Bcl2-associated Athanogene 3 Interactome Analysis Reveals a New Role in Modulating Proteasome Activity*

PubMed Central

Chen, Ying; Yang, Li-Na; Cheng, Li; Tu, Shun; Guo, Shu-Juan; Le, Huang-Ying; Xiong, Qian; Mo, Ran; Li, Chong-Yang; Jeong, Jun-Seop; Jiang, Lizhi; Blackshaw, Seth; Bi, Li-Jun; Zhu, Heng; Tao, Sheng-Ce; Ge, Feng

2013-01-01

Bcl2-associated athanogene 3 (BAG3), a member of the BAG family of co-chaperones, plays a critical role in regulating apoptosis, development, cell motility, autophagy, and tumor metastasis and in mediating cell adaptive responses to stressful stimuli. BAG3 carries a BAG domain, a WW domain, and a proline-rich repeat (PXXP), all of which mediate binding to different partners. To elucidate BAG3's interaction network at the molecular level, we employed quantitative immunoprecipitation combined with knockdown and human proteome microarrays to comprehensively profile the BAG3 interactome in humans. We identified a total of 382 BAG3-interacting proteins with diverse functions, including transferase activity, nucleic acid binding, transcription factors, proteases, and chaperones, suggesting that BAG3 is a critical regulator of diverse cellular functions. In addition, we characterized interactions between BAG3 and some of its newly identified partners in greater detail. In particular, bioinformatic analysis revealed that the BAG3 interactome is strongly enriched in proteins functioning within the proteasome-ubiquitination process and that compose the proteasome complex itself, suggesting that a critical biological function of BAG3 is associated with the proteasome. Functional studies demonstrated that BAG3 indeed interacts with the proteasome and modulates its activity, sustaining cell survival and underlying resistance to therapy through the down-modulation of apoptosis. Taken as a whole, this study expands our knowledge of the BAG3 interactome, provides a valuable resource for understanding how BAG3 affects different cellular functions, and demonstrates that biologically relevant data can be harvested using this kind of integrated approach. PMID:23824909

Proteome-scale human interactomics

PubMed Central

Luck, Katja; Sheynkman, Gloria M.; Zhang, Ivy; Vidal, Marc

2017-01-01

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome-scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life. PMID:28284537

Functional integrative levels in the human interactome recapitulate organ organization.

PubMed

Souiai, Ouissem; Becker, Emmanuelle; Prieto, Carlos; Benkahla, Alia; De las Rivas, Javier; Brun, Christine

2011-01-01

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This 'Largest Common Interactome Network' represents a 'functional interactome core'. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

Proteome-Scale Human Interactomics.

PubMed

Luck, Katja; Sheynkman, Gloria M; Zhang, Ivy; Vidal, Marc

2017-05-01

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life. Copyright © 2017 Elsevier Ltd. All rights reserved.

SteinerNet: a web server for integrating ‘omic’ data to discover hidden components of response pathways

PubMed Central

Tuncbag, Nurcan; McCallum, Scott; Huang, Shao-shan Carol; Fraenkel, Ernest

2012-01-01

High-throughput technologies including transcriptional profiling, proteomics and reverse genetics screens provide detailed molecular descriptions of cellular responses to perturbations. However, it is difficult to integrate these diverse data to reconstruct biologically meaningful signaling networks. Previously, we have established a framework for integrating transcriptional, proteomic and interactome data by searching for the solution to the prize-collecting Steiner tree problem. Here, we present a web server, SteinerNet, to make this method available in a user-friendly format for a broad range of users with data from any species. At a minimum, a user only needs to provide a set of experimentally detected proteins and/or genes and the server will search for connections among these data from the provided interactomes for yeast, human, mouse, Drosophila melanogaster and Caenorhabditis elegans. More advanced users can upload their own interactome data as well. The server provides interactive visualization of the resulting optimal network and downloadable files detailing the analysis and results. We believe that SteinerNet will be useful for researchers who would like to integrate their high-throughput data for a specific condition or cellular response and to find biologically meaningful pathways. SteinerNet is accessible at http://fraenkel.mit.edu/steinernet. PMID:22638579

Functional Integrative Levels in the Human Interactome Recapitulate Organ Organization

PubMed Central

Prieto, Carlos; Benkahla, Alia; De Las Rivas, Javier; Brun, Christine

2011-01-01

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization. PMID:21799769

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing

PubMed Central

Lambourne, Luke; Vidal, Marc

2017-01-01

Alternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing. PMID:28846689

The Rab-binding Profiles of Bacterial Virulence Factors during Infection*

PubMed Central

So, Ernest C.; Schroeder, Gunnar N.; Carson, Danielle; Mattheis, Corinna; Mousnier, Aurélie; Broncel, Malgorzata; Tate, Edward W.; Frankel, Gad

2016-01-01

Legionella pneumophila, the causative agent of Legionnaire's disease, uses its type IV secretion system to translocate over 300 effector proteins into host cells. These effectors subvert host cell signaling pathways to ensure bacterial proliferation. Despite their importance for pathogenesis, the roles of most of the effectors are yet to be characterized. Key to understanding the function of effectors is the identification of host proteins they bind during infection. We previously developed a novel tandem-affinity purification (TAP) approach using hexahistidine and BirA-specific biotinylation tags for isolating translocated effector complexes from infected cells whose composition were subsequently deciphered by mass spectrometry. Here we further advanced the workflow for the TAP approach and determined the infection-dependent interactomes of the effectors SidM and LidA, which were previously reported to promiscuously bind multiple Rab GTPases in vitro. In this study we defined a stringent subset of Rab GTPases targeted by SidM and LidA during infection, comprising of Rab1A, 1B, 6, and 10; in addition, LidA targets Rab14 and 18. Taken together, this study illustrates the power of this approach to profile the intracellular interactomes of bacterial effectors during infection. PMID:26755725

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

PubMed

Larsen, Peter; Hamada, Yuki; Gilbert, Jack

2012-07-31

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. Copyright © 2012 Elsevier B.V. All rights reserved.

System-wide identification of RNA-binding proteins by interactome capture.

PubMed

Castello, Alfredo; Horos, Rastislav; Strein, Claudia; Fischer, Bernd; Eichelbaum, Katrin; Steinmetz, Lars M; Krijgsveld, Jeroen; Hentze, Matthias W

2013-03-01

Owing to their preeminent biological functions, the repertoire of expressed RNA-binding proteins (RBPs) and their activity states are highly informative about cellular systems. We have developed a novel and unbiased technique, called interactome capture, for identifying the active RBPs of cultured cells. By making use of in vivo UV cross-linking of RBPs to polyadenylated RNAs, covalently bound proteins are captured with oligo(dT) magnetic beads. After stringent washes, the mRNA interactome is determined by quantitative mass spectrometry (MS). The protocol takes 3 working days for analysis of single proteins by western blotting, and about 2 weeks for the determination of complete cellular mRNA interactomes by MS. The most important advantage of interactome capture over other in vitro and in silico approaches is that only RBPs bound to RNA in a physiological environment are identified. When applied to HeLa cells, interactome capture revealed hundreds of novel RBPs. Interactome capture can also be broadly used to compare different biological states, including metabolic stress, cell cycle, differentiation, development or the response to drugs.

Characterization of a Protein Interactome by Co-Immunoprecipitation and Shotgun Mass Spectrometry.

PubMed

Maccarrone, Giuseppina; Bonfiglio, Juan Jose; Silberstein, Susana; Turck, Christoph W; Martins-de-Souza, Daniel

2017-01-01

Identifying the partners of a given protein (the interactome) may provide leads about the protein's function and the molecular mechanisms in which it is involved. One of the alternative strategies used to characterize protein interactomes consists of co-immunoprecipitation (co-IP) followed by shotgun mass spectrometry. This enables the isolation and identification of a protein target in its native state and its interactome from cells or tissue lysates under physiological conditions. In this chapter, we describe a co-IP protocol for interactome studies that uses an antibody against a protein of interest bound to protein A/G plus agarose beads to isolate a protein complex. The interacting proteins may be further fractionated by SDS-PAGE, followed by in-gel tryptic digestion and nano liquid chromatography high-resolution tandem mass spectrometry (nLC ESI-MS/MS) for identification purposes. The computational tools, strategy for protein identification, and use of interactome databases also will be described.

Interactome Networks and Human Disease

PubMed Central

Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

2011-01-01

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease. PMID:21414488

The interactome of CCT complex - A computational analysis.

PubMed

Narayanan, Aswathy; Pullepu, Dileep; Kabir, M Anaul

2016-10-01

The eukaryotic chaperonin, CCT (Chaperonin Containing TCP1 or TriC-TCP-1 Ring Complex) has been subjected to physical and genetic analyses in S. cerevisiae which can be extrapolated to human CCT (hCCT), owing to its structural and functional similarities with yeast CCT (yCCT). Studies on hCCT and its interactome acquire an additional dimension, as it has been implicated in several disease conditions like neurodegeneration and cancer. We attempt to study its stress response role in general, which will be reflected in the aspects of human diseases and yeast physiology, through computational analysis of the interactome. Towards consolidating and analysing the interactome data, we prepared and compared the unique CCT-interacting protein lists for S. cerevisiae and H. sapiens, performed GO term classification and enrichment studies which provide information on the diversity in CCT interactome, in terms of protein classes in the data set. Enrichment with disease-associated proteins and pathways highlight the medical importance of CCT. Different analyses converge, suggesting the significance of WD-repeat proteins, protein kinases and cytoskeletal proteins in the interactome. The prevalence of proteasomal subunits and ribosomal proteins suggest a possible cross-talk between protein-synthesis, folding and degradation machinery. A network of chaperones and chaperonins that function in combination can also be envisaged from the CCT interactome-Hsp70 interactome analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

AIM: A comprehensive Arabidopsis Interactome Module database and related interologs in plants

USDA-ARS?s Scientific Manuscript database

Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250,000 modules th...

Network biology discovers pathogen contact points in host protein-protein interactomes.

PubMed

Ahmed, Hadia; Howton, T C; Sun, Yali; Weinberger, Natascha; Belkhadir, Youssef; Mukhtar, M Shahid

2018-06-13

In all organisms, major biological processes are controlled by complex protein-protein interactions networks (interactomes), yet their structural complexity presents major analytical challenges. Here, we integrate a compendium of over 4300 phenotypes with Arabidopsis interactome (AI-1 MAIN ). We show that nodes with high connectivity and betweenness are enriched and depleted in conditional and essential phenotypes, respectively. Such nodes are located in the innermost layers of AI-1 MAIN and are preferential targets of pathogen effectors. We extend these network-centric analyses to Cell Surface Interactome (CSI LRR ) and predict its 35 most influential nodes. To determine their biological relevance, we show that these proteins physically interact with pathogen effectors and modulate plant immunity. Overall, our findings contrast with centrality-lethality rule, discover fast information spreading nodes, and highlight the structural properties of pathogen targets in two different interactomes. Finally, this theoretical framework could possibly be applicable to other inter-species interactomes to reveal pathogen contact points.

Interactome INSIDER: a structural interactome browser for genomic studies.

PubMed

Meyer, Michael J; Beltrán, Juan Felipe; Liang, Siqi; Fragoza, Robert; Rumack, Aaron; Liang, Jin; Wei, Xiaomu; Yu, Haiyuan

2018-01-01

We present Interactome INSIDER, a tool to link genomic variant information with structural protein-protein interactomes. Underlying this tool is the application of machine learning to predict protein interaction interfaces for 185,957 protein interactions with previously unresolved interfaces in human and seven model organisms, including the entire experimentally determined human binary interactome. Predicted interfaces exhibit functional properties similar to those of known interfaces, including enrichment for disease mutations and recurrent cancer mutations. Through 2,164 de novo mutagenesis experiments, we show that mutations of predicted and known interface residues disrupt interactions at a similar rate and much more frequently than mutations outside of predicted interfaces. To spur functional genomic studies, Interactome INSIDER (http://interactomeinsider.yulab.org) enables users to identify whether variants or disease mutations are enriched in known and predicted interaction interfaces at various resolutions. Users may explore known population variants, disease mutations, and somatic cancer mutations, or they may upload their own set of mutations for this purpose.

A TRPV2 interactome-based signature for prognosis in glioblastoma patients.

PubMed

Doñate-Macián, Pau; Gómez, Antonio; Dégano, Irene R; Perálvarez-Marín, Alex

2018-04-06

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico , we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease.

A TRPV2 interactome-based signature for prognosis in glioblastoma patients

PubMed Central

Dégano, Irene R.; Perálvarez-Marín, Alex

2018-01-01

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico, we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease. PMID:29719613

DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome.

PubMed

Luo, Heng; Zhang, Ping; Cao, Xi Hang; Du, Dizheng; Ye, Hao; Huang, Hui; Li, Can; Qin, Shengying; Wan, Chunling; Shi, Leming; He, Lin; Yang, Lun

2016-11-02

The cost of developing a new drug has increased sharply over the past years. To ensure a reasonable return-on-investment, it is useful for drug discovery researchers in both industry and academia to identify all the possible indications for early pipeline molecules. For the first time, we propose the term computational "drug candidate positioning" or "drug positioning", to describe the above process. It is distinct from drug repositioning, which identifies new uses for existing drugs and maximizes their value. Since many therapeutic effects are mediated by unexpected drug-protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles to predict indications. Here we introduce the server DPDR-CPI, which can make real-time predictions based only on the structure of the small molecule. When a user submits a molecule, the server will dock it across 611 human proteins, generating a CPI profile of features that can be used for predictions. It can suggest the likelihood of relevance of the input molecule towards ~1,000 human diseases with top predictions listed. DPDR-CPI achieved an overall AUROC of 0.78 during 10-fold cross-validations and AUROC of 0.76 for the independent validation. The server is freely accessible via http://cpi.bio-x.cn/dpdr/.

The Rab-binding Profiles of Bacterial Virulence Factors during Infection.

PubMed

So, Ernest C; Schroeder, Gunnar N; Carson, Danielle; Mattheis, Corinna; Mousnier, Aurélie; Broncel, Malgorzata; Tate, Edward W; Frankel, Gad

2016-03-11

Legionella pneumophila, the causative agent of Legionnaire's disease, uses its type IV secretion system to translocate over 300 effector proteins into host cells. These effectors subvert host cell signaling pathways to ensure bacterial proliferation. Despite their importance for pathogenesis, the roles of most of the effectors are yet to be characterized. Key to understanding the function of effectors is the identification of host proteins they bind during infection. We previously developed a novel tandem-affinity purification (TAP) approach using hexahistidine and BirA-specific biotinylation tags for isolating translocated effector complexes from infected cells whose composition were subsequently deciphered by mass spectrometry. Here we further advanced the workflow for the TAP approach and determined the infection-dependent interactomes of the effectors SidM and LidA, which were previously reported to promiscuously bind multiple Rab GTPases in vitro. In this study we defined a stringent subset of Rab GTPases targeted by SidM and LidA during infection, comprising of Rab1A, 1B, 6, and 10; in addition, LidA targets Rab14 and 18. Taken together, this study illustrates the power of this approach to profile the intracellular interactomes of bacterial effectors during infection. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Developing and applying a gene functional association network for anti-angiogenic kinase inhibitor activity assessment in an angiogenesis co-culture model

PubMed Central

Chen, Yuefeng; Wei, Tao; Yan, Lei; Lawrence, Frank; Qian, Hui-Rong; Burkholder, Timothy P; Starling, James J; Yingling, Jonathan M; Shou, Jianyong

2008-01-01

Background Tumor angiogenesis is a highly regulated process involving intercellular communication as well as the interactions of multiple downstream signal transduction pathways. Disrupting one or even a few angiogenesis pathways is often insufficient to achieve sustained therapeutic benefits due to the complexity of angiogenesis. Targeting multiple angiogenic pathways has been increasingly recognized as a viable strategy. However, translation of the polypharmacology of a given compound to its antiangiogenic efficacy remains a major technical challenge. Developing a global functional association network among angiogenesis-related genes is much needed to facilitate holistic understanding of angiogenesis and to aid the development of more effective anti-angiogenesis therapeutics. Results We constructed a comprehensive gene functional association network or interactome by transcript profiling an in vitro angiogenesis model, in which human umbilical vein endothelial cells (HUVECs) formed capillary structures when co-cultured with normal human dermal fibroblasts (NHDFs). HUVEC competence and NHDF supportiveness of cord formation were found to be highly cell-passage dependent. An enrichment test of Biological Processes (BP) of differentially expressed genes (DEG) revealed that angiogenesis related BP categories significantly changed with cell passages. Built upon 2012 DEGs identified from two microarray studies, the resulting interactome captured 17226 functional gene associations and displayed characteristics of a scale-free network. The interactome includes the involvement of oncogenes and tumor suppressor genes in angiogenesis. We developed a network walking algorithm to extract connectivity information from the interactome and applied it to simulate the level of network perturbation by three multi-targeted anti-angiogenic kinase inhibitors. Simulated network perturbation correlated with observed anti-angiogenesis activity in a cord formation bioassay. Conclusion We established a comprehensive gene functional association network to model in vitro angiogenesis regulation. The present study provided a proof-of-concept pilot of applying network perturbation analysis to drug phenotypic activity assessment. PMID:18518970

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

USDA-ARS?s Scientific Manuscript database

An interactome is the genome-wide roadmap of protein-protein interactions that occur within an organism. Interactomes for humans, the fruit fly, and now plants such as Arabidopsis thaliana and Oryza sativa have been generated using high throughput experimental methods. It is possible to use these ...

Centrality in the host-pathogen interactome is associated with pathogen fitness during infection.

PubMed

Crua Asensio, Núria; Muñoz Giner, Elisabet; de Groot, Natalia Sánchez; Torrent Burgas, Marc

2017-01-16

To perform their functions proteins must interact with each other, but how these interactions influence bacterial infection remains elusive. Here we demonstrate that connectivity in the host-pathogen interactome is directly related to pathogen fitness during infection. Using Y. pestis as a model organism, we show that the centrality-lethality rule holds for pathogen fitness during infection but only when the host-pathogen interactome is considered. Our results suggest that the importance of pathogen proteins during infection is directly related to their number of interactions with the host. We also show that pathogen proteins causing an extensive rewiring of the host interactome have a higher impact in pathogen fitness during infection. Hence, we conclude that hubs in the host-pathogen interactome should be explored as promising targets for antimicrobial drug design.

Emerging role of the Jun N-terminal kinase interactome in human health.

PubMed

Guo, Xiao-Xi; An, Su; Yang, Yang; Liu, Ying; Hao, Qian; Tang, Tao; Xu, Tian-Rui

2018-02-08

The c-Jun N-terminal kinases (JNKs) are located downstream of Ras-mitogen activated protein kinase signaling cascades. More than 20 years of study has shown that JNKs control cell fate and many cellular functions. JNKs and their interacting proteins form a complicated network with diverse biological functions and physiological effects. Members of the JNK interactome include Jun, amyloid precursor protein, and insulin receptor substrate. Recent studies have shown that the JNK interactome is involved in tumorigenesis, neuron development, and insulin resistance. In this review, we summarize the features of the JNK interactome and classify its members into three groups: upstream regulators, downstream effectors, and scaffold partners. We also highlight the unique cellular signaling mechanisms of JNKs and provide more insights into the roles of the JNK interactome in human diseases. © 2018 International Federation for Cell Biology.

Centrality in the host-pathogen interactome is associated with pathogen fitness during infection

NASA Astrophysics Data System (ADS)

Crua Asensio, Núria; Muñoz Giner, Elisabet; de Groot, Natalia Sánchez; Torrent Burgas, Marc

2017-01-01

To perform their functions proteins must interact with each other, but how these interactions influence bacterial infection remains elusive. Here we demonstrate that connectivity in the host-pathogen interactome is directly related to pathogen fitness during infection. Using Y. pestis as a model organism, we show that the centrality-lethality rule holds for pathogen fitness during infection but only when the host-pathogen interactome is considered. Our results suggest that the importance of pathogen proteins during infection is directly related to their number of interactions with the host. We also show that pathogen proteins causing an extensive rewiring of the host interactome have a higher impact in pathogen fitness during infection. Hence, we conclude that hubs in the host-pathogen interactome should be explored as promising targets for antimicrobial drug design.

Heat Shock Partially Dissociates the Overlapping Modules of the Yeast Protein-Protein Interaction Network: A Systems Level Model of Adaptation

PubMed Central

Mihalik, Ágoston; Csermely, Peter

2011-01-01

Network analysis became a powerful tool giving new insights to the understanding of cellular behavior. Heat shock, the archetype of stress responses, is a well-characterized and simple model of cellular dynamics. S. cerevisiae is an appropriate model organism, since both its protein-protein interaction network (interactome) and stress response at the gene expression level have been well characterized. However, the analysis of the reorganization of the yeast interactome during stress has not been investigated yet. We calculated the changes of the interaction-weights of the yeast interactome from the changes of mRNA expression levels upon heat shock. The major finding of our study is that heat shock induced a significant decrease in both the overlaps and connections of yeast interactome modules. In agreement with this the weighted diameter of the yeast interactome had a 4.9-fold increase in heat shock. Several key proteins of the heat shock response became centers of heat shock-induced local communities, as well as bridges providing a residual connection of modules after heat shock. The observed changes resemble to a ‘stratus-cumulus’ type transition of the interactome structure, since the unstressed yeast interactome had a globally connected organization, similar to that of stratus clouds, whereas the heat shocked interactome had a multifocal organization, similar to that of cumulus clouds. Our results showed that heat shock induces a partial disintegration of the global organization of the yeast interactome. This change may be rather general occurring in many types of stresses. Moreover, other complex systems, such as single proteins, social networks and ecosystems may also decrease their inter-modular links, thus develop more compact modules, and display a partial disintegration of their global structure in the initial phase of crisis. Thus, our work may provide a model of a general, system-level adaptation mechanism to environmental changes. PMID:22022244

Columbia University: Computational Human High-grade Glioblastoma Multiforme Interactome - miRNA (Post-transcriptional) Layer | Office of Cancer Genomics

Cancer.gov

The Human High-Grade Glioma Interactome (HGi) contains a genome-wide complement of molecular interactions that are Glioblastoma Multiforme (GBM)-specific. HGi v3 contains the post-transcriptional layer of the HGi, which includes the miRNA-target (RNA-RNA) layer of the interactome. Read the Abstract

The Topology of the Growing Human Interactome Data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-01

We have long moved past the one-gene-one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype-phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein-protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast's proteins - that are involved in regulation of transcription, RNA splicing and other cellcycle- related processes-suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the "core" of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.

The topology of the growing human interactome data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-23

We have long moved past the one-gene–one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype–phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein- protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast’s proteins — that are involved in regulation of transcription, RNA splicing and other cellcycle-related processes—suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the “core” of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.

New insights into protein-protein interaction data lead to increased estimates of the S. cerevisiae interactome size.

PubMed

Sambourg, Laure; Thierry-Mieg, Nicolas

2010-12-21

As protein interactions mediate most cellular mechanisms, protein-protein interaction networks are essential in the study of cellular processes. Consequently, several large-scale interactome mapping projects have been undertaken, and protein-protein interactions are being distilled into databases through literature curation; yet protein-protein interaction data are still far from comprehensive, even in the model organism Saccharomyces cerevisiae. Estimating the interactome size is important for evaluating the completeness of current datasets, in order to measure the remaining efforts that are required. We examined the yeast interactome from a new perspective, by taking into account how thoroughly proteins have been studied. We discovered that the set of literature-curated protein-protein interactions is qualitatively different when restricted to proteins that have received extensive attention from the scientific community. In particular, these interactions are less often supported by yeast two-hybrid, and more often by more complex experiments such as biochemical activity assays. Our analysis showed that high-throughput and literature-curated interactome datasets are more correlated than commonly assumed, but that this bias can be corrected for by focusing on well-studied proteins. We thus propose a simple and reliable method to estimate the size of an interactome, combining literature-curated data involving well-studied proteins with high-throughput data. It yields an estimate of at least 37, 600 direct physical protein-protein interactions in S. cerevisiae. Our method leads to higher and more accurate estimates of the interactome size, as it accounts for interactions that are genuine yet difficult to detect with commonly-used experimental assays. This shows that we are even further from completing the yeast interactome map than previously expected.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions.

PubMed

Wuchty, S; Rajagopala, S V; Blazie, S M; Parrish, J R; Khuri, S; Finley, R L; Uetz, P

2017-01-01

The functions of roughly a third of all proteins in Streptococcus pneumoniae , a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein's function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae . We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae , the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

RASopathies: Presentation at the Genome, Interactome, and Phenome Levels.

PubMed

Pevec, Urska; Rozman, Neva; Gorsek, Blaz; Kunej, Tanja

2016-05-01

Clinical symptoms often reflect molecular correlations between mutated proteins. Alignment between interactome and phenome levels reveals new disease genes and connections between previously unrelated diseases. Despite a great potential for novel discoveries, this approach is still rarely used in genomics. In the present study, we analyzed the data of 6 syndromes belonging to the RASopathy class of disorders (RASopathies) and presented them as a model to study associations between genome, interactome, and phenome levels. Causative genes and clinical symptoms were collected from OMIM and NCBI GeneReviews databases for 6 syndromes: Noonan, Noonan syndrome with multiple lentigines, neurofibromatosis type 1, cardiofaciocutaneous, and Legius and Costello syndrome. The STRING tool was used for the identification of protein interactions. Six RASopathy syndromes were found to be associated with 12 causative genes. We constructed an interactome of RASopathy proteins and their neighbors and developed a database of 328 clinical symptoms. The collected data was presented at genome, interactome, and phenome levels and as an integrated network of all 3 data types. The present study provides a baseline for future studies of associations between interactome and phenome in RASopathies and could serve as a novel approach to analyze phenotypically and genetically related diseases.

The functional interactome landscape of the human histone deacetylase family

PubMed Central

Joshi, Preeti; Greco, Todd M; Guise, Amanda J; Luo, Yang; Yu, Fang; Nesvizhskii, Alexey I; Cristea, Ileana M

2013-01-01

Histone deacetylases (HDACs) are a diverse family of essential transcriptional regulatory enzymes, that function through the spatial and temporal recruitment of protein complexes. As the composition and regulation of HDAC complexes are only partially characterized, we built the first global protein interaction network for all 11 human HDACs in T cells. Integrating fluorescence microscopy, immunoaffinity purifications, quantitative mass spectrometry, and bioinformatics, we identified over 200 unreported interactions for both well-characterized and lesser-studied HDACs, a subset of which were validated by orthogonal approaches. We establish HDAC11 as a member of the survival of motor neuron complex and pinpoint a functional role in mRNA splicing. We designed a complementary label-free and metabolic-labeling mass spectrometry-based proteomics strategy for profiling interaction stability among different HDAC classes, revealing that HDAC1 interactions within chromatin-remodeling complexes are largely stable, while transcription factors preferentially exist in rapid equilibrium. Overall, this study represents a valuable resource for investigating HDAC functions in health and disease, encompassing emerging themes of HDAC regulation in cell cycle and RNA processing and a deeper functional understanding of HDAC complex stability. PMID:23752268

"Fuzziness" in the celular interactome: a historical perspective.

PubMed

Welch, G Rickey

2012-01-01

Some historical background is given for appreciating the impact of the empirical construct known as the cellular protein-protein interactome, which is a seemingly de novo entity that has arisen of late within the context of postgenomic systems biology. The approach here builds on a generalized principle of "fuzziness" in protein behavior, proposed by Tompa and Fuxreiter.(1) Recent controversies in the analysis and interpretation of the interactome studies are rationalized historically under the auspices of this concept. There is an extensive literature on protein-protein interactions, dating to the mid-1900s, which may help clarify the "fuzziness" in the interactome picture and, also, provide a basis for understanding the physiological importance of protein-protein interactions in vivo.

Towards Establishment of a Rice Stress Response Interactome

PubMed Central

Seo, Young-Su; Chern, Mawsheng; Bartley, Laura E.; Han, Muho; Jung, Ki-Hong; Lee, Insuk; Walia, Harkamal; Richter, Todd; Xu, Xia; Cao, Peijian; Bai, Wei; Ramanan, Rajeshwari; Amonpant, Fawn; Arul, Loganathan; Canlas, Patrick E.; Ruan, Randy; Park, Chang-Jin; Chen, Xuewei; Hwang, Sohyun; Jeon, Jong-Seong; Ronald, Pamela C.

2011-01-01

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein–protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance. PMID:21533176

Interactome of E. piscicida and grouper liver proteins reveals strategies of bacterial infection and host immune response.

PubMed

Li, Hui; Zhu, Qing-Feng; Peng, Xuan-Xian; Peng, Bo

2017-01-03

The occurrence of infectious diseases is related to heterogeneous protein interactions between a host and a microbe. Therefore, elucidating the host-pathogen interplay is essential. We previously revealed the protein interactome between Edwardsiella piscicida and fish gill cells, and the present study identified the protein interactome between E. piscicida and E. drummondhayi liver cells. E. drummondhayi liver cells and bacterial pull-down approaches were used to identify E. piscicida outer membrane proteins that bind to liver cells and fish liver cell proteins that interact with bacterial cells, respectively. Eight bacterial proteins and 11 fish proteins were characterized. Heterogeneous protein-protein interactions between these bacterial cells and fish liver cells were investigated through far-Western blotting and co-immunoprecipitation. A network was constructed based on 42 heterogeneous protein-protein interactions between seven bacterial proteins and 10 fish proteins. A comparison of the new interactome with the previously reported interactome showed that four bacterial proteins overlapped, whereas all of the identified fish proteins were new, suggesting a difference between bacterial tricks for evading host immunity and the host strategy for combating bacterial infection. Furthermore, these bacterial proteins were found to regulate the expression of host innate immune-related proteins. These findings indicate that the interactome contributes to bacterial infection and host immunity.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions

PubMed Central

Rajagopala, S. V.; Blazie, S. M.; Parrish, J. R.; Khuri, S.; Finley, R. L.

2017-01-01

ABSTRACT The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein’s function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins. PMID:28744484

APID interactomes: providing proteome-based interactomes with controlled quality for multiple species and derived networks

PubMed Central

Alonso-López, Diego; Gutiérrez, Miguel A.; Lopes, Katia P.; Prieto, Carlos; Santamaría, Rodrigo; De Las Rivas, Javier

2016-01-01

APID (Agile Protein Interactomes DataServer) is an interactive web server that provides unified generation and delivery of protein interactomes mapped to their respective proteomes. This resource is a new, fully redesigned server that includes a comprehensive collection of protein interactomes for more than 400 organisms (25 of which include more than 500 interactions) produced by the integration of only experimentally validated protein–protein physical interactions. For each protein–protein interaction (PPI) the server includes currently reported information about its experimental validation to allow selection and filtering at different quality levels. As a whole, it provides easy access to the interactomes from specific species and includes a global uniform compendium of 90,379 distinct proteins and 678,441 singular interactions. APID integrates and unifies PPIs from major primary databases of molecular interactions, from other specific repositories and also from experimentally resolved 3D structures of protein complexes where more than two proteins were identified. For this purpose, a collection of 8,388 structures were analyzed to identify specific PPIs. APID also includes a new graph tool (based on Cytoscape.js) for visualization and interactive analyses of PPI networks. The server does not require registration and it is freely available for use at http://apid.dep.usal.es. PMID:27131791

Elucidation of the 14-3-3ζ interactome reveals critical roles of RNA-splicing factors during adipogenesis.

PubMed

Mugabo, Yves; Sadeghi, Mina; Fang, Nancy N; Mayor, Thibault; Lim, Gareth E

2018-05-04

Adipogenesis involves a complex signaling network requiring strict temporal and spatial organization of effector molecules. Molecular scaffolds, such as 14-3-3 proteins, facilitate such organization, and we have previously identified 14-3-3ζ as an essential scaffold in adipocyte differentiation. The interactome of 14-3-3ζ is large and diverse, and it is possible that novel adipogenic factors may be present within it, but this possibility has not yet been tested. Herein, we generated mouse embryonic fibroblasts from mice overexpressing a tandem affinity purification (TAP) epitope-tagged 14-3-3ζ molecule. After inducing adipogenesis, TAP-14-3-3ζ complexes were purified, followed by MS analysis to determine the 14-3-3ζ interactome. We observed more than 100 proteins that were unique to adipocyte differentiation, 56 of which were novel interacting partners. Among these, we were able to identify previously established regulators of adipogenesis ( i.e. Ptrf/Cavin1) within the 14-3-3ζ interactome, confirming the utility of this approach to detect adipogenic factors. We found that proteins related to RNA metabolism, processing, and splicing were enriched in the interactome. Analysis of transcriptomic data revealed that 14-3-3ζ depletion in 3T3-L1 cells affected alternative splicing of mRNA during adipocyte differentiation. siRNA-mediated depletion of RNA-splicing factors within the 14-3-3ζ interactome, that is, of Hnrpf, Hnrpk, Ddx6, and Sfpq, revealed that they have essential roles in adipogenesis and in the alternative splicing of Pparg and the adipogenesis-associated gene Lpin1 In summary, we have identified novel adipogenic factors within the 14-3-3ζ interactome. Further characterization of additional proteins within the 14-3-3ζ interactome may help identify novel targets to block obesity-associated expansion of adipose tissues. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

DOE PAGES

Shatsky, Maxim; Dong, Ming; Liu, Haichuan; ...

2016-04-20

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

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

Shatsky, Maxim; Dong, Ming; Liu, Haichuan

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

Novel candidate genes of the PARK7 interactome as mediators of apoptosis and acetylation in multiple sclerosis: An in silico analysis.

PubMed

Vavougios, George D; Zarogiannis, Sotirios G; Krogfelt, Karen Angeliki; Gourgoulianis, Konstantinos; Mitsikostas, Dimos Dimitrios; Hadjigeorgiou, Georgios

2018-01-01

currently only 4 studies have explored the potential role of PARK7's dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilk's λ = 0.176, χ 2 = 45.204, p = 1.5275e -10 ) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS. Copyright © 2017 Elsevier B.V. All rights reserved.

A protein domain-based interactome network for C. elegans early embryogenesis

PubMed Central

Boxem, Mike; Maliga, Zoltan; Klitgord, Niels; Li, Na; Lemmens, Irma; Mana, Miyeko; de Lichtervelde, Lorenzo; Mul, Joram D.; van de Peut, Diederik; Devos, Maxime; Simonis, Nicolas; Yildirim, Muhammed A.; Cokol, Murat; Kao, Huey-Ling; de Smet, Anne-Sophie; Wang, Haidong; Schlaitz, Anne-Lore; Hao, Tong; Milstein, Stuart; Fan, Changyu; Tipsword, Mike; Drew, Kevin; Galli, Matilde; Rhrissorrakrai, Kahn; Drechsel, David; Koller, Daphne; Roth, Frederick P.; Iakoucheva, Lilia M.; Dunker, A. Keith; Bonneau, Richard; Gunsalus, Kristin C.; Hill, David E.; Piano, Fabio; Tavernier, Jan; van den Heuvel, Sander; Hyman, Anthony A.; Vidal, Marc

2008-01-01

Summary Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or “interactome” networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed new insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms. PMID:18692475

Photocrosslinking approaches to interactome mapping

PubMed Central

Pham, Nam D.; Parker, Randy B.; Kohler, Jennifer J.

2012-01-01

Photocrosslinking approaches can be used to map interactome networks within the context of living cells. Photocrosslinking methods rely on use of metabolic engineering or genetic code expansion to incorporate photocrosslinking analogs of amino acids or sugars into cellular biomolecules. Immunological and mass spectrometry techniques are used to analyze crosslinked complexes, thereby defining specific interactomes. Because photocrosslinking can be conducted in native, cellular settings, it can be used to define context-dependent interactions. Photocrosslinking methods are also ideally suited for determining interactome dynamics, mapping interaction interfaces, and identifying transient interactions in which intrinsically disordered proteins and glycoproteins engage. Here we discuss the application of cell-based photocrosslinking to the study of specific problems in immune cell signaling, transcription, membrane protein dynamics, nucleocytoplasmic transport, and chaperone-assisted protein folding. PMID:23149092

The distinctive cell division interactome of Neisseria gonorrhoeae.

PubMed

Zou, Yinan; Li, Yan; Dillon, Jo-Anne R

2017-12-12

Bacterial cell division is an essential process driven by the formation of a Z-ring structure, as a cytoskeletal scaffold at the mid-cell, followed by the recruitment of various proteins which form the divisome. The cell division interactome reflects the complement of different interactions between all divisome proteins. To date, only two cell division interactomes have been characterized, in Escherichia coli and in Streptococcus pneumoniae. The cell divison proteins encoded by Neisseria gonorrhoeae include FtsZ, FtsA, ZipA, FtsK, FtsQ, FtsI, FtsW, and FtsN. The purpose of the present study was to characterize the cell division interactome of N. gonorrhoeae using several different methods to identify protein-protein interactions. We also characterized the specific subdomains of FtsA implicated in interactions with FtsZ, FtsQ, FtsN and FtsW. Using a combination of bacterial two-hybrid (B2H), glutathione S-transferase (GST) pull-down assays, and surface plasmon resonance (SPR), nine interactions were observed among the eight gonococcal cell division proteins tested. ZipA did not interact with any other cell division proteins. Comparisons of the N. gonorrhoeae cell division interactome with the published interactomes from E. coli and S. pneumoniae indicated that FtsA-FtsZ and FtsZ-FtsK interactions were common to all three species. FtsA-FtsW and FtsK-FtsN interactions were only present in N. gonorrhoeae. The 2A and 2B subdomains of FtsA Ng were involved in interactions with FtsQ, FtsZ, and FtsN, and the 2A subdomain was involved in interaction with FtsW. Results from this research indicate that N. gonorrhoeae has a distinctive cell division interactome as compared with other microorganisms.

