism spectrum disorder—neurological disorders that exhibit elevated mTORC1 activity. Through a protein–protein interaction network analysis, we have identified common proteins shared among these mTORC1-related diseases. One such protein is Parkinson protein 7, which has been implicated in Parkinson's disease, yet not associated with epilepsy, Alzheimers disease, or autism spectrum disorder. To verify our finding, we provide evidence that the protein expression of Parkinson protein 7, including new protein synthesis, is sensitive to mTORC1 inhibition. Using a mouse model of tuberous sclerosis complex, a disease that displays both epilepsy and autism spectrum disorder phenotypes and has overactive mTORC1 signaling, we show that Parkinson protein 7 protein is elevated in the dendrites and

A thermodynamic definition of protein domains.

PubMed

Porter, Lauren L; Rose, George D

2012-06-12

Protein domains are conspicuous structural units in globular proteins, and their identification has been a topic of intense biochemical interest dating back to the earliest crystal structures. Numerous disparate domain identification algorithms have been proposed, all involving some combination of visual intuition and/or structure-based decomposition. Instead, we present a rigorous, thermodynamically-based approach that redefines domains as cooperative chain segments. In greater detail, most small proteins fold with high cooperativity, meaning that the equilibrium population is dominated by completely folded and completely unfolded molecules, with a negligible subpopulation of partially folded intermediates. Here, we redefine structural domains in thermodynamic terms as cooperative folding units, based on m-values, which measure the cooperativity of a protein or its substructures. In our analysis, a domain is equated to a contiguous segment of the folded protein whose m-value is largely unaffected when that segment is excised from its parent structure. Defined in this way, a domain is a self-contained cooperative unit; i.e., its cooperativity depends primarily upon intrasegment interactions, not intersegment interactions. Implementing this concept computationally, the domains in a large representative set of proteins were identified; all exhibit consistency with experimental findings. Specifically, our domain divisions correspond to the experimentally determined equilibrium folding intermediates in a set of nine proteins. The approach was also proofed against a representative set of 71 additional proteins, again with confirmatory results. Our reframed interpretation of a protein domain transforms an indeterminate structural phenomenon into a quantifiable molecular property grounded in solution thermodynamics.

The APSES family proteins in fungi: Characterizations, evolution and functions.

PubMed

Zhao, Yong; Su, Hao; Zhou, Jing; Feng, Huihua; Zhang, Ke-Qin; Yang, Jinkui

2015-08-01

The APSES protein family belongs to transcriptional factors of the basic helix-loop-helix (bHLH) class, the originally described members (APSES: Asm1p, Phd1p, Sok2p, Efg1p and StuAp) are used to designate this group of proteins, and they have been identified as key regulators of fungal development and other biological processes. APSES proteins share a highly conserved DNA-binding domain (APSES domain) of about 100 amino acids, whose central domain is predicted to form a typical bHLH structure. Besides APSES domain, several APSES proteins also contain additional domains, such as KilA-N and ankyrin repeats. In recent years, an increasing number of APSES proteins have been identified from diverse fungi, and they involve in numerous biological processes, such as sporulation, cellular differentiation, mycelial growth, secondary metabolism and virulence. Most fungi, including Aspergillus fumigatus, Aspergillus nidulans, Candida albicans, Fusarium graminearum, and Neurospora crassa, contain five APSES proteins. However, Cryptococcus neoformans only contains two APSES proteins, and Saccharomyces cerevisiae contains six APSES proteins. The phylogenetic analysis showed the APSES domains from different fungi were grouped into four clades (A, B, C and D), which is consistent with the result of homologous alignment of APSES domains using DNAman. The roles of APSES proteins in clade C have been studied in detail, while little is known about the roles of other APSES proteins in clades A, B and D. In this review, the biochemical properties and functional domains of APSES proteins are predicted and compared, and the phylogenetic relationship among APSES proteins from various fungi are analyzed based on the APSES domains. Moreover, the functions of APSES proteins in different fungi are summarized and discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

A Novel Cylindrical Representation for Characterizing Intrinsic Properties of Protein Sequences.

PubMed

Yu, Jia-Feng; Dou, Xiang-Hua; Wang, Hong-Bo; Sun, Xiao; Zhao, Hui-Ying; Wang, Ji-Hua

2015-06-22

The composition and sequence order of amino acid residues are the two most important characteristics to describe a protein sequence. Graphical representations facilitate visualization of biological sequences and produce biologically useful numerical descriptors. In this paper, we propose a novel cylindrical representation by placing the 20 amino acid residue types in a circle and sequence positions along the z axis. This representation allows visualization of the composition and sequence order of amino acids at the same time. Ten numerical descriptors and one weighted numerical descriptor have been developed to quantitatively describe intrinsic properties of protein sequences on the basis of the cylindrical model. Their applications to similarity/dissimilarity analysis of nine ND5 proteins indicated that these numerical descriptors are more effective than several classical numerical matrices. Thus, the cylindrical representation obtained here provides a new useful tool for visualizing and charactering protein sequences. An online server is available at http://biophy.dzu.edu.cn:8080/CNumD/input.jsp .

Computational enzyme design: transitioning from catalytic proteins to enzymes.

PubMed

Mak, Wai Shun; Siegel, Justin B

2014-08-01

The widespread interest in enzymes stem from their ability to catalyze chemical reactions under mild and ecologically friendly conditions with unparalleled catalytic proficiencies. While thousands of naturally occurring enzymes have been identified and characterized, there are still numerous important applications for which there are no biological catalysts capable of performing the desired chemical transformation. In order to engineer enzymes for which there is no natural starting point, efforts using a combination of quantum chemistry and force-field based protein molecular modeling have led to the design of novel proteins capable of catalyzing chemical reactions not catalyzed by naturally occurring enzymes. Here we discuss the current status and potential avenues to pursue as the field of computational enzyme design moves forward. Published by Elsevier Ltd.

Hydrophobic-domain-dependent protein-protein interactions mediate the localization of GPAT enzymes to ER subdomains

USDA-ARS?s Scientific Manuscript database

The endoplasmic reticulum (ER) is a dynamic network that consists of numerous regions or subdomains with discrete morphological features and functional properties, including those involved in protein and oil-body formation, anterograde transport of secretory proteins, the exchange of macromolecules ...

Characterization of the heterotrimeric G-protein family and its transmembrane regulator from capsicum (Capsicum annuum L.).

PubMed

Romero-Castillo, Rafael A; Roy Choudhury, Swarup; León-Félix, Josefina; Pandey, Sona

2015-05-01

Throughout evolution, organisms have created numerous mechanisms to sense and respond to their environment. One such highly conserved mechanism involves regulation by heterotrimeric G-protein complex comprised of alpha (Gα), beta (Gβ) and gamma (Gγ) subunits. In plants, these proteins play important roles in signal transduction pathways related to growth and development including response to biotic and abiotic stresses and consequently affect yield. In this work, we have identified and characterized the complete heterotrimeric G-protein repertoire in the Capsicum annuum (Capsicum) genome which consists of one Gα, one Gβ and three Gγ genes. We have also identified one RGS gene in the Capsicum genome that acts as a regulator of the G-protein signaling. Biochemical activities of the proteins were confirmed by assessing the GTP-binding and GTPase activity of the recombinant Gα protein and its regulation by the GTPase acceleration activity of the RGS protein. Interaction between different subunits was established using yeast- and plant-based analyses. Gene and protein expression profiles of specific G-protein components revealed interesting spatial and temporal regulation patterns, especially during root development and during fruit development and maturation. This research thus details the characterization of the first heterotrimeric G-protein family from a domesticated, commercially important vegetable crop. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2017-05-01

An important source of uncertainty, which causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. Therefore, finding a subset among numerous physical parameters in numerical models in the atmospheric and oceanic sciences, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach in China. The results imply that nonlinear interactions among parameters play a key role in the identification of sensitive parameters in arid and semi-arid regions of China compared to those in northern, northeastern, and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

Optimization of protein-protein docking for predicting Fc-protein interactions.