A convex optimization approach for identification of human tissue-specific interactomes.

PubMed

Mohammadi, Shahin; Grama, Ananth

2016-06-15

Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/tissue-selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes. We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (Edge Set Enrichment Analysis, Gene Ontology Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state-of-the-art techniques. Finally, using case studies of Alzheimer's and Parkinson's diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets. http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html mohammadi@purdue.edu. © The Author 2016. Published by Oxford University Press.

A Rich-Club Organization in Brain Ischemia Protein Interaction Network

PubMed Central

Alawieh, Ali; Sabra, Zahraa; Sabra, Mohammed; Tomlinson, Stephen; Zaraket, Fadi A.

2015-01-01

Ischemic stroke involves multiple pathophysiological mechanisms with complex interactions. Efforts to decipher those mechanisms and understand the evolution of cerebral injury is key for developing successful interventions. In an innovative approach, we use literature mining, natural language processing and systems biology tools to construct, annotate and curate a brain ischemia interactome. The curated interactome includes proteins that are deregulated after cerebral ischemia in human and experimental stroke. Network analysis of the interactome revealed a rich-club organization indicating the presence of a densely interconnected hub structure of prominent contributors to disease pathogenesis. Functional annotation of the interactome uncovered prominent pathways and highlighted the critical role of the complement and coagulation cascade in the initiation and amplification of injury starting by activation of the rich-club. We performed an in-silico screen for putative interventions that have pleiotropic effects on rich-club components and we identified estrogen as a prominent candidate. Our findings show that complex network analysis of disease related interactomes may lead to a better understanding of pathogenic mechanisms and provide cost-effective and mechanism-based discovery of candidate therapeutics. PMID:26310627

RNA-Binding Proteins Revisited - The Emerging Arabidopsis mRNA Interactome.

PubMed

Köster, Tino; Marondedze, Claudius; Meyer, Katja; Staiger, Dorothee

2017-06-01

RNA-protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture - where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Immunological network signatures of cancer progression and survival

PubMed Central

2011-01-01

Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides. PMID:21453479

A proteome-scale map of the human interactome network

PubMed Central

Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J.; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D.; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E.; Braun, Pascal; Brehme, Marc; Broly, Martin P.; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J.; Hardy, Madeleine F.; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R.; Palagi, Alexandre; Poulin, Matthew M.; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M.; Scholz, Annemarie; Shah, Akash A.; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O.; Trigg, Shelly A.; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E.; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M.; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A.; Hill, David E.; Hao, Tong; Roth, Frederick P.; Vidal, Marc

2014-01-01

SUMMARY Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution. PMID:25416956

Altered Protein Interactions of the Endogenous Interactome of PTPIP51 towards MAPK Signaling

PubMed Central

Brobeil, Alexander; Chehab, Rajaa; Dietel, Eric; Gattenlöhner, Stefan; Wimmer, Monika

2017-01-01

Protein–protein interactions play a pivotal role in normal cellular functions as well as in carcinogenesis. The protein–protein interactions form functional clusters during signal transduction. To elucidate the fine calibration of the protein–protein interactions of protein tyrosine phosphatase interacting protein 51 (PTPIP51) a small molecule drug, namely LDC-3, directly targeting PTPIP51 is now available. Therefore, LDC-3 allows for the studying of the regulation of the endogenous interactome by modulating PTPIP51 binding capacity. Small interfering ribonucleic acid (siRNA) experiments show that the modification in PTPIP51 binding capacity is induced by LDC-3. Application of LDC-3 annuls the known regulatory phosphorylation mechanisms for PTPIP51 and consequently, significantly alters the assembly of the PTPIP51 associated protein complexes. The treatment of human keratinocytes (HaCaT cells) with LDC-3 induces an altered protein–protein interaction profile of the endogenous interactome of PTPIP51. In addition, LDC-3 stabilizes PTPIP51 within a mitogen activated protein kinase (MAPK) complex composed of Raf-1 and the scaffold protein 14-3-3, independent of the phosphorylation status of PTPIP51. Of note, under LDC-3 treatment the regulatory function of the PTP1B on PTPIP51 fails to impact the PTPIP51 interaction characteristics, as reported for the HaCaT cell line. In summary, LDC-3 gives the unique opportunity to directly modulate PTPIP51 in malignant cells, thus targeting potential dysregulated signal transduction pathways such as the MAPK cascade. The provided data give critical insights in the therapeutic potential of PTPIP51 protein interactions and thus are basic for possible targeted therapy regimens. PMID:28754031

Next-Generation Technologies for Multiomics Approaches Including Interactome Sequencing

PubMed Central

Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

2015-01-01

The development of high-speed analytical techniques such as next-generation sequencing and microarrays allows high-throughput analysis of biological information at a low cost. These techniques contribute to medical and bioscience advancements and provide new avenues for scientific research. Here, we outline a variety of new innovative techniques and discuss their use in omics research (e.g., genomics, transcriptomics, metabolomics, proteomics, and interactomics). We also discuss the possible applications of these methods, including an interactome sequencing technology that we developed, in future medical and life science research. PMID:25649523

Disease networks. Uncovering disease-disease relationships through the incomplete interactome.

PubMed

Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan Dina; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

2015-02-20

According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes. Copyright © 2015, American Association for the Advancement of Science.

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis.

PubMed

Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.

Rare disruptive variants in the DISC1 Interactome and Regulome: association with cognitive ability and schizophrenia.

PubMed

Teng, S; Thomson, P A; McCarthy, S; Kramer, M; Muller, S; Lihm, J; Morris, S; Soares, D C; Hennah, W; Harris, S; Camargo, L M; Malkov, V; McIntosh, A M; Millar, J K; Blackwood, D H; Evans, K L; Deary, I J; Porteous, D J; McCombie, W R

2018-05-01

Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWER across ), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWER across P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWER across P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.

Receptor Tyrosine Kinase MET Interactome and Neurodevelopmental Disorder Partners at the Developing Synapse

PubMed Central

Xie, Zhihui; Li, Jing; Baker, Jonathan; Eagleson, Kathie L.; Coba, Marcelo P.; Levitt, Pat

2016-01-01

Background Atypical synapse development and plasticity are implicated in many neurodevelopmental disorders (NDDs). NDD-associated, high confidence risk genes have been identified, yet little is known about functional relationships at the level of protein-protein interactions, which are the dominant molecular bases responsible for mediating circuit development. Methods Proteomics in three independent developing neocortical synaptosomal preparations identified putative interacting proteins of the ligand-activated MET receptor tyrosine kinase, an autism risk gene that mediates synapse development. The candidates were translated into interactome networks and analyzed bioinformatically. Additionally, three independent quantitative proximity ligation assays (PLA) in cultured neurons and four independent immunoprecipitation analyses of synaptosomes validated protein interactions. Results Approximately 11% (8/72) of MET-interacting proteins, including SHANK3, SYNGAP1 and GRIN2B, are associated with NDDs. Proteins in the MET interactome were translated into a novel MET interactome network based on human protein-protein interaction databases. High confidence genes from different NDD datasets that encode synaptosomal proteins were analyzed for being enriched in MET interactome proteins. This was found for autism, but not schizophrenia, bipolar disorder, major depressive disorder or attentional deficit hyperactivity disorder. There is correlated gene expression between MET and its interactive partners in developing human temporal and visual neocortices, but not with highly expressed genes that are not in the interactome. PLA and biochemical analyses demonstrate that MET-protein partner interactions are dynamically regulated by receptor activation. Conclusions The results provide a novel molecular framework for deciphering the functional relations of key regulators of synaptogenesis that contribute to both typical cortical development and to NDDs. PMID:27086544

Transcriptional atlas of cardiogenesis maps congenital heart disease interactome.

PubMed

Li, Xing; Martinez-Fernandez, Almudena; Hartjes, Katherine A; Kocher, Jean-Pierre A; Olson, Timothy M; Terzic, Andre; Nelson, Timothy J

2014-07-01

Mammalian heart development is built on highly conserved molecular mechanisms with polygenetic perturbations resulting in a spectrum of congenital heart diseases (CHD). However, knowledge of cardiogenic ontogeny that regulates proper cardiogenesis remains largely based on candidate-gene approaches. Mapping the dynamic transcriptional landscape of cardiogenesis from a genomic perspective is essential to integrate the knowledge of heart development into translational applications that accelerate disease discovery efforts toward mechanistic-based treatment strategies. Herein, we designed a time-course transcriptome analysis to investigate the genome-wide dynamic expression landscape of innate murine cardiogenesis ranging from embryonic stem cells to adult cardiac structures. This comprehensive analysis generated temporal and spatial expression profiles, revealed stage-specific gene functions, and mapped the dynamic transcriptome of cardiogenesis to curated pathways. Reconciling known genetic underpinnings of CHD, we deconstructed a disease-centric dynamic interactome encoded within this cardiogenic atlas to identify stage-specific developmental disturbances clustered on regulation of epithelial-to-mesenchymal transition (EMT), BMP signaling, NF-AT signaling, TGFb-dependent EMT, and Notch signaling. Collectively, this cardiogenic transcriptional landscape defines the time-dependent expression of cardiac ontogeny and prioritizes regulatory networks at the interface between health and disease. Copyright © 2014 the American Physiological Society.

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

PubMed

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

PubMed Central

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly. PMID:25572661

The functional interactome of GSTP: A regulatory biomolecular network at the interface with the Nrf2 adaption response to oxidative stress.

PubMed

Bartolini, Desirée; Galli, Francesco

2016-04-15

Glutathione S-transferase P (GSTP), and possibly other members of the subfamily of cytosolic GSTs, are increasingly proposed to have roles far beyond the classical GSH-dependent enzymatic detoxification of electrophilic metabolites and xenobiotics. Emerging evidence suggests that these are essential components of the redox sensing and signaling platform of cells. GSTP monomers physically interact with cellular proteins, such as other cytosolic GSTs, signaling kinases and the membrane peroxidase peroxiredoxin 6. Other interactions reported in literature include that with regulatory proteins such as Fanconi anemia complementation group C protein, transglutaminase 2 and several members of the keratin family of genes. Transcription factors downstream of inflammatory and oxidative stress pathways, namely STAT3 and Nrf2, were recently identified to be further components of this interactome. Together these pieces of evidence suggest the existence of a regulatory biomolecular network in which GSTP represents a node of functional convergence and coordination of signaling and transcription proteins, namely the "GSTP interactome", associated with key cellular processes such as cell cycle regulation and the stress response. These aspects and the methodological approach to explore the cellular interactome(s) are discussed in this review paper. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of the PAK4 interactome reveals PAK4 phosphorylation of N-WASP and promotion of Arp2/3-dependent actin polymerization.

PubMed

Zhao, Miao; Spiess, Matthias; Johansson, Henrik J; Olofsson, Helene; Hu, Jianjiang; Lehtiö, Janne; Strömblad, Staffan

2017-09-29

p21-activated kinase 4 (PAK4) regulates cell proliferation, apoptosis, cell motility and F-actin remodeling, but the PAK4 interactome has not been systematically analyzed. Here, we comprehensively characterized the human PAK4 interactome by iTRAQ quantitative mass spectrometry of PAK4-immunoprecipitations. Consistent with its multiple reported functions, the PAK4 interactome was enriched in diverse protein networks, including the 14-3-3, proteasome, replication fork, CCT and Arp2/3 complexes. Because PAK4 co-immunoprecipitated most subunits of the Arp2/3 complex, we hypothesized that PAK4 may play a role in Arp2/3 dependent actin regulation. Indeed, we found that PAK4 interacts with and phosphorylates the nucleation promoting factor N-WASP at Ser484/Ser485 and promotes Arp2/3-dependent actin polymerization in vitro. Also, PAK4 ablation in vivo reduced N-WASP Ser484/Ser485 phosphorylation and altered the cellular balance between G- and F-actin as well as the actin organization. By presenting the PAK4 interactome, we here provide a powerful resource for further investigations and as proof of principle, we also indicate a novel mechanism by which PAK4 regulates actin cytoskeleton remodeling.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

NASA Astrophysics Data System (ADS)

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

Physical and in silico approaches identify DNA-PK in a Tax DNA-damage response interactome

PubMed Central

Ramadan, Emad; Ward, Michael; Guo, Xin; Durkin, Sarah S; Sawyer, Adam; Vilela, Marcelo; Osgood, Christopher; Pothen, Alex; Semmes, Oliver J

2008-01-01

Background We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities. The physical mapping process involved the affinity isolation of Tax complexes followed by sequence identification using tandem mass spectrometry. To date we have mapped 250 cellular components within this interactome. Here we present our approach to prioritizing these interactions via an in silico culling process. Results We first constructed an in silico Tax interactome comprised of 46 literature-confirmed protein-protein interactions. This number was then reduced to four Tax-interactions suspected to play a role in DNA damage response (Rad51, TOP1, Chk2, 53BP1). The first-neighbor and second-neighbor interactions of these four proteins were assembled from available human protein interaction databases. Through an analysis of betweenness and closeness centrality measures, and numbers of interactions, we ranked proteins in the first neighborhood. When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists. An overlapping clustering of the Tax-specific second-neighborhood protein network showed DNA-PK to be one of three bridge proteins that link multiple clusters in the DNA damage response network. Conclusion The interaction of Tax with DNA-PK represents an important biological paradigm as suggested via consensus findings in vivo and in silico. We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome. PMID:18922151

Determination of Protein Interactome of Transcription Factor Sox2 in Embryonic Stem Cells Engineered for Inducible Expression of Four Reprogramming Factors*

PubMed Central

Gao, Zhiguang; Cox, Jesse L.; Gilmore, Joshua M.; Ormsbee, Briana D.; Mallanna, Sunil K.; Washburn, Michael P.; Rizzino, Angie

2012-01-01

Unbiased proteomic screens provide a powerful tool for defining protein-protein interaction networks. Previous studies employed multidimensional protein identification technology to identify the Sox2-interactome in embryonic stem cells (ESC) undergoing differentiation in response to a small increase in the expression of epitope-tagged Sox2. Thus far the Sox2-interactome in ESC has not been determined. To identify the Sox2-interactome in ESC, we engineered ESC for inducible expression of different combinations of epitope-tagged Sox2 along with Oct4, Klf4, and c-Myc. Epitope-tagged Sox2 was used to circumvent the lack of suitable Sox2 antibodies needed to perform an unbiased proteomic screen of Sox2-associated proteins. Although i-OS-ESC differentiate when both Oct4 and Sox2 are elevated, i-OSKM-ESC do not differentiate even when the levels of the four transcription factors are coordinately elevated ∼2–3-fold. Our findings with i-OS-ESC and i-OSKM-ESC provide new insights into the reasons why ESC undergo differentiation when Sox2 and Oct4 are elevated in ESC. Importantly, the use of i-OSKM-ESC enabled us to identify the Sox2-interactome in undifferentiated ESC. Using multidimensional protein identification technology, we identified >70 proteins that associate with Sox2 in ESC. We extended these findings by testing the function of the Sox2-assoicated protein Smarcd1 and demonstrate that knockdown of Smarcd1 disrupts the self-renewal of ESC and induces their differentiation. Together, our work provides the first description of the Sox2-interactome in ESC and indicates that Sox2 along with other master regulators is part of a highly integrated protein-protein interaction landscape in ESC. PMID:22334693

Grouping annotations on the subcellular layered interactome demonstrates enhanced autophagy activity in a recurrent experimental autoimmune uveitis T cell line.

PubMed

Jia, Xiuzhi; Li, Jingbo; Shi, Dejing; Zhao, Yu; Dong, Yucui; Ju, Huanyu; Yang, Jinfeng; Sun, Jianhua; Li, Xia; Ren, Huan

2014-01-01

Human uveitis is a type of T cell-mediated autoimmune disease that often shows relapse-remitting courses affecting multiple biological processes. As a cytoplasmic process, autophagy has been seen as an adaptive response to cell death and survival, yet the link between autophagy and T cell-mediated autoimmunity is not certain. In this study, based on the differentially expressed genes (GSE19652) between the recurrent versus monophasic T cell lines, whose adoptive transfer to susceptible animals may result in respective recurrent or monophasic uveitis, we proposed grouping annotations on a subcellular layered interactome framework to analyze the specific bioprocesses that are linked to the recurrence of T cell autoimmunity. That is, the subcellular layered interactome was established by the Cytoscape and Cerebral plugin based on differential expression, global interactome, and subcellular localization information. Then, the layered interactomes were grouping annotated by the ClueGO plugin based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The analysis showed that significant bioprocesses with autophagy were orchestrated in the cytoplasmic layered interactome and that mTOR may have a regulatory role in it. Furthermore, by setting up recurrent and monophasic uveitis in Lewis rats, we confirmed by transmission electron microscopy that, in comparison to the monophasic disease, recurrent uveitis in vivo showed significantly increased autophagy activity and extended lymphocyte infiltration to the affected retina. In summary, our framework methodology is a useful tool to disclose specific bioprocesses and molecular targets that can be attributed to a certain disease. Our results indicated that targeted inhibition of autophagy pathways may perturb the recurrence of uveitis.

Receptor Tyrosine Kinase MET Interactome and Neurodevelopmental Disorder Partners at the Developing Synapse.

PubMed

Xie, Zhihui; Li, Jing; Baker, Jonathan; Eagleson, Kathie L; Coba, Marcelo P; Levitt, Pat

2016-12-15

Atypical synapse development and plasticity are implicated in many neurodevelopmental disorders (NDDs). NDD-associated, high-confidence risk genes have been identified, yet little is known about functional relationships at the level of protein-protein interactions, which are the dominant molecular bases responsible for mediating circuit development. Proteomics in three independent developing neocortical synaptosomal preparations identified putative interacting proteins of the ligand-activated MET receptor tyrosine kinase, an autism risk gene that mediates synapse development. The candidates were translated into interactome networks and analyzed bioinformatically. Additionally, three independent quantitative proximity ligation assays in cultured neurons and four independent immunoprecipitation analyses of synaptosomes validated protein interactions. Approximately 11% (8/72) of MET-interacting proteins, including SHANK3, SYNGAP1, and GRIN2B, are associated with NDDs. Proteins in the MET interactome were translated into a novel MET interactome network based on human protein-protein interaction databases. High-confidence genes from different NDD datasets that encode synaptosomal proteins were analyzed for being enriched in MET interactome proteins. This was found for autism but not schizophrenia, bipolar disorder, major depressive disorder, or attention-deficit/hyperactivity disorder. There is correlated gene expression between MET and its interactive partners in developing human temporal and visual neocortices but not with highly expressed genes that are not in the interactome. Proximity ligation assays and biochemical analyses demonstrate that MET-protein partner interactions are dynamically regulated by receptor activation. The results provide a novel molecular framework for deciphering the functional relations of key regulators of synaptogenesis that contribute to both typical cortical development and to NDDs. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins.

PubMed

Mehla, Jitender; Dedrick, Rebekah M; Caufield, J Harry; Siefring, Rachel; Mair, Megan; Johnson, Allison; Hatfull, Graham F; Uetz, Peter

2015-08-01

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis. Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

Quantitative interactome reveals that porcine reproductive and respiratory syndrome virus nonstructural protein 2 forms a complex with viral nucleocapsid protein and cellular vimentin.

PubMed

Song, Tao; Fang, Liurong; Wang, Dang; Zhang, Ruoxi; Zeng, Songlin; An, Kang; Chen, Huanchun; Xiao, Shaobo

2016-06-16

Porcine reproductive and respiratory syndrome virus (PRRSV) is an Arterivirus that has heavily impacted the global swine industry. The PRRSV nonstructural protein 2 (nsp2) plays crucial roles in viral replication and host immune regulation, most likely by interacting with viral or cellular proteins that have not yet been identified. In this study, a quantitative interactome approach based on immunoprecipitation and stable isotope labeling with amino acids in cell culture (SILAC) was performed to identify nsp2-interacting proteins in PRRSV-infected cells with an nsp2-specific monoclonal antibody. Nine viral proteins and 62 cellular proteins were identified as potential nsp2-interacting partners. Our data demonstrate that the PRRSV nsp1α, nsp1β, and nucleocapsid proteins all interact directly with nsp2. Nsp2-interacting cellular proteins were classified into different functional groups and an interactome network of nsp2 was generated. Interestingly, cellular vimentin, a known receptor for PRRSV, forms a complex with nsp2 by using viral nucleocapsid protein as an intermediate. Taken together, the nsp2 interactome under the condition of virus infection clarifies a role of nsp2 in PRRSV replication and immune evasion. Viral proteins must interact with other virus-encoded proteins and/or host cellular proteins to function, and interactome analysis is an ideal approach for identifying such interacting proteins. In this study, we used the quantitative interactome methodology to identify the viral and cellular proteins that potentially interact with the nonstructural protein 2 (nsp2) of porcine reproductive and respiratory syndrome virus (PRRSV) under virus infection conditions, thus providing a rich source of potential viral and cellular interaction partners for PRRSV nsp2. Based on the interactome data, we further demonstrated that PRRSV nsp2 and nucleocapsid protein together with cellular vimentin, form a complex that may be essential for viral attachment and replication, which partly explains the role of nsp2 in PRRSV replication and immune evasion. Copyright © 2016 Elsevier B.V. All rights reserved.

Rearrangement of the Protein Phosphatase 1 Interactome During Heart Failure Progression.

PubMed

Chiang, David Y; Alsina, Katherina M; Corradini, Eleonora; Fitzpatrick, Martin; Ni, Li; Lahiri, Satadru K; Reynolds, Julia; Pan, Xiaolu; Scott, Larry; Heck, Albert J R; Wehrens, Xander H

2018-04-18

Background -Heart failure (HF) is a complex disease with a rising prevalence despite advances in treatment. Protein phosphatase 1 (PP1) has long been implicated in HF pathogenesis but its exact role is both unclear and controversial. Most previous studies measured only the PP1 catalytic subunit (PP1c) without investigating its diverse set of interactors, which confer localization and substrate specificity to the holoenzyme. In this study we define the PP1 interactome in cardiac tissue and test the hypothesis that this interactome becomes rearranged during HF progression at the level of specific PP1c interactors. Methods -Mice were subjected to transverse aortic constriction and grouped based on ejection fraction (EF) into sham, hypertrophy, moderate HF (EF 30-40%), and severe HF (EF<30%). Cardiac lysates were subjected to affinity-purification using anti-PP1c antibodies followed by high-resolution mass spectrometry. Ppp1r7 was knocked down in mouse cardiomyocytes and HeLa cells using adeno-associated virus serotype 9 (AAV9) and siRNA, respectively. Calcium imaging was performed on isolated ventricular myocytes. Results -Seventy-one and 98 PP1c interactors were quantified from mouse cardiac and HeLa lysates, respectively, including many novel interactors and protein complexes. This represents the largest reproducible PP1 interactome dataset ever captured from any tissue, including both primary and secondary/tertiary interactors. Nine PP1c interactors with changes in their binding to PP1c were strongly associated with HF progression including two known (Ppp1r7, Ppp1r18) and 7 novel interactors. Within the entire cardiac PP1 interactome, Ppp1r7 had the highest binding to PP1c. Cardiac-specific knockdown in mice led to cardiac dysfunction and disruption of calcium release from the sarcoplasmic reticulum. Conclusions -PP1 is best studied at the level of its interactome, which undergoes significant rearrangement during HF progression. The nine key interactors that are associated with HF progression may represent potential targets in HF therapy. In particular, Ppp1r7 may play a central role in regulating the PP1 interactome by acting as a competitive molecular "sponge" of PP1c.

Evidence for network evolution in an arabidopsis interactome map

USDA-ARS?s Scientific Manuscript database

Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the pl...

Functional proteomic and interactome analysis of proteins associated with beef tenderness in angus cattle

USDA-ARS?s Scientific Manuscript database

Beef is a source of high quality protein for the human population, and beef tenderness has significant influence on beef palatability, consumer expectation and industry profitability. To further elucidate the factors affecting beef tenderness, functional proteomics and bioinformatics interactome ana...

Comprehensive interactome of Otx2 in the adult mouse neural retina.

PubMed

Fant, Bruno; Samuel, Alexander; Audebert, Stéphane; Couzon, Agnès; El Nagar, Salsabiel; Billon, Nathalie; Lamonerie, Thomas

2015-11-01

The Otx2 homeodomain transcription factor exerts multiple functions in specific developmental contexts, probably through the regulation of different sets of genes. Protein partners of Otx2 have been shown to modulate its activity. Therefore, the Otx2 interactome may play a key role in selecting a precise target-gene repertoire, hence determining its function in a specific tissue. To address the nature of Otx2 interactome, we generated a new recombinant Otx2(CTAP-tag) mouse line, designed for protein complexes purification. We validated this mouse line by establishing the Otx2 interactome in the adult neural retina. In this tissue, Otx2 is thought to have overlapping function with its paralog Crx. Our analysis revealed that, in contrary to Crx, Otx2 did not develop interactions with proteins that are known to regulate phototransduction genes but showed specific partnership with factors associated with retinal development. The relationship between Otx2 and Crx in the neural retina should therefore be considered as complementarity rather than redundancy. Furthermore, study of the Otx2 interactome revealed strong associations with RNA processing and translation machineries, suggesting unexpected roles for Otx2 in the regulation of selected target genes all along the transcription/translation pathway. The Otx2(CTAP-tag) line, therefore, appears suitable for a systematic approach to Otx2 protein-protein interactions. genesis 53:685-694, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis.

PubMed

Pankow, Sandra; Bamberger, Casimir; Calzolari, Diego; Martínez-Bartolomé, Salvador; Lavallée-Adam, Mathieu; Balch, William E; Yates, John R

2015-12-24

Deletion of phenylalanine 508 of the cystic fibrosis transmembrane conductance regulator (∆F508 CFTR) is the major cause of cystic fibrosis, one of the most common inherited childhood diseases. The mutated CFTR anion channel is not fully glycosylated and shows minimal activity in bronchial epithelial cells of patients with cystic fibrosis. Low temperature or inhibition of histone deacetylases can partly rescue ∆F508 CFTR cellular processing defects and function. A favourable change of ∆F508 CFTR protein-protein interactions was proposed as a mechanism of rescue; however, CFTR interactome dynamics during temperature shift and inhibition of histone deacetylases are unknown. Here we report the first comprehensive analysis of the CFTR and ∆F508 CFTR interactome and its dynamics during temperature shift and inhibition of histone deacetylases. By using a novel deep proteomic analysis method, we identify 638 individual high-confidence CFTR interactors and discover a ∆F508 deletion-specific interactome, which is extensively remodelled upon rescue. Detailed analysis of the interactome remodelling identifies key novel interactors, whose loss promote ∆F508 CFTR channel function in primary cystic fibrosis epithelia or which are critical for CFTR biogenesis. Our results demonstrate that global remodelling of ∆F508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of cystic fibrosis caused by deletion of F508.

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

PubMed

Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George

2017-01-01

Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.

Identification and functional analysis of the BIM interactome; new clues on its possible involvement in Epstein-Barr Virus-associated diseases.

PubMed

Rouka, Erasmia; Kyriakou, Despoina

2015-12-01

Epigenetic deregulation is a common feature in the pathogenesis of Epstein-Barr Virus (EBV)-related lymphomas and carcinomas. Previous studies have demonstrated a strong association between EBV latency in B-cells and epigenetic silencing of the tumor suppressor gene BIM. This study aimed to the construction and functional analysis of the BIM interactome in order to identify novel host genes that may be targeted by EBV. Fifty-nine unique interactors were found to compose the BIM gene network. Ontological analysis at the pathway level highlighted infectious diseases along with neuropathologies. These results underline the possible interplay between the BIM interactome and EBV-associated disorders.

The Endogenous GRP78 Interactome in Human Head and Neck Cancers: A Deterministic Role of Cell Surface GRP78 in Cancer Stemness.

PubMed

Chen, Hsin-Ying; Chang, Joseph Tung-Chieh; Chien, Kun-Yi; Lee, Yun-Shien; You, Guo-Rung; Cheng, Ann-Joy

2018-01-11

Cell surface glucose regulated protein 78 (GRP78), an endoplasmic reticulum (ER) chaperone, was suggested to be a cancer stem cell marker, but the influence of this molecule on cancer stemness is poorly characterized. In this study, we developed a mass spectrometry platform to detect the endogenous interactome of GRP78 and investigated its role in cancer stemness. The interactome results showed that cell surface GRP78 associates with multiple molecules. The influence of cell population heterogeneity of head and neck cancer cell lines (OECM1, FaDu, and BM2) according to the cell surface expression levels of GRP78 and the GRP78 interactome protein, Progranulin, was investigated. The four sorted cell groups exhibited distinct cell cycle distributions, asymmetric/symmetric cell divisions, and different relative expression levels of stemness markers. Our results demonstrate that cell surface GRP78 promotes cancer stemness, whereas drives cells toward a non-stemlike phenotype when it chaperones Progranulin. We conclude that cell surface GRP78 is a chaperone exerting a deterministic influence on cancer stemness.

Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.

PubMed

Castello, Alfredo; Horos, Rastislav; Strein, Claudia; Fischer, Bernd; Eichelbaum, Katrin; Steinmetz, Lars M; Krijgsveld, Jeroen; Hentze, Matthias W

2016-01-01

RNA associates with RNA-binding proteins (RBPs) from synthesis to decay, forming dynamic ribonucleoproteins (RNPs). In spite of the preeminent role of RBPs regulating RNA fate, the scope of cellular RBPs has remained largely unknown. We have recently developed a novel and comprehensive method to identify the repertoire of active RBPs of cultured cells, called RNA interactome capture. Using in vivo UV cross-linking on cultured cells, proteins are covalently bound to RNA if the contact between the two is direct ("zero distance"). Protein-RNA complexes are purified by poly(A) tail-dependent oligo(dT) capture and analyzed by quantitative mass spectrometry. Because UV irradiation is applied to living cells and purification is performed using highly stringent washes, RNA interactome capture identifies physiologic and direct protein-RNA interactions. Applied to HeLa cells, this protocol revealed the near-complete repertoire of RBPs, including hundreds of novel RNA binders. Apart from its RBP discovery capacity, quantitative and comparative RNA interactome capture can also be used to study the responses of the RBP repertoire to different physiological cues and processes, including metabolic stress, differentiation, development, or the response to drugs.

RNA/DNA Hybrid Interactome Identifies DXH9 as a Molecular Player in Transcriptional Termination and R-Loop-Associated DNA Damage.

PubMed

Cristini, Agnese; Groh, Matthias; Kristiansen, Maiken S; Gromak, Natalia

2018-05-08

R-loops comprise an RNA/DNA hybrid and displaced single-stranded DNA. They play important biological roles and are implicated in pathology. Even so, proteins recognizing these structures are largely undefined. Using affinity purification with the S9.6 antibody coupled to mass spectrometry, we defined the RNA/DNA hybrid interactome in HeLa cells. This consists of known R-loop-associated factors SRSF1, FACT, and Top1, and yet uncharacterized interactors, including helicases, RNA processing, DNA repair, and chromatin factors. We validate specific examples of these interactors and characterize their involvement in R-loop biology. A top candidate DHX9 helicase promotes R-loop suppression and transcriptional termination. DHX9 interacts with PARP1, and both proteins prevent R-loop-associated DNA damage. DHX9 and other interactome helicases are overexpressed in cancer, linking R-loop-mediated DNA damage and disease. Our RNA/DNA hybrid interactome provides a powerful resource to study R-loop biology in health and disease. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Identification of host cellular proteins that interact with the M protein of a highly pathogenic porcine reproductive and respiratory syndrome virus vaccine strain.

PubMed

Wang, Qian; Li, Yanwei; Dong, Hong; Wang, Li; Peng, Jinmei; An, Tongqing; Yang, Xufu; Tian, Zhijun; Cai, Xuehui

2017-02-22

The highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) continues to pose one of the greatest threats to the swine industry. M protein is the most conserved and important structural protein of PRRSV. However, information about the host cellular proteins that interact with M protein remains limited. Host cellular proteins that interact with the M protein of HP-PRRSV were immunoprecipitated from MARC-145 cells infected with PRRSV HuN4-F112 using the M monoclonal antibody (mAb). The differentially expressed proteins were identified by LC-MS/MS. The screened proteins were used for bioinformatics analysis including Gene Ontology, the interaction network, and the enriched KEGG pathways. Some interested cellular proteins were validated to interact with M protein by CO-IP. The PRRSV HuN4-F112 infection group had 10 bands compared with the control group. The bands included 219 non-redundant cellular proteins that interact with M protein, which were identified by LC-MS/MS with high confidence. The gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway bioinformatic analyses indicated that the identified proteins could be assigned to several different subcellular locations and functional classes. Functional analysis of the interactome profile highlighted cellular pathways associated with protein translation, infectious disease, and signal transduction. Two interested cellular proteins-nuclear factor of activated T cells 45 kDa (NF45) and proliferating cell nuclear antigen (PCNA)-that could interact with M protein were validated by Co-IP and confocal analyses. The interactome data between PRRSV M protein and cellular proteins were identified and contribute to the understanding of the roles of M protein in the replication and pathogenesis of PRRSV. The interactome of M protein will aid studies of virus/host interactions and provide means to decrease the threat of PRRSV to the swine industry in the future.

Deriving Heterospecific Self-Assembling Protein-Protein Interactions Using a Computational Interactome Screen.

PubMed

Crooks, Richard O; Baxter, Daniel; Panek, Anna S; Lubben, Anneke T; Mason, Jody M

2016-01-29

Interactions between naturally occurring proteins are highly specific, with protein-network imbalances associated with numerous diseases. For designed protein-protein interactions (PPIs), required specificity can be notoriously difficult to engineer. To accelerate this process, we have derived peptides that form heterospecific PPIs when combined. This is achieved using software that generates large virtual libraries of peptide sequences and searches within the resulting interactome for preferentially interacting peptides. To demonstrate feasibility, we have (i) generated 1536 peptide sequences based on the parallel dimeric coiled-coil motif and varied residues known to be important for stability and specificity, (ii) screened the 1,180,416 member interactome for predicted Tm values and (iii) used predicted Tm cutoff points to isolate eight peptides that form four heterospecific PPIs when combined. This required that all 32 hypothetical off-target interactions within the eight-peptide interactome be disfavoured and that the four desired interactions pair correctly. Lastly, we have verified the approach by characterising all 36 pairs within the interactome. In analysing the output, we hypothesised that several sequences are capable of adopting antiparallel orientations. We subsequently improved the software by removing sequences where doing so led to fully complementary electrostatic pairings. Our approach can be used to derive increasingly large and therefore complex sets of heterospecific PPIs with a wide range of potential downstream applications from disease modulation to the design of biomaterials and peptides in synthetic biology. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Transcription Factor NRF2 as a Therapeutic Target for Chronic Diseases: A Systems Medicine Approach.

PubMed

Cuadrado, Antonio; Manda, Gina; Hassan, Ahmed; Alcaraz, María José; Barbas, Coral; Daiber, Andreas; Ghezzi, Pietro; León, Rafael; López, Manuela G; Oliva, Baldo; Pajares, Marta; Rojo, Ana I; Robledinos-Antón, Natalia; Valverde, Angela M; Guney, Emre; Schmidt, Harald H H W

2018-04-01

Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This network joins apparently heterogeneous phenotypes such as autoimmune, respiratory, digestive, cardiovascular, metabolic, and neurodegenerative diseases, along with cancer. Importantly, this approach matches and confirms in silico several applications for NRF2-modulating drugs validated in vivo at different phases of clinical development. Pharmacologically, their profile is as diverse as electrophilic dimethyl fumarate, synthetic triterpenoids like bardoxolone methyl and sulforaphane, protein-protein or DNA-protein interaction inhibitors, and even registered drugs such as metformin and statins, which activate NRF2 and may be repurposed for indications within the NRF2 cluster of disease phenotypes. Thus, NRF2 represents one of the first targets fully embraced by classic and systems medicine approaches to facilitate both drug development and drug repurposing by focusing on a set of disease phenotypes that appear to be mechanistically linked. The resulting NRF2 drugome may therefore rapidly advance several surprising clinical options for this subset of chronic diseases. Copyright © 2018 by The Author(s).

The RNA-binding protein LARP1 is a post-transcriptional regulator of survival and tumorigenesis in ovarian cancer

PubMed Central

Hopkins, Thomas G.; Mura, Manuela; Al-Ashtal, Hiba A.; Lahr, Roni M.; Abd-Latip, Normala; Sweeney, Katrina; Lu, Haonan; Weir, Justin; El-Bahrawy, Mona; Steel, Jennifer H.; Ghaem-Maghami, Sadaf; Aboagye, Eric O.; Berman, Andrea J.; Blagden, Sarah P.