PubMed

Agostino, Mark; Mancera, Ricardo L; Ramsland, Paul A; Fernández-Recio, Juan

2016-11-01

The antibody crystallizable fragment (Fc) is recognized by effector proteins as part of the immune system. Pathogens produce proteins that bind Fc in order to subvert or evade the immune response. The structural characterization of the determinants of Fc-protein association is essential to improve our understanding of the immune system at the molecular level and to develop new therapeutic agents. Furthermore, Fc-binding peptides and proteins are frequently used to purify therapeutic antibodies. Although several structures of Fc-protein complexes are available, numerous others have not yet been determined. Protein-protein docking could be used to investigate Fc-protein complexes; however, improved approaches are necessary to efficiently model such cases. In this study, a docking-based structural bioinformatics approach is developed for predicting the structures of Fc-protein complexes. Based on the available set of X-ray structures of Fc-protein complexes, three regions of the Fc, loosely corresponding to three turns within the structure, were defined as containing the essential features for protein recognition and used as restraints to filter the initial docking search. Rescoring the filtered poses with an optimal scoring strategy provided a success rate of approximately 80% of the test cases examined within the top ranked 20 poses, compared to approximately 20% by the initial unrestrained docking. The developed docking protocol provides a significant improvement over the initial unrestrained docking and will be valuable for predicting the structures of currently undetermined Fc-protein complexes, as well as in the design of peptides and proteins that target Fc. Copyright © 2016 John Wiley & Sons, Ltd.

Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.

NRIP is newly identified as a Z-disc protein, activating calmodulin signaling for skeletal muscle contraction and regeneration.

PubMed

Chen, Hsin-Hsiung; Chen, Wen-Pin; Yan, Wan-Lun; Huang, Yuan-Chun; Chang, Szu-Wei; Fu, Wen-Mei; Su, Ming-Jai; Yu, I-Shing; Tsai, Tzung-Chieh; Yan, Yu-Ting; Tsao, Yeou-Ping; Chen, Show-Li

2015-11-15

Nuclear receptor interaction protein (NRIP, also known as DCAF6 and IQWD1) is a Ca(2+)-dependent calmodulin-binding protein. In this study, we newly identify NRIP as a Z-disc protein in skeletal muscle. NRIP-knockout mice were generated and found to have reduced muscle strength, susceptibility to fatigue and impaired adaptive exercise performance. The mechanisms of NRIP-regulated muscle contraction depend on NRIP being downstream of Ca(2+) signaling, where it stimulates activation of both 'calcineurin-nuclear factor of activated T-cells, cytoplasmic 1' (CaN-NFATc1; also known as NFATC1) and calmodulin-dependent protein kinase II (CaMKII) through interaction with calmodulin (CaM), resulting in the induction of mitochondrial activity and the expression of genes encoding the slow class of myosin, and in the regulation of Ca(2+) homeostasis through the internal Ca(2+) stores of the sarcoplasmic reticulum. Moreover, NRIP-knockout mice have a delayed regenerative capacity. The amount of NRIP can be enhanced after muscle injury and is responsible for muscle regeneration, which is associated with the increased expression of myogenin, desmin and embryonic myosin heavy chain during myogenesis, as well as for myotube formation. In conclusion, NRIP is a novel Z-disc protein that is important for skeletal muscle strength and regenerative capacity. © 2015. Published by The Company of Biologists Ltd.

Metaproteomics of saliva identifies human protein markers specific for individuals with periodontitis and dental caries compared to orally healthy controls.

PubMed

Belstrøm, Daniel; Jersie-Christensen, Rosa R; Lyon, David; Damgaard, Christian; Jensen, Lars J; Holmstrup, Palle; Olsen, Jesper V

2016-01-01

The composition of the salivary microbiota has been reported to differentiate between patients with periodontitis, dental caries and orally healthy individuals. To identify characteristics of diseased and healthy saliva we thus wanted to compare saliva metaproteomes from patients with periodontitis and dental caries to healthy individuals. Stimulated saliva samples were collected from 10 patients with periodontitis, 10 patients with dental caries and 10 orally healthy individuals. The proteins in the saliva samples were subjected to denaturing buffer and digested enzymatically with LysC and trypsin. The resulting peptide mixtures were cleaned up by solid-phase extraction and separated online with 2 h gradients by nano-scale C18 reversed-phase chromatography connected to a mass spectrometer through an electrospray source. The eluting peptides were analyzed on a tandem mass spectrometer operated in data-dependent acquisition mode. We identified a total of 35,664 unique peptides from 4,161 different proteins, of which 1,946 and 2,090 were of bacterial and human origin, respectively. The human protein profiles displayed significant overexpression of the complement system and inflammatory markers in periodontitis and dental caries compared to healthy controls. Bacterial proteome profiles and functional annotation were very similar in health and disease. Overexpression of proteins related to the complement system and inflammation seems to correlate with oral disease status. Similar bacterial proteomes in healthy and diseased individuals suggests that the salivary microbiota predominantly thrives in a planktonic state expressing no disease-associated characteristics of metabolic activity.

Combining an Optical Resonance Biosensor with Enzyme Activity Kinetics to Understand Protein Adsorption and Denaturation

PubMed Central

Wilson, Kerry A.; Finch, Craig A.; Anderson, Phillip; Vollmer, Frank; Hickman, James J.

2014-01-01

Understanding protein adsorption and resultant conformation changes on modified and unmodified silicon dioxide surfaces is a subject of keen interest in biosensors, microfluidic systems and for medical diagnostics. However, it has been proven difficult to investigate the kinetics of the adsorption process on these surfaces as well as understand the topic of the denaturation of proteins and its effect on enzyme activity. A highly sensitive optical whispering gallery mode (WGM) resonator was used to study a catalytic enzyme’s adsorption processes on different silane modified glass substrates (plain glass control, DETA, 13F, and SiPEG). The WGM sensor was able to obtain high resolution kinetic data of glucose oxidase (GO) adsorption with sensitivity of adsorption better than that possible with SPR. The kinetic data, in combination with a functional assay of the enzyme activity, was used to test hypotheses on adsorption mechanisms. By fitting numerical models to the WGM sensograms for protein adsorption, and by confirming numerical predictions of enzyme activity in a separate assay, we were able to identify mechanisms for GO adsorption on different alkylsilanes and infer information about the adsorption of protein on nanostructured surfaces. PMID:25453976

Combining an optical resonance biosensor with enzyme activity kinetics to understand protein adsorption and denaturation.

PubMed

Wilson, Kerry A; Finch, Craig A; Anderson, Phillip; Vollmer, Frank; Hickman, James J

2015-01-01

Understanding protein adsorption and resultant conformation changes on modified and unmodified silicon dioxide surfaces is a subject of keen interest in biosensors, microfluidic systems and for medical diagnostics. However, it has been proven difficult to investigate the kinetics of the adsorption process on these surfaces as well as understand the topic of the denaturation of proteins and its effect on enzyme activity. A highly sensitive optical whispering gallery mode (WGM) resonator was used to study a catalytic enzyme's adsorption processes on different silane modified glass substrates (plain glass control, DETA, 13 F, and SiPEG). The WGM sensor was able to obtain high resolution kinetic data of glucose oxidase (GO) adsorption with sensitivity of adsorption better than that possible with SPR. The kinetic data, in combination with a functional assay of the enzyme activity, was used to test hypotheses on adsorption mechanisms. By fitting numerical models to the WGM sensograms for protein adsorption, and by confirming numerical predictions of enzyme activity in a separate assay, we were able to identify mechanisms for GO adsorption on different alkylsilanes and infer information about the adsorption of protein on nanostructured surfaces. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Novel Highly Divergent Protein Family Identified from a Viviparous Insect by RNA-seq Analysis: A Potential Target for Tsetse Fly-Specific Abortifacients

PubMed Central

Benoit, Joshua B.; Attardo, Geoffrey M.; Michalkova, Veronika; Krause, Tyler B.; Bohova, Jana; Zhang, Qirui; Baumann, Aaron A.; Mireji, Paul O.; Takáč, Peter; Denlinger, David L.; Ribeiro, Jose M.; Aksoy, Serap