2016-01-01

RNA-binding proteins (RBPs) are increasingly identified as post-transcriptional drivers of cancer progression. The RBP LARP1 is an mRNA stability regulator, and elevated expression of the protein in hepatocellular and lung cancers is correlated with adverse prognosis. LARP1 associates with an mRNA interactome that is enriched for oncogenic transcripts. Here we explore the role of LARP1 in epithelial ovarian cancer, a disease characterized by the rapid acquisition of resistance to chemotherapy through the induction of pro-survival signalling. We show, using ovarian cell lines and xenografts, that LARP1 is required for cancer cell survival and chemotherapy resistance. LARP1 promotes tumour formation in vivo and maintains cancer stem cell-like populations. Using transcriptomic analysis following LARP1 knockdown, cross-referenced against the LARP1 interactome, we identify BCL2 and BIK as LARP1 mRNA targets. We demonstrate that, through an interaction with the 3′ untranslated regions (3′ UTRs) of BCL2 and BIK, LARP1 stabilizes BCL2 but destabilizes BIK with the net effect of resisting apoptosis. Together, our data indicate that by differentially regulating the stability of a selection of mRNAs, LARP1 promotes ovarian cancer progression and chemotherapy resistance. PMID:26717985

The Co-Metabolism within the Gut-Brain Metabolic Interaction: Potential Targets for Drug Treatment and Design.

PubMed

Obrenovich, Mark; Flückiger, Rudolf; Sykes, Lorraine; Donskey, Curtis

2016-01-01

We know that within the complex mammalian gut is any number of metabolic biomes. The gut has been sometimes called the "second brain" within the "gut-brain axis". A more informative term would be the gut-brain metabolic interactome, which is coined here to underscore the relationship between the digestive system and cognitive function or dysfunction as the case may be. Co-metabolism between the host and the intestinal microbiota is essential for life's processes. How diet, lifestyle, antibiotics and other factors shape the gut microbiome constitutes a rapidly growing area of research. Conversely, the gut microbiome also affects mammalian systems. Metabolites of the gut-brain axis are potential targets for treatment and drug design since the interaction or biochemical interplay results in net metabolite production or end-products with either positive or negative effects on human health. This review explores the gut-brain metabolic interactome, with particular emphasis on drug design and treatment strategies and how commensal bacteria or their disruption lead to dysbiosis and the effect this has on neurochemistry. Increasing data indicate that the intestinal microbiome can affect neurobiology, from mental and even behavioral health to memory, depression, mood, anxiety, obesity, cravings and even the creation and maintenance of the blood brain barrier.

Computational genomic analysis of PARK7 interactome reveals high BBS1 gene expression as a prognostic factor favoring survival in malignant pleural mesothelioma.

PubMed

Vavougios, Georgios D; Solenov, Evgeniy I; Hatzoglou, Chrissi; Baturina, Galina S; Katkova, Liubov E; Molyvdas, Paschalis Adam; Gourgoulianis, Konstantinos I; Zarogiannis, Sotirios G

2015-10-01

The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients (network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease. Copyright © 2015 the American Physiological Society.

Different adaptation strategies of two citrus scion/rootstock combinations in response to drought stress

PubMed Central

Coelho Filho, Mauricio Antônio; Morillon, Raphaël; Bonatto, Diego; da Silva Gesteira, Abelmon

2017-01-01

Scion/rootstock interaction is important for plant development and for breeding programs. In this context, polyploid rootstocks presented several advantages, mainly in relation to biotic and abiotic stresses. Here we analyzed the response to drought of two different scion/rootstock combinations presenting different polyploidy: the diploid (2x) and autotetraploid (4x) Rangpur lime (Citrus limonia, Osbeck) rootstocks grafted with 2x Valencia Delta sweet orange (Citrus sinensis) scions, named V/2xRL and V/4xRL, respectively. Based on previous gene expression data, we developed an interactomic approach to identify proteins involved in V/2xRL and V/4xRL response to drought. A main interactomic network containing 3,830 nodes and 97,652 edges was built from V/2xRL and V/4xRL data. Exclusive proteins of the V/2xRL and V/4xRL networks (2,056 and 1,001, respectively), as well as common to both networks (773) were identified. Functional clusters were obtained and two models of drought stress response for the V/2xRL and V/4xRL genotypes were designed. Even if the V/2xRL plant implement some tolerance mechanisms, the global plant response to drought was rapid and quickly exhaustive resulting in a general tendency to dehydration avoidance, which presented some advantage in short and strong drought stress conditions, but which, in long terms, does not allow the plant survival. At the contrary, the V/4xRL plants presented a response which strong impacts on development but that present some advantages in case of prolonged drought. Finally, some specific proteins, which presented high centrality on interactomic analysis were identified as good candidates for subsequent functional analysis of citrus genes related to drought response, as well as be good markers of one or another physiological mechanism implemented by the plants. PMID:28545114

Simultaneously measuring multiple protein interactions and their correlations in a cell by Protein-interactome Footprinting

PubMed Central

Luo, Si-Wei; Liang, Zhi; Wu, Jia-Rui

2017-01-01

Quantitatively detecting correlations of multiple protein-protein interactions (PPIs) in vivo is a big challenge. Here we introduce a novel method, termed Protein-interactome Footprinting (PiF), to simultaneously measure multiple PPIs in one cell. The principle of PiF is that each target physical PPI in the interactome is simultaneously transcoded into a specific DNA sequence based on dimerization of the target proteins fused with DNA-binding domains. The interaction intensity of each target protein is quantified as the copy number of the specific DNA sequences bound by each fusion protein dimers. Using PiF, we quantitatively reveal dynamic patterns of PPIs and their correlation network in E. coli two-component systems. PMID:28338015

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC.

PubMed

Blumert, Conny; Kalkhof, Stefan; Brocke-Heidrich, Katja; Kohajda, Tibor; von Bergen, Martin; Horn, Friedemann

2013-12-06

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively. The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications. © 2013. Published by Elsevier B.V. All rights reserved.

The role of the interactome in the maintenance of deleterious variability in human populations

PubMed Central

Garcia-Alonso, Luz; Jiménez-Almazán, Jorge; Carbonell-Caballero, Jose; Vela-Boza, Alicia; Santoyo-López, Javier; Antiñolo, Guillermo; Dopazo, Joaquin

2014-01-01

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins. PMID:25261458

The role of the interactome in the maintenance of deleterious variability in human populations.

PubMed

Garcia-Alonso, Luz; Jiménez-Almazán, Jorge; Carbonell-Caballero, Jose; Vela-Boza, Alicia; Santoyo-López, Javier; Antiñolo, Guillermo; Dopazo, Joaquin

2014-09-26

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins. © 2014 The Authors. Published under the terms of the CC BY 4.0 license.

Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

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

Ecker, Joseph Robert; Trigg, Shelly; Garza, Renee

Biofuel crop cultivation is a necessary step in heading towards a sustainable future, making their genomic studies a priority. While technology platforms that currently exist for studying non-model crop species, like switch-grass or sorghum, have yielded large quantities of genomic and expression data, still a large gap exists between molecular mechanism and phenotype. The aspect of molecular activity at the level of protein-protein interactions has recently begun to bridge this gap, providing a more global perspective. Interactome analysis has defined more specific functional roles of proteins based on their interaction partners, neighborhoods, and other network features, making it possible tomore » distinguish unique modules of immune response to different plant pathogens(Jiang, Dong, and Zhang 2016). As we work towards cultivating heartier biofuel crops, interactome data will lead to uncovering crop-specific defense and development networks. However, the collection of protein interaction data has been limited to expensive, time-consuming, hard-to-scale assays that mostly require cloned ORF collections. For these reasons, we have successfully developed a highly scalable, economical, and sensitive yeast two-hybrid assay, ProCREate, that can be universally applied to generate proteome-wide primary interactome data. ProCREate enables en masse pooling and massively paralleled sequencing for the identification of interacting proteins by exploiting Cre-lox recombination. ProCREate can be used to screen ORF/cDNA libraries from feedstock plant tissues. The interactome data generated will yield deeper insight into many molecular processes and pathways that can be used to guide improvement of feedstock productivity and sustainability.« less

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

PubMed

Perez-Lopez, Áron R; Szalay, Kristóf Z; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-11

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Expanding the Interactome of TES by Exploiting TES Modules with Different Subcellular Localizations.

PubMed

Sala, Stefano; Van Troys, Marleen; Medves, Sandrine; Catillon, Marie; Timmerman, Evy; Staes, An; Schaffner-Reckinger, Elisabeth; Gevaert, Kris; Ampe, Christophe

2017-05-05

The multimodular nature of many eukaryotic proteins underlies their temporal or spatial engagement in a range of protein cocomplexes. Using the multimodule protein testin (TES), we here report a proteomics approach to increase insight in cocomplex diversity. The LIM-domain containing and tumor suppressor protein TES is present at different actin cytoskeleton adhesion structures in cells and influences cell migration, adhesion and spreading. TES module accessibility has been proposed to vary due to conformational switching and variants of TES lacking specific domains target to different subcellular locations. By applying iMixPro AP-MS ("intelligent Mixing of Proteomes"-affinity purification-mass spectrometry) to a set of tagged-TES modular variants, we identified proteins residing in module-specific cocomplexes. The obtained distinct module-specific interactomes combine to a global TES interactome that becomes more extensive and richer in information. Applying pathway analysis to the module interactomes revealed expected actin-related canonical pathways and also less expected pathways. We validated two new TES cocomplex partners: TGFB1I1 and a short form of the glucocorticoid receptor. TES and TGFB1I1 are shown to oppositely affect cell spreading providing biological validity for their copresence in complexes since they act in similar processes.

The interactome of the copper transporter ATP7A belongs to a network of neurodevelopmental and neurodegeneration factors

PubMed Central

Comstra, Heather S; McArthy, Jacob; Rudin-Rush, Samantha; Hartwig, Cortnie; Gokhale, Avanti; Zlatic, Stephanie A; Blackburn, Jessica B; Werner, Erica; Petris, Michael; D’Souza, Priya; Panuwet, Parinya; Barr, Dana Boyd; Lupashin, Vladimir; Vrailas-Mortimer, Alysia; Faundez, Victor

2017-01-01

Genetic and environmental factors, such as metals, interact to determine neurological traits. We reasoned that interactomes of molecules handling metals in neurons should include novel metal homeostasis pathways. We focused on copper and its transporter ATP7A because ATP7A null mutations cause neurodegeneration. We performed ATP7A immunoaffinity chromatography and identified 541 proteins co-isolating with ATP7A. The ATP7A interactome concentrated gene products implicated in neurodegeneration and neurodevelopmental disorders, including subunits of the Golgi-localized conserved oligomeric Golgi (COG) complex. COG null cells possess altered content and subcellular localization of ATP7A and CTR1 (SLC31A1), the transporter required for copper uptake, as well as decreased total cellular copper, and impaired copper-dependent metabolic responses. Changes in the expression of ATP7A and COG subunits in Drosophila neurons altered synapse development in larvae and copper-induced mortality of adult flies. We conclude that the ATP7A interactome encompasses a novel COG-dependent mechanism to specify neuronal development and survival. DOI: http://dx.doi.org/10.7554/eLife.24722.001 PMID:28355134

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

NASA Astrophysics Data System (ADS)

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Vascular Endothelial Growth Factor (VEGF) Promotes Assembly of the p130Cas Interactome to Drive Endothelial Chemotactic Signaling and Angiogenesis.

PubMed

Evans, Ian M; Kennedy, Susan A; Paliashvili, Ketevan; Santra, Tapesh; Yamaji, Maiko; Lovering, Ruth C; Britton, Gary; Frankel, Paul; Kolch, Walter; Zachary, Ian C

2017-02-01

p130Cas is a polyvalent adapter protein essential for cardiovascular development, and with a key role in cell movement. In order to identify the pathways by which p130Cas exerts its biological functions in endothelial cells we mapped the p130Cas interactome and its dynamic changes in response to VEGF using high-resolution mass spectrometry and reconstruction of protein interaction (PPI) networks with the aid of multiple PPI databases. VEGF enriched the p130Cas interactome in proteins involved in actin cytoskeletal dynamics and cell movement, including actin-binding proteins, small GTPases and regulators or binders of GTPases. Detailed studies showed that p130Cas association of the GTPase-binding scaffold protein, IQGAP1, plays a key role in VEGF chemotactic signaling, endothelial polarization, VEGF-induced cell migration, and endothelial tube formation. These findings indicate a cardinal role for assembly of the p130Cas interactome in mediating the cell migratory response to VEGF in angiogenesis, and provide a basis for further studies of p130Cas in cell movement. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome.

PubMed

Li, Yiwei; Ilie, Lucian

2017-11-15

Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Many computational methods have been proposed among which sequence-based ones are very promising. However, so far no such method is able to predict effectively the entire human interactome: they require too much time or memory. We present SPRINT (Scoring PRotein INTeractions), a new sequence-based algorithm and tool for predicting protein-protein interactions. We comprehensively compare SPRINT with state-of-the-art programs on seven most reliable human PPI datasets and show that it is more accurate while running orders of magnitude faster and using very little memory. SPRINT is the only sequence-based program that can effectively predict the entire human interactome: it requires between 15 and 100 min, depending on the dataset. Our goal is to transform the very challenging problem of predicting the entire human interactome into a routine task. The source code of SPRINT is freely available from https://github.com/lucian-ilie/SPRINT/ and the datasets and predicted PPIs from www.csd.uwo.ca/faculty/ilie/SPRINT/ .

Systematic analyses of the ultraviolet radiation resistance-associated gene product (UVRAG) protein interactome by tandem affinity purification.

PubMed

Son, Ji-Hye; Hwang, Eurim C; Kim, Joungmok

2016-03-01

Ultraviolet radiation resistance-associated gene product (UVRAG) was originally identified as a protein involved in cellular responses to UV irradiation. Subsequent studies have demonstrated that UVRAG plays as an important role in autophagy, a lysosome-dependent catabolic program, as a part of a pro-autophagy PIK3C3/VPS34 lipid kinase complex. Several recent studies have shown that UVRAG is also involved in autophagy-independent cellular functions, such as DNA repair/stability and vesicular trafficking/fusion. Here, we examined the UVRAG protein interactome to obtain information about its functional network. To this end, we screened UVRAG-interacting proteins using a tandem affinity purification method coupled with MALDI-TOF/MS analysis. Our results demonstrate that UVRAG interacts with various proteins involved in a wide spectrum of cellular functions, including genome stability, protein translational elongation, protein localization (trafficking), vacuole organization, transmembrane transport as well as autophagy. Notably, the interactome list of high-confidence UVRAG-interacting proteins is enriched for proteins involved in the regulation of genome stability. Our systematic UVRAG interactome analysis should provide important clues for understanding a variety of UVRAG functions.

The IBD interactome: an integrated view of aetiology, pathogenesis and therapy.

PubMed

de Souza, Heitor S P; Fiocchi, Claudio; Iliopoulos, Dimitrios

2017-12-01

Crohn's disease and ulcerative colitis are prototypical complex diseases characterized by chronic and heterogeneous manifestations, induced by interacting environmental, genomic, microbial and immunological factors. These interactions result in an overwhelming complexity that cannot be tackled by studying the totality of each pathological component (an '-ome') in isolation without consideration of the interaction among all relevant -omes that yield an overall 'network effect'. The outcome of this effect is the 'IBD interactome', defined as a disease network in which dysregulation of individual -omes causes intestinal inflammation mediated by dysfunctional molecular modules. To define the IBD interactome, new concepts and tools are needed to implement a systems approach; an unbiased data-driven integration strategy that reveals key players of the system, pinpoints the central drivers of inflammation and enables development of targeted therapies. Powerful bioinformatics tools able to query and integrate multiple -omes are available, enabling the integration of genomic, epigenomic, transcriptomic, proteomic, metabolomic and microbiome information to build a comprehensive molecular map of IBD. This approach will enable identification of IBD molecular subtypes, correlations with clinical phenotypes and elucidation of the central hubs of the IBD interactome that will aid discovery of compounds that can specifically target the hubs that control the disease.

Network Approach to Disease Diagnosis

NASA Astrophysics Data System (ADS)

Sharma, Amitabh; Bashan, Amir; Barabasi, Alber-Laszlo

2014-03-01

Human diseases could be viewed as perturbations of the underlying biological system. A thorough understanding of the topological and dynamical properties of the biological system is crucial to explain the mechanisms of many complex diseases. Recently network-based approaches have provided a framework for integrating multi-dimensional biological data that results in a better understanding of the pathophysiological state of complex diseases. Here we provide a network-based framework to improve the diagnosis of complex diseases. This framework is based on the integration of transcriptomics and the interactome. We analyze the overlap between the differentially expressed (DE) genes and disease genes (DGs) based on their locations in the molecular interaction network (''interactome''). Disease genes and their protein products tend to be much more highly connected than random, hence defining a disease sub-graph (called disease module) in the interactome. DE genes, even though different from the known set of DGs, may be significantly associated with the disease when considering their closeness to the disease module in the interactome. This new network approach holds the promise to improve the diagnosis of patients who cannot be diagnosed using conventional tools. Support was provided by HL066289 and HL105339 grants from the U.S. National Institutes of Health.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

PubMed Central

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-01-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates. PMID:25960144

Bacterial Interactomes: Interacting Protein Partners Share Similar Function and Are Validated in Independent Assays More Frequently Than Previously Reported*

PubMed Central

Shatsky, Maxim; Allen, Simon; Gold, Barbara L.; Liu, Nancy L.; Juba, Thomas R.; Reveco, Sonia A.; Elias, Dwayne A.; Prathapam, Ramadevi; He, Jennifer; Yang, Wenhong; Szakal, Evelin D.; Liu, Haichuan; Singer, Mary E.; Geller, Jil T.; Lam, Bonita R.; Saini, Avneesh; Trotter, Valentine V.; Hall, Steven C.; Fisher, Susan J.; Brenner, Steven E.; Chhabra, Swapnil R.; Hazen, Terry C.; Wall, Judy D.; Witkowska, H. Ewa; Biggin, Mark D.; Chandonia, John-Marc; Butland, Gareth

2016-01-01

Numerous affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested. PMID:26873250

Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms.

PubMed

Li, Jiannong; Bennett, Keiryn; Stukalov, Alexey; Fang, Bin; Zhang, Guolin; Yoshida, Takeshi; Okamoto, Isamu; Kim, Jae-Young; Song, Lanxi; Bai, Yun; Qian, Xiaoning; Rawal, Bhupendra; Schell, Michael; Grebien, Florian; Winter, Georg; Rix, Uwe; Eschrich, Steven; Colinge, Jacques; Koomen, John; Superti-Furga, Giulio; Haura, Eric B

2013-11-05

We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.

AIM: a comprehensive Arabidopsis interactome module database and related interologs in plants.

PubMed

Wang, Yi; Thilmony, Roger; Zhao, Yunjun; Chen, Guoping; Gu, Yong Q

2014-01-01

Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250,000 modules that were generated using multiple analysis methods and integration of microarray expression data. All the modules in AIM are well annotated using multiple gene function knowledge databases. AIM provides a user-friendly interface for different types of searches and offers a powerful graphical viewer for displaying module networks linked to the enrichment annotation terms. Both interactive Venn diagram and power graph viewer are integrated into the database for easy comparison of modules. In addition, predicted interologs from other plant species (homologous proteins from different species that share a conserved interaction module) are available for each Arabidopsis module. AIM is a powerful systems biology platform for obtaining valuable insights into the function of proteins in Arabidopsis and other plants using the modules of the Arabidopsis interactome. Database URL:http://probes.pw.usda.gov/AIM Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Mining protein interactomes to improve their reliability and support the advancement of network medicine.

PubMed

Alanis-Lobato, Gregorio

2015-01-01

High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

SH3 interactome conserves general function over specific form

PubMed Central

Xin, Xiaofeng; Gfeller, David; Cheng, Jackie; Tonikian, Raffi; Sun, Lin; Guo, Ailan; Lopez, Lianet; Pavlenco, Alevtina; Akintobi, Adenrele; Zhang, Yingnan; Rual, Jean-François; Currell, Bridget; Seshagiri, Somasekar; Hao, Tong; Yang, Xinping; Shen, Yun A; Salehi-Ashtiani, Kourosh; Li, Jingjing; Cheng, Aaron T; Bouamalay, Dryden; Lugari, Adrien; Hill, David E; Grimes, Mark L; Drubin, David G; Grant, Barth D; Vidal, Marc; Boone, Charles; Sidhu, Sachdev S; Bader, Gary D

2013-01-01

Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form. PMID:23549480

Proteomic profile of Mycobacterium tuberculosis after eupomatenoid-5 induction reveals potential drug targets.

PubMed

Ghiraldi-Lopes, Luciana D; Campanerut-Sá, Paula Az; Meneguello, Jean E; Seixas, Flávio Av; Lopes-Ortiz, Mariana A; Scodro, Regiane Bl; Pires, Claudia Ta; da Silva, Rosi Z; Siqueira, Vera Ld; Nakamura, Celso V; Cardoso, Rosilene F

2017-08-01

We investigated a proteome profile, protein-protein interaction and morphological changes of Mycobacterium tuberculosis after different times of eupomatenoid-5 (EUP-5) induction to evaluate the cellular response to the drug-induced damages. The bacillus was induced to sub-minimal inhibitory concentration of EUP-5 at 12 h, 24 h and 48 h. The proteins were separated by 2D gel electrophoresis, identified by LC/MS-MS. Scanning electron microscopy and Search Tool for the Retrieval of Interacting Genes/Proteins analyses were performed. EUP-5 impacts mainly in M. tuberculosis proteins of intermediary metabolism and interactome suggests a multisite disturbance that contributes to bacilli death. Scanning electron microscopy revealed the loss of bacillary form. Some of the differentially expressed proteins have the potential to be drug targets such as citrate synthase (Rv0896), phosphoglycerate kinase (Rv1437), ketol-acid reductoisomerase (Rv3001c) and ATP synthase alpha chain (Rv1308).

The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells.

PubMed

Whisenant, Thomas C; Peralta, Eigen R; Aarreberg, Lauren D; Gao, Nina J; Head, Steven R; Ordoukhanian, Phillip; Williamson, Jamie R; Salomon, Daniel R

2015-01-01

Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as "central" interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, "peripheral" interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA splicing interactomes that is important for understanding T cell activation.

The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells

PubMed Central

Aarreberg, Lauren D.; Gao, Nina J.; Head, Steven R.; Ordoukhanian, Phillip; Williamson, Jamie R.; Salomon, Daniel R.

2015-01-01

Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as “central” interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, “peripheral” interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA splicing interactomes that is important for understanding T cell activation. PMID:26641092

A systems immunology approach identifies the collective impact of 5 miRs in Th2 inflammation.

PubMed

Kılıç, Ayşe; Santolini, Marc; Nakano, Taiji; Schiller, Matthias; Teranishi, Mizue; Gellert, Pascal; Ponomareva, Yuliya; Braun, Thomas; Uchida, Shizuka; Weiss, Scott T; Sharma, Amitabh; Renz, Harald

2018-06-07

Allergic asthma is a chronic inflammatory disease dominated by a CD4+ T helper 2 (Th2) cell signature. The immune response amplifies in self-enforcing loops, promoting Th2-driven cellular immunity and leaving the host unable to terminate inflammation. Posttranscriptional mechanisms, including microRNAs (miRs), are pivotal in maintaining immune homeostasis. Since an altered expression of various miRs has been associated with T cell-driven diseases, including asthma, we hypothesized that miRs control mechanisms ensuring Th2 stability and maintenance in the lung. We isolated murine CD4+ Th2 cells from allergic inflamed lungs and profiled gene and miR expression. Instead of focusing on the magnitude of miR differential expression, here we addressed the secondary consequences for the set of molecular interactions in the cell, the interactome. We developed the Impact of Differential Expression Across Layers, a network-based algorithm to prioritize disease-relevant miRs based on the central role of their targets in the molecular interactome. This method identified 5 Th2-related miRs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. Overall, a systems biology tool was developed and validated, highlighting the role of miRs in Th2-driven immune response. This result offers potentially novel approaches for therapeutic interventions.

TCTEX1D4 Interactome in Human Testis: Unraveling the Function of Dynein Light Chain in Spermatozoa

PubMed Central

Freitas, Maria João; Korrodi-Gregório, Luís; Morais-Santos, Filipa; da Cruz e Silva, Edgar

2014-01-01

Abstract Studies were designed to identify the TCTEX1D4 interactome in human testis, with the purpose of unraveling putative protein complexes essential to male reproduction and thus novel TCTEX1D4 functions. TCTEX1D4 is a dynein light chain that belongs to the DYNT1/TCTEX1 family. In spermatozoa, it appears to be important to sperm motility, intraflagellar transport, and acrosome reaction. To contribute to the knowledge on TCTEX1D4 function in testis and spermatozoa, a yeast two-hybrid assay was performed in testis, which allowed the identification of 40 novel TCTEX1D4 interactors. Curiously, another dynein light chain, TCTEX1D2, was identified and its existence demonstrated for the first time in human spermatozoa. Immunofluorescence studies proved that TCTEX1D2 is an intra-acrosomal protein also present in the midpiece, suggesting a role in cargo movement in human spermatozoa. Further, an in silico profile of TCTEX1D4 revealed that most TCTEX1D4 interacting proteins were not previously characterized and the ones described present a very broad nature. This reinforces TCTEX1D4 as a dynein light chain that is capable of interacting with a variety of functionally different proteins. These observations collectively contribute to a deeper molecular understanding of the human spermatozoa function. PMID:24606217

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Sequential Elution Interactome Analysis of the Mind Bomb 1 Ubiquitin Ligase Reveals a Novel Role in Dendritic Spine Outgrowth*

PubMed Central

Mertz, Joseph; Tan, Haiyan; Pagala, Vishwajeeth; Bai, Bing; Chen, Ping-Chung; Li, Yuxin; Cho, Ji-Hoon; Shaw, Timothy; Wang, Xusheng; Peng, Junmin

2015-01-01

The mind bomb 1 (Mib1) ubiquitin ligase is essential for controlling metazoan development by Notch signaling and possibly the Wnt pathway. It is also expressed in postmitotic neurons and regulates neuronal morphogenesis and synaptic activity by mechanisms that are largely unknown. We sought to comprehensively characterize the Mib1 interactome and study its potential function in neuron development utilizing a novel sequential elution strategy for affinity purification, in which Mib1 binding proteins were eluted under different stringency and then quantified by the isobaric labeling method. The strategy identified the Mib1 interactome with both deep coverage and the ability to distinguish high-affinity partners from low-affinity partners. A total of 817 proteins were identified during the Mib1 affinity purification, including 56 high-affinity partners and 335 low-affinity partners, whereas the remaining 426 proteins are likely copurified contaminants or extremely weak binding proteins. The analysis detected all previously known Mib1-interacting proteins and revealed a large number of novel components involved in Notch and Wnt pathways, endocytosis and vesicle transport, the ubiquitin-proteasome system, cellular morphogenesis, and synaptic activities. Immunofluorescence studies further showed colocalization of Mib1 with five selected proteins: the Usp9x (FAM) deubiquitinating enzyme, alpha-, beta-, and delta-catenins, and CDKL5. Mutations of CDKL5 are associated with early infantile epileptic encephalopathy-2 (EIEE2), a severe form of mental retardation. We found that the expression of Mib1 down-regulated the protein level of CDKL5 by ubiquitination, and antagonized CDKL5 function during the formation of dendritic spines. Thus, the sequential elution strategy enables biochemical characterization of protein interactomes; and Mib1 analysis provides a comprehensive interactome for investigating its role in signaling networks and neuronal development. PMID:25931508

Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia.

PubMed

Rampino, Antonio; Walker, Rosie May; Torrance, Helen Scott; Anderson, Susan Maguire; Fazio, Leonardo; Di Giorgio, Annabella; Taurisano, Paolo; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Ursini, Gianluca; Caforio, Grazia; Blasi, Giuseppe; Millar, J Kirsty; Porteous, David John; Thomson, Pippa Ann; Bertolino, Alessandro; Evans, Kathryn Louise

2014-01-01

Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

Expression of DISC1-Interactome Members Correlates with Cognitive Phenotypes Related to Schizophrenia

PubMed Central

Rampino, Antonio; Walker, Rosie May; Torrance, Helen Scott; Anderson, Susan Maguire; Fazio, Leonardo; Di Giorgio, Annabella; Taurisano, Paolo; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Ursini, Gianluca; Caforio, Grazia; Blasi, Giuseppe; Millar, J. Kirsty; Porteous, David John; Thomson, Pippa Ann; Bertolino, Alessandro; Evans, Kathryn Louise

2014-01-01

Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions. PMID:24940743

Towards Personalized Medicine Mediated by in Vitro Virus-Based Interactome Approaches

PubMed Central

Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

2014-01-01

We have developed a simple in vitro virus (IVV) selection system based on cell-free co-translation, using a highly stable and efficient mRNA display method. The IVV system is applicable to the high-throughput and comprehensive analysis of proteins and protein–ligand interactions. Huge amounts of genomic sequence data have been generated over the last decade. The accumulated genetic alterations and the interactome networks identified within cells represent a universal feature of a disease, and knowledge of these aspects can help to determine the optimal therapy for the disease. The concept of the “integrome” has been developed as a means of integrating large amounts of data. We have developed an interactome analysis method aimed at providing individually-targeted health care. We also consider future prospects for this system. PMID:24756093

Preparation of Gap Junctions in Membrane Microdomains for Immunoprecipitation and Mass Spectrometry Interactome Analysis.

PubMed

Fowler, Stephanie; Akins, Mark; Bennett, Steffany A L

2016-01-01

Protein interaction networks at gap junction plaques are increasingly implicated in a variety of intracellular signaling cascades. Identifying protein interactions of integral membrane proteins is a valuable tool for determining channel function. However, several technical challenges exist. Subcellular fractionation of the bait protein matrix is usually required to identify less abundant proteins in complex homogenates. Sufficient solvation of the lipid environment without perturbation of the protein interactome must also be achieved. The present chapter describes the flotation of light and heavy liver tissue membrane microdomains to facilitate the identification and analysis of endogenous gap junction proteins and includes technical notes for translation to other integral membrane proteins, tissues, or cell culture models. These procedures are valuable tools for the enrichment of gap junction membrane compartments and for the identification of gap junction signaling interactomes.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

PubMed

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

In silico prediction of protein-protein interactions in human macrophages

PubMed Central

2014-01-01

Background Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level. PMID:24636261

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

Inferring the Brassica rapa Interactome Using Protein–Protein Interaction Data from Arabidopsis thaliana

PubMed Central

Yang, Jianhua; Osman, Kim; Iqbal, Mudassar; Stekel, Dov J.; Luo, Zewei; Armstrong, Susan J.; Franklin, F. Chris H.

2013-01-01

Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein–protein interaction (PPI) data are available from the major PPI databases (DBs). It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i) A. thaliana PPI data from three major DBs, BioGRID, IntAct, and TAIR. (ii) ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i) ortholog predictions, (ii) identification of gene duplication based on synteny and collinearity, and (iii) BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain–domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability. PMID:23293649

High-Confidence Interactome for RNF41 Built on Multiple Orthogonal Assays.

PubMed

Masschaele, Delphine; Wauman, Joris; Vandemoortele, Giel; De Sutter, Delphine; De Ceuninck, Leentje; Eyckerman, Sven; Tavernier, Jan

2018-04-06

Ring finger protein 41 (RNF41) is an E3 ubiquitin ligase involved in the ubiquitination and degradation of many proteins including ErbB3 receptors, BIRC6, and parkin. Next to this, RNF41 regulates the intracellular trafficking of certain JAK2-associated cytokine receptors by ubiquitinating and suppressing USP8, which, in turn, destabilizes the ESCRT-0 complex. To further elucidate the function of RNF41 we used different orthogonal approaches to reveal the RNF41 protein complex: affinity purification-mass spectrometry, BioID, and Virotrap. We combined these results with known data sets for RNF41 obtained with microarray MAPPIT and Y2H screens. This way, we establish a comprehensive high-resolution interactome network comprising 175 candidate protein partners. To remove potential methodological artifacts from this network, we distilled the data into a high-confidence interactome map by retaining a total of 19 protein hits identified in two or more of the orthogonal methods. AP2S1, a novel RNF41 interaction partner, was selected from this high-confidence interactome for further functional validation. We reveal a role for AP2S1 in leptin and LIF receptor signaling and show that RNF41 stabilizes and relocates AP2S1.

A Viral-Human Interactome Based on Structural Motif-Domain Interactions Captures the Human Infectome

PubMed Central

Guo, Xianwu; Rodríguez-Pérez, Mario A.

2013-01-01

Protein interactions between a pathogen and its host are fundamental in the establishment of the pathogen and underline the infection mechanism. In the present work, we developed a single predictive model for building a host-viral interactome based on the identification of structural descriptors from motif-domain interactions of protein complexes deposited in the Protein Data Bank (PDB). The structural descriptors were used for searching, in a database of protein sequences of human and five clinically important viruses; therefore, viral and human proteins sharing a descriptor were predicted as interacting proteins. The analysis of the host-viral interactome allowed to identify a set of new interactions that further explain molecular mechanism associated with viral infections and showed that it was able to capture human proteins already associated to viral infections (human infectome) and non-infectious diseases (human diseasome). The analysis of human proteins targeted by viral proteins in the context of a human interactome showed that their neighbors are enriched in proteins reported with differential expression under infection and disease conditions. It is expected that the findings of this work will contribute to the development of systems biology for infectious diseases, and help guide the rational identification and prioritization of novel drug targets. PMID:23951184

Big data mining powers fungal research: recent advances in fission yeast systems biology approaches.

PubMed

Wang, Zhe

2017-06-01

Biology research has entered into big data era. Systems biology approaches therefore become the powerful tools to obtain the whole landscape of how cell separate, grow, and resist the stresses. Fission yeast Schizosaccharomyces pombe is wonderful unicellular eukaryote model, especially studying its division and metabolism can facilitate to understanding the molecular mechanism of cancer and discovering anticancer agents. In this perspective, we discuss the recent advanced fission yeast systems biology tools, mainly focus on metabolomics profiling and metabolic modeling, protein-protein interactome and genetic interaction network, DNA sequencing and applications, and high-throughput phenotypic screening. We therefore hope this review can be useful for interested fungal researchers as well as bioformaticians.

mRNA interactome capture in mammalian cells.

PubMed

Kastelic, Nicolai; Landthaler, Markus

2017-08-15

Throughout their entire life cycle, mRNAs are associated with RNA-binding proteins (RBPs), forming ribonucleoprotein (RNP) complexes with highly dynamic compositions. Their interplay is one key to control gene regulatory mechanisms from mRNA synthesis to decay. To assay the global scope of RNA-protein interactions, we and others have published a method combining crosslinking with highly stringent oligo(dT) affinity purification to enrich proteins associated with polyadenylated RNA (poly(A)+ RNA). Identification of the poly(A)+ RNA-bound proteome (also: mRNA interactome capture) has by now been applied to a diversity of cell lines and model organisms, uncovering comprehensive repertoires of RBPs and hundreds of novel RBP candidates. In addition to determining the RBP catalog in a given biological system, mRNA interactome capture allows the examination of changes in protein-mRNA interactions in response to internal and external stimuli, altered cellular programs and disease. Copyright © 2017. Published by Elsevier Inc.

An in vivo proteomic analysis of the Me31B interactome in Drosophila germ granules.

PubMed

DeHaan, Hunter; McCambridge, Aidan; Armstrong, Brittany; Cruse, Carlie; Solanki, Dhruv; Trinidad, Jonathan C; Arkov, Alexey L; Gao, Ming

2017-11-01

Drosophila Me31B is a conserved protein of germ granules, ribonucleoprotein complexes essential for germ cell development. Me31B post-transcriptionally regulates mRNAs by interacting with other germ granule proteins. However, a Me31B interactome is lacking. Here, we use an in vivo proteomics approach to show that the Me31B interactome contains polypeptides from four functional groups: RNA regulatory proteins, glycolytic enzymes, cytoskeleton/motor proteins, and germ plasm components. We further show that Me31B likely colocalizes with the germ plasm components Tudor (Tud), Vasa, and Aubergine in the nuage and germ plasm and provide evidence that Me31B may directly bind to Tud in a symmetrically dimethylated arginine-dependent manner. Our study supports the role of Me31B in RNA regulation and suggests its novel roles in germ granule assembly and function. © 2017 Federation of European Biochemical Societies.

Serial interactome capture of the human cell nucleus.

PubMed

Conrad, Thomas; Albrecht, Anne-Susann; de Melo Costa, Veronica Rodrigues; Sauer, Sascha; Meierhofer, David; Ørom, Ulf Andersson

2016-04-04

Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present 'serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)-RNA-protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA-RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs.

An "on-matrix" digestion procedure for AP-MS experiments dissects the interplay between complex-conserved and serotype-specific reactivities in Dengue virus-human plasma interactome.

PubMed

Ramos, Yassel; Huerta, Vivian; Martín, Dayron; Palomares, Sucel; Yero, Alexis; Pupo, Dianne; Gallien, Sebastien; Martín, Alejandro M; Pérez-Riverol, Yasset; Sarría, Mónica; Guirola, Osmany; Chinea, Glay; Domon, Bruno; González, Luis Javier

2017-07-13

The interactions between the four Dengue virus (DENV) serotypes and plasma proteins are crucial in the initial steps of viral infection to humans. Affinity purification combined with quantitative mass spectrometry analysis, has become one of the most powerful tools for the investigation on novel protein-protein interactions. Using this approach, we report here that a significant number of bait-interacting proteins do not dissociate under standard elution conditions, i.e. acid pH and chaotropic agents, and that this problem can be circumvented by using the "on-matrix" digestion procedure described here. This procedure enabled the identification of 16 human plasma proteins interacting with domain III from the envelope protein of DENV serotypes 1, 3 and 4 that would have not been detected otherwise and increased the known DIIIE interactors in human plasma to 59 proteins. Selected Reaction Monitoring analysis evidenced DENV interactome in human plasma is rather conserved although significant differences on the reactivity of viral serotypes with specific proteins do exist. A comparison between the serotype-dependent profile of reactivity and the conservation pattern of amino acid residues suggests an evolutionary selection of highly conserved interactions with the host and other interactions mediated for surface regions of higher variability. False negative results on the identification of interacting proteins in pull-down experiments compromise the subsequent interpretation of results and the formulation of a working hypothesis for the derived future work. In this study we demonstrate the presence of bait-interacting proteins reluctant to dissociate under elution conditions of acid pH and presence of chaotropics. We propose the direct proteolytic digestion of proteins while still bound to the affinity matrix ("on-matrix" digestion) and evaluate the impact of this methodology in the comparative study of the interactome of the four serotypes of Dengue virus mediated by the domain III of the viral envelope glycoprotein. Fifty nine proteins were identified as putative interaction partners of Dengue virus (IPs) either due to direct binding or by co-isolation with interacting proteins. Collectively the IPs identified from the pull-down with the recombinant domain III proteins representing the four viral serotypes, 29% were identified only after "on-matrix" digestion which demonstrate the usefulness of this method of recovering bait-bound proteins. Results highlight a particular importance of "on-matrix" digestion procedure for comparative studies where a stronger interaction with one of the interest baits could prevent a bound protein to elute under standard conditions thus leading to misinterpretation as absent in the interactome of this particular bait. The analysis of the Interaction Network indicates that Dengue virus interactome mediated by the domain III of the envelope protein is rather conserved in the viral complex suggesting a key role of these interactions for viral infection thus making candidates to explore for potential biomarkers of clinical outcome in DENV-caused disease. Interestingly, some particular IPs exhibit significant differences in the strength of the interaction with the viral serotypes representing interactions that involve more variable regions in the surface of the domain III. Since such variable regions are the consequence of the interaction with antibodies generated by human immune response; this result relates the interaction with proteins from human plasma with the interplay of the virus and the human immune system. Copyright © 2017 Elsevier B.V. All rights reserved.

Inborn errors of metabolism and the human interactome: a systems medicine approach.

PubMed

Woidy, Mathias; Muntau, Ania C; Gersting, Søren W

2018-02-05

The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.

Schizophrenia interactome with 504 novel protein–protein interactions

PubMed Central

Ganapathiraju, Madhavi K; Thahir, Mohamed; Handen, Adam; Sarkar, Saumendra N; Sweet, Robert A; Nimgaonkar, Vishwajit L; Loscher, Christine E; Bauer, Eileen M; Chaparala, Srilakshmi

2016-01-01

Genome-wide association studies of schizophrenia (GWAS) have revealed the role of rare and common genetic variants, but the functional effects of the risk variants remain to be understood. Protein interactome-based studies can facilitate the study of molecular mechanisms by which the risk genes relate to schizophrenia (SZ) genesis, but protein–protein interactions (PPIs) are unknown for many of the liability genes. We developed a computational model to discover PPIs, which is found to be highly accurate according to computational evaluations and experimental validations of selected PPIs. We present here, 365 novel PPIs of liability genes identified by the SZ Working Group of the Psychiatric Genomics Consortium (PGC). Seventeen genes that had no previously known interactions have 57 novel interactions by our method. Among the new interactors are 19 drug targets that are targeted by 130 drugs. In addition, we computed 147 novel PPIs of 25 candidate genes investigated in the pre-GWAS era. While there is little overlap between the GWAS genes and the pre-GWAS genes, the interactomes reveal that they largely belong to the same pathways, thus reconciling the apparent disparities between the GWAS and prior gene association studies. The interactome including 504 novel PPIs overall, could motivate other systems biology studies and trials with repurposed drugs. The PPIs are made available on a webserver, called Schizo-Pi at http://severus.dbmi.pitt.edu/schizo-pi with advanced search capabilities. PMID:27336055

Interactome of the hepatitis C virus: Literature mining with ANDSystem.

PubMed

Saik, Olga V; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2016-06-15

A study of the molecular genetics mechanisms of host-pathogen interactions is of paramount importance in developing drugs against viral diseases. Currently, the literature contains a huge amount of information that describes interactions between HCV and human proteins. In addition, there are many factual databases that contain experimentally verified data on HCV-host interactions. The sources of such data are the original data along with the data manually extracted from the literature. However, the manual analysis of scientific publications is time consuming and, because of this, databases created with such an approach often do not have complete information. One of the most promising methods to provide actualisation and completeness of information is text mining. Here, with the use of a previously developed method by the authors using ANDSystem, an automated extraction of information on the interactions between HCV and human proteins was conducted. As a data source for the text mining approach, PubMed abstracts and full text articles were used. Additionally, external factual databases were analyzed. On the basis of this analysis, a special version of ANDSystem, extended with the HCV interactome, was created. The HCV interactome contains information about the interactions between 969 human and 11 HCV proteins. Among the 969 proteins, 153 'new' proteins were found not previously referred to in any external databases of protein-protein interactions for HCV-host interactions. Thus, the extended ANDSystem possesses a more comprehensive detailing of HCV-host interactions versus other existing databases. It was interesting that HCV proteins more preferably interact with human proteins that were already involved in a large number of protein-protein interactions as well as those associated with many diseases. Among human proteins of the HCV interactome, there were a large number of proteins regulated by microRNAs. It turned out that the results obtained for protein-protein interactions and microRNA-regulation did not depend on how well the proteins were studied, while protein-disease interactions appeared to be dependent on the level of study. In particular, the mean number of diseases linked to well-studied proteins (proteins were considered well-studied if they were mentioned in 50 or more PubMed publications) from the HCV interactome was 20.8, significantly exceeding the mean number of associations with diseases (10.1) for the total set of well-studied human proteins present in ANDSystem. For proteins not highly poorly-studied investigated, proteins from the HCV interactome (each protein was referred to in less than 50 publications) distribution of the number of diseases associated with them had no statistically significant differences from the distribution of the number of diseases associated with poorly-studied proteins based on the total set of human proteins stored in ANDSystem. With this, the average number of associations with diseases for the HCV interactome and the total set of human proteins were 0.3 and 0.2, respectively. Thus, ANDSystem, extended with the HCV interactome, can be helpful in a wide range of issues related to analyzing HCV-host interactions in the search for anti-HCV drug targets. The demo version of the extended ANDSystem covered here containing only interactions between human proteins, genes, metabolites, diseases, miRNAs and molecular-genetic pathways, as well as interactions between human proteins/genes and HCV proteins, is freely available at the following web address: http://www-bionet.sscc.ru/psd/andhcv/. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

APP is cleaved by Bace1 in pre-synaptic vesicles and establishes a pre-synaptic interactome, via its intracellular domain, with molecular complexes that regulate pre-synaptic vesicles functions.

PubMed

Del Prete, Dolores; Lombino, Franco; Liu, Xinran; D'Adamio, Luciano

2014-01-01

Amyloid Precursor Protein (APP) is a type I membrane protein that undergoes extensive processing by secretases, including BACE1. Although mutations in APP and genes that regulate processing of APP, such as PSENs and BRI2/ITM2B, cause dementias, the normal function of APP in synaptic transmission, synaptic plasticity and memory formation is poorly understood. To grasp the biochemical mechanisms underlying the function of APP in the central nervous system, it is important to first define the sub-cellular localization of APP in synapses and the synaptic interactome of APP. Using biochemical and electron microscopy approaches, we have found that APP is localized in pre-synaptic vesicles, where it is processed by Bace1. By means of a proteomic approach, we have characterized the synaptic interactome of the APP intracellular domain. We focused on this region of APP because in vivo data underline the central functional and pathological role of the intracellular domain of APP. Consistent with the expression of APP in pre-synaptic vesicles, the synaptic APP intracellular domain interactome is predominantly constituted by pre-synaptic, rather than post-synaptic, proteins. This pre-synaptic interactome of the APP intracellular domain includes proteins expressed on pre-synaptic vesicles such as the vesicular SNARE Vamp2/Vamp1 and the Ca2+ sensors Synaptotagmin-1/Synaptotagmin-2, and non-vesicular pre-synaptic proteins that regulate exocytosis, endocytosis and recycling of pre-synaptic vesicles, such as target-membrane-SNAREs (Syntaxin-1b, Syntaxin-1a, Snap25 and Snap47), Munc-18, Nsf, α/β/γ-Snaps and complexin. These data are consistent with a functional role for APP, via its carboxyl-terminal domain, in exocytosis, endocytosis and/or recycling of pre-synaptic vesicles.

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

PubMed

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN.

System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

PubMed Central

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

Transcriptional over-expression of chloride intracellular channels 3 and 4 in malignant pleural mesothelioma.

PubMed

Tasiopoulou, Vasiliki; Magouliotis, Dimitrios; Solenov, Evgeniy I; Vavougios, Georgios; Molyvdas, Paschalis-Adam; Gourgoulianis, Konstantinos I; Hatzoglou, Chrissi; Zarogiannis, Sotirios G

2015-12-01

Chloride Intracellular Channels (CLICs) are contributing to the regulation of multiple cellular functions. CLICs have been found over-expressed in several malignancies, and therefore they are currently considered as potential drug targets. The goal of our study was to assess the gene expression levels of the CLIC's 1-6 in malignant pleural mesothelioma (MPM) as compared to controls. We used gene expression data from a publicly available microarray dataset comparing MPM versus healthy tissue in order to investigate the differential expression profile of CLIC 1-6. False discovery rates were calculated and the interactome of the significantly differentially expressed CLICs was constructed and Functional Enrichment Analysis for Gene Ontologies (FEAGO) was performed. In MPM, the gene expressions of CLIC3 and CLIC4 were significantly increased compared to controls (p=0.001 and p<0.001 respectively). A significant positive correlation between the gene expressions of CLIC3 and CLIC4 (p=0.0008 and Pearson's r=0.51) was found. Deming regression analysis provided an association equation between the CLIC3 and CLIC4 gene expressions: CLIC3=4.42CLIC4-10.07. Our results indicate that CLIC3 and CLIC4 are over-expressed in human MPM. Moreover, their expressions correlate suggesting that they either share common gene expression inducers or that their products act synergistically. FAEGO showed that CLIC interactome might contribute to TGF beta signaling and water transport. Copyright © 2015 Elsevier Ltd. All rights reserved.

A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma

PubMed Central

Sharma, Amitabh; Menche, Jörg; Huang, C. Chris; Ort, Tatiana; Zhou, Xiaobo; Kitsak, Maksim; Sahni, Nidhi; Thibault, Derek; Voung, Linh; Guo, Feng; Ghiassian, Susan Dina; Gulbahce, Natali; Baribaud, Frédéric; Tocker, Joel; Dobrin, Radu; Barnathan, Elliot; Liu, Hao; Panettieri, Reynold A.; Tantisira, Kelan G.; Qiu, Weiliang; Raby, Benjamin A.; Silverman, Edwin K.; Vidal, Marc; Weiss, Scott T.; Barabási, Albert-László

2015-01-01

Recent advances in genetics have spurred rapid progress towards the systematic identification of genes involved in complex diseases. Still, the detailed understanding of the molecular and physiological mechanisms through which these genes affect disease phenotypes remains a major challenge. Here, we identify the asthma disease module, i.e. the local neighborhood of the interactome whose perturbation is associated with asthma, and validate it for functional and pathophysiological relevance, using both computational and experimental approaches. We find that the asthma disease module is enriched with modest GWAS P-values against the background of random variation, and with differentially expressed genes from normal and asthmatic fibroblast cells treated with an asthma-specific drug. The asthma module also contains immune response mechanisms that are shared with other immune-related disease modules. Further, using diverse omics (genomics, gene-expression, drug response) data, we identify the GAB1 signaling pathway as an important novel modulator in asthma. The wiring diagram of the uncovered asthma module suggests a relatively close link between GAB1 and glucocorticoids (GCs), which we experimentally validate, observing an increase in the level of GAB1 after GC treatment in BEAS-2B bronchial epithelial cells. The siRNA knockdown of GAB1 in the BEAS-2B cell line resulted in a decrease in the NFkB level, suggesting a novel regulatory path of the pro-inflammatory factor NFkB by GAB1 in asthma. PMID:25586491

Comparison of Normal and Breast Cancer Cell lines using Proteome, Genome and Interactome data

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

Patwardhan, Anil J.; Strittmatter, Eric F.; Camp, David G.

2005-12-01

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of both protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled the confident identification of 2,235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multi-step search strategy was used to identify post-translational modifications and detected several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal andmore » cancer cell lines.« less

The human cytoplasmic dynein interactome reveals novel activators of motility

PubMed Central

Redwine, William B; DeSantis, Morgan E; Hollyer, Ian; Htet, Zaw Min; Tran, Phuoc Tien; Swanson, Selene K; Florens, Laurence; Washburn, Michael P; Reck-Peterson, Samara L

2017-01-01

In human cells, cytoplasmic dynein-1 is essential for long-distance transport of many cargos, including organelles, RNAs, proteins, and viruses, towards microtubule minus ends. To understand how a single motor achieves cargo specificity, we identified the human dynein interactome by attaching a promiscuous biotin ligase (‘BioID’) to seven components of the dynein machinery, including a subunit of the essential cofactor dynactin. This method reported spatial information about the large cytosolic dynein/dynactin complex in living cells. To achieve maximal motile activity and to bind its cargos, human dynein/dynactin requires ‘activators’, of which only five have been described. We developed methods to identify new activators in our BioID data, and discovered that ninein and ninein-like are a new family of dynein activators. Analysis of the protein interactomes for six activators, including ninein and ninein-like, suggests that each dynein activator has multiple cargos. DOI: http://dx.doi.org/10.7554/eLife.28257.001 PMID:28718761

Identification of the Interactome of a Palmitoylated Membrane Protein, Phosphatidylinositol 4-Kinase Type II Alpha.

PubMed

Gokhale, Avanti; Ryder, Pearl V; Zlatic, Stephanie A; Faundez, Victor

2016-01-01

Phosphatidylinositol 4-kinases (PI4K) are enzymes responsible for the production of phosphatidylinositol 4-phosphates, important intermediates in several cell signaling pathways. PI4KIIα is the most abundant membrane-associated kinase in mammalian cells and is involved in a variety of essential cellular functions. However, the precise role(s) of PI4KIIα in the cell is not yet completely deciphered. Here we present an experimental protocol that uses a chemical cross-linker, DSP, combined with immunoprecipitation and immunoaffinity purification to identify novel PI4KIIα interactors. As predicted, PI4KIIα participates in transient, low-affinity interactions that are stabilized by the use of DSP. Using this optimized protocol we have successfully identified actin cytoskeleton regulators-the WASH complex and RhoGEF1, as major novel interactors of PI4KIIα. While this chapter focuses on the PI4KIIα interactome, this protocol can and has been used to generate other membrane interactome networks.

ZikaBase: An integrated ZIKV- Human Interactome Map database.

PubMed

Gurumayum, Sanathoi; Brahma, Rahul; Naorem, Leimarembi Devi; Muthaiyan, Mathavan; Gopal, Jeyakodi; Venkatesan, Amouda

2018-01-15

Re-emergence of ZIKV has caused infections in more than 1.5 million people. The molecular mechanism and pathogenesis of ZIKV is not well explored due to unavailability of adequate model and lack of publically accessible resources to provide information of ZIKV-Human protein interactome map till today. This study made an attempt to curate the ZIKV-Human interaction proteins from published literatures and RNA-Seq data. 11 direct interaction, 12 associated genes are retrieved from literatures and 3742 Differentially Expressed Genes (DEGs) are obtained from RNA-Seq analysis. The genes have been analyzed to construct the ZIKV-Human Interactome Map. The importance of the study has been illustrated by the enrichment analysis and observed that direct interaction and associated genes are enriched in viral entry into host cell. Also, ZIKV infection modulates 32% signal and 27% immune system pathways. The integrated database, ZikaBase has been developed to help the virology research community and accessible at https://test5.bicpu.edu.in. Copyright © 2017 Elsevier Inc. All rights reserved.

A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human.

PubMed

Vo, Tommy V; Das, Jishnu; Meyer, Michael J; Cordero, Nicolas A; Akturk, Nurten; Wei, Xiaomu; Fair, Benjamin J; Degatano, Andrew G; Fragoza, Robert; Liu, Lisa G; Matsuyama, Akihisa; Trickey, Michelle; Horibata, Sachi; Grimson, Andrew; Yamano, Hiroyuki; Yoshida, Minoru; Roth, Frederick P; Pleiss, Jeffrey A; Xia, Yu; Yu, Haiyuan

2016-01-14

Here, we present FissionNet, a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species. FissionNet unravels previously unreported interactions implicated in processes such as gene silencing and pre-mRNA splicing. We developed a rigorous network comparison framework that accounts for assay sensitivity and specificity, revealing extensive species-specific network rewiring between fission yeast, budding yeast, and human. Surprisingly, although genes are better conserved between the yeasts, S. pombe interactions are significantly better conserved in human than in S. cerevisiae. Our framework also reveals that different modes of gene duplication influence the extent to which paralogous proteins are functionally repurposed. Finally, cross-species interactome mapping demonstrates that coevolution of interacting proteins is remarkably prevalent, a result with important implications for studying human disease in model organisms. Overall, FissionNet is a valuable resource for understanding protein functions and their evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Serum Amyloid P Component (SAP) Interactome in Human Plasma Containing Physiological Calcium Levels.

PubMed

Poulsen, Ebbe Toftgaard; Pedersen, Kata Wolff; Marzeda, Anna Maria; Enghild, Jan J

2017-02-14

The pentraxin serum amyloid P component (SAP) is secreted by the liver and found in plasma at a concentration of approximately 30 mg/L. SAP is a 25 kDa homopentamer known to bind both protein and nonprotein ligands, all in a calcium-dependent manner. The function of SAP is unclear but likely involves the humoral innate immune system spanning the complement system, inflammation, and coagulation. Also, SAP is known to bind to the generic structure of amyloid deposits and possibly to protect them against proteolysis. In this study, we have characterized the SAP interactome in human plasma containing the physiological Ca 2+ concentration using SAP affinity pull-down and co-immunoprecipitation experiments followed by mass spectrometry analyses. The analyses resulted in the identification of 33 proteins, of which 24 were direct or indirect interaction partners not previously reported. The SAP interactome can be divided into categories that include apolipoproteins, the complement system, coagulation, and proteolytic regulation.

Using neighborhood cohesiveness to infer interactions between protein domains.

PubMed

Segura, Joan; Sorzano, C O S; Cuenca-Alba, Jesus; Aloy, Patrick; Carazo, J M

2015-08-01

In recent years, large-scale studies have been undertaken to describe, at least partially, protein-protein interaction maps, or interactomes, for a number of relevant organisms, including human. However, current interactomes provide a somehow limited picture of the molecular details involving protein interactions, mostly because essential experimental information, especially structural data, is lacking. Indeed, the gap between structural and interactomics information is enlarging and thus, for most interactions, key experimental information is missing. We elaborate on the observation that many interactions between proteins involve a pair of their constituent domains and, thus, the knowledge of how protein domains interact adds very significant information to any interactomic analysis. In this work, we describe a novel use of the neighborhood cohesiveness property to infer interactions between protein domains given a protein interaction network. We have shown that some clustering coefficients can be extended to measure a degree of cohesiveness between two sets of nodes within a network. Specifically, we used the meet/min coefficient to measure the proportion of interacting nodes between two sets of nodes and the fraction of common neighbors. This approach extends previous works where homolog coefficients were first defined around network nodes and later around edges. The proposed approach substantially increases both the number of predicted domain-domain interactions as well as its accuracy as compared with current methods. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Interactome analysis of transcriptional coactivator multiprotein bridging factor 1 unveils a yeast AP-1-like transcription factor involved in oxidation tolerance of mycopathogen Beauveria bassiana.

PubMed

Chu, Xin-Ling; Dong, Wei-Xia; Ding, Jin-Li; Feng, Ming-Guang; Ying, Sheng-Hua

2018-02-01

Oxidation tolerance is an important determinant to predict the virulence and biocontrol potential of Beauveria bassiana, a well-known entomopathogenic fungus. As a transcriptional coactivator, multiprotein bridging factor 1 mediates the activity of transcription factor in diverse physiological processes, and its homolog in B. bassiana (BbMBF1) contributes to fungal oxidation tolerance. In this study, the BbMBF1-interactomes under oxidative stress and normal growth condition were deciphered by mass spectrometry integrated with the immunoprecipitation. BbMBF1p factor has a broad interaction with proteins that are involved in various cellular processes, and this interaction is dynamically regulated by oxidative stress. Importantly, a B. bassiana homolog of yeast AP-1-like transcription factor (BbAP-1) was specifically associated with the BbMBF1-interactome under oxidation and significantly contributed to fungal oxidation tolerance. In addition, qPCR analysis revealed that several antioxidant genes are jointly controlled by BbAP-1 and BbMBF1. Conclusively, it is proposed that BbMBF1p protein mediates BbAP-1p factor to transcribe the downstream antioxidant genes in B. bassiana under oxidative stress. This study demonstrates for the first time a proteomic view of the MBF1-interactome in fungi, and presents an initial framework to probe the transcriptional mechanism involved in fungal response to oxidation, which will provide a new strategy to improve the biocontrol efficacy of B. bassiana.

ImmunemiR - A Database of Prioritized Immune miRNA Disease Associations and its Interactome.

PubMed

Prabahar, Archana; Natarajan, Jeyakumar

2017-01-01

MicroRNAs are the key regulators of gene expression and their abnormal expression in the immune system may be associated with several human diseases such as inflammation, cancer and autoimmune diseases. Elucidation of miRNA disease association through the interactome will deepen the understanding of its disease mechanisms. A specialized database for immune miRNAs is highly desirable to demonstrate the immune miRNA disease associations in the interactome. miRNAs specific to immune related diseases were retrieved from curated databases such as HMDD, miR2disease and PubMed literature based on MeSH classification of immune system diseases. The additional data such as miRNA target genes, genes coding protein-protein interaction information were compiled from related resources. Further, miRNAs were prioritized to specific immune diseases using random walk ranking algorithm. In total 245 immune miRNAs associated with 92 OMIM disease categories were identified from external databases. The resultant data were compiled as ImmunemiR, a database of prioritized immune miRNA disease associations. This database provides both text based annotation information and network visualization of its interactome. To our knowledge, ImmunemiR is the first available database to provide a comprehensive repository of human immune disease associated miRNAs with network visualization options of its target genes, protein-protein interactions (PPI) and its disease associations. It is freely available at http://www.biominingbu.org/immunemir/. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Comprehensive Identification of mRNA-Binding Proteins of Leishmania donovani by Interactome Capture.

PubMed

Nandan, Devki; Thomas, Sneha A; Nguyen, Anne; Moon, Kyung-Mee; Foster, Leonard J; Reiner, Neil E

2017-01-01

Leishmania are unicellular eukaryotes responsible for leishmaniasis in humans. Like other trypanosomatids, leishmania regulate protein coding gene expression almost exclusively at the post-transcriptional level with the help of RNA binding proteins (RBPs). Due to the presence of polycystronic transcription units, leishmania do not regulate RNA polymerase II-dependent transcription initiation. Recent evidence suggests that the main control points in gene expression are mRNA degradation and translation. Protein-RNA interactions are involved in every aspect of RNA biology, such as mRNA splicing, polyadenylation, localization, degradation, and translation. A detailed picture of these interactions would likely prove to be highly informative in understanding leishmania biology and virulence. We developed a strategy involving covalent UV cross-linking of RBPs to mRNA in vivo, followed by interactome capture using oligo(dT) magnetic beads to define comprehensively the mRNA interactome of growing L. donovani amastigotes. The protein mass spectrometry analysis of captured proteins identified 79 mRNA interacting proteins which withstood very stringent washing conditions. Strikingly, we found that 49 of these mRNA interacting proteins had no orthologs or homologs in the human genome. Consequently, these may represent high quality candidates for selective drug targeting leading to novel therapeutics. These results show that this unbiased, systematic strategy has the promise to be applicable to study the mRNA interactome during various biological settings such as metabolic changes, stress (low pH environment, oxidative stress and nutrient deprivation) or drug treatment.

A meta-analysis to evaluate the cellular processes regulated by the interactome of endogenous and over-expressed estrogen receptor alpha.

PubMed

Simões, Joana; Amado, Francisco M; Vitorino, Rui; Helguero, Luisa A

2015-01-01

The nature of the proteins complexes that regulate ERα subcellular localization and activity is still an open question in breast cancer biology. Identification of such complexes will help understand development of endocrine resistance in ER+ breast cancer. Mass spectrometry (MS) has allowed comprehensive analysis of the ERα interactome. We have compared six published works analyzing the ERα interactome of MCF-7 and HeLa cells in order to identify a shared or different pathway-related fingerprint. Overall, 806 ERα interacting proteins were identified. The cellular processes were differentially represented according to the ERα purification methodology, indicating that the methodologies used are complementary. While in MCF-7 cells, the interactome of endogenous and over-expressed ERα essentially represents the same biological processes and cellular components, the proteins identified were not over-lapping; thus, suggesting that the biological response may differ as the regulatory/participating proteins in these complexes are different. Interestingly, biological processes uniquely associated to ERα over-expressed in HeLa cell line included L-serine biosynthetic process, cellular amino acid biosynthetic process and cell redox homeostasis. In summary, all the approaches analyzed in this meta-analysis are valid and complementary; in particular, for those cases where the processes occur at low frequency with normal ERα levels, and can be identified when the receptor is over-expressed. However special effort should be put into validating these findings in cells expressing physiological ERα levels.

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: Linking systems biology with vaccine development

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

Adams, Leslie G.; Khare, Sangeeta; Lawhon, Sara D.

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhancedmore » approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic *sipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines.« less

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: linking systems biology with vaccine development.

PubMed

Adams, L Garry; Khare, Sangeeta; Lawhon, Sara D; Rossetti, Carlos A; Lewin, Harris A; Lipton, Mary S; Turse, Joshua E; Wylie, Dennis C; Bai, Yu; Drake, Kenneth L

2011-09-22

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhanced approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host-pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic ΔsipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host-pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host-pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed

Klapa, Maria I; Tsafou, Kalliopi; Theodoridis, Evangelos; Tsakalidis, Athanasios; Moschonas, Nicholas K

2013-10-02

Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. First, we defined the UniProtKB manually reviewed human "complete" proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human "complete" proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms.

Characterization of the Cardiac Overexpression of HSPB2 Reveals Mitochondrial and Myogenic Roles Supported by a Cardiac HspB2 Interactome.

PubMed

Grose, Julianne H; Langston, Kelsey; Wang, Xiaohui; Squires, Shayne; Mustafi, Soumyajit Banerjee; Hayes, Whitney; Neubert, Jonathan; Fischer, Susan K; Fasano, Matthew; Saunders, Gina Moore; Dai, Qiang; Christians, Elisabeth; Lewandowski, E Douglas; Ping, Peipei; Benjamin, Ivor J

2015-01-01

Small Heat Shock Proteins (sHSPs) are molecular chaperones that transiently interact with other proteins, thereby assisting with quality control of proper protein folding and/or degradation. They are also recruited to protect cells from a variety of stresses in response to extreme heat, heavy metals, and oxidative-reductive stress. Although ten human sHSPs have been identified, their likely diverse biological functions remain an enigma in health and disease, and much less is known about non-redundant roles in selective cells and tissues. Herein, we set out to comprehensively characterize the cardiac-restricted Heat Shock Protein B-2 (HspB2), which exhibited ischemic cardioprotection in transgenic overexpressing mice including reduced infarct size and maintenance of ATP levels. Global yeast two-hybrid analysis using HspB2 (bait) and a human cardiac library (prey) coupled with co-immunoprecipitation studies for mitochondrial target validation revealed the first HspB2 "cardiac interactome" to contain many myofibril and mitochondrial-binding partners consistent with the overexpression phenotype. This interactome has been submitted to the Biological General Repository for Interaction Datasets (BioGRID). A related sHSP chaperone HspB5 had only partially overlapping binding partners, supporting specificity of the interactome as well as non-redundant roles reported for these sHSPs. Evidence that the cardiac yeast two-hybrid HspB2 interactome targets resident mitochondrial client proteins is consistent with the role of HspB2 in maintaining ATP levels and suggests new chaperone-dependent functions for metabolic homeostasis. One of the HspB2 targets, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), has reported roles in HspB2 associated phenotypes including cardiac ATP production, mitochondrial function, and apoptosis, and was validated as a potential client protein of HspB2 through chaperone assays. From the clientele and phenotypes identified herein, it is tempting to speculate that small molecule activators of HspB2 might be deployed to mitigate mitochondrial related diseases such as cardiomyopathy and neurodegenerative disease.

The cell-cycle interactome: a source of growth regulators?

PubMed

Blomme, Jonas; Inzé, Dirk; Gonzalez, Nathalie

2014-06-01

When plants develop, cell proliferation and cell expansion are tightly controlled in order to generate organs with a determinate final size such as leaves. Several studies have demonstrated the importance of the cell proliferation phase for leaf growth, illustrating that cell-cycle regulation is crucial for correct leaf development. A large and complex set of interacting proteins that constitute the cell-cycle interactome controls the transition from one cell-cycle phase to another. Here, we review the current knowledge on cell-cycle regulators from this interactome affecting final leaf size when their expression is altered, mainly in Arabidopsis. In addition to the description of mutants of CYCLIN-DEPENDENT KINASES (CDKs), CYCLINS (CYCs), and their transcriptional and post-translational regulators, a phenotypic analysis of gain- and loss-of-function mutants for 27 genes encoding proteins that interact with cell-cycle proteins is presented. This compilation of information shows that when cell-cycle-related genes are mis-expressed, leaf growth is often altered and that, seemingly, three main trends appear to be crucial in the regulation of final organ size by cell-cycle-related genes: (i) cellular compensation; (ii) gene dosage; and (iii) correct transition through the G2/M phase by ANAPHASE PROMOTING COMPLEX/CYCLOSOME (APC/C) activation. In conclusion, this meta-analysis shows that the cell-cycle interactome is enriched in leaf growth regulators, and illustrates the potential to identify new leaf growth regulators among putative new cell-cycle regulators. © The Author 2013. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The Porphyromonas gingivalis/Host Interactome Shows Enrichment in GWASdb Genes Related to Alzheimer's Disease, Diabetes and Cardiovascular Diseases

PubMed Central

Carter, Chris J.; France, James; Crean, StJohn; Singhrao, Sim K.

2017-01-01

Periodontal disease is of established etiology in which polymicrobial synergistic ecology has become dysbiotic under the influence of Porphyromonas gingivalis. Following breakdown of the host's protective oral tissue barriers, P. gingivalis migrates to developing inflammatory pathologies that associate with Alzheimer's disease (AD). Periodontal disease is a risk factor for cardiovascular disorders (CVD), type II diabetes mellitus (T2DM), AD and other chronic diseases, whilst T2DM exacerbates periodontitis. This study analyzed the relationship between the P. gingivalis/host interactome and the genes identified in genome-wide association studies (GWAS) for the aforementioned conditions using data from GWASdb (P < 1E-03) and, in some cases, from the NCBI/EBI GWAS database (P < 1E-05). Gene expression data from periodontitis or P. gingivalis microarray was compared to microarray datasets from the AD hippocampus and/or from carotid artery plaques. The results demonstrated that the host genes of the P. gingivalis interactome were significantly enriched in genes deposited in GWASdb genes related to cognitive disorders, AD and dementia, and its co-morbid conditions T2DM, obesity, and CVD. The P. gingivalis/host interactome was also enriched in GWAS genes from the more stringent NCBI-EBI database for AD, atherosclerosis and T2DM. The misregulated genes in periodontitis tissue or P. gingivalis infected macrophages also matched those in the AD hippocampus or atherosclerotic plaques. Together, these data suggest important gene/environment interactions between P. gingivalis and susceptibility genes or gene expression changes in conditions where periodontal disease is a contributory factor. PMID:29311898

The Porphyromonas gingivalis/Host Interactome Shows Enrichment in GWASdb Genes Related to Alzheimer's Disease, Diabetes and Cardiovascular Diseases.

PubMed

Carter, Chris J; France, James; Crean, StJohn; Singhrao, Sim K

2017-01-01

Periodontal disease is of established etiology in which polymicrobial synergistic ecology has become dysbiotic under the influence of Porphyromonas gingivalis . Following breakdown of the host's protective oral tissue barriers, P. gingivalis migrates to developing inflammatory pathologies that associate with Alzheimer's disease (AD). Periodontal disease is a risk factor for cardiovascular disorders (CVD), type II diabetes mellitus (T2DM), AD and other chronic diseases, whilst T2DM exacerbates periodontitis. This study analyzed the relationship between the P. gingivalis /host interactome and the genes identified in genome-wide association studies (GWAS) for the aforementioned conditions using data from GWASdb ( P < 1E-03) and, in some cases, from the NCBI/EBI GWAS database ( P < 1E-05). Gene expression data from periodontitis or P. gingivalis microarray was compared to microarray datasets from the AD hippocampus and/or from carotid artery plaques. The results demonstrated that the host genes of the P. gingivalis interactome were significantly enriched in genes deposited in GWASdb genes related to cognitive disorders, AD and dementia, and its co-morbid conditions T2DM, obesity, and CVD. The P. gingivalis /host interactome was also enriched in GWAS genes from the more stringent NCBI-EBI database for AD, atherosclerosis and T2DM. The misregulated genes in periodontitis tissue or P. gingivalis infected macrophages also matched those in the AD hippocampus or atherosclerotic plaques. Together, these data suggest important gene/environment interactions between P. gingivalis and susceptibility genes or gene expression changes in conditions where periodontal disease is a contributory factor.

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

PubMed Central

Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A. G.; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. PMID:23696811

Mapping transcription factor interactome networks using HaloTag protein arrays.

PubMed

Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

2016-07-19

Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

Bacterial interactomes: Interacting protein partners share similar function and are validated in independent assays more frequently than previously reported.

DOE PAGES

Shatsky, Maxim; Allen, Simon; Gold, Barbara; ...

2016-05-01

Numerous affinity purification – mass-spectrometry (AP-MS) and yeast two hybrid (Y2H) screens have each defined thousands of pairwise protein-protein interactions (PPIs), most between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial Y2H and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared to the nine published interactomes, our two networks are smaller; are much less highly connected; have significantly lower false discovery rates; and are much moremore » enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays. Lastly, our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.« less

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

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

Klopffleisch, Karsten; Phan, Nguyen; Chen, Jay

2011-01-01

The heterotrimeric G-protein complex is minimally composed of G{alpha}, G{beta}, and G{gamma} subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, wemore » detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.« less

Native KCC2 interactome reveals PACSIN1 as a critical regulator of synaptic inhibition.

PubMed

Mahadevan, Vivek; Khademullah, C Sahara; Dargaei, Zahra; Chevrier, Jonah; Uvarov, Pavel; Kwan, Julian; Bagshaw, Richard D; Pawson, Tony; Emili, Andrew; De Koninck, Yves; Anggono, Victor; Airaksinen, Matti; Woodin, Melanie A

2017-10-13

KCC2 is a neuron-specific K + -Cl - cotransporter essential for establishing the Cl - gradient required for hyperpolarizing inhibition in the central nervous system (CNS). KCC2 is highly localized to excitatory synapses where it regulates spine morphogenesis and AMPA receptor confinement. Aberrant KCC2 function contributes to human neurological disorders including epilepsy and neuropathic pain. Using functional proteomics, we identified the KCC2-interactome in the mouse brain to determine KCC2-protein interactions that regulate KCC2 function. Our analysis revealed that KCC2 interacts with diverse proteins, and its most predominant interactors play important roles in postsynaptic receptor recycling. The most abundant KCC2 interactor is a neuronal endocytic regulatory protein termed PACSIN1 (SYNDAPIN1). We verified the PACSIN1-KCC2 interaction biochemically and demonstrated that shRNA knockdown of PACSIN1 in hippocampal neurons increases KCC2 expression and hyperpolarizes the reversal potential for Cl - . Overall, our global native-KCC2 interactome and subsequent characterization revealed PACSIN1 as a novel and potent negative regulator of KCC2.

Native KCC2 interactome reveals PACSIN1 as a critical regulator of synaptic inhibition

PubMed Central

Mahadevan, Vivek; Chevrier, Jonah; Uvarov, Pavel; Kwan, Julian; Bagshaw, Richard D; Pawson, Tony; Emili, Andrew; De Koninck, Yves; Anggono, Victor; Airaksinen, Matti

2017-01-01

KCC2 is a neuron-specific K+-Cl– cotransporter essential for establishing the Cl- gradient required for hyperpolarizing inhibition in the central nervous system (CNS). KCC2 is highly localized to excitatory synapses where it regulates spine morphogenesis and AMPA receptor confinement. Aberrant KCC2 function contributes to human neurological disorders including epilepsy and neuropathic pain. Using functional proteomics, we identified the KCC2-interactome in the mouse brain to determine KCC2-protein interactions that regulate KCC2 function. Our analysis revealed that KCC2 interacts with diverse proteins, and its most predominant interactors play important roles in postsynaptic receptor recycling. The most abundant KCC2 interactor is a neuronal endocytic regulatory protein termed PACSIN1 (SYNDAPIN1). We verified the PACSIN1-KCC2 interaction biochemically and demonstrated that shRNA knockdown of PACSIN1 in hippocampal neurons increases KCC2 expression and hyperpolarizes the reversal potential for Cl-. Overall, our global native-KCC2 interactome and subsequent characterization revealed PACSIN1 as a novel and potent negative regulator of KCC2. PMID:29028184

The MYO6 interactome reveals adaptor complexes coordinating early endosome and cytoskeletal dynamics.

PubMed

O'Loughlin, Thomas; Masters, Thomas A; Buss, Folma

2018-04-01

The intracellular functions of myosin motors requires a number of adaptor molecules, which control cargo attachment, but also fine-tune motor activity in time and space. These motor-adaptor-cargo interactions are often weak, transient or highly regulated. To overcome these problems, we use a proximity labelling-based proteomics strategy to map the interactome of the unique minus end-directed actin motor MYO6. Detailed biochemical and functional analysis identified several distinct MYO6-adaptor modules including two complexes containing RhoGEFs: the LIFT (LARG-Induced F-actin for Tethering) complex that controls endosome positioning and motility through RHO-driven actin polymerisation; and the DISP (DOCK7-Induced Septin disPlacement) complex, a novel regulator of the septin cytoskeleton. These complexes emphasise the role of MYO6 in coordinating endosome dynamics and cytoskeletal architecture. This study provides the first in vivo interactome of a myosin motor protein and highlights the power of this approach in uncovering dynamic and functionally diverse myosin motor complexes. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis.

PubMed

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-09-27

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

PubMed Central

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-01-01

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification. PMID:21952135

Shifted Transversal Design smart-pooling for high coverage interactome mapping

PubMed Central

Xin, Xiaofeng; Rual, Jean-François; Hirozane-Kishikawa, Tomoko; Hill, David E.; Vidal, Marc; Boone, Charles; Thierry-Mieg, Nicolas

2009-01-01

“Smart-pooling,” in which test reagents are multiplexed in a highly redundant manner, is a promising strategy for achieving high efficiency, sensitivity, and specificity in systems-level projects. However, previous applications relied on low redundancy designs that do not leverage the full potential of smart-pooling, and more powerful theoretical constructions, such as the Shifted Transversal Design (STD), lack experimental validation. Here we evaluate STD smart-pooling in yeast two-hybrid (Y2H) interactome mapping. We employed two STD designs and two established methods to perform ORFeome-wide Y2H screens with 12 baits. We found that STD pooling achieves similar levels of sensitivity and specificity as one-on-one array-based Y2H, while the costs and workloads are divided by three. The screening-sequencing approach is the most cost- and labor-efficient, yet STD identifies about twofold more interactions. Screening-sequencing remains an appropriate method for quickly producing low-coverage interactomes, while STD pooling appears as the method of choice for obtaining maps with higher coverage. PMID:19447967

Exploring the interactome: microfluidic isolation of proteins and interacting partners for quantitative analysis by electron microscopy.

PubMed

Giss, Dominic; Kemmerling, Simon; Dandey, Venkata; Stahlberg, Henning; Braun, Thomas

2014-05-20

Multimolecular protein complexes are important for many cellular processes. However, the stochastic nature of the cellular interactome makes the experimental detection of complex protein assemblies difficult and quantitative analysis at the single molecule level essential. Here, we present a fast and simple microfluidic method for (i) the quantitative isolation of endogenous levels of untagged protein complexes from minute volumes of cell lysates under close to physiological conditions and (ii) the labeling of specific components constituting these complexes. The method presented uses specific antibodies that are conjugated via a photocleavable linker to magnetic beads that are trapped in microcapillaries to immobilize the target proteins. Proteins are released by photocleavage, eluted, and subsequently analyzed by quantitative transmission electron microscopy at the single molecule level. Additionally, before photocleavage, immunogold can be employed to label proteins that interact with the primary target protein. Thus, the presented method provides a new way to study the interactome and, in combination with single molecule transmission electron microscopy, to structurally characterize the large, dynamic, heterogeneous multimolecular protein complexes formed.

Systematic Determination of Human Cyclin Dependent Kinase (CDK)-9 Interactome Identifies Novel Functions in RNA Splicing Mediated by the DEAD Box (DDX)-5/17 RNA Helicases.

PubMed

Yang, Jun; Zhao, Yingxin; Kalita, Mridul; Li, Xueling; Jamaluddin, Mohammad; Tian, Bing; Edeh, Chukwudi B; Wiktorowicz, John E; Kudlicki, Andrzej; Brasier, Allan R

2015-10-01

Inducible transcriptional elongation is a rapid, stereotypic mechanism for activating immediate early immune defense genes by the epithelium in response to viral pathogens. Here, the recruitment of a multifunctional complex containing the cyclin dependent kinase 9 (CDK9) triggers the process of transcriptional elongation activating resting RNA polymerase engaged with innate immune response (IIR) genes. To identify additional functional activity of the CDK9 complex, we conducted immunoprecipitation (IP) enrichment-stable isotope labeling LC-MS/MS of the CDK9 complex in unstimulated cells and from cells activated by a synthetic dsRNA, polyinosinic/polycytidylic acid [poly (I:C)]. 245 CDK9 interacting proteins were identified with high confidence in the basal state and 20 proteins in four functional classes were validated by IP-SRM-MS. These data identified that CDK9 interacts with DDX 5/17, a family of ATP-dependent RNA helicases, important in alternative RNA splicing of NFAT5, and mH2A1 mRNA two proteins controlling redox signaling. A direct comparison of the basal versus activated state was performed using stable isotope labeling and validated by IP-SRM-MS. Recruited into the CDK9 interactome in response to poly(I:C) stimulation are HSPB1, DNA dependent kinases, and cytoskeletal myosin proteins that exchange with 60S ribosomal structural proteins. An integrated human CDK9 interactome map was developed containing all known human CDK9- interacting proteins. These data were used to develop a probabilistic global map of CDK9-dependent target genes that predicted two functional states controlling distinct cellular functions, one important in immune and stress responses. The CDK9-DDX5/17 complex was shown to be functionally important by shRNA-mediated knockdown, where differential accumulation of alternatively spliced NFAT5 and mH2A1 transcripts and alterations in downstream redox signaling were seen. The requirement of CDK9 for DDX5 recruitment to NFAT5 and mH2A1 chromatin target was further demonstrated using chromatin immunoprecipitation (ChIP). These data indicate that CDK9 is a dynamic multifunctional enzyme complex mediating not only transcriptional elongation, but also alternative RNA splicing and potentially translational control. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

The Reactive Species Interactome: Evolutionary Emergence, Biological Significance, and Opportunities for Redox Metabolomics and Personalized Medicine.

PubMed

Cortese-Krott, Miriam M; Koning, Anne; Kuhnle, Gunter G C; Nagy, Peter; Bianco, Christopher L; Pasch, Andreas; Wink, David A; Fukuto, Jon M; Jackson, Alan A; van Goor, Harry; Olson, Kenneth R; Feelisch, Martin

2017-10-01

Oxidative stress is thought to account for aberrant redox homeostasis and contribute to aging and disease. However, more often than not, administration of antioxidants is ineffective, suggesting that our current understanding of the underlying regulatory processes is incomplete. Recent Advances: Similar to reactive oxygen species and reactive nitrogen species, reactive sulfur species are now emerging as important signaling molecules, targeting regulatory cysteine redox switches in proteins, affecting gene regulation, ion transport, intermediary metabolism, and mitochondrial function. To rationalize the complexity of chemical interactions of reactive species with themselves and their targets and help define their role in systemic metabolic control, we here introduce a novel integrative concept defined as the reactive species interactome (RSI). The RSI is a primeval multilevel redox regulatory system whose architecture, together with the physicochemical characteristics of its constituents, allows efficient sensing and rapid adaptation to environmental changes and various other stressors to enhance fitness and resilience at the local and whole-organism level. To better characterize the RSI-related processes that determine fluxes through specific pathways and enable integration, it is necessary to disentangle the chemical biology and activity of reactive species (including precursors and reaction products), their targets, communication systems, and effects on cellular, organ, and whole-organism bioenergetics using system-level/network analyses. Understanding the mechanisms through which the RSI operates will enable a better appreciation of the possibilities to modulate the entire biological system; moreover, unveiling molecular signatures that characterize specific environmental challenges or other forms of stress will provide new prevention/intervention opportunities for personalized medicine. Antioxid. Redox Signal. 00, 000-000.

Approaches for assessing and discovering protein interactions in cancer

PubMed Central

Mohammed, Hisham; Carroll, Jason S.

2013-01-01

Significant insight into the function of proteins, can be delineated by discovering and characterising interacting proteins. There are numerous methods for the discovery of unknown associated protein networks, with purification of the bait (the protein of interest) followed by Mass Spectrometry (MS) as a common theme. In recent years, advances have permitted the purification of endogenous proteins and methods for scaling down starting material. As such, approaches for rapid, unbiased identification of protein interactomes are becoming a standard tool in the researchers toolbox, rather than a technique that is only available to specialists. This review will highlight some of the recent technical advances in proteomic based discovery approaches, the pros and cons of various methods and some of the key findings in cancer related systems. PMID:24072816

Protein Interactome of Muscle Invasive Bladder Cancer

PubMed Central

Bhat, Akshay; Heinzel, Andreas; Mayer, Bernd; Perco, Paul; Mühlberger, Irmgard; Husi, Holger; Merseburger, Axel S.; Zoidakis, Jerome; Vlahou, Antonia; Schanstra, Joost P.; Mischak, Harald; Jankowski, Vera

2015-01-01

Muscle invasive bladder carcinoma is a complex, multifactorial disease caused by disruptions and alterations of several molecular pathways that result in heterogeneous phenotypes and variable disease outcome. Combining this disparate knowledge may offer insights for deciphering relevant molecular processes regarding targeted therapeutic approaches guided by molecular signatures allowing improved phenotype profiling. The aim of the study is to characterize muscle invasive bladder carcinoma on a molecular level by incorporating scientific literature screening and signatures from omics profiling. Public domain omics signatures together with molecular features associated with muscle invasive bladder cancer were derived from literature mining to provide 286 unique protein-coding genes. These were integrated in a protein-interaction network to obtain a molecular functional map of the phenotype. This feature map educated on three novel disease-associated pathways with plausible involvement in bladder cancer, namely Regulation of actin cytoskeleton, Neurotrophin signalling pathway and Endocytosis. Systematic integration approaches allow to study the molecular context of individual features reported as associated with a clinical phenotype and could potentially help to improve the molecular mechanistic description of the disorder. PMID:25569276

Small Molecule Interactome Mapping by Photoaffinity Labeling Reveals Binding Site Hotspots for the NSAIDs.

PubMed

Gao, Jinxu; Mfuh, Adelphe; Amako, Yuka; Woo, Christina M

2018-03-28

Many therapeutics elicit cell-type specific polypharmacology that is executed by a network of molecular recognition events between a small molecule and the whole proteome. However, measurement of the structures that underpin the molecular associations between the proteome and even common therapeutics, such as the nonsteroidal anti-inflammatory drugs (NSAIDs), is limited by the inability to map the small molecule interactome. To address this gap, we developed a platform termed small molecule interactome mapping by photoaffinity labeling (SIM-PAL) and applied it to the in cellulo direct characterization of specific NSAID binding sites. SIM-PAL uses (1) photochemical conjugation of NSAID derivatives in the whole proteome and (2) enrichment and isotope-recoding of the conjugated peptides for (3) targeted mass spectrometry-based assignment. Using SIM-PAL, we identified the NSAID interactome consisting of over 1000 significantly enriched proteins and directly characterized nearly 200 conjugated peptides representing direct binding sites of the photo-NSAIDs with proteins from Jurkat and K562 cells. The enriched proteins were often identified as parts of complexes, including known targets of NSAID activity (e.g., NF-κB) and novel interactions (e.g., AP-2, proteasome). The conjugated peptides revealed direct NSAID binding sites from the cell surface to the nucleus and a specific binding site hotspot for the three photo-NSAIDs on histones H2A and H2B. NSAID binding stabilized COX-2 and histone H2A by cellular thermal shift assay. Since small molecule stabilization of protein complexes is a gain of function regulatory mechanism, it is conceivable that NSAIDs affect biological processes through these broader proteomic interactions. SIM-PAL enabled characterization of NSAID binding site hotspots and is amenable to map global binding sites for virtually any molecule of interest.

Lubricin: A Principal Modulator of the Psychoneuroendocrine - Osteoimmune Interactome - Implications for Novel Treatments of Osteoarthritic Pathologies.

PubMed

Khakshooy, Allen; Balenton, Nicole; Chiappelli, Francesco

2017-01-01

Lubricin is a synovial glycoprotein that contributes to joint lubrication. We propose the hypothesis that lubricin is a key modulator of the psychoneuroendocrine-osteoimmune interactome, with important clinical relevance for osteoarthritic pathologies. We consider a variety of neuroendocrine-immune factors, including inflammatory cytokines and chemokines that may contribute to the modulation of lubricin in rheumatic complications. Based on our preliminary immunocytochemistry and fractal analysis data, and in the context of translational research of modern healthcare, we propose that molecular lubricin gene expression modification by means of the novel CRISPR/Cas system be considered for osteoarthritic therapies.

A human XPC protein interactome--a resource.

PubMed

Lubin, Abigail; Zhang, Ling; Chen, Hua; White, Victoria M; Gong, Feng

2013-12-23

Global genome nucleotide excision repair (GG-NER) is responsible for identifying and removing bulky adducts from non-transcribed DNA that result from damaging agents such as UV radiation and cisplatin. Xeroderma pigmentosum complementation group C (XPC) is one of the essential damage recognition proteins of the GG-NER pathway and its dysfunction results in xeroderma pigmentosum (XP), a disorder involving photosensitivity and a predisposition to cancer. To better understand the identification of DNA damage by XPC in the context of chromatin and the role of XPC in the pathogenesis of XP, we characterized the interactome of XPC using a high throughput yeast two-hybrid screening. Our screening showed 49 novel interactors of XPC involved in DNA repair and replication, proteolysis and post-translational modifications, transcription regulation, signal transduction, and metabolism. Importantly, we validated the XPC-OTUD4 interaction by co-IP and provided evidence that OTUD4 knockdown in human cells indeed affects the levels of ubiquitinated XPC, supporting a hypothesis that the OTUD4 deubiquitinase is involved in XPC recycling by cleaving the ubiquitin moiety. This high-throughput characterization of the XPC interactome provides a resource for future exploration and suggests that XPC may have many uncharacterized cellular functions.

PodNet, a protein-protein interaction network of the podocyte.

PubMed

Warsow, Gregor; Endlich, Nicole; Schordan, Eric; Schordan, Sandra; Chilukoti, Ravi K; Homuth, Georg; Moeller, Marcus J; Fuellen, Georg; Endlich, Karlhans

2013-07-01

Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

The extraction of drug-disease correlations based on module distance in incomplete human interactome.

PubMed

Yu, Liang; Wang, Bingbo; Ma, Xiaoke; Gao, Lin

2016-12-23

Extracting drug-disease correlations is crucial in unveiling disease mechanisms, as well as discovering new indications of available drugs, or drug repositioning. Both the interactome and the knowledge of disease-associated and drug-associated genes remain incomplete. We present a new method to predict the associations between drugs and diseases. Our method is based on a module distance, which is originally proposed to calculate distances between modules in incomplete human interactome. We first map all the disease genes and drug genes to a combined protein interaction network. Then based on the module distance, we calculate the distances between drug gene sets and disease gene sets, and take the distances as the relationships of drug-disease pairs. We also filter possible false positive drug-disease correlations by p-value. Finally, we validate the top-100 drug-disease associations related to six drugs in the predicted results. The overlapping between our predicted correlations with those reported in Comparative Toxicogenomics Database (CTD) and literatures, and their enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways demonstrate our approach can not only effectively identify new drug indications, but also provide new insight into drug-disease discovery.

Functional Proteomics Identifies Acinus L as a Direct Insulin- and Amino Acid-Dependent Mammalian Target of Rapamycin Complex 1 (mTORC1) Substrate*

PubMed Central

Schwarz, Jennifer Jasmin; Wiese, Heike; Tölle, Regine Charlotte; Zarei, Mostafa; Dengjel, Jörn; Warscheid, Bettina; Thedieck, Kathrin

2015-01-01

The serine/threonine kinase mammalian target of rapamycin (mTOR) governs growth, metabolism, and aging in response to insulin and amino acids (aa), and is often activated in metabolic disorders and cancer. Much is known about the regulatory signaling network that encompasses mTOR, but surprisingly few direct mTOR substrates have been established to date. To tackle this gap in our knowledge, we took advantage of a combined quantitative phosphoproteomic and interactomic strategy. We analyzed the insulin- and aa-responsive phosphoproteome upon inhibition of the mTOR complex 1 (mTORC1) component raptor, and investigated in parallel the interactome of endogenous mTOR. By overlaying these two datasets, we identified acinus L as a potential novel mTORC1 target. We confirmed acinus L as a direct mTORC1 substrate by co-immunoprecipitation and MS-enhanced kinase assays. Our study delineates a triple proteomics strategy of combined phosphoproteomics, interactomics, and MS-enhanced kinase assays for the de novo-identification of mTOR network components, and provides a rich source of potential novel mTOR interactors and targets for future investigation. PMID:25907765

Epigenetic Drug Repositioning for Alzheimer's Disease Based on Epigenetic Targets in Human Interactome.

PubMed

Chatterjee, Paulami; Roy, Debjani; Rathi, Nitin

2018-01-01

Epigenetics has emerged as an important field in drug discovery. Alzheimer's disease (AD), the leading neurodegenerative disorder throughout the world, is shown to have an epigenetic basis. Currently, there are very few effective epigenetic drugs available for AD. In this work, for the first time we have proposed 14 AD repositioning epigenetic drugs and identified their targets from extensive human interactome. Interacting partners of the AD epigenetic proteins were identified from the extensive human interactome to construct Epigenetic Protein-Protein Interaction Network (EP-PPIN). Epigenetic Drug-Target Network (EP-DTN) was constructed with the drugs associated with the proteins of EP-PPIN. Regulation of non-coding RNAs associated with the target proteins of these drugs was also studied. AD related target proteins, epigenetic targets, enriched pathways, and functional categories of the proposed repositioning drugs were also studied. The proposed 14 AD epigenetic repositioning drugs have overlapping targets and miRs with known AD epigenetic targets and miRs. Furthermore, several shared functional categories and enriched pathways were obtained for these drugs with FDA approved epigenetic drugs and known AD drugs. The findings of our work might provide insight into future AD epigenetic-therapeutics.

Mass Spectrometry-Based Screening Platform Reveals Orco Interactome in Drosophila melanogaster.

PubMed

Yu, Kate E; Kim, Do-Hyoung; Kim, Yong-In; Jones, Walton D; Lee, J Eugene

2018-02-28

Animals use their odorant receptors to receive chemical information from the environment. Insect odorant receptors differ from the G protein-coupled odorant receptors in vertebrates and nematodes, and very little is known about their protein-protein interactions. Here, we introduce a mass spectrometric platform designed for the large-scale analysis of insect odorant receptor protein-protein interactions. Using this platform, we obtained the first Orco interactome from Drosophila melanogaster . From a total of 1,186 identified proteins, we narrowed the interaction candidates to 226, of which only two-thirds have been named. These candidates include the known olfactory proteins Or92a and Obp51a. Around 90% of the proteins having published names likely function inside the cell, and nearly half of these intracellular proteins are associated with the endomembrane system. In a basic loss-of-function electrophysiological screen, we found that the disruption of eight (i.e., Rab5, CG32795, Mpcp, Tom70, Vir-1, CG30427, Eaat1, and CG2781) of 28 randomly selected candidates affects olfactory responses in vivo . Thus, because this Orco interactome includes physiologically meaningful candidates, we anticipate that our platform will help guide further research on the molecular mechanisms of the insect odorant receptor family.

High-throughput proteomics : optical approaches.

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

Davidson, George S.

2008-09-01

Realistic cell models could greatly accelerate our ability to engineer biochemical pathways and the production of valuable organic products, which would be of great use in the development of biofuels, pharmaceuticals, and the crops for the next green revolution. However, this level of engineering will require a great deal more knowledge about the mechanisms of life than is currently available. In particular, we need to understand the interactome (which proteins interact) as it is situated in the three dimensional geometry of the cell (i.e., a situated interactome), and the regulation/dynamics of these interactions. Methods for optical proteomics have become availablemore » that allow the monitoring and even disruption/control of interacting proteins in living cells. Here, a range of these methods is reviewed with respect to their role in elucidating the interactome and the relevant spatial localizations. Development of these technologies and their integration into the core competencies of research organizations can position whole institutions and teams of researchers to lead in both the fundamental science and the engineering applications of cellular biology. That leadership could be particularly important with respect to problems of national urgency centered around security, biofuels, and healthcare.« less

Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

PubMed Central

2011-01-01

Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

How perfect can protein interactomes be?

PubMed

Levy, Emmanuel D; Landry, Christian R; Michnick, Stephen W

2009-03-03

Any engineered device should certainly not contain nonfunctional components, for this would be a waste of energy and money. In contrast, evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with "junk" DNA and spurious DNA binding sites. Here, we question whether such a notion should be applied to protein interactomes-that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions (PPIs), which we term "noisy." We propose a simple relationship between the fraction of noisy interactions expected in a given organism and three parameters: (i) the number of mutations needed to create and destroy interactions, (ii) the size of the proteome, and (iii) the fitness cost of noisy interactions. All three parameters suggest that noisy PPIs are expected to exist. Their existence could help to explain why PPIs determined from large-scale studies often lack functional relationships between interacting proteins, why PPIs are poorly conserved across organisms, and why the PPI space appears to be immensely large. Finally, we propose experimental strategies to estimate the fraction of evolutionary noise in PPI networks.

Interactome Mapping Guided by Tissue-Specific Phosphorylation in Age-Related Macular Degeneration

PubMed Central

Sripathi, Srinivas R.; He, Weilue; Prigge, Cameron L.; Sylvester, O’Donnell; Um, Ji-Yeon; Powell, Folami L.; Neksumi, Musa; Bernstein, Paul S.; Choo, Dong-Won; Bartoli, Manuela; Gutsaeva, Diana R.; Jahng, Wan Jin

2017-01-01

The current study aims to determine the molecular mechanisms of age-related macular degeneration (AMD) using the phosphorylation network. Specifically, we examined novel biomarkers for oxidative stress by protein interaction mapping using in vitro and in vivo models that mimic the complex and progressive characteristics of AMD. We hypothesized that the early apoptotic reactions could be initiated by protein phosphorylation in region-dependent (peripheral retina vs. macular) and tissue-dependent (retinal pigment epithelium vs. retina) manner under chronic oxidative stress. The analysis of protein interactome and oxidative biomarkers showed the presence of tissue- and region-specific post-translational mechanisms that contribute to AMD progression and suggested new therapeutic targets that include ubiquitin, erythropoietin, vitronectin, MMP2, crystalline, nitric oxide, and prohibitin. Phosphorylation of specific target proteins in RPE cells is a central regulatory mechanism as a survival tool under chronic oxidative imbalance. The current interactome map demonstrates a positive correlation between oxidative stress-mediated phosphorylation and AMD progression and provides a basis for understanding oxidative stress-induced cytoskeletal changes and the mechanism of aggregate formation induced by protein phosphorylation. This information could provide an effective therapeutic approach to treat age-related neurodegeneration. PMID:28580316

Interactome Mapping Guided by Tissue-Specific Phosphorylation in Age-Related Macular Degeneration.

PubMed

Sripathi, Srinivas R; He, Weilue; Prigge, Cameron L; Sylvester, O'Donnell; Um, Ji-Yeon; Powell, Folami L; Neksumi, Musa; Bernstein, Paul S; Choo, Dong-Won; Bartoli, Manuela; Gutsaeva, Diana R; Jahng, Wan Jin

2017-02-01

The current study aims to determine the molecular mechanisms of age-related macular degeneration (AMD) using the phosphorylation network. Specifically, we examined novel biomarkers for oxidative stress by protein interaction mapping using in vitro and in vivo models that mimic the complex and progressive characteristics of AMD. We hypothesized that the early apoptotic reactions could be initiated by protein phosphorylation in region-dependent (peripheral retina vs. macular) and tissue-dependent (retinal pigment epithelium vs. retina) manner under chronic oxidative stress. The analysis of protein interactome and oxidative biomarkers showed the presence of tissue- and region-specific post-translational mechanisms that contribute to AMD progression and suggested new therapeutic targets that include ubiquitin, erythropoietin, vitronectin, MMP2, crystalline, nitric oxide, and prohibitin. Phosphorylation of specific target proteins in RPE cells is a central regulatory mechanism as a survival tool under chronic oxidative imbalance. The current interactome map demonstrates a positive correlation between oxidative stress-mediated phosphorylation and AMD progression and provides a basis for understanding oxidative stress-induced cytoskeletal changes and the mechanism of aggregate formation induced by protein phosphorylation. This information could provide an effective therapeutic approach to treat age-related neurodegeneration.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed Central

2013-01-01

Background Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. Results First, we defined the UniProtKB manually reviewed human “complete” proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Conclusions Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human “complete” proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms. PMID:24088582

Interactome Analysis of NS1 Protein Encoded by Influenza A H7N9 Virus Reveals an Inhibitory Role of NS1 in Host mRNA Maturation.

PubMed

Kuo, Rei-Lin; Chen, Chi-Jene; Tam, Ee-Hong; Huang, Chung-Guei; Li, Li-Hsin; Li, Zong-Hua; Su, Pei-Chia; Liu, Hao-Ping; Wu, Chih-Ching

2018-04-06

Influenza A virus infections can result in severe respiratory diseases. The H7N9 subtype of avian influenza A virus has been transmitted to humans and caused severe disease and death. Nonstructural protein 1 (NS1) of influenza A virus is a virulence determinant during viral infection. To elucidate the functions of the NS1 encoded by influenza A H7N9 virus (H7N9 NS1), interaction partners of H7N9 NS1 in human cells were identified with immunoprecipitation followed by SDS-PAGE coupled with liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). We identified 36 cellular proteins as the interacting partners of the H7N9 NS1, and they are involved in RNA processing, mRNA splicing via spliceosome, and the mRNA surveillance pathway. Two of the interacting partners, cleavage and polyadenylation specificity factor subunit 2 (CPSF2) and CPSF7, were confirmed to interact with H7N9 NS1 using coimmunoprecipitation and immunoblotting based on the previous finding that the two proteins are involved in pre-mRNA polyadenylation machinery. Furthermore, we illustrate that overexpression of H7N9 NS1, as well as infection by the influenza A H7N9 virus, interfered with pre-mRNA polyadenylation in host cells. This study comprehensively profiled the interactome of H7N9 NS1 in host cells, and the results demonstrate a novel endotype for H7N9 NS1 in inhibiting host mRNA maturation.

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

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

Uehara, Takeki, E-mail: takeki.uehara@shionogi.co.jp; Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085; Minowa, Yohsuke

2011-09-15

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificitymore » in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: >We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. >The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. >This model enables us to detect genotoxic as well as non-genotoxic hepatocarcinogens.« less

When the human viral infectome and diseasome networks collide: towards a systems biology platform for the aetiology of human diseases

PubMed Central

2011-01-01

Background Comprehensive understanding of molecular mechanisms underlying viral infection is a major challenge towards the discovery of new antiviral drugs and susceptibility factors of human diseases. New advances in the field are expected from systems-level modelling and integration of the incessant torrent of high-throughput "-omics" data. Results Here, we describe the Human Infectome protein interaction Network, a novel systems virology model of a virtual virus-infected human cell concerning 110 viruses. This in silico model was applied to comprehensively explore the molecular relationships between viruses and their associated diseases. This was done by merging virus-host and host-host physical protein-protein interactomes with the set of genes essential for viral replication and involved in human genetic diseases. This systems-level approach provides strong evidence that viral proteomes target a wide range of functional and inter-connected modules of proteins as well as highly central and bridging proteins within the human interactome. The high centrality of targeted proteins was correlated to their essentiality for viruses' lifecycle, using functional genomic RNAi data. A stealth-attack of viruses on proteins bridging cellular functions was demonstrated by simulation of cellular network perturbations, a property that could be essential in the molecular aetiology of some human diseases. Networking the Human Infectome and Diseasome unravels the connectivity of viruses to a wide range of diseases and profiled molecular basis of Hepatitis C Virus-induced diseases as well as 38 new candidate genetic predisposition factors involved in type 1 diabetes mellitus. Conclusions The Human Infectome and Diseasome Networks described here provide a unique gateway towards the comprehensive modelling and analysis of the systems level properties associated to viral infection as well as candidate genes potentially involved in the molecular aetiology of human diseases. PMID:21255393

The Reactive Species Interactome: Evolutionary Emergence, Biological Significance, and Opportunities for Redox Metabolomics and Personalized Medicine

PubMed Central

Koning, Anne; Kuhnle, Gunter G.C.; Nagy, Peter; Bianco, Christopher L.; Pasch, Andreas; Wink, David A.; Fukuto, Jon M.; Jackson, Alan A.; van Goor, Harry; Olson, Kenneth R.

2017-01-01

Abstract Significance: Oxidative stress is thought to account for aberrant redox homeostasis and contribute to aging and disease. However, more often than not, administration of antioxidants is ineffective, suggesting that our current understanding of the underlying regulatory processes is incomplete. Recent Advances: Similar to reactive oxygen species and reactive nitrogen species, reactive sulfur species are now emerging as important signaling molecules, targeting regulatory cysteine redox switches in proteins, affecting gene regulation, ion transport, intermediary metabolism, and mitochondrial function. To rationalize the complexity of chemical interactions of reactive species with themselves and their targets and help define their role in systemic metabolic control, we here introduce a novel integrative concept defined as the reactive species interactome (RSI). The RSI is a primeval multilevel redox regulatory system whose architecture, together with the physicochemical characteristics of its constituents, allows efficient sensing and rapid adaptation to environmental changes and various other stressors to enhance fitness and resilience at the local and whole-organism level. Critical Issues: To better characterize the RSI-related processes that determine fluxes through specific pathways and enable integration, it is necessary to disentangle the chemical biology and activity of reactive species (including precursors and reaction products), their targets, communication systems, and effects on cellular, organ, and whole-organism bioenergetics using system-level/network analyses. Future Directions: Understanding the mechanisms through which the RSI operates will enable a better appreciation of the possibilities to modulate the entire biological system; moreover, unveiling molecular signatures that characterize specific environmental challenges or other forms of stress will provide new prevention/intervention opportunities for personalized medicine. Antioxid. Redox Signal. 27, 684–712. PMID:28398072

Recent Progress in CFTR Interactome Mapping and Its Importance for Cystic Fibrosis.

PubMed

Lim, Sang Hyun; Legere, Elizabeth-Ann; Snider, Jamie; Stagljar, Igor

2017-01-01

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride channel found in secretory epithelia with a plethora of known interacting proteins. Mutations in the CFTR gene cause cystic fibrosis (CF), a disease that leads to progressive respiratory illness and other complications of phenotypic variance resulting from perturbations of this protein interaction network. Studying the collection of CFTR interacting proteins and the differences between the interactomes of mutant and wild type CFTR provides insight into the molecular machinery of the disease and highlights possible therapeutic targets. This mini review focuses on functional genomics and proteomics approaches used for systematic, high-throughput identification of CFTR-interacting proteins to provide comprehensive insight into CFTR regulation and function.

RNA interactome capture in yeast.

PubMed

Beckmann, Benedikt M

2017-04-15

RNA-binding proteins (RBPs) are key players in post-transcriptional regulation of gene expression in eukaryotic cells. To be able to unbiasedly identify RBPs in Saccharomyces cerevisiae, we developed a yeast RNA interactome capture protocol which employs RNA labeling, covalent UV crosslinking of RNA and proteins at 365nm wavelength (photoactivatable-ribonucleoside-enhanced crosslinking, PAR-CL) and finally purification of the protein-bound mRNA. The method can be easily implemented in common workflows and takes about 3days to complete. Next to a comprehensive explanation of the method, we focus on our findings about the choice of crosslinking in yeast and discuss the rationale of individual steps in the protocol. Copyright © 2016. Published by Elsevier Inc.

Interactome Analyses of Mature γ-Secretase Complexes Reveal Distinct Molecular Environments of Presenilin (PS) Paralogs and Preferential Binding of Signal Peptide Peptidase to PS2*

PubMed Central

Jeon, Amy Hye Won; Böhm, Christopher; Chen, Fusheng; Huo, Hairu; Ruan, Xueying; Ren, Carl He; Ho, Keith; Qamar, Seema; Mathews, Paul M.; Fraser, Paul E.; Mount, Howard T. J.; St George-Hyslop, Peter; Schmitt-Ulms, Gerold

2013-01-01

γ-Secretase plays a pivotal role in the production of neurotoxic amyloid β-peptides (Aβ) in Alzheimer disease (AD) and consists of a heterotetrameric core complex that includes the aspartyl intramembrane protease presenilin (PS). The human genome codes for two presenilin paralogs. To understand the causes for distinct phenotypes of PS paralog-deficient mice and elucidate whether PS mutations associated with early-onset AD affect the molecular environment of mature γ-secretase complexes, quantitative interactome comparisons were undertaken. Brains of mice engineered to express wild-type or mutant PS1, or HEK293 cells stably expressing PS paralogs with N-terminal tandem-affinity purification tags served as biological source materials. The analyses revealed novel interactions of the γ-secretase core complex with a molecular machinery that targets and fuses synaptic vesicles to cellular membranes and with the H+-transporting lysosomal ATPase macrocomplex but uncovered no differences in the interactomes of wild-type and mutant PS1. The catenin/cadherin network was almost exclusively found associated with PS1. Another intramembrane protease, signal peptide peptidase, predominantly co-purified with PS2-containing γ-secretase complexes and was observed to influence Aβ production. PMID:23589300

Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders.

PubMed

Carter, C J

2013-01-01

Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E - 05  (ADHD)  to  1.22E - 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself.

Large-scale De Novo Prediction of Physical Protein-Protein Association*

PubMed Central

Elefsinioti, Antigoni; Saraç, Ömer Sinan; Hegele, Anna; Plake, Conrad; Hubner, Nina C.; Poser, Ina; Sarov, Mihail; Hyman, Anthony; Mann, Matthias; Schroeder, Michael; Stelzl, Ulrich; Beyer, Andreas

2011-01-01

Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org. PMID:21836163

The Sharpin interactome reveals a role for Sharpin in lamellipodium formation via the Arp2/3 complex.

PubMed

Khan, Meraj H; Salomaa, Siiri I; Jacquemet, Guillaume; Butt, Umar; Miihkinen, Mitro; Deguchi, Takahiro; Kremneva, Elena; Lappalainen, Pekka; Humphries, Martin J; Pouwels, Jeroen

2017-09-15

Sharpin, a multifunctional adaptor protein, regulates several signalling pathways. For example, Sharpin enhances signal-induced NF-κB signalling as part of the linear ubiquitin assembly complex (LUBAC) and inhibits integrins, the T cell receptor, caspase 1 and PTEN. However, despite recent insights into Sharpin and LUBAC function, a systematic approach to identify the signalling pathways regulated by Sharpin has not been reported. Here, we present the first 'Sharpin interactome', which identifies a large number of novel potential Sharpin interactors in addition to several known ones. These data suggest that Sharpin and LUBAC might regulate a larger number of biological processes than previously identified, such as endosomal trafficking, RNA processing, metabolism and cytoskeleton regulation. Importantly, using the Sharpin interactome, we have identified a novel role for Sharpin in lamellipodium formation. We demonstrate that Sharpin interacts with Arp2/3, a protein complex that catalyses actin filament branching. We have identified the Arp2/3-binding site in Sharpin and demonstrate using a specific Arp2/3-binding deficient mutant that the Sharpin-Arp2/3 interaction promotes lamellipodium formation in a LUBAC-independent fashion.This article has an associated First Person interview with the first author of the paper. © 2017. Published by The Company of Biologists Ltd.

Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

PubMed

Romero-Durán, Francisco J; Alonso, Nerea; Yañez, Matilde; Caamaño, Olga; García-Mera, Xerardo; González-Díaz, Humberto

2016-04-01

The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. These compounds form large multi-target complex networks (drug-target interactome network) resulting in a very challenging data analysis problem. Artificial Neural Network (ANN) algorithms may help us predict the interactions of drugs and targets in CNS interactome. In this work, we trained different ANN models able to predict a large number of drug-target interactions. These models predict a dataset of thousands of interactions of central nervous system (CNS) drugs characterized by > 30 different experimental measures in >400 different experimental protocols for >150 molecular and cellular targets present in 11 different organisms (including human). The model was able to classify cases of non-interacting vs. interacting drug-target pairs with satisfactory performance. A second aim focus on two main directions: the synthesis and assay of new derivatives of TVP1022 (S-analogues of rasagiline) and the comparison with other rasagiline derivatives recently reported. Finally, we used the best of our models to predict drug-target interactions for the best new synthesized compound against a large number of CNS protein targets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization of the zinc-induced Shank3 interactome of mouse synaptosome.

PubMed

Lee, Yeunkum; Ryu, Jae Ryun; Kang, Hyojin; Kim, Yoonhee; Kim, Shinhyun; Zhang, Yinhua; Jin, Chunmei; Cho, Hyo Min; Kim, Won-Ki; Sun, Woong; Han, Kihoon

2017-12-16

Variants of the SHANK3 gene, which encodes a core scaffold protein of the postsynaptic density of excitatory synapses, have been causally associated with numerous brain disorders. Shank3 proteins directly bind zinc ions through their C-terminal sterile α motif domain, which enhances the multimerization and synaptic localization of Shank3, to regulate excitatory synaptic strength. However, no studies have explored whether zinc affects the protein interactions of Shank3, which might contribute to the synaptic changes observed after zinc application. To examine this, we first purified Shank3 protein complexes from mouse brain synaptosomal lysates that were incubated with different concentrations of ZnCl 2 , and analyzed them with mass spectrometry. We used strict criteria to identify 71 proteins that specifically interacted with Shank3 when extra ZnCl 2 was added to the lysate. To characterize the zinc-induced Shank3 interactome, we performed various bioinformatic analyses that revealed significant associations of the interactome with subcellular compartments, including mitochondria, and brain disorders, such as bipolar disorder and schizophrenia. Together, our results showing that zinc affected the Shank3 protein interactions of in vitro mouse synaptosomes provided an additional link between zinc and core synaptic proteins that have been implicated in multiple brain disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

PubMed Central

Rohira, Harsha; Bhat, Ashwini G.; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; S, Gayathri; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; J, Balaganesh; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N.; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K.; Bhardwaj, Anshu

2012-01-01

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach. PMID:22808064

HIV–host interactome revealed directly from infected cells

PubMed Central

Luo, Yang; Jacobs, Erica Y.; Greco, Todd M.; Mohammed, Kevin D.; Tong, Tommy; Keegan, Sarah; Binley, James M.; Cristea, Ileana M.; Fenyö, David; Rout, Michael P.; Chait, Brian T.; Muesing, Mark A.

2016-01-01

Although genetically compact, HIV-1 commandeers vast arrays of cellular machinery to sustain and protect it during cycles of viral outgrowth. Transposon-mediated saturation linker scanning mutagenesis was used to isolate fully replication-competent viruses harbouring a potent foreign epitope tag. Using these viral isolates, we performed differential isotopic labelling and affinity-capture mass spectrometric analyses on samples obtained from cultures of human lymphocytes to classify the vicinal interactomes of the viral Env and Vif proteins as they occur during natural infection. Importantly, interacting proteins were recovered without bias, regardless of their potential for positive, negative or neutral impact on viral replication. We identified specific host associations made with trimerized Env during its biosynthesis, at virological synapses, with innate immune effectors (such as HLA-E) and with certain cellular signalling pathways (for example, Notch1). We also defined Vif associations with host proteins involved in the control of nuclear transcription and nucleoside biosynthesis as well as those interacting stably or transiently with the cytoplasmic protein degradation apparatus. Our approach is broadly applicable to elucidating pathogen–host interactomes, providing high-certainty identification of interactors by their direct access during cycling infection. Understanding the pathophysiological consequences of these associations is likely to provide strategic targets for antiviral intervention. PMID:27375898

A side-effect free method for identifying cancer drug targets.

PubMed

Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

Analysis of the interactome of the Ser/Thr Protein Phosphatase type 1 in Plasmodium falciparum.

PubMed

Hollin, Thomas; De Witte, Caroline; Lenne, Astrid; Pierrot, Christine; Khalife, Jamal

2016-03-17

Protein Phosphatase 1 (PP1) is an enzyme essential to cell viability in the malaria parasite Plasmodium falciparum (Pf). The activity of PP1 is regulated by the binding of regulatory subunits, of which there are up to 200 in humans, but only 3 have been so far reported for the parasite. To better understand the P. falciparum PP1 (PfPP1) regulatory network, we here report the use of three strategies to characterize the PfPP1 interactome: co-affinity purified proteins identified by mass spectrometry, yeast two-hybrid (Y2H) screening and in silico analysis of the P. falciparum predicted proteome. Co-affinity purification followed by MS analysis identified 6 PfPP1 interacting proteins (Pips) of which 3 contained the RVxF consensus binding, 2 with a Fxx[RK]x[RK] motif, also shown to be a PP1 binding motif and one with both binding motifs. The Y2H screens identified 134 proteins of which 30 present the RVxF binding motif and 20 have the Fxx[RK]x[RK] binding motif. The in silico screen of the Pf predicted proteome using a consensus RVxF motif as template revealed the presence of 55 potential Pips. As further demonstration, 35 candidate proteins were validated as PfPP1 interacting proteins in an ELISA-based assay. To the best of our knowledge, this is the first study on PfPP1 interactome. The data reports several conserved PP1 interacting proteins as well as a high number of specific interactors to PfPP1. Their analysis indicates a high diversity of biological functions for PP1 in Plasmodium. Based on the present data and on an earlier study of the Pf interactome, a potential implication of Pips in protein folding/proteolysis, transcription and pathogenicity networks is proposed. The present work provides a starting point for further studies on the structural basis of these interactions and their functions in P. falciparum.

Prediction of GCRV virus-host protein interactome based on structural motif-domain interactions.

PubMed

Zhang, Aidi; He, Libo; Wang, Yaping

2017-03-02

Grass carp hemorrhagic disease, caused by grass carp reovirus (GCRV), is the most fatal causative agent in grass carp aquaculture. Protein-protein interactions between virus and host are one avenue through which GCRV can trigger infection and induce disease. Experimental approaches for the detection of host-virus interactome have many inherent limitations, and studies on protein-protein interactions between GCRV and its host remain rare. In this study, based on known motif-domain interaction information, we systematically predicted the GCRV virus-host protein interactome by using motif-domain interaction pair searching strategy. These proteins derived from different domain families and were predicted to interact with different motif patterns in GCRV. JAM-A protein was successfully predicted to interact with motifs of GCRV Sigma1-like protein, and shared the similar binding mode compared with orthoreovirus. Differentially expressed genes during GCRV infection process were extracted and mapped to our predicted interactome, the overlapped genes displayed different tissue expression distributions on the whole, the overall expression level in intestinal is higher than that of other three tissues, which may suggest that the functions of these genes are more active in intestinal. Function annotation and pathway enrichment analysis revealed that the host targets were largely involved in signaling pathway and immune pathway, such as interferon-gamma signaling pathway, VEGF signaling pathway, EGF receptor signaling pathway, B cell activation, and T cell activation. Although the predicted PPIs may contain some false positives due to limited data resource and poor research background in non-model species, the computational method still provide reasonable amount of interactions, which can be further validated by high throughput experiments. The findings of this work will contribute to the development of system biology for GCRV infectious diseases, and help guide the identification of novel receptors of GCRV in its host.

Protein interactome analysis of 12 mitogen-activated protein kinase kinase kinase in rice using a yeast two-hybrid system.

PubMed

Singh, Raksha; Lee, Jae-Eun; Dangol, Sarmina; Choi, Jihyun; Yoo, Ran Hee; Moon, Jae Sun; Shim, Jae-Kyung; Rakwal, Randeep; Agrawal, Ganesh Kumar; Jwa, Nam-Soo

2014-01-01

The mitogen-activated protein kinase (MAPK) cascade is composed at least of MAP3K (for MAPK kinase kinase), MAP2K, and MAPK family modules. These components together play a central role in mediating extracellular signals to the cell and vice versa by interacting with their partner proteins. However, the MAP3K-interacting proteins remain poorly investigated in plants. Here, we utilized a yeast two-hybrid system and bimolecular fluorescence complementation in the model crop rice (Oryza sativa) to map MAP3K-interacting proteins. We identified 12 novel nonredundant interacting protein pairs (IPPs) representing 11 nonredundant interactors using 12 rice MAP3Ks (available as full-length cDNA in the rice KOME (http://cdna01.dna.affrc.go.jp/cDNA/) at the time of experimental design and execution) as bait and a rice seedling cDNA library as prey. Of the 12 MAP3Ks, only six had interacting protein partners. The established MAP3K interactome consisted of two kinases, three proteases, two forkhead-associated domain-containing proteins, two expressed proteins, one E3 ligase, one regulatory protein, and one retrotransposon protein. Notably, no MAP3K showed physical interaction with either MAP2K or MAPK. Seven IPPs (58.3%) were confirmed in vivo by bimolecular fluorescence complementation. Subcellular localization of 14 interactors, together involved in nine IPPs (75%) further provide prerequisite for biological significance of the IPPs. Furthermore, GO of identified interactors predicted their involvement in diverse physiological responses, which were supported by a literature survey. These findings increase our knowledge of the MAP3K-interacting proteins, help in proposing a model of MAPK modules, provide a valuable resource for developing a complete map of the rice MAPK interactome, and allow discussion for translating the interactome knowledge to rice crop improvement against environmental factors. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

PubMed

Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

2017-01-01

Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum).

PubMed

Bhardwaj, Jyoti; Gangwar, Indu; Panzade, Ganesh; Shankar, Ravi; Yadav, Sudesh Kumar

2016-06-03

Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and involved processes. This information would ease the effort and increase the efficacy for similar studies on other legumes. Public access is available at http://14.139.59.221/MauPIR/ .

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

PubMed

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information and is a productive avenue in generating new hypotheses. The second objective of InteractomeBrowser is to fill the gap between interaction databases and dynamic modeling. It is thus compatible with the network analysis software Cytoscape and with the Gene Interaction Network simulation software (GINsim). We provide examples underlying the benefits of this visualization tool for large gene set analysis related to thymocyte differentiation. The InteractomeBrowser plugin is a powerful tool to get quick access to a knowledge database that includes both predicted and validated molecular interactions. InteractomeBrowser is available through the TranscriptomeBrowser framework and can be found at: http://tagc.univ-mrs.fr/tbrowser/. Our database is updated on a regular basis.

ARMOUR - A Rice miRNA: mRNA Interaction Resource.

PubMed

Sanan-Mishra, Neeti; Tripathi, Anita; Goswami, Kavita; Shukla, Rohit N; Vasudevan, Madavan; Goswami, Hitesh

2018-01-01

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

A Systems Biology Methodology Combining Transcriptome and Interactome Datasets to Assess the Implications of Cytokinin Signaling for Plant Immune Networks.

PubMed

Kunz, Meik; Dandekar, Thomas; Naseem, Muhammad

2017-01-01

Cytokinins (CKs) play an important role in plant growth and development. Also, several studies highlight the modulatory implications of CKs for plant-pathogen interaction. However, the underlying mechanisms of CK mediating immune networks in plants are still not fully understood. A detailed analysis of high-throughput transcriptome (RNA-Seq and microarrays) datasets under modulated conditions of plant CKs and its mergence with cellular interactome (large-scale protein-protein interaction data) has the potential to unlock the contribution of CKs to plant defense. Here, we specifically describe a detailed systems biology methodology pertinent to the acquisition and analysis of various omics datasets that delineate the role of plant CKs in impacting immune pathways in Arabidopsis.

Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

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

Davidson, George S.; Brown, William Michael

2007-09-01

Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes tomore » make use of the new data.3« less

Comparative Metabolite Fingerprinting of the Rumen System during Colonisation of Three Forage Grass (Lolium perenne L.) Varieties

PubMed Central

Kingston-Smith, Alison H.; Davies, Teri E.; Rees Stevens, Pauline; Mur, Luis A. J.

2013-01-01

The rumen microbiota enable ruminants to degrade complex ligno-cellulosic compounds to produce high quality protein for human consumption. However, enteric fermentation by domestic ruminants generates negative by-products: greenhouse gases (methane) and environmental nitrogen pollution. The current lack of cultured isolates representative of the totality of rumen microbial species creates an information gap about the in vivo function of the rumen microbiota and limits our ability to apply predictive biology for improvement of feed for ruminants. In this work we took a whole ecosystem approach to understanding how the metabolism of the microbial population responds to introduction of its substrate. Fourier Transform Infra Red (FTIR) spectroscopy-based metabolite fingerprinting was used to discriminate differences in the plant-microbial interactome of the rumen when using three forage grass varieties (Lolium perenne L. cv AberDart, AberMagic and Premium) as substrates for microbial colonisation and fermentation. Specific examination of spectral regions associated with fatty acids, amides, sugars and alkanes indicated that although the three forages were apparently similar by traditional nutritional analysis, patterns of metabolite flux within the plant-microbial interactome were distinct and plant genotype dependent. Thus, the utilisation pattern of forage nutrients by the rumen microbiota can be influenced by subtleties determined by forage genotypes. These data suggest that our interactomic approach represents an important means to improve forages and ultimately the livestock environment. PMID:24312434

Comprehensively Characterizing the Thioredoxin Interactome In Vivo Highlights the Central Role Played by This Ubiquitous Oxidoreductase in Redox Control*

PubMed Central

Arts, Isabelle S.; Vertommen, Didier; Baldin, Francesca; Laloux, Géraldine; Collet, Jean-François

2016-01-01

Thioredoxin (Trx) is a ubiquitous oxidoreductase maintaining protein-bound cysteine residues in the reduced thiol state. Here, we combined a well-established method to trap Trx substrates with the power of bacterial genetics to comprehensively characterize the in vivo Trx redox interactome in the model bacterium Escherichia coli. Using strains engineered to optimize trapping, we report the identification of a total 268 Trx substrates, including 201 that had never been reported to depend on Trx for reduction. The newly identified Trx substrates are involved in a variety of cellular processes, ranging from energy metabolism to amino acid synthesis and transcription. The interaction between Trx and two of its newly identified substrates, a protein required for the import of most carbohydrates, PtsI, and the bacterial actin homolog MreB was studied in detail. We provide direct evidence that PtsI and MreB contain cysteine residues that are susceptible to oxidation and that participate in the formation of an intermolecular disulfide with Trx. By considerably expanding the number of Trx targets, our work highlights the role played by this major oxidoreductase in a variety of cellular processes. Moreover, as the dependence on Trx for reduction is often conserved across species, it also provides insightful information on the interactome of Trx in organisms other than E. coli. PMID:27081212

The cyclin D1-CDK4 oncogenic interactome enables identification of potential novel oncogenes and clinical prognosis

PubMed Central

Jirawatnotai, Siwanon; Sharma, Samanta; Michowski, Wojciech; Suktitipat, Bhoom; Geng, Yan; Quackenbush, John; Elias, Joshua E; Gygi, Steven P; Wang, Yaoyu E; Sicinski, Piotr

2014-01-01

Overexpression of cyclin D1 and its catalytic partner, CDK4, is frequently seen in human cancers. We constructed cyclin D1 and CDK4 protein interaction network in a human breast cancer cell line MCF7, and identified novel CDK4 protein partners. Among CDK4 interactors we observed several proteins functioning in protein folding and in complex assembly. One of the novel partners of CDK4 is FKBP5, which we found to be required to maintain CDK4 levels in cancer cells. An integrative analysis of the extended cyclin D1 cancer interactome and somatic copy number alterations in human cancers identified BAIAPL21 as a potential novel human oncogene. We observed that in several human tumor types BAIAPL21 is expressed at higher levels as compared to normal tissue. Forced overexpression of BAIAPL21 augmented anchorage independent growth, increased colony formation by cancer cells and strongly enhanced the ability of cells to form tumors in vivo. Lastly, we derived an Aggregate Expression Score (AES), which quantifies the expression of all cyclin D1 interactors in a given tumor. We observed that AES has a prognostic value among patients with ER-positive breast cancers. These studies illustrate the utility of analyzing the interactomes of proteins involved in cancer to uncover potential oncogenes, or to allow better cancer prognosis. PMID:25486477

Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

PubMed Central

Li, Jing-Woei; Lee, Heung-Man; Wang, Ying; Tong, Amy Hin-Yan; Yip, Kevin Y.; Tsui, Stephen Kwok-Wing; Lok, Si; Ozaki, Risa; Luk, Andrea O; Kong, Alice P. S.; So, Wing-Yee; Ma, Ronald C. W.; Chan, Juliana C. N.; Chan, Ting-Fung

2016-01-01

Protein interactions play significant roles in complex diseases. We analyzed peripheral blood mononuclear cells (PBMC) transcriptome using a multi-method strategy. We constructed a tissue-specific interactome (T2Di) and identified 420 molecular signatures associated with T2D-related comorbidity and symptoms, mainly implicated in inflammation, adipogenesis, protein phosphorylation and hormonal secretion. Apart from explaining the residual associations within the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study, the T2Di signatures were enriched in pathogenic cell type-specific regulatory elements related to fetal development, immunity and expression quantitative trait loci (eQTL). The T2Di revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T2D-GWAS gene implicated in pancreatic function. The T2Di also included known anti-diabetic drug targets (e.g. PPARD, MAOB) and identified possible druggable targets (e.g. NCOR2, PDGFR). These T2Di signatures were validated by an independent computational method, and by expression data of pancreatic islet, muscle and liver with some of the signatures (CEBPB, SREBF1, MLST8, SRF, SRRT and SLC12A9) confirmed in PBMC from an independent cohort of 66 T2D and 66 control subjects. By combining prior knowledge and transcriptome analysis, we have constructed an interactome to explain the multi-layered regulatory pathways in T2D. PMID:27752041

Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders

PubMed Central

Carter, C. J.

2013-01-01

Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E − 05  (ADHD)  to  1.22E − 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself. PMID:23533776

Caspofungin exposure alters the core septin AspB interactome of Aspergillus fumigatus.

PubMed

Vargas-Muñiz, José M; Renshaw, Hilary; Waitt, Greg; Soderblom, Erik J; Moseley, M Arthur; Palmer, Jonathan M; Juvvadi, Praveen R; Keller, Nancy P; Steinbach, William J

2017-04-01

Aspergillus fumigatus, the main etiological agent of invasive aspergillosis, is a leading cause of death in immunocompromised patients. Septins, a conserved family of GTP-binding proteins, serve as scaffolding proteins to recruit enzymes and key regulators to different cellular compartments. Deletion of the A. fumigatus septin aspB increases susceptibility to the echinocandin antifungal caspofungin. However, how AspB mediates this response to caspofungin is unknown. Here, we characterized the AspB interactome under basal conditions and after exposure to a clinically relevant concentration of caspofungin. While A. fumigatus AspB interacted with 334 proteins, including kinases, cell cycle regulators, and cell wall synthesis-related proteins under basal growth conditions, caspofungin exposure altered AspB interactions. A total of 69 of the basal interactants did not interact with AspB after exposure to caspofungin, and 54 new interactants were identified following caspofungin exposure. We generated A. fumigatus deletion strains for 3 proteins (ArpB, Cyp4, and PpoA) that only interacted with AspB following exposure to caspofungin that were previously annotated as induced after exposure to antifungal agents, yet only PpoA was implicated in the response to caspofungin. Taken together, we defined how the septin AspB interactome is altered in the presence of a clinically relevant antifungal. Copyright © 2017 Elsevier Inc. All rights reserved.

Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

PubMed

Rönnberg, Tuomas; Jääskeläinen, Kirsi; Blot, Guillaume; Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

2012-01-01

Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

MitProNet: A Knowledgebase and Analysis Platform of Proteome, Interactome and Diseases for Mammalian Mitochondria

PubMed Central

Mao, Song; Chai, Xiaoqiang; Hu, Yuling; Hou, Xugang; Tang, Yiheng; Bi, Cheng; Li, Xiao

2014-01-01

Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated biological mechanisms underlying mitochondrial functions and human mitochondrial diseases. MitProNet is freely accessible at http://bio.scu.edu.cn:8085/MitProNet. PMID:25347823

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

PubMed Central

Huang, Shao-shan Carol; Clarke, David C.; Gosline, Sara J. C.; Labadorf, Adam; Chouinard, Candace R.; Gordon, William; Lauffenburger, Douglas A.; Fraenkel, Ernest

2013-01-01

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets. PMID:23408876

Interacting Network of the Gap Junction (GJ) Protein Connexin43 (Cx43) is Modulated by Ischemia and Reperfusion in the Heart.

PubMed

Martins-Marques, Tania; Anjo, Sandra Isabel; Pereira, Paulo; Manadas, Bruno; Girão, Henrique

2015-11-01

The coordinated and synchronized cardiac muscle contraction relies on an efficient gap junction-mediated intercellular communication (GJIC) between cardiomyocytes, which involves the rapid anisotropic impulse propagation through connexin (Cx)-containing channels, namely of Cx43, the most abundant Cx in the heart. Expectedly, disturbing mechanisms that affect channel activity, localization and turnover of Cx43 have been implicated in several cardiomyopathies, such as myocardial ischemia. Besides gap junction-mediated intercellular communication, Cx43 has been associated with channel-independent functions, including modulation of cell adhesion, differentiation, proliferation and gene transcription. It has been suggested that the role played by Cx43 is dictated by the nature of the proteins that interact with Cx43. Therefore, the characterization of the Cx43-interacting network and its dynamics is vital to understand not only the molecular mechanisms underlying pathological malfunction of gap junction-mediated intercellular communication, but also to unveil novel and unanticipated biological functions of Cx43. In the present report, we applied a quantitative SWATH-MS approach to characterize the Cx43 interactome in rat hearts subjected to ischemia and ischemia-reperfusion. Our results demonstrate that, in the heart, Cx43 interacts with proteins related with various biological processes such as metabolism, signaling and trafficking. The interaction of Cx43 with proteins involved in gene transcription strengthens the emerging concept that Cx43 has a role in gene expression regulation. Importantly, our data shows that the interactome of Cx43 (Connexome) is differentially modulated in diseased hearts. Overall, the characterization of Cx43-interacting network may contribute to the establishment of new therapeutic targets to modulate cardiac function in physiological and pathological conditions. Data are available via ProteomeXchange with identifier PXD002331. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Predicted Arabidopsis Interactome Resource and Gene Set Linkage Analysis: A Transcriptomic Analysis Resource.

PubMed

Yao, Heng; Wang, Xiaoxuan; Chen, Pengcheng; Hai, Ling; Jin, Kang; Yao, Lixia; Mao, Chuanzao; Chen, Xin

2018-05-01

An advanced functional understanding of omics data is important for elucidating the design logic of physiological processes in plants and effectively controlling desired traits in plants. We present the latest versions of the Predicted Arabidopsis Interactome Resource (PAIR) and of the gene set linkage analysis (GSLA) tool, which enable the interpretation of an observed transcriptomic change (differentially expressed genes [DEGs]) in Arabidopsis ( Arabidopsis thaliana ) with respect to its functional impact for biological processes. PAIR version 5.0 integrates functional association data between genes in multiple forms and infers 335,301 putative functional interactions. GSLA relies on this high-confidence inferred functional association network to expand our perception of the functional impacts of an observed transcriptomic change. GSLA then interprets the biological significance of the observed DEGs using established biological concepts (annotation terms), describing not only the DEGs themselves but also their potential functional impacts. This unique analytical capability can help researchers gain deeper insights into their experimental results and highlight prospective directions for further investigation. We demonstrate the utility of GSLA with two case studies in which GSLA uncovered how molecular events may have caused physiological changes through their collective functional influence on biological processes. Furthermore, we showed that typical annotation-enrichment tools were unable to produce similar insights to PAIR/GSLA. The PAIR version 5.0-inferred interactome and GSLA Web tool both can be accessed at http://public.synergylab.cn/pair/. © 2018 American Society of Plant Biologists. All Rights Reserved.

Hypothesis: NDL proteins function in stress responses by regulating microtubule organization

PubMed Central

Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals and plants. It is well established that stress responses leads to the microtubule depolymerization and reorganization which is crucial for stress tolerance. NDRG is a microtubule-associated protein which mediates the microtubule organization in animals by causing acetylation and increases the stability of α-tubulin. As NDL1 is highly homologous to NDRG, involvement of NDL1 in the microtubule organization during plant stress can also be expected. Discovery of interaction of NDL with protein kinesin light chain- related 1, enodomembrane family protein 70, syntaxin-23, tubulin alpha-2 chain, as a part of G protein interactome initiative encourages us to postulate microtubule stabilizing functions for NDL family in plants. Our search for NDL interactors in G protein interactome also predicts the role of NDL proteins in abiotic stress tolerance management. Based on published report in animals and predicted interacting partners for NDL in G protein interactome lead us to hypothesize involvement of NDL in the microtubule organization during abiotic stress management in plants. PMID:26583023

Hypothesis: NDL proteins function in stress responses by regulating microtubule organization.

PubMed

Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals and plants. It is well established that stress responses leads to the microtubule depolymerization and reorganization which is crucial for stress tolerance. NDRG is a microtubule-associated protein which mediates the microtubule organization in animals by causing acetylation and increases the stability of α-tubulin. As NDL1 is highly homologous to NDRG, involvement of NDL1 in the microtubule organization during plant stress can also be expected. Discovery of interaction of NDL with protein kinesin light chain- related 1, enodomembrane family protein 70, syntaxin-23, tubulin alpha-2 chain, as a part of G protein interactome initiative encourages us to postulate microtubule stabilizing functions for NDL family in plants. Our search for NDL interactors in G protein interactome also predicts the role of NDL proteins in abiotic stress tolerance management. Based on published report in animals and predicted interacting partners for NDL in G protein interactome lead us to hypothesize involvement of NDL in the microtubule organization during abiotic stress management in plants.

NR4A nuclear receptors are orphans but not lonesome.

PubMed

Kurakula, Kondababu; Koenis, Duco S; van Tiel, Claudia M; de Vries, Carlie J M

2014-11-01

The NR4A subfamily of nuclear receptors consists of three mammalian members: Nur77, Nurr1, and NOR-1. The NR4A receptors are involved in essential physiological processes such as adaptive and innate immune cell differentiation, metabolism and brain function. They act as transcription factors that directly modulate gene expression, but can also form trans-repressive complexes with other transcription factors. In contrast to steroid hormone nuclear receptors such as the estrogen receptor or the glucocorticoid receptor, no ligands have been described for the NR4A receptors. This lack of known ligands might be explained by the structure of the ligand-binding domain of NR4A receptors, which shows an active conformation and a ligand-binding pocket that is filled with bulky amino acid side-chains. Other mechanisms, such as transcriptional control, post-translational modifications and protein-protein interactions therefore seem to be more important in regulating the activity of the NR4A receptors. For Nur77, over 80 interacting proteins (the interactome) have been identified so far, and roughly half of these interactions has been studied in more detail. Although the NR4As show some overlap in interacting proteins, less information is available on the interactome of Nurr1 and NOR-1. Therefore, the present review will describe the current knowledge on the interactomes of all three NR4A nuclear receptors with emphasis on Nur77. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantifying domain-ligand affinities and specificities by high-throughput holdup assay

PubMed Central

Vincentelli, Renaud; Luck, Katja; Poirson, Juline; Polanowska, Jolanta; Abdat, Julie; Blémont, Marilyne; Turchetto, Jeremy; Iv, François; Ricquier, Kevin; Straub, Marie-Laure; Forster, Anne; Cassonnet, Patricia; Borg, Jean-Paul; Jacob, Yves; Masson, Murielle; Nominé, Yves; Reboul, Jérôme; Wolff, Nicolas; Charbonnier, Sebastian; Travé, Gilles

2015-01-01

Many protein interactions are mediated by small linear motifs interacting specifically with defined families of globular domains. Quantifying the specificity of a motif requires measuring and comparing its binding affinities to all its putative target domains. To this aim, we developed the high-throughput holdup assay, a chromatographic approach that can measure up to a thousand domain-motif equilibrium binding affinities per day. Extracts of overexpressed domains are incubated with peptide-coated resins and subjected to filtration. Binding affinities are deduced from microfluidic capillary electrophoresis of flow-throughs. After benchmarking the approach on 210 PDZ-peptide pairs with known affinities, we determined the affinities of two viral PDZ-binding motifs derived from Human Papillomavirus E6 oncoproteins for 209 PDZ domains covering 79% of the human PDZome. We obtained exquisite sequence-dependent binding profiles, describing quantitatively the PDZome recognition specificity of each motif. This approach, applicable to many categories of domain-ligand interactions, has a wide potential for quantifying the specificities of interactomes. PMID:26053890

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

PubMed

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com.

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

PubMed Central

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com. PMID:20221258

Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

PubMed

Anandkumar, Balakrishna; Haga, Steve W; Wu, Hui-Fen

2014-02-01

The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.

A survey of the interactome of Kaposi's sarcoma-associated herpesvirus ORF45 revealed its binding to viral ORF33 and cellular USP7, resulting in stabilization of ORF33 that is required for production of progeny viruses.

PubMed

Gillen, Joseph; Li, Wenwei; Liang, Qiming; Avey, Denis; Wu, Jianjun; Wu, Fayi; Myoung, JinJong; Zhu, Fanxiu

2015-05-01

The ORF45 protein of Kaposi's sarcoma-associated herpesvirus (KSHV) is a gammaherpesvirus-specific immediate-early tegument protein. Our previous studies have revealed its crucial roles in both early and late stages of KSHV infection. In this study, we surveyed the interactome of ORF45 using a panel of monoclonal antibodies. In addition to the previously identified extracellular regulated kinase (ERK) and p90 ribosomal S6 kinase (RSK) proteins, we found several other copurified proteins, including prominent ones of ∼38 kDa and ∼130 kDa. Mass spectrometry revealed that the 38-kDa protein is viral ORF33 and the 130-kDa protein is cellular USP7 (ubiquitin-specific protease 7). We mapped the ORF33-binding domain to the highly conserved carboxyl-terminal 19 amino acids (aa) of ORF45 and the USP7-binding domain to the reported consensus motif in the central region of ORF45. Using immunofluorescence staining, we observed colocalization of ORF45 with ORF33 or USP7 both under transfected conditions and in KSHV-infected cells. Moreover, we noticed ORF45-dependent relocalization of a portion of ORF33/USP7 from the nucleus to the cytoplasm. We found that ORF45 caused an increase in ORF33 protein accumulation that was abolished if either the ORF33- or USP7-binding domain in ORF45 was deleted. Furthermore, deletion of the conserved carboxyl terminus of ORF45 in the KSHV genome drastically reduced the level of ORF33 protein in KSHV-infected cells and abolished production of progeny virions. Collectively, our results not only reveal new components of the ORF45 interactome, but also demonstrate that the interactions among these proteins are crucial for KSHV lytic replication. Kaposi's sarcoma-associated herpesvirus (KSHV) is the causative agent of several human cancers. KSHV ORF45 is a multifunctional protein that is required for KSHV lytic replication, but the exact mechanisms by which ORF45 performs its critical functions are unclear. Our previous studies revealed that all ORF45 protein in cells exists in high-molecular-weight complexes. We therefore sought to characterize the interactome of ORF45 to provide insights into its roles during lytic replication. Using a panel of monoclonal antibodies, we surveyed the ORF45 interactome in KSHV-infected cells. We identified two new binding partners of ORF45: the viral protein ORF33 and cellular ubiquitin-specific protease 7 (USP7). We further demonstrate that the interaction between ORF45 and ORF33 is crucial for the efficient production of KSHV viral particles, suggesting that the targeted interference with this interaction may represent a novel strategy to inhibit KSHV lytic replication. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome.

PubMed

Akram, Pakeeza; Liao, Li

2017-12-06

Identification of common genes associated with comorbid diseases can be critical in understanding their pathobiological mechanism. This work presents a novel method to predict missing common genes associated with a disease pair. Searching for missing common genes is formulated as an optimization problem to minimize network based module separation from two subgraphs produced by mapping genes associated with disease onto the interactome. Using cross validation on more than 600 disease pairs, our method achieves significantly higher average receiver operating characteristic ROC Score of 0.95 compared to a baseline ROC score 0.60 using randomized data. Missing common genes prediction is aimed to complete gene set associated with comorbid disease for better understanding of biological intervention. It will also be useful for gene targeted therapeutics related to comorbid diseases. This method can be further considered for prediction of missing edges to complete the subgraph associated with disease pair.

The NRF2-related interactome and regulome contain multifunctional proteins and fine-tuned autoregulatory loops.

PubMed

Papp, Diána; Lenti, Katalin; Módos, Dezső; Fazekas, Dávid; Dúl, Zoltán; Türei, Dénes; Földvári-Nagy, László; Nussinov, Ruth; Csermely, Péter; Korcsmáros, Tamás

2012-06-21

NRF2 is a well-known, master transcription factor (TF) of oxidative and xenobiotic stress responses. Recent studies uncovered an even wider regulatory role of NRF2 influencing carcinogenesis, inflammation and neurodegeneration. Prompted by these advances here we present a systems-level resource for NRF2 interactome and regulome that includes 289 protein-protein, 7469 TF-DNA and 85 miRNA interactions. As systems-level examples of NRF2-related signaling we identified regulatory loops of NRF2 interacting proteins (e.g., JNK1 and CBP) and a fine-tuned regulatory system, where 35 TFs regulated by NRF2 influence 63 miRNAs that down-regulate NRF2. The presented network and the uncovered regulatory loops may facilitate the development of efficient, NRF2-based therapeutic agents. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Mapping the local protein interactome of the NuA3 histone acetyltransferase

PubMed Central

Smart, Sherri K; Mackintosh, Samuel G; Edmondson, Ricky D; Taverna, Sean D; Tackett, Alan J

2009-01-01

Protein–protein interactions modulate cellular functions ranging from the activity of enzymes to signal transduction cascades. A technology termed transient isotopic differentiation of interactions as random or targeted (transient I-DIRT) is described for the identification of stable and transient protein–protein interactions in vivo. The procedure combines mild in vivo chemical cross-linking and non-stringent affinity purification to isolate low abundance chromatin-associated protein complexes. Using isotopic labeling and mass spectrometric readout, purified proteins are categorized with respect to the protein ‘bait’ as stable, transient, or contaminant. Here we characterize the local interactome of the chromatin-associated NuA3 histone lysine-acetyltransferase protein complex. We describe transient associations with the yFACT nucleosome assembly complex, RSC chromatin remodeling complex and a nucleosome assembly protein. These novel, physical associations with yFACT, RSC, and Nap1 provide insight into the mechanism of NuA3-associated transcription and chromatin regulation. PMID:19621382

A comparative study of disease genes and drug targets in the human protein interactome

PubMed Central

2015-01-01

Background Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. Results In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. Conclusions The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing. PMID:25861037

A network biology-based approach to evaluating the effect of environmental contaminants on human interactome and diseases.

PubMed

Iida, M; Takemoto, K

2018-09-30

Environmental contaminant exposure can pose significant risks to human health. Therefore, evaluating the impact of this exposure is of great importance; however, it is often difficult because both the molecular mechanism of disease and the mode of action of the contaminants are complex. We used network biology techniques to quantitatively assess the impact of environmental contaminants on the human interactome and diseases with a particular focus on seven major contaminant categories: persistent organic pollutants (POPs), dioxins, polycyclic aromatic hydrocarbons (PAHs), pesticides, perfluorochemicals (PFCs), metals, and pharmaceutical and personal care products (PPCPs). We integrated publicly available data on toxicogenomics, the diseasome, protein-protein interactions (PPIs), and gene essentiality and found that a few contaminants were targeted to many genes, and a few genes were targeted by many contaminants. The contaminant targets were hub proteins in the human PPI network, whereas the target proteins in most categories did not contain abundant essential proteins. Generally, contaminant targets and disease-associated proteins were closely associated with the PPI network, and the closeness of the associations depended on the disease type and chemical category. Network biology techniques were used to identify environmental contaminants with broad effects on the human interactome and contaminant-sensitive biomarkers. Moreover, this method enabled us to quantify the relationship between environmental contaminants and human diseases, which was supported by epidemiological and experimental evidence. These methods and findings have facilitated the elucidation of the complex relationship between environmental exposure and adverse health outcomes. Copyright © 2018 Elsevier Inc. All rights reserved.

The protein interactome of collapsin response mediator protein-2 (CRMP2/DPYSL2) reveals novel partner proteins in brain tissue.

PubMed

Martins-de-Souza, Daniel; Cassoli, Juliana S; Nascimento, Juliana M; Hensley, Kenneth; Guest, Paul C; Pinzon-Velasco, Andres M; Turck, Christoph W

2015-10-01

Collapsin response mediator protein-2 (CRMP2) is a CNS protein involved in neuronal development, axonal and neuronal growth, cell migration, and protein trafficking. Recent studies have linked perturbations in CRMP2 function to neurodegenerative disorders such as Alzheimer's disease, neuropathic pain, and Batten disease, and to psychiatric disorders such as schizophrenia. Like most proteins, CRMP2 functions though interactions with a molecular network of proteins and other molecules. Here, we have attempted to identify additional proteins of the CRMP2 interactome to provide further leads about its roles in neurological functions. We used a combined co-immunoprecipitation and shotgun proteomic approach in order to identify CRMP2 protein partners. We identified 78 CRMP2 protein partners not previously reported in public protein interaction databases. These were involved in seven biological processes, which included cell signaling, growth, metabolism, trafficking, and immune function, according to Gene Ontology classifications. Furthermore, 32 different molecular functions were found to be associated with these proteins, such as RNA binding, ribosomal functions, transporter activity, receptor activity, serine/threonine phosphatase activity, cell adhesion, cytoskeletal protein binding and catalytic activity. In silico pathway interactome construction revealed a highly connected network with the most overrepresented functions corresponding to semaphorin interactions, along with axon guidance and WNT5A signaling. Taken together, these findings suggest that the CRMP2 pathway is critical for regulating neuronal and synaptic architecture. Further studies along these lines might uncover novel biomarkers and drug targets for use in drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of the interactome between fish plasma proteins and Edwardsiella tarda reveals tissue-specific strategies against bacterial infection.

PubMed

Li, Hui; Huang, Xiaoyan; Zeng, Zaohai; Peng, Xuan-Xian; Peng, Bo

2016-09-01

Elucidating the complex pathogen-host interaction is essential for a comprehensive understanding of how these remarkable agents invade their hosts and how the hosts defend against these invaders. During the infection, pathogens interact intensively with host to enable their survival, which can be revealed through their interactome. Edwardsiella tarda is a Gram-negative bacterial pathogen causing huge economic loss in aquaculture and a spectrum of intestinal and extraintestinal diseases in humans. E. tarda is an ideal model for host-pathogen investigation as it infects fish in three distinct steps: entering the host, circulating through the blood and establishing infection. We adopted a previous established proteomic approach that inactivated E. tarda cells and covalent crosslink fish plasma proteins were used to capture plasma proteins and bacterial outer membrane proteins, respectively. By the combinatorial use of proteomic and biochemical approaches, six plasma proteins and seven outer membrane proteins (OMPs) were identified. Interactions among these proteins were validated with protein-array, far-Western blotting and co-immunoprecipitation. At last, seventeen plasma protein-bacteria protein-protein interaction were confirmed to be involved in the interaction network, forming a complex interactome. Compared to our previous results, different host proteins were detected, whereas some of the bacterial proteins were similar, which indicates that hosts adopt tissue-specific strategies to cope with the same pathogen during infection. Thus, our results provide a robust demonstration of both bacterial initiators and host receptors or interacting proteins to further explore infection and anti-infective mechanisms between hosts and microbes. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Systems Biology Approach to Reveal Putative Host-Derived Biomarkers of Periodontitis by Network Topology Characterization of MMP-REDOX/NO and Apoptosis Integrated Pathways.

PubMed

Zeidán-Chuliá, Fares; Gürsoy, Mervi; Neves de Oliveira, Ben-Hur; Özdemir, Vural; Könönen, Eija; Gürsoy, Ulvi K

2015-01-01

Periodontitis, a formidable global health burden, is a common chronic disease that destroys tooth-supporting tissues. Biomarkers of the early phase of this progressive disease are of utmost importance for global health. In this context, saliva represents a non-invasive biosample. By using systems biology tools, we aimed to (1) identify an integrated interactome between matrix metalloproteinase (MMP)-REDOX/nitric oxide (NO) and apoptosis upstream pathways of periodontal inflammation, and (2) characterize the attendant topological network properties to uncover putative biomarkers to be tested in saliva from patients with periodontitis. Hence, we first generated a protein-protein network model of interactions ("BIOMARK" interactome) by using the STRING 10 database, a search tool for the retrieval of interacting genes/proteins, with "Experiments" and "Databases" as input options and a confidence score of 0.400. Second, we determined the centrality values (closeness, stress, degree or connectivity, and betweenness) for the "BIOMARK" members by using the Cytoscape software. We found Ubiquitin C (UBC), Jun proto-oncogene (JUN), and matrix metalloproteinase-14 (MMP14) as the most central hub- and non-hub-bottlenecks among the 211 genes/proteins of the whole interactome. We conclude that UBC, JUN, and MMP14 are likely an optimal candidate group of host-derived biomarkers, in combination with oral pathogenic bacteria-derived proteins, for detecting periodontitis at its early phase by using salivary samples from patients. These findings therefore have broader relevance for systems medicine in global health as well.

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

PubMed Central

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

The Orphan Disease Networks

PubMed Central

Zhang, Minlu; Zhu, Cheng; Jacomy, Alexis; Lu, Long J.; Jegga, Anil G.

2011-01-01

The low prevalence rate of orphan diseases (OD) requires special combined efforts to improve diagnosis, prevention, and discovery of novel therapeutic strategies. To identify and investigate relationships based on shared genes or shared functional features, we have conducted a bioinformatic-based global analysis of all orphan diseases with known disease-causing mutant genes. Starting with a bipartite network of known OD and OD-causing mutant genes and using the human protein interactome, we first construct and topologically analyze three networks: the orphan disease network, the orphan disease-causing mutant gene network, and the orphan disease-causing mutant gene interactome. Our results demonstrate that in contrast to the common disease-causing mutant genes that are predominantly nonessential, a majority of orphan disease-causing mutant genes are essential. In confirmation of this finding, we found that OD-causing mutant genes are topologically important in the protein interactome and are ubiquitously expressed. Additionally, functional enrichment analysis of those genes in which mutations cause ODs shows that a majority result in premature death or are lethal in the orthologous mouse gene knockout models. To address the limitations of traditional gene-based disease networks, we also construct and analyze OD networks on the basis of shared enriched features (biological processes, cellular components, pathways, phenotypes, and literature citations). Analyzing these functionally-linked OD networks, we identified several additional OD-OD relations that are both phenotypically similar and phenotypically diverse. Surprisingly, we observed that the wiring of the gene-based and other feature-based OD networks are largely different; this suggests that the relationship between ODs cannot be fully captured by the gene-based network alone. PMID:21664998

Interactome analysis of longitudinal pharyngeal infection of cynomolgus macaques by group A Streptococcus.

PubMed

Shea, Patrick R; Virtaneva, Kimmo; Kupko, John J; Porcella, Stephen F; Barry, William T; Wright, Fred A; Kobayashi, Scott D; Carmody, Aaron; Ireland, Robin M; Sturdevant, Daniel E; Ricklefs, Stacy M; Babar, Imran; Johnson, Claire A; Graham, Morag R; Gardner, Donald J; Bailey, John R; Parnell, Michael J; Deleo, Frank R; Musser, James M

2010-03-09

Relatively little is understood about the dynamics of global host-pathogen transcriptome changes that occur during bacterial infection of mucosal surfaces. To test the hypothesis that group A Streptococcus (GAS) infection of the oropharynx provokes a distinct host transcriptome response, we performed genome-wide transcriptome analysis using a nonhuman primate model of experimental pharyngitis. We also identified host and pathogen biological processes and individual host and pathogen gene pairs with correlated patterns of expression, suggesting interaction. For this study, 509 host genes and seven biological pathways were differentially expressed throughout the entire 32-day infection cycle. GAS infection produced an initial widespread significant decrease in expression of many host genes, including those involved in cytokine production, vesicle formation, metabolism, and signal transduction. This repression lasted until day 4, at which time a large increase in expression of host genes was observed, including those involved in protein translation, antigen presentation, and GTP-mediated signaling. The interactome analysis identified 73 host and pathogen gene pairs with correlated expression levels. We discovered significant correlations between transcripts of GAS genes involved in hyaluronic capsule production and host endocytic vesicle formation, GAS GTPases and host fibrinolytic genes, and GAS response to interaction with neutrophils. We also identified a strong signal, suggesting interaction between host gammadelta T cells and genes in the GAS mevalonic acid synthesis pathway responsible for production of isopentenyl-pyrophosphate, a short-chain phospholipid that stimulates these T cells. Taken together, our results are unique in providing a comprehensive understanding of the host-pathogen interactome during mucosal infection by a bacterial pathogen.

The Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism

PubMed Central

Eagleson, Kathie L.; Xie, Zhihui; Levitt, Pat

2016-01-01

People with autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy - the influence of one gene on distinct phenotypes - raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multi-functional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain, and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with ASD, reduces transcription and disrupts socially-relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways, and has a complex protein interactome that is enriched in ASD and other NDD candidates. The interactome is co-regulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, impacting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. PMID:27837921

Systematic Differences in Signal Emitting and Receiving Revealed by PageRank Analysis of a Human Protein Interactome

PubMed Central

Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell. PMID:23028653

Network-based association of hypoxia-responsive genes with cardiovascular diseases

NASA Astrophysics Data System (ADS)

Wang, Rui-Sheng; Oldham, William M.; Loscalzo, Joseph

2014-10-01

Molecular oxygen is indispensable for cellular viability and function. Hypoxia is a stress condition in which oxygen demand exceeds supply. Low cellular oxygen content induces a number of molecular changes to activate regulatory pathways responsible for increasing the oxygen supply and optimizing cellular metabolism under limited oxygen conditions. Hypoxia plays critical roles in the pathobiology of many diseases, such as cancer, heart failure, myocardial ischemia, stroke, and chronic lung diseases. Although the complicated associations between hypoxia and cardiovascular (and cerebrovascular) diseases (CVD) have been recognized for some time, there are few studies that investigate their biological link from a systems biology perspective. In this study, we integrate hypoxia genes, CVD genes, and the human protein interactome in order to explore the relationship between hypoxia and cardiovascular diseases at a systems level. We show that hypoxia genes are much closer to CVD genes in the human protein interactome than that expected by chance. We also find that hypoxia genes play significant bridging roles in connecting different cardiovascular diseases. We construct a hypoxia-CVD bipartite network and find several interesting hypoxia-CVD modules with significant gene ontology similarity. Finally, we show that hypoxia genes tend to have more CVD interactors in the human interactome than in random networks of matching topology. Based on these observations, we can predict novel genes that may be associated with CVD. This network-based association study gives us a broad view of the relationships between hypoxia and cardiovascular diseases and provides new insights into the role of hypoxia in cardiovascular biology.

A comparative study of disease genes and drug targets in the human protein interactome.

PubMed

Sun, Jingchun; Zhu, Kevin; Zheng, W; Xu, Hua

2015-01-01

Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing.

A comprehensive protein-protein interactome for yeast PAS kinase 1 reveals direct inhibition of respiration through the phosphorylation of Cbf1.

PubMed

DeMille, Desiree; Bikman, Benjamin T; Mathis, Andrew D; Prince, John T; Mackay, Jordan T; Sowa, Steven W; Hall, Tacie D; Grose, Julianne H

2014-07-15

Per-Arnt-Sim (PAS) kinase is a sensory protein kinase required for glucose homeostasis in yeast, mice, and humans, yet little is known about the molecular mechanisms of its function. Using both yeast two-hybrid and copurification approaches, we identified the protein-protein interactome for yeast PAS kinase 1 (Psk1), revealing 93 novel putative protein binding partners. Several of the Psk1 binding partners expand the role of PAS kinase in glucose homeostasis, including new pathways involved in mitochondrial metabolism. In addition, the interactome suggests novel roles for PAS kinase in cell growth (gene/protein expression, replication/cell division, and protein modification and degradation), vacuole function, and stress tolerance. In vitro kinase studies using a subset of 25 of these binding partners identified Mot3, Zds1, Utr1, and Cbf1 as substrates. Further evidence is provided for the in vivo phosphorylation of Cbf1 at T211/T212 and for the subsequent inhibition of respiration. This respiratory role of PAS kinase is consistent with the reported hypermetabolism of PAS kinase-deficient mice, identifying a possible molecular mechanism and solidifying the evolutionary importance of PAS kinase in the regulation of glucose homeostasis. © 2014 DeMille et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Comparative analysis of protein-protein interactions in the defense response of rice and wheat.

PubMed

Cantu, Dario; Yang, Baoju; Ruan, Randy; Li, Kun; Menzo, Virginia; Fu, Daolin; Chern, Mawsheng; Ronald, Pamela C; Dubcovsky, Jorge

2013-03-12

Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in rice has the potential to further enhance the translation of advances in rice to wheat and other grasses. The objective of this study was to determine the degree of conservation in the protein-protein interactions in the rice and wheat defense response interactomes. As entry points we selected proteins that serve as key regulators of the rice defense response: the RAR1/SGT1/HSP90 protein complex, NPR1, XA21, and XB12 (XA21 interacting protein 12). Using available wheat sequence databases and phylogenetic analyses we identified and cloned the wheat orthologs of these four rice proteins, including recently duplicated paralogs, and their known direct interactors and tested 86 binary protein interactions using yeast-two-hybrid (Y2H) assays. All interactions between wheat proteins were further tested using in planta bimolecular fluorescence complementation (BiFC). Eighty three percent of the known rice interactions were confirmed when wheat proteins were tested with rice interactors and 76% were confirmed using wheat protein pairs. All interactions in the RAR1/SGT1/ HSP90, NPR1 and XB12 nodes were confirmed for the identified orthologous wheat proteins, whereas only forty four percent of the interactions were confirmed in the interactome node centered on XA21. We hypothesize that this reduction may be associated with a different sub-functionalization history of the multiple duplications that occurred in this gene family after the divergence of the wheat and rice lineages. The observed high conservation of interactions between proteins that serve as key regulators of the rice defense response suggests that the existing rice interactome can be used to predict interactions in wheat. Such predictions are less reliable for nodes that have undergone a different history of duplications and sub-functionalization in the two lineages.

Utilising the EGFR interactome to identify mechanisms of drug resistance in non-small cell lung cancer - Proof of concept towards a systems pharmacology approach.

PubMed

Saafan, Hisham; Foerster, Sarah; Parra-Guillen, Zinnia P; Hammer, Elke; Michaelis, Martin; Cinatl, Jindrich; Völker, Uwe; Fröhlich, Holger; Kloft, Charlotte; Ritter, Christoph A

2016-10-30

Drug treatment of epidermal growth factor receptor (EGFR) positive non-small cell lung cancer has improved substantially by targeting activating mutations within the receptor tyrosine kinase domain. However, the development of drug resistance still limits this approach. As root causes, large heterogeneity between tumour entities but also within tumour cells have been suggested. Therefore, approaches to identify these multitude and complex mechanisms are urgently required. Affinity purification coupled with high resolution mass spectrometry was applied to isolate and characterise the EGFR interactome from HCC4006 non-small cell lung cancer cells and their variant HCC4006 r ERLO 0.5 adapted to grow in the presence of therapeutically relevant concentrations of erlotinib. Bioinformatics analyses were carried out to identify proteins and their related molecular functions that interact differentially with EGFR in the untreated state or when incubated with erlotinib prior to EGFR activation. Across all experimental conditions 375 proteins were detected to participate in the EGFR interactome, 90% of which constituted a complex protein interaction network that was bioinformatically reconstructed from literature data. Treatment of HCC4006 r ERLO 0.5 cells carrying a resistance phenotype to erlotinib was associated with an increase of protein levels of members of the clathrin-associated adaptor protein family AP2 (AP2A1, AP2A2, AP2B1), structural proteins of cytoskeleton rearrangement as well as signalling molecules such as Shc. Validation experiments confirmed activation of the Ras-Raf-Mek-Erk (MAPK)-pathway, of which Shc is an initiating adaptor molecule, in HCC4006 r ERLO 0.5 cells. Taken together, differential proteins in the EGFR interactome of HCC4006 r ERLO 0.5 cells were identified that could be related to multiple resistance mechanisms including alterations in growth factor receptor expression, cellular remodelling processes suggesting epithelial-to-mesenchymal transition as well as alterations in downstream signalling. Knowledge of these mechanisms is a pivotal step to build an integrative model of drug resistance in a systems pharmacology manner and to be able to investigate the interplay of these mechanisms and ultimately recommend combinatorial treatment strategies to overcome drug resistance. Copyright © 2016 Elsevier B.V. All rights reserved.

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Host cell interactome of PA protein of H5N1 influenza A virus in chicken cells.

PubMed

Wang, Qiao; Li, Qinghe; Liu, Ranran; Zheng, Maiqing; Wen, Jie; Zhao, Guiping

2016-03-16

Influenza A virus (IAV) heavily depends on viral-host protein interactions in order to replicate and spread. Identification of host factors that interact with viral proteins plays crucial roles in understanding the mechanism of IAV infection. Here we report the interaction landscape of H5N1 IAV PA protein in chicken cells through the use of affinity purification and mass spectrometry. PA protein was expressed in chicken cells and PA interacting complexes were captured by co-immunoprecipitation and analyzed by mass spectrometry. A total of 134 proteins were identified as PA-host interacting factors. Protein complexes including the minichromosome maintenance complex (MCM), 26S proteasome and the coat protein I (COPI) complex associated with PA in chicken cells, indicating the essential roles of these functional protein complexes during the course of IAV infection. Gene Ontology and pathway enrichment analysis both showed strong enrichment of PA interacting proteins in the category of DNA replication, covering genes such as PCNA, MCM2, MCM3, MCM4, MCM5 and MCM7. This study has uncovered the comprehensive interactome of H5N1 IAV PA protein in its chicken host and helps to establish the foundation for further investigation into the newly identified viral-host interactions. Influenza A virus (IAV) is a great threat to public health and avian production. However, the manner in which avian IAV recruits the host cellular machinery for replication and how the host antagonizes the IAV infection was previously poorly understood. Here we present the viral-host interactome of the H5N1 IAV PA protein and reveal the comprehensive association of host factors with PA. Copyright © 2016 Elsevier B.V. All rights reserved.

Oncoprotein AEG-1 is an endoplasmic reticulum RNA-binding protein whose interactome is enriched in organelle resident protein-encoding mRNAs.

PubMed

Hsu, Jack C-C; Reid, David W; Hoffman, Alyson M; Sarkar, Devanand; Nicchitta, Christopher V

2018-05-01

Astrocyte elevated gene-1 (AEG-1), an oncogene whose overexpression promotes tumor cell proliferation, angiogenesis, invasion, and enhanced chemoresistance, is thought to function primarily as a scaffolding protein, regulating PI3K/Akt and Wnt/β-catenin signaling pathways. Here we report that AEG-1 is an endoplasmic reticulum (ER) resident integral membrane RNA-binding protein (RBP). Examination of the AEG-1 RNA interactome by HITS-CLIP and PAR-CLIP methodologies revealed a high enrichment for endomembrane organelle-encoding transcripts, most prominently those encoding ER resident proteins, and within this cohort, for integral membrane protein-encoding RNAs. Cluster mapping of the AEG-1/RNA interaction sites demonstrated a normalized rank order interaction of coding sequence >5' untranslated region, with 3' untranslated region interactions only weakly represented. Intriguingly, AEG-1/membrane protein mRNA interaction sites clustered downstream from encoded transmembrane domains, suggestive of a role in membrane protein biogenesis. Secretory and cytosolic protein-encoding mRNAs were also represented in the AEG-1 RNA interactome, with the latter category notably enriched in genes functioning in mRNA localization, translational regulation, and RNA quality control. Bioinformatic analyses of RNA-binding motifs and predicted secondary structure characteristics indicate that AEG-1 lacks established RNA-binding sites though shares the property of high intrinsic disorder commonly seen in RBPs. These data implicate AEG-1 in the localization and regulation of secretory and membrane protein-encoding mRNAs and provide a framework for understanding AEG-1 function in health and disease. © 2018 Hsu et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

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

Interactome analysis reveals ZNF804A, a schizophrenia risk gene, as a novel component of protein translational machinery critical for embryonic neurodevelopment

PubMed Central

Zhou, Y; Dong, F; Lanz, T A; Reinhart, V; Li, M; Liu, L; Zou, J; Xi, H S; Mao, Y

2018-01-01

Recent genome-wide association studies identified over 100 genetic loci that significantly associate with schizophrenia (SZ). A top candidate gene, ZNF804A, was robustly replicated in different populations. However, its neural functions are largely unknown. Here we show in mouse that ZFP804A, the homolog of ZNF804A, is required for normal progenitor proliferation and neuronal migration. Using a yeast two-hybrid genome-wide screen, we identified novel interacting proteins of ZNF804A. Rather than transcriptional factors, genes involved in mRNA translation are highly represented in our interactome result. ZNF804A co-fractionates with translational machinery and modulates the translational efficiency as well as the mTOR pathway. The ribosomal protein RPSA interacts with ZNF804A and rescues the migration and translational defects caused by ZNF804A knockdown. RNA immunoprecipitation–RNAseq (RIP-Seq) identified transcripts bound to ZFP804A. Consistently, ZFP804A associates with many short transcripts involved in translational and mitochondrial regulation. Moreover, among the transcripts associated with ZFP804A, a SZ risk gene, neurogranin (NRGN), is one of ZFP804A targets. Interestingly, downregulation of ZFP804A decreases NRGN expression and overexpression of NRGN can ameliorate ZFP804A-mediated migration defect. To verify the downstream targets of ZNF804A, a Duolink in situ interaction assay confirmed genes from our RIP-Seq data as the ZNF804A targets. Thus, our work uncovered a novel mechanistic link of a SZ risk gene to neurodevelopment and translational control. The interactome-driven approach here is an effective way for translating genome-wide association findings into novel biological insights of human diseases. PMID:28924186

The Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism.

PubMed

Eagleson, Kathie L; Xie, Zhihui; Levitt, Pat

2017-03-01

People with autism spectrum disorder and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy-the influence of one gene on distinct phenotypes-raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multifunctional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with autism spectrum disorder, reduces transcription and disrupts socially relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways and has a complex protein interactome that is enriched in autism spectrum disorder and other NDD candidates. The interactome is coregulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, affecting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Characterization of the Human NEK7 Interactome Suggests Catalytic and Regulatory Properties Distinct from Those of NEK6

PubMed Central

2015-01-01

Human NEK7 is a regulator of cell division and plays an important role in growth and survival of mammalian cells. Human NEK6 and NEK7 are closely related, consisting of a conserved C-terminal catalytic domain and a nonconserved and disordered N-terminal regulatory domain, crucial to mediate the interactions with their respective proteins. Here, in order to better understand NEK7 cellular functions, we characterize the NEK7 interactome by two screening approaches: one using a yeast two-hybrid system and the other based on immunoprecipitation followed by mass spectrometry analysis. These approaches led to the identification of 61 NEK7 interactors that contribute to a variety of biological processes, including cell division. Combining additional interaction and phosphorylation assays from yeast two-hybrid screens, we validated CC2D1A, TUBB2B, MNAT1, and NEK9 proteins as potential NEK7 interactors and substrates. Notably, endogenous RGS2, TUBB, MNAT1, NEK9, and PLEKHA8 localized with NEK7 at key sites throughout the cell cycle, especially during mitosis and cytokinesis. Furthermore, we obtained evidence that the closely related kinases NEK6 and NEK7 do not share common interactors, with the exception of NEK9, and display different modes of protein interaction, depending on their N- and C-terminal regions, in distinct fashions. In summary, our work shows for the first time a comprehensive NEK7 interactome that, combined with functional in vitro and in vivo assays, suggests that NEK7 is a multifunctional kinase acting in different cellular processes in concert with cell division signaling and independently of NEK6. PMID:25093993

Network-based study reveals potential infection pathways of hepatitis-C leading to various diseases.

PubMed

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement.

Network-Based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement. PMID:24743187

Characterization of clinical signs in the human interactome.

PubMed

Chagoyen, Monica; Pazos, Florencio

2016-06-15

Many diseases are related by shared associated molecules and pathways, exhibiting comorbidities and common phenotypes, an indication of the continuous nature of the human pathological landscape. Although it is continuous, this landscape is always partitioned into discrete diseases when studied at the molecular level. Clinical signs are also important phenotypic descriptors that can reveal the molecular mechanisms that underlie pathological states, but have seldom been the subject of systemic research. Here, we quantify the modular nature of the clinical signs associated with genetic diseases in the human interactome. We found that clinical signs are reflected as modules at the molecular network level, to at least to the same extent as diseases. They can thus serve as a valid complementary partition of the human pathological landscape, with implications for etiology research, diagnosis and treatment. monica.chagoyen@cnb.csic.es Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The RNA-binding protein repertoire of embryonic stem cells.

PubMed

Kwon, S Chul; Yi, Hyerim; Eichelbaum, Katrin; Föhr, Sophia; Fischer, Bernd; You, Kwon Tae; Castello, Alfredo; Krijgsveld, Jeroen; Hentze, Matthias W; Kim, V Narry

2013-09-01

RNA-binding proteins (RBPs) have essential roles in RNA-mediated gene regulation, and yet annotation of RBPs is limited mainly to those with known RNA-binding domains. To systematically identify the RBPs of embryonic stem cells (ESCs), we here employ interactome capture, which combines UV cross-linking of RBP to RNA in living cells, oligo(dT) capture and MS. From mouse ESCs (mESCs), we have defined 555 proteins constituting the mESC mRNA interactome, including 283 proteins not previously annotated as RBPs. Of these, 68 new RBP candidates are highly expressed in ESCs compared to differentiated cells, implicating a role in stem-cell physiology. Two well-known E3 ubiquitin ligases, Trim25 (also called Efp) and Trim71 (also called Lin41), are validated as RBPs, revealing a potential link between RNA biology and protein-modification pathways. Our study confirms and expands the atlas of RBPs, providing a useful resource for the study of the RNA-RBP network in stem cells.

SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes.

PubMed

Brannan, Kristopher W; Jin, Wenhao; Huelga, Stephanie C; Banks, Charles A S; Gilmore, Joshua M; Florens, Laurence; Washburn, Michael P; Van Nostrand, Eric L; Pratt, Gabriel A; Schwinn, Marie K; Daniels, Danette L; Yeo, Gene W

2016-10-20

RNA metabolism is controlled by an expanding, yet incomplete, catalog of RNA-binding proteins (RBPs), many of which lack characterized RNA binding domains. Approaches to expand the RBP repertoire to discover non-canonical RBPs are currently needed. Here, HaloTag fusion pull down of 12 nuclear and cytoplasmic RBPs followed by quantitative mass spectrometry (MS) demonstrates that proteins interacting with multiple RBPs in an RNA-dependent manner are enriched for RBPs. This motivated SONAR, a computational approach that predicts RNA binding activity by analyzing large-scale affinity precipitation-MS protein-protein interactomes. Without relying on sequence or structure information, SONAR identifies 1,923 human, 489 fly, and 745 yeast RBPs, including over 100 human candidate RBPs that contain zinc finger domains. Enhanced CLIP confirms RNA binding activity and identifies transcriptome-wide RNA binding sites for SONAR-predicted RBPs, revealing unexpected RNA binding activity for disease-relevant proteins and DNA binding proteins. Copyright © 2016 Elsevier Inc. All rights reserved.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

PubMed

Javierre, Biola M; Burren, Oliver S; Wilder, Steven P; Kreuzhuber, Roman; Hill, Steven M; Sewitz, Sven; Cairns, Jonathan; Wingett, Steven W; Várnai, Csilla; Thiecke, Michiel J; Burden, Frances; Farrow, Samantha; Cutler, Antony J; Rehnström, Karola; Downes, Kate; Grassi, Luigi; Kostadima, Myrto; Freire-Pritchett, Paula; Wang, Fan; Stunnenberg, Hendrik G; Todd, John A; Zerbino, Daniel R; Stegle, Oliver; Ouwehand, Willem H; Frontini, Mattia; Wallace, Chris; Spivakov, Mikhail; Fraser, Peter

2016-11-17

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

Shatsky, Maxim; Allen, Simon; Gold, Barbara

Numerous affinity purification – mass-spectrometry (AP-MS) and yeast two hybrid (Y2H) screens have each defined thousands of pairwise protein-protein interactions (PPIs), most between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial Y2H and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared to the nine published interactomes, our two networks are smaller; are much less highly connected; have significantly lower false discovery rates; and are much moremore » enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays. Lastly, our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.« less

Deconstruction of the beaten Path-Sidestep interaction network provides insights into neuromuscular system development

PubMed Central

Li, Hanqing; Watson, Ash; Olechwier, Agnieszka; Anaya, Michael; Sorooshyari, Siamak K; Harnett, Dermott P; Lee, Hyung-Kook (Peter); Vielmetter, Jost; Fares, Mario A; Garcia, K Christopher; Özkan, Engin

2017-01-01

An ‘interactome’ screen of all Drosophila cell-surface and secreted proteins containing immunoglobulin superfamily (IgSF) domains discovered a network formed by paralogs of Beaten Path (Beat) and Sidestep (Side), a ligand-receptor pair that is central to motor axon guidance. Here we describe a new method for interactome screening, the Bio-Plex Interactome Assay (BPIA), which allows identification of many interactions in a single sample. Using the BPIA, we ‘deorphanized’ four more members of the Beat-Side network. We confirmed interactions using surface plasmon resonance. The expression patterns of beat and side genes suggest that Beats are neuronal receptors for Sides expressed on peripheral tissues. side-VI is expressed in muscle fibers targeted by the ISNb nerve, as well as at growth cone choice points and synaptic targets for the ISN and TN nerves. beat-V genes, encoding Side-VI receptors, are expressed in ISNb and ISN motor neurons. PMID:28829740

The cardiac TBX5 interactome reveals a chromatin remodeling network essential for cardiac septation

PubMed Central

Waldron, Lauren; Steimle, Jeffrey D.; Greco, Todd M.; Gomez, Nicholas C.; Dorr, Kerry M.; Kweon, Junghun; Temple, Brenda; Yang, Xinan Holly; Wilczewski, Caralynn M.; Davis, Ian J.; Cristea, Ileana M.; Moskowitz, Ivan P.; Conlon, Frank L.

2016-01-01

SUMMARY Human mutations in the cardiac transcription factor gene TBX5 cause Congenital Heart Disease (CHD), however the underlying mechanism is unknown. We report characterization of the endogenous TBX5 cardiac interactome and demonstrate that TBX5, long considered a transcriptional activator, interacts biochemically and genetically with the Nucleosome Remodeling and Deacetylase (NuRD) repressor complex. Incompatible gene programs are repressed by TBX5 in the developing heart. CHD missense mutations that disrupt the TBX5-NuRD interaction cause depression of a subset of repressed genes. Furthermore, the TBX5-NuRD interaction is required for heart development. Phylogenetic analysis showed that the TBX5-NuRD interaction domain evolved during early diversification of vertebrates, simultaneous with the evolution of cardiac septation. Collectively, this work defines a TBX5-NuRD interaction essential to cardiac development and the evolution of the mammalian heart, and when altered may contribute to human CHD. PMID:26859351

Protein-mRNA interactome capture: cartography of the mRNP landscape

PubMed Central

Ryder, Sean P.

2016-01-01

RNA-binding proteins play a variety of roles in cellular physiology. Some regulate mRNA processing, mRNA abundance, and translation efficiency. Some fight off invader RNA through small RNA-driven silencing pathways. Others sense foreign sequences in the form of double-stranded RNA and activate the innate immune response. Yet others, for example cytoplasmic aconitase, act as bi-functional proteins, processing metabolites in one conformation and regulating metabolic gene expression in another. Not all are involved in gene regulation. Some play structural roles, for example, connecting the translational machinery to the endoplasmic reticulum outer membrane. Despite their pervasive role and relative importance, it has remained difficult to identify new RNA-binding proteins in a systematic, unbiased way. A recent body of literature from several independent labs has defined robust, easily adaptable protocols for mRNA interactome discovery. In this review, I summarize the methods and review some of the intriguing findings from their application to a wide variety of biological systems. PMID:29098073

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae.

PubMed

Uthe, Henriette; Vanselow, Jens T; Schlosser, Andreas

2017-02-27

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15 N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis.

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

PubMed

Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

Global changes of the RNA-bound proteome during the maternal-to-zygotic transition in Drosophila

PubMed Central

Sysoev, Vasiliy O.; Fischer, Bernd; Frese, Christian K.; Gupta, Ishaan; Krijgsveld, Jeroen; Hentze, Matthias W.; Castello, Alfredo; Ephrussi, Anne

2016-01-01

The maternal-to-zygotic transition (MZT) is a process that occurs in animal embryos at the earliest developmental stages, during which maternally deposited mRNAs and other molecules are degraded and replaced by products of the zygotic genome. The zygotic genome is not activated immediately upon fertilization, and in the pre-MZT embryo post-transcriptional control by RNA-binding proteins (RBPs) orchestrates the first steps of development. To identify relevant Drosophila RBPs organism-wide, we refined the RNA interactome capture method for comparative analysis of the pre- and post-MZT embryos. We determine 523 proteins as high-confidence RBPs, half of which were not previously reported to bind RNA. Comparison of the RNA interactomes of pre- and post-MZT embryos reveals high dynamicity of the RNA-bound proteome during early development, and suggests active regulation of RNA binding of some RBPs. This resource provides unprecedented insight into the system of RBPs that govern the earliest steps of Drosophila development. PMID:27378189

The mRNA-bound proteome of the early fly embryo

PubMed Central

Wessels, Hans-Hermann; Imami, Koshi; Baltz, Alexander G.; Kolinski, Marcin; Beldovskaya, Anastasia; Selbach, Matthias; Small, Stephen; Ohler, Uwe; Landthaler, Markus

2016-01-01

Early embryogenesis is characterized by the maternal to zygotic transition (MZT), in which maternally deposited messenger RNAs are degraded while zygotic transcription begins. Before the MZT, post-transcriptional gene regulation by RNA-binding proteins (RBPs) is the dominant force in embryo patterning. We used two mRNA interactome capture methods to identify RBPs bound to polyadenylated transcripts within the first 2 h of Drosophila melanogaster embryogenesis. We identified a high-confidence set of 476 putative RBPs and confirmed RNA-binding activities for most of 24 tested candidates. Most proteins in the interactome are known RBPs or harbor canonical RBP features, but 99 exhibited previously uncharacterized RNA-binding activity. mRNA-bound RBPs and TFs exhibit distinct expression dynamics, in which the newly identified RBPs dominate the first 2 h of embryonic development. Integrating our resource with in situ hybridization data from existing databases showed that mRNAs encoding RBPs are enriched in posterior regions of the early embryo, suggesting their general importance in posterior patterning and germ cell maturation. PMID:27197210

Deep-proteome mapping of WM-266-4 human metastatic melanoma cells: From oncogenic addiction to druggable targets

PubMed Central

Litou, Zoi I.; Konstandi, Ourania A.; Giannopoulou, Aikaterini F.; Anastasiadou, Ema; Voutsinas, Gerassimos E.; Tsangaris, George Th.; Stravopodis, Dimitrios J.

2017-01-01

Cutaneous melanoma is a malignant tumor of skin melanocytes that are pigment-producing cells located in the basal layer (stratum basale) of epidermis. Accumulation of genetic mutations within their oncogenes or tumor-suppressor genes compels melanocytes to aberrant proliferation and spread to distant organs of the body, thereby resulting in severe and/or lethal malignancy. Metastatic melanoma’s heavy mutational load, molecular heterogeneity and resistance to therapy necessitate the development of novel biomarkers and drug-based protocols that target key proteins involved in perpetuation of the disease. To this direction, we have herein employed a nano liquid chromatography-tandem mass spectrometry (nLC-MS/MS) proteomics technology to profile the deep-proteome landscape of WM-266-4 human metastatic melanoma cells. Our advanced melanoma-specific catalogue proved to contain 6,681 unique proteins, which likely constitute the hitherto largest single cell-line-derived proteomic collection of the disease. Through engagement of UNIPROT, DAVID, KEGG, PANTHER, INTACT, CYTOSCAPE, dbEMT and GAD bioinformatics resources, WM-266-4 melanoma proteins were categorized according to their sub-cellular compartmentalization, function and tumorigenicity, and successfully reassembled in molecular networks and interactomes. The obtained data dictate the presence of plastically inter-converted sub-populations of non-cancer and cancer stem cells, and also indicate the oncoproteomic resemblance of melanoma to glioma and lung cancer. Intriguingly, WM-266-4 cells seem to be subjected to both epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial (MET) programs, with 1433G and ADT3 proteins being identified in the EMT/MET molecular interface. Oncogenic addiction of WM-266-4 cells to autocrine/paracrine signaling of IL17-, DLL3-, FGF(2/13)- and OSTP-dependent sub-routines suggests their critical contribution to the metastatic melanoma chemotherapeutic refractoriness. Interestingly, the 1433G family member that is shared between the BRAF- and EMT/MET-specific interactomes likely emerges as a novel and promising druggable target for the malignancy. Derailed proliferation and metastatic capacity of WM-266-4 cells could also derive from their metabolic addiction to pathways associated with glutamate/ammonia, propanoate and sulfur homeostasis, whose successful targeting may prove beneficial for advanced melanoma-affected patients. PMID:28158294

Impact of Eclipse of 21 August 2017 ON the Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Knupp, K.

2017-12-01

The (total) solar eclipse of 21 August 2017 presents a prodigious opportunity to improve our understanding of the physical response of decreases in turbulence within the ABL produced by a rapid reduction in solar radiation, since the transition in this eclipse case, close to local solar noon, is more rapid than at natural sunset. A mesoscale network of three UAH atmospheric profiling systems will be set up around Clarksville, TN, and Hopkinsville, KY, to document the details of the physical response of the ABL to the rapid decrease in solar radiation. The region offers a heterogeneous surface, including expansive agricultural and forested regions. Data from the following mobile systems will be examined: Mobile Integrated Profiling System (MIPS) with a 915 MHz Doppler wind profiler, X-band Profiling Radar (XPR), Microwave Profiling Radiometer (MPR), lidar ceilometer, and Doppler mini-sodar, Rapidly Deployable Atmospheric Profiling System (RaDAPS) with a 915 MHz Doppler wind profiler, MPR, lidar ceilometer, Doppler mini-sodar, Mobile Doppler Lidar and Sounding system (MoDLS) with a Doppler Wind Lidar and MPR. A tethered balloon will provide high temporal and vertical resolution in situ sampling of the surface layer temperature and humidity vertical profiles over the lowest 120 m AGL. Two of the profiling systems (MIPS and MoDLS) will include 20 Hz sonic anemometer measurements for documentation of velocity component (u, v, w) variance, buoyancy flux, and momentum flux. The Mobile Alabama X-band (MAX) dual polarization radar will be paired with the Ft. Campbell WSR-88D radar, located 29 km east of the MAX, to provide dual Doppler radar coverage of flow within the ABL over the profiler domain. The measurements during this eclipse will also provide information on the response of insects to rapidly changing lighting conditions. During the natural afternoon-to-evening transition, daytime insect concentrations decrease rapidly, and stronger-flying nighttime flyers emerge rapidly following sunset. We hypothesize that a similar transition will occur on a limited basis: nighttime flyers will emerge, but the daytime flyers will not rapidly disappear due to the short time scale of the darkness. This insect transition will be measured with the radar wind profilers and the MAX and WSR-88D dual polarization radars.

Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges.

PubMed

Maryáš, Josef; Faktor, Jakub; Dvořáková, Monika; Struhárová, Iva; Grell, Peter; Bouchal, Pavel

2014-03-01

Metastases are responsible for most of the cases of death in patients with solid tumors. There is thus an urgent clinical need of better understanding the exact molecular mechanisms and finding novel therapeutics targets and biomarkers of metastatic disease of various tumors. Metastases are formed in a complicated biological process called metastatic cascade. Up to now, proteomics has enabled the identification of number of metastasis-associated proteins and potential biomarkers in cancer tissues, microdissected cells, model systems, and secretomes. Expression profiles and biological role of key proteins were confirmed in verification and functional experiments. This communication reviews these observations and analyses the methodological aspects of the proteomics approaches used. Moreover, it reviews contribution of current proteomics in the field of functional characterization and interactome analysis of proteins involved in various events in metastatic cascade. It is evident that ongoing technical progress will further increase proteome coverage and sample capacity of proteomics technologies, giving complex answers to clinical and functional questions asked. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

PubMed

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Net Venn - An integrated network analysis web platform for gene lists

USDA-ARS?s Scientific Manuscript database

Many lists containing biological identifiers such as gene lists have been generated in various genomics projects. Identifying the overlap among gene lists can enable us to understand the similarities and differences between the datasets. Here, we present an interactome network-based web application...

Profiling of 3696 Nuclear Receptor-Coregulator Interactions: A Resource for Biological and Clinical Discovery.

PubMed

Broekema, Marjoleine F; Hollman, Danielle A A; Koppen, Arjen; van den Ham, Henk-Jan; Melchers, Diana; Pijnenburg, Dirk; Ruijtenbeek, Rob; van Mil, Saskia W C; Houtman, René; Kalkhoven, Eric

2018-06-01

Nuclear receptors (NRs) are ligand-inducible transcription factors that play critical roles in metazoan development, reproduction, and physiology and therefore are implicated in a broad range of pathologies. The transcriptional activity of NRs critically depends on their interaction(s) with transcriptional coregulator proteins, including coactivators and corepressors. Short leucine-rich peptide motifs in these proteins (LxxLL in coactivators and LxxxIxxxL in corepressors) are essential and sufficient for NR binding. With 350 different coregulator proteins identified to date and with many coregulators containing multiple interaction motifs, an enormous combinatorial potential is present for selective NR-mediated gene regulation. However, NR-coregulator interactions have often been determined experimentally on a one-to-one basis across diverse experimental conditions. In addition, NR-coregulator interactions are difficult to predict because the molecular determinants that govern specificity are not well established. Therefore, many biologically and clinically relevant NR-coregulator interactions may remain to be discovered. Here, we present a comprehensive overview of 3696 NR-coregulator interactions by systematically characterizing the binding of 24 nuclear receptors with 154 coregulator peptides. We identified unique ligand-dependent NR-coregulator interaction profiles for each NR, confirming many well-established NR-coregulator interactions. Hierarchical clustering based on the NR-coregulator interaction profiles largely recapitulates the classification of NR subfamilies based on the primary amino acid sequences of the ligand-binding domains, indicating that amino acid sequence is an important, although not the only, molecular determinant in directing and fine-tuning NR-coregulator interactions. This NR-coregulator peptide interactome provides an open data resource for future biological and clinical discovery as well as NR-based drug design.

Emory University: "LC-MS analysis of PRAS40 protein-protein interactions" | Office of Cancer Genomics

Cancer.gov

This study focuses on subcellular localization and interactome of nuclear PRAS40 in HeLa cells.  Read the abstract.  Experimental Approaches Read the detailed Experimental Approaches. If you cannot access the manuscript, or if you have additional questions, please email Andrei Ivanov.

Insights into the polerovirus-plant interactome revealed by co-immunoprecipitation and mass spectrometry

USDA-ARS?s Scientific Manuscript database

The identification of host proteins that interact with virus proteins is a major challenge for the field of virology. Phloem-limited viruses pose extraordinary challenges for in vivo protein interaction experiments because these viruses are localized in very few and highly specialized host cells. ...

MicroRNA profiling reveals unique miRNA signatures in IGF-1 treated embryonic striatal stem cell fate decisions in striatal neurogenesis in vitro.

PubMed

Pati, Soumya; Supeno, Nor Entan; Muthuraju, Sangu; Abdul Hadi, Raisah; Ghani, Abdul Rahman Izaini; Idris, Fauziah Mohamad; Maletic-Savatic, Mirjana; Abdullah, Jafri Malin; Jaafar, Hasnan

2014-01-01

The striatum is considered to be the central processing unit of the basal ganglia in locomotor activity and cognitive function of the brain. IGF-1 could act as a control switch for the long-term proliferation and survival of EGF+bFGF-responsive cultured embryonic striatal stem cell (ESSC), while LIF imposes a negative impact on cell proliferation. The IGF-1-treated ESSCs also showed elevated hTERT expression with demonstration of self-renewal and trilineage commitment (astrocytes, oligodendrocytes, and neurons). In order to decipher the underlying regulatory microRNA (miRNA)s in IGF-1/LIF-treated ESSC-derived neurogenesis, we performed in-depth miRNA profiling at 12 days in vitro and analyzed the candidates using the Partek Genome Suite software. The annotated miRNA fingerprints delineated the differential expressions of miR-143, miR-433, and miR-503 specific to IGF-1 treatment. Similarly, the LIF-treated ESSCs demonstrated specific expression of miR-326, miR-181, and miR-22, as they were nonsignificant in IGF-treated ESSCs. To elucidate the possible downstream pathways, we performed in silico mapping of the said miRNAs into ingenuity pathway analysis. Our findings revealed the important mRNA targets of the miRNAs and suggested specific interactomes. The above studies introduced a new genre of miRNAs for ESSC-based neuroregenerative therapeutic applications.

Emory University: "LC-MS analysis of PRAS40 protein-protein interactions" | Office of Cancer Genomics

Cancer.gov

This study focuses on subcellular localization and interactome of nuclear PRAS40 in HeLa cells.  Read the abstract.  Experimental Approaches Read the detailed Experimental Approaches. If you cannot access the manuscript, or if you have additional questions, please email Andrei Ivanov. Data

Use of The Yeast Two-Hybrid System to Identify Targets of Fungal Effectors

USDA-ARS?s Scientific Manuscript database

The yeast-two hybrid (Y2H) system is a binary method widely used to determine direct interactions between paired proteins. Although having certain limitations, this method has become one of the two main systemic tools (along with affinity purification/mass spectrometry) for interactome mapping in mo...

The interactomic analysis reveals pathogenic protein networks in Phomopsis longicolla underlying seed decay of soybean

USDA-ARS?s Scientific Manuscript database

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease causes poor seed quality and is one of the most economically important diseases in soybean. The objectives of this study were to perform ...

BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference.

PubMed

Garcia-Garcia, Javier; Schleker, Sylvia; Klein-Seetharaman, Judith; Oliva, Baldo

2012-07-01

Protein-protein interactions (PPIs) play a crucial role in biology, and high-throughput experiments have greatly increased the coverage of known interactions. Still, identification of complete inter- and intraspecies interactomes is far from being complete. Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs). Here, we present the BIANA (Biologic Interactions and Network Analysis) Interolog Prediction Server (BIPS), which offers a web-based interface to facilitate PPI predictions based on interolog information. BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases. Additional metadata can be used to improve the reliability of the predicted interactions. Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach. The specificity is between 72 and 98%, whereas sensitivity varies between 1 and 59%, depending on the sequence identity cut-off used to calculate similarities between sequences. BIPS is freely accessible at http://sbi.imim.es/BIPS.php.

On an algorithmic definition for the components of the minimal cell.

PubMed

Martínez, Octavio; Reyes-Valdés, M Humberto

2018-01-01

Living cells are highly complex systems comprising a multitude of elements that are engaged in the many convoluted processes observed during the cell cycle. However, not all elements and processes are essential for cell survival and reproduction under steady-state environmental conditions. To distinguish between essential from expendable cell components and thus define the 'minimal cell' and the corresponding 'minimal genome', we postulate that the synthesis of all cell elements can be represented as a finite set of binary operators, and within this framework we show that cell elements that depend on their previous existence to be synthesized are those that are essential for cell survival. An algorithm to distinguish essential cell elements is presented and demonstrated within an interactome. Data and functions implementing the algorithm are given as supporting information. We expect that this algorithmic approach will lead to the determination of the complete interactome of the minimal cell, which could then be experimentally validated. The assumptions behind this hypothesis as well as its consequences for experimental and theoretical biology are discussed.

Interactome Screening Identifies the ER Luminal Chaperone Hsp47 as a Regulator of the Unfolded Protein Response Transducer IRE1α.

PubMed

Sepulveda, Denisse; Rojas-Rivera, Diego; Rodríguez, Diego A; Groenendyk, Jody; Köhler, Andres; Lebeaupin, Cynthia; Ito, Shinya; Urra, Hery; Carreras-Sureda, Amado; Hazari, Younis; Vasseur-Cognet, Mireille; Ali, Maruf M U; Chevet, Eric; Campos, Gisela; Godoy, Patricio; Vaisar, Tomas; Bailly-Maitre, Béatrice; Nagata, Kazuhiro; Michalak, Marek; Sierralta, Jimena; Hetz, Claudio

2018-01-18

Maintenance of endoplasmic reticulum (ER) proteostasis is controlled by a dynamic signaling network known as the unfolded protein response (UPR). IRE1α is a major UPR transducer, determining cell fate under ER stress. We used an interactome screening to unveil several regulators of the UPR, highlighting the ER chaperone Hsp47 as the major hit. Cellular and biochemical analysis indicated that Hsp47 instigates IRE1α signaling through a physical interaction. Hsp47 directly binds to the ER luminal domain of IRE1α with high affinity, displacing the negative regulator BiP from the complex to facilitate IRE1α oligomerization. The regulation of IRE1α signaling by Hsp47 is evolutionarily conserved as validated using fly and mouse models of ER stress. Hsp47 deficiency sensitized cells and animals to experimental ER stress, revealing the significance of Hsp47 to global proteostasis maintenance. We conclude that Hsp47 adjusts IRE1α signaling by fine-tuning the threshold to engage an adaptive UPR. Copyright © 2018 Elsevier Inc. All rights reserved.

Competing endogenous RNA and interactome bioinformatic analyses on human telomerase.

PubMed

Arancio, Walter; Pizzolanti, Giuseppe; Genovese, Swonild Ilenia; Baiamonte, Concetta; Giordano, Carla

2014-04-01

We present a classic interactome bioinformatic analysis and a study on competing endogenous (ce) RNAs for hTERT. The hTERT gene codes for the catalytic subunit and limiting component of the human telomerase complex. Human telomerase reverse transcriptase (hTERT) is essential for the integrity of telomeres. Telomere dysfunctions have been widely reported to be involved in aging, cancer, and cellular senescence. The hTERT gene network has been analyzed using the BioGRID interaction database (http://thebiogrid.org/) and related analysis tools such as Osprey (http://biodata.mshri.on.ca/osprey/servlet/Index) and GeneMANIA (http://genemania.org/). The network of interaction of hTERT transcripts has been further analyzed following the competing endogenous (ce) RNA hypotheses (messenger [m] RNAs cross-talk via micro [mi] RNAs) using the miRWalk database and tools (www.ma.uni-heidelberg.de/apps/zmf/mirwalk/). These analyses suggest a role for Akt, nuclear factor-κB (NF-κB), heat shock protein 90 (HSP90), p70/p80 autoantigen, 14-3-3 proteins, and dynein in telomere functions. Roles for histone acetylation/deacetylation and proteoglycan metabolism are also proposed.

Distinctive Behaviors of Druggable Proteins in Cellular Networks

PubMed Central

Workman, Paul; Al-Lazikani, Bissan

2015-01-01

The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. PMID:26699810

Factors affecting interactome-based prediction of human genes associated with clinical signs.

PubMed

González-Pérez, Sara; Pazos, Florencio; Chagoyen, Mónica

2017-07-17

Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome. Our analysis reveals that these approaches can locate genes associated with clinical signs with variable performance that depends on the sign and associated disease. We analyzed several clinical and biological factors that explain these variable results, including number of genes involved (mono- vs. oligogenic diseases), mode of inheritance, type of clinical sign and gene product function. Our results indicate that the characteristics of the clinical signs and their related diseases should be considered for interpreting the results of network-prediction methods, such as those aimed at discovering disease-related genes and variants. These results are important due the increasing use of clinical signs as an alternative to diseases for studying the molecular basis of human pathologies.

Characterization of hampin/MSL1 as a node in the nuclear interactome

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

Dmitriev, Ruslan I.; Korneenko, Tatyana V.; Department of Physiology, Pharmacology, Metabolism, and Cardiovascular Sciences, University of Toledo College of Medicine, Toledo, OH 43614

2007-04-20

Hampin, homolog of Drosophila MSL1, is a partner of histone acetyltransferase MYST1/MOF. Functions of these proteins remain poorly understood beyond their participation in chromatin remodeling complex MSL. In order to identify new proteins interacting with hampin, we screened a mouse cDNA library in yeast two-hybrid system with mouse hampin as bait and found five high-confidence interactors: MYST1, TPR proteins TTC4 and KIAA0103, NOP17 (homolog of a yeast nucleolar protein), and transcription factor GC BP. Subsequently, all these proteins were used as baits in library screenings and more new interactions were found: tumor suppressor RASSF1C and spliceosome component PRP3 for KIAA0103,more » ring finger RNF10 for RASSF1C, and RNA polymerase II regulator NELF-C for MYST1. The majority of the observed interactions was confirmed in vitro by pull-down of bacterially expressed proteins. Reconstruction of a fragment of mammalian interactome suggests that hampin may be linked to diverse regulatory processes in the nucleus.« less

The nuclear DEK interactome supports multi-functionality.

PubMed

Smith, Eric A; Krumpelbeck, Eric F; Jegga, Anil G; Prell, Malte; Matrka, Marie M; Kappes, Ferdinand; Greis, Kenneth D; Ali, Abdullah M; Meetei, Amom R; Wells, Susanne I

2018-01-01

DEK is an oncoprotein that is overexpressed in many forms of cancer and participates in numerous cellular pathways. Of these different pathways, relevant interacting partners and functions of DEK are well described in regard to the regulation of chromatin structure, epigenetic marks, and transcription. Most of this understanding was derived by investigating DNA-binding and chromatin processing capabilities of the oncoprotein. To facilitate the generation of mechanism-driven hypotheses regarding DEK activities in underexplored areas, we have developed the first DEK interactome model using tandem-affinity purification and mass spectrometry. With this approach, we identify IMPDH2, DDX21, and RPL7a as novel DEK binding partners, hinting at new roles for the oncogene in de novo nucleotide biosynthesis and ribosome formation. Additionally, a hydroxyurea-specific interaction with replication protein A (RPA) was observed, suggesting that a DEK-RPA complex may form in response to DNA replication fork stalling. Taken together, these findings highlight diverse activities for DEK across cellular pathways and support a model wherein this molecule performs a plethora of functions. © 2017 Wiley Periodicals, Inc.

Interactome Analysis of Microtubule-targeting Agents Reveals Cytotoxicity Bases in Normal Cells.

PubMed

Gutiérrez-Escobar, Andrés Julián; Méndez-Callejas, Gina

2017-12-01

Cancer causes millions of deaths annually and microtubule-targeting agents (MTAs) are the most commonly-used anti-cancer drugs. However, the high toxicity of MTAs on normal cells raises great concern. Due to the non-selectivity of MTA targets, we analyzed the interaction network in a non-cancerous human cell. Subnetworks of fourteen MTAs were reconstructed and the merged network was compared against a randomized network to evaluate the functional richness. We found that 71.4% of the MTA interactome nodes are shared, which affects cellular processes such as apoptosis, cell differentiation, cell cycle control, stress response, and regulation of energy metabolism. Additionally, possible secondary targets were identified as client proteins of interphase microtubules. MTAs affect apoptosis signaling pathways by interacting with client proteins of interphase microtubules, suggesting that their primary targets are non-tumor cells. The paclitaxel and doxorubicin networks share essential topological axes, suggesting synergistic effects. This may explain the exacerbated toxicity observed when paclitaxel and doxorubicin are used in combination for cancer treatment. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

NASA Astrophysics Data System (ADS)

Han, Jing-Dong J.; Bertin, Nicolas; Hao, Tong; Goldberg, Debra S.; Berriz, Gabriel F.; Zhang, Lan V.; Dupuy, Denis; Walhout, Albertha J. M.; Cusick, Michael E.; Roth, Frederick P.; Vidal, Marc

2004-07-01

In apparently scale-free protein-protein interaction networks, or `interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the `hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: `party' hubs, which interact with most of their partners simultaneously, and `date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes-or modules -to each other, whereas party hubs function inside modules.

A Synthetic Coiled-Coil Interactome Provides Heterospecific Modules for Molecular Engineering

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

Reinke, Aaron W.; Grant, Robert A.; Keating, Amy E.

2010-06-21

The versatile coiled-coil protein motif is widely used to induce and control macromolecular interactions in biology and materials science. Yet the types of interaction patterns that can be constructed using known coiled coils are limited. Here we greatly expand the coiled-coil toolkit by measuring the complete pairwise interactions of 48 synthetic coiled coils and 7 human bZIP coiled coils using peptide microarrays. The resulting 55-member protein 'interactome' includes 27 pairs of interacting peptides that preferentially heteroassociate. The 27 pairs can be used in combinations to assemble sets of 3 to 6 proteins that compose networks of varying topologies. Of specialmore » interest are heterospecific peptide pairs that participate in mutually orthogonal interactions. Such pairs provide the opportunity to dimerize two separate molecular systems without undesired crosstalk. Solution and structural characterization of two such sets of orthogonal heterodimers provide details of their interaction geometries. The orthogonal pair, along with the many other network motifs discovered in our screen, provide new capabilities for synthetic biology and other applications.« less

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae

PubMed Central

Uthe, Henriette; Vanselow, Jens T.; Schlosser, Andreas

2017-01-01

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis. PMID:28240253

Polyubiquitin-Photoactivatable Crosslinking Reagents for Mapping Ubiquitin Interactome Identify Rpn1 as a Proteasome Ubiquitin-Associating Subunit.

PubMed

Chojnacki, Michal; Mansour, Wissam; Hameed, Dharjath S; Singh, Rajesh K; El Oualid, Farid; Rosenzweig, Rina; Nakasone, Mark A; Yu, Zanlin; Glaser, Fabian; Kay, Lewis E; Fushman, David; Ovaa, Huib; Glickman, Michael H

2017-04-20

Ubiquitin (Ub) signaling is a diverse group of processes controlled by covalent attachment of small protein Ub and polyUb chains to a range of cellular protein targets. The best documented Ub signaling pathway is the one that delivers polyUb proteins to the 26S proteasome for degradation. However, studies of molecular interactions involved in this process have been hampered by the transient and hydrophobic nature of these interactions and the lack of tools to study them. Here, we develop Ub-phototrap (Ub PT ), a synthetic Ub variant containing a photoactivatable crosslinking side chain. Enzymatic polymerization into chains of defined lengths and linkage types provided a set of reagents that led to identification of Rpn1 as a third proteasome ubiquitin-associating subunit that coordinates docking of substrate shuttles, unloading of substrates, and anchoring of polyUb conjugates. Our work demonstrates the value of Ub PT , and we expect that its future uses will help define and investigate the ubiquitin interactome. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improvement of band gap profile in Cu(InGa)Se{sub 2} solar cells through rapid thermal annealing

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

Chen, D.S.; College of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 200090; Yang, J.

Highlights: • Proper RTA treatment can effectively optimize band gap profile to more expected level. • Inter-diffusion of atoms account for the improvement of the graded band gap profile. • The variation of the band gap profile created an absolute gain in the efficiency by 1.22%. - Abstract: In the paper, the effect of rapid thermal annealing on non-optimal double-graded band gap profiles was investigated by using X-ray photoelectron spectroscopy and capacitance–voltage measurement techniques. Experimental results revealed that proper rapid thermal annealing treatment can effectively improve band gap profile to more optimal level. The annealing treatment could not only reducemore » the values of front band gap and minimum band gap, but also shift the position of the minimum band gap toward front electrode and enter into space charge region. In addition, the thickness of Cu(InGa)Se{sub 2} thin film decreased by 25 nm after rapid thermal annealing treatment. All of these modifications were attributed to the inter-diffusion of atoms during thermal treatment process. Simultaneously, the variation of the band gap profile created an absolute gain in the efficiency by 1.22%, short-circuit current density by 2.16 mA/cm{sup 2} and filled factor by 3.57%.« less

Notch3 Interactome Analysis Identified WWP2 as a Negative Regulator of Notch3 Signaling in Ovarian Cancer

PubMed Central

Guan, Bin; Wu, Ren-Chin; Zhu, Heng; Blackshaw, Seth; Shih, Ie-Ming; Wang, Tian-Li

2014-01-01

The Notch3 signaling pathway is thought to play a critical role in cancer development, as evidenced by the Notch3 amplification and rearrangement observed in human cancers. However, the molecular mechanism by which Notch3 signaling contributes to tumorigenesis is largely unknown. In an effort to identify the molecular modulators of the Notch3 signaling pathway, we screened for Notch3-intracellular domain (N3-ICD) interacting proteins using a human proteome microarray. Pathway analysis of the Notch3 interactome demonstrated that ubiquitin C was the molecular hub of the top functional network, suggesting the involvement of ubiquitination in modulating Notch3 signaling. Thereby, we focused on functional characterization of an E3 ubiquitin-protein ligase, WWP2, a top candidate in the Notch3 interactome list. Co-immunoprecipitation experiments showed that WWP2 interacted with N3-ICD but not with intracellular domains from other Notch receptors. Wild-type WWP2 but not ligase-deficient mutant WWP2 increases mono-ubiquitination of the membrane-tethered Notch3 fragment, therefore attenuating Notch3 pathway activity in cancer cells and leading to cell cycle arrest. The mono-ubiquitination by WWP2 may target an endosomal/lysosomal degradation fate for Notch3 as suggested by the fact that the process could be suppressed by the endosomal/lysosomal inhibitor. Analysis of The Cancer Genome Atlas dataset showed that the majority of ovarian carcinomas harbored homozygous or heterozygous deletions in WWP2 locus, and there was an inverse correlation in the expression levels between WWP2 and Notch3 in ovarian carcinomas. Furthermore, ectopic expression of WWP2 decreased tumor development in a mouse xenograft model and suppressed the Notch3-induced phenotypes including increase in cancer stem cell-like cell population and platinum resistance. Taken together, our results provide evidence that WWP2 serves as a tumor suppressor by negatively regulating Notch3 signaling in ovarian cancer. PMID:25356737

Hub Protein Controversy: Taking a Closer Look at Plant Stress Response Hubs

PubMed Central

Vandereyken, Katy; Van Leene, Jelle; De Coninck, Barbara; Cammue, Bruno P. A.

2018-01-01

Plant stress responses involve numerous changes at the molecular and cellular level and are regulated by highly complex signaling pathways. Studying protein-protein interactions (PPIs) and the resulting networks is therefore becoming increasingly important in understanding these responses. Crucial in PPI networks are the so-called hubs or hub proteins, commonly defined as the most highly connected central proteins in scale-free PPI networks. However, despite their importance, a growing amount of confusion and controversy seems to exist regarding hub protein identification, characterization and classification. In order to highlight these inconsistencies and stimulate further clarification, this review critically analyses the current knowledge on hub proteins in the plant interactome field. We focus on current hub protein definitions, including the properties generally seen as hub-defining, and the challenges and approaches associated with hub protein identification. Furthermore, we give an overview of the most important large-scale plant PPI studies of the last decade that identified hub proteins, pointing out the lack of overlap between different studies. As such, it appears that although major advances are being made in the plant interactome field, defining hub proteins is still heavily dependent on the quality, origin and interpretation of the acquired PPI data. Nevertheless, many hub proteins seem to have a reported role in the plant stress response, including transcription factors, protein kinases and phosphatases, ubiquitin proteasome system related proteins, (co-)chaperones and redox signaling proteins. A significant number of identified plant stress hubs are however still functionally uncharacterized, making them interesting targets for future research. This review clearly shows the ongoing improvements in the plant interactome field but also calls attention to the need for a more comprehensive and precise identification of hub proteins, allowing a more efficient systems biology driven unraveling of complex processes, including those involved in stress responses. PMID:29922309

Discovery and targeted LC-MS/MS of purified polerovirus reveals differences in the virus-host interactome associated with altered aphid transmission

USDA-ARS?s Scientific Manuscript database

The transmission of viruses in the Luteoviridae, such as Cereal yellow dwarf virus (CYDV), requires a series of precisely orchestrated interactions between virus proteins, plant proteins, and aphid proteins. These viruses are retained in the phloem for aphid acquisition and are transmitted by aphids...

Escherichia coli O157:H7 and rectoanal junction cell interactome

USDA-ARS?s Scientific Manuscript database

Introduction. Cattle are the primary E. coli O157 (O157) reservoir and principal source of human infection. The anatomical site of O157 persistence is the bovine recto-anal (RAJ) junction; hence, an in-depth understanding of O157-RAJ interactions will help develop novel modalities to limit O157 in c...

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

PubMed

Larkin, S E T; Johnston, H E; Jackson, T R; Jamieson, D G; Roumeliotis, T I; Mockridge, C I; Michael, A; Manousopoulou, A; Papachristou, E K; Brown, M D; Clarke, N W; Pandha, H; Aukim-Hastie, C L; Cragg, M S; Garbis, S D; Townsend, P A

2016-10-25

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6. Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

Transcriptome Profiling of Human FoxP3+ Regulatory T Cells

PubMed Central

Bhairavabhotla, Ravikiran; Kim, Yong C.; Glass, Deborah D.; Escobar, Thelma M.; Patel, Mira C.; Zahr, Rami; Nguyen, Cuong K.; Kilaru, Gokhul K.; Muljo, Stefan A.; Shevach, Ethan M.

2015-01-01

The major goal of this study was to perform an in depth characterization of the “gene signature” of human FoxP3+ T regulatory cells (Tregs). Highly purified Tregs and T conventional cells (Tconvs) from multiple healthy donors (HD), either freshly explanted or activated in vitro, were analyzed via RNA sequencing (RNA-seq) and gene expression changes validated using the nCounter system. Additionally, we analyzed microRNA (miRNA) expression using TaqMan low-density arrays. Our results confirm previous studies demonstrating selective gene expression of FoxP3, IKZF2, and CTLA4 in Tregs. Notably, a number of yet uncharacterized genes (RTKN2, LAYN, UTS2, CSF2RB, TRIB1, F5, CECAM4, CD70, ENC1 and NKG7) were identified and validated as being differentially expressed in human Tregs. We further characterize the functional roles of RTKN2 and LAYN by analyzing their roles in vitro human Treg suppression assays by knocking them down in Tregs and overexpressing them in Tconvs. In order to facilitate a better understanding of the human Treg gene expression signature, we have generated from our results a hypothetical interactome of genes and miRNAs in Tregs and Tconvs, PMID:26686412

The Scientific Challenge of Expanding the Frontiers of Nutrition.

PubMed

Rezzi, Serge; Solari, Soren; Bouche, Nicolas; Baetge, Emmanuel E

2016-01-01

Nutritional research is entering a paradigm shift which necessitates the modeling of complex interactions between diet, genetics, lifestyle, and environmental factors. This requires the development of analytical and processing capabilities for multiple data and information sources to be able to improve targeted and personalized nutritional approaches for the maintenance of health. Ideally, such knowledge will be employed to underpin the development of concepts that combine consumer and medical nutrition with diagnostic targeting for early intervention designed to maintain proper metabolic homeostasis and delay the onset of chronic diseases. Nutritional status is fundamental to any description of health, and when combined with other data on lifestyle, environment, and genetics, it can be used to drive stratified or even personalized nutritional strategies for health maintenance and preventive medicine. In this work, we will discuss the importance of developing new nutrient assessment methods and diagnostic capabilities for nutritional status to generate scientific hypotheses and actionable concepts from which to develop targeted and eventually personalized nutritional solutions for health protection. We describe efforts to develop algorithms for dietary nutrient intake and a holistic nutritional profiling platform as the basis of understanding the complex nutrition and health interactome. © 2016 Nestec Ltd., Vevey/S. Karger AG, Basel.

The MAPK Signaling Cascade is a Central Hub in the Regulation of Cell Cycle, Apoptosis and Cytoskeleton Remodeling by Tripeptidyl-Peptidase II

PubMed Central

Sompallae, Ramakrishna; Stavropoulou, Vaia; Houde, Mathieu; Masucci, Maria G.

2008-01-01

Tripeptidyl-peptidase II (TPPII) is a serine peptidase highly expressed in malignant Burkitt’s lymphoma cells (BL). We have previously shown that overexpression of TPPII correlates with chromosomal instability, centrosomal and mitotic spindle abnormalities and resistance to apoptosis induced by spindle poisons. Furthermore, TPPII knockdown by RNAi was associated with endoreplication and the accumulation of polynucleated cells that failed to complete cell division, indicating a role of TPPII in the cell cycle. Here we have applied a global approach of gene expression analysis to gain insights on the mechanism by which TPPII regulates this phenotype. mRNA profiling of control and TPPII knockdown BL cells identified one hundred and eighty five differentially expressed genes. Functional categorization of these genes highlighted major physiological functions such as apoptosis, cell cycle progression, cytoskeleton remodeling, proteolysis, and signal transduction. Pathways and protein interactome analysis revealed a significant enrichment in components of MAP kinases signaling. These findings suggest that TPPII influences a wide network of signaling pathways that are regulated by MAPKs and exerts thereby a pleiotropic effect on biological processes associated with cell survival, proliferation and genomic instability. PMID:19787088

Comparative Profiling of Ubiquitin Proteasome System Interplay with Influenza A Virus PB2 Polymerase Protein Recapitulating Virus Evolution in Humans.

PubMed

Biquand, Elise; Poirson, Juline; Karim, Marwah; Declercq, Marion; Malausse, Nicolas; Cassonnet, Patricia; Barbezange, Cyril; Straub, Marie-Laure; Jones, Louis; Munier, Sandie; Naffakh, Nadia; van der Werf, Sylvie; Jacob, Yves; Masson, Murielle; Demeret, Caroline

2017-01-01

The optimized exploitation of cell resources is one cornerstone of a successful infection. Differential mapping of host-pathogen protein-protein interactions (PPIs) on the basis of comparative interactomics of multiple strains is an effective strategy to highlight correlations between host proteome hijacking and biological or pathogenic traits. Here, we developed an interactomic pipeline to deliver high-confidence comparative maps of PPIs between a given pathogen and the human ubiquitin proteasome system (UPS). This subarray of the human proteome represents a range of essential cellular functions and promiscuous targets for many viruses. The screening pipeline was applied to the influenza A virus (IAV) PB2 polymerase proteins of five strains representing different levels of virulence in humans. An extensive PB2-UPS interplay has been detected that recapitulates the evolution of IAVs in humans. Functional validation with several IAV strains, including the seasonal H1N1 pdm09 and H3N2 viruses, confirmed the biological relevance of most identified UPS factors and revealed strain-independent and strain-specific effects of UPS factor invalidation on IAV infection. This strategy is applicable to proteins from any other virus or pathogen, providing a valuable resource with which to explore the UPS-pathogen interplay and its relationship with pathogenicity. IMPORTANCE Influenza A viruses (IAVs) are responsible for mild-to-severe seasonal respiratory illness of public health concern worldwide, and the risk of avian strain outbreaks in humans is a constant threat. Elucidating the requisites of IAV adaptation to humans is thus of prime importance. In this study, we explored how PB2 replication proteins of IAV strains with different levels of virulence in humans hijack a major protein modification pathway of the human host cell, the ubiquitin proteasome system (UPS). We found that the PB2 protein engages in an extended interplay with the UPS that evolved along with the virus's adaptation to humans. This suggests that UPS hijacking underlies the efficient infection of humans and can be used as an indicator for evaluation of the potential of avian IAVs to infect humans. Several UPS factors were found to be necessary for infection with circulating IAV strains, pointing to potential targets for therapeutic approaches.

Myotubularin related protein-2 and its phospholipid substrate PIP2 control Piezo2-mediated mechanotransduction in peripheral sensory neurons

PubMed Central

Narayanan, Pratibha; Hütte, Meike; Kudryasheva, Galina; Taberner, Francisco J; Lechner, Stefan G; Rehfeldt, Florian; Gomez-Varela, David

2018-01-01

Piezo2 ion channels are critical determinants of the sense of light touch in vertebrates. Yet, their regulation is only incompletely understood. We recently identified myotubularin related protein-2 (Mtmr2), a phosphoinositide (PI) phosphatase, in the native Piezo2 interactome of murine dorsal root ganglia (DRG). Here, we demonstrate that Mtmr2 attenuates Piezo2-mediated rapidly adapting mechanically activated (RA-MA) currents. Interestingly, heterologous Piezo1 and other known MA current subtypes in DRG appeared largely unaffected by Mtmr2. Experiments with catalytically inactive Mtmr2, pharmacological blockers of PI(3,5)P2 synthesis, and osmotic stress suggest that Mtmr2-dependent Piezo2 inhibition involves depletion of PI(3,5)P2. Further, we identified a PI(3,5)P2 binding region in Piezo2, but not Piezo1, that confers sensitivity to Mtmr2 as indicated by functional analysis of a domain-swapped Piezo2 mutant. Altogether, our results propose local PI(3,5)P2 modulation via Mtmr2 in the vicinity of Piezo2 as a novel mechanism to dynamically control Piezo2-dependent mechanotransduction in peripheral sensory neurons. PMID:29521261

High-density functional-RNA arrays as a versatile platform for studying RNA-based interactions.

PubMed

Phillips, Jack O; Butt, Louise E; Henderson, Charlotte A; Devonshire, Martin; Healy, Jess; Conway, Stuart J; Locker, Nicolas; Pickford, Andrew R; Vincent, Helen A; Callaghan, Anastasia J

2018-05-28

We are just beginning to unravel the myriad of interactions in which non-coding RNAs participate. The intricate RNA interactome is the foundation of many biological processes, including bacterial virulence and human disease, and represents unexploited resources for the development of potential therapeutic interventions. However, identifying specific associations of a given RNA from the multitude of possible binding partners within the cell requires robust high-throughput systems for their rapid screening. Here, we present the first demonstration of functional-RNA arrays as a novel platform technology designed for the study of such interactions using immobilized, active RNAs. We have generated high-density RNA arrays by an innovative method involving surface-capture of in vitro transcribed RNAs. This approach has significant advantages over existing technologies, particularly in its versatility in regards to binding partner character. Indeed, proof-of-principle application of RNA arrays to both RNA-small molecule and RNA-RNA pairings is demonstrated, highlighting their potential as a platform technology for mapping RNA-based networks and for pharmaceutical screening. Furthermore, the simplicity of the method supports greater user-accessibility over currently available technologies. We anticipate that functional-RNA arrays will find broad utility in the expanding field of RNA characterization.

Systems biology: a new tool for farm animal science.

PubMed

Hollung, Kristin; Timperio, Anna M; Olivan, Mamen; Kemp, Caroline; Coto-Montes, Ana; Sierra, Veronica; Zolla, Lello

2014-03-01

It is rapidly emerging that the tender meat phenotype is affected by an enormous amount of variables, not only tied to genetics (livestock breeding selection), but also to extrinsic factors, such as feeding conditions, physical activity, rearing environment, administration of hormonal growth promotants, pre-slaughter handling and stress. Proteomics has been widely accepted by meat scientists over the last years and is now commonly used to shed light on the postmortem processes involved in meat tenderization. This review discusses the latest findings with the use of proteomics and systems biology to study the different biochemical pathways postmortem aiming at understanding the concerted action of different molecular mechanisms responsible for meat quality. The conversion of muscle to meat postmortem can be described as a sequence of events involving molecular pathways controlled by a complex interplay of many factors. Among the different pathways emerging are the influence of apoptosis