2014-01-01

In tsetse flies, nutrients for intrauterine larval development are synthesized by the modified accessory gland (milk gland) and provided in mother's milk during lactation. Interference with at least two milk proteins has been shown to extend larval development and reduce fecundity. The goal of this study was to perform a comprehensive characterization of tsetse milk proteins using lactation-specific transcriptome/milk proteome analyses and to define functional role(s) for the milk proteins during lactation. Differential analysis of RNA-seq data from lactating and dry (non-lactating) females revealed enrichment of transcripts coding for protein synthesis machinery, lipid metabolism and secretory proteins during lactation. Among the genes induced during lactation were those encoding the previously identified milk proteins (milk gland proteins 1–3, transferrin and acid sphingomyelinase 1) and seven new genes (mgp4–10). The genes encoding mgp2–10 are organized on a 40 kb syntenic block in the tsetse genome, have similar exon-intron arrangements, and share regions of amino acid sequence similarity. Expression of mgp2–10 is female-specific and high during milk secretion. While knockdown of a single mgp failed to reduce fecundity, simultaneous knockdown of multiple variants reduced milk protein levels and lowered fecundity. The genomic localization, gene structure similarities, and functional redundancy of MGP2–10 suggest that they constitute a novel highly divergent protein family. Our data indicates that MGP2–10 function both as the primary amino acid resource for the developing larva and in the maintenance of milk homeostasis, similar to the function of the mammalian casein family of milk proteins. This study underscores the dynamic nature of the lactation cycle and identifies a novel family of lactation-specific proteins, unique to Glossina sp., that are essential to larval development. The specificity of MGP2–10 to tsetse and their critical role during

A novel highly divergent protein family identified from a viviparous insect by RNA-seq analysis: a potential target for tsetse fly-specific abortifacients.

PubMed

Benoit, Joshua B; Attardo, Geoffrey M; Michalkova, Veronika; Krause, Tyler B; Bohova, Jana; Zhang, Qirui; Baumann, Aaron A; Mireji, Paul O; Takáč, Peter; Denlinger, David L; Ribeiro, Jose M; Aksoy, Serap

2014-04-01

In tsetse flies, nutrients for intrauterine larval development are synthesized by the modified accessory gland (milk gland) and provided in mother's milk during lactation. Interference with at least two milk proteins has been shown to extend larval development and reduce fecundity. The goal of this study was to perform a comprehensive characterization of tsetse milk proteins using lactation-specific transcriptome/milk proteome analyses and to define functional role(s) for the milk proteins during lactation. Differential analysis of RNA-seq data from lactating and dry (non-lactating) females revealed enrichment of transcripts coding for protein synthesis machinery, lipid metabolism and secretory proteins during lactation. Among the genes induced during lactation were those encoding the previously identified milk proteins (milk gland proteins 1-3, transferrin and acid sphingomyelinase 1) and seven new genes (mgp4-10). The genes encoding mgp2-10 are organized on a 40 kb syntenic block in the tsetse genome, have similar exon-intron arrangements, and share regions of amino acid sequence similarity. Expression of mgp2-10 is female-specific and high during milk secretion. While knockdown of a single mgp failed to reduce fecundity, simultaneous knockdown of multiple variants reduced milk protein levels and lowered fecundity. The genomic localization, gene structure similarities, and functional redundancy of MGP2-10 suggest that they constitute a novel highly divergent protein family. Our data indicates that MGP2-10 function both as the primary amino acid resource for the developing larva and in the maintenance of milk homeostasis, similar to the function of the mammalian casein family of milk proteins. This study underscores the dynamic nature of the lactation cycle and identifies a novel family of lactation-specific proteins, unique to Glossina sp., that are essential to larval development. The specificity of MGP2-10 to tsetse and their critical role during lactation

Probabilistic numerics and uncertainty in computations

PubMed Central

Hennig, Philipp; Osborne, Michael A.; Girolami, Mark

2015-01-01

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations. PMID:26346321

Probabilistic numerics and uncertainty in computations.

PubMed

Hennig, Philipp; Osborne, Michael A; Girolami, Mark

2015-07-08

We deliver a call to arms for probabilistic numerical methods : algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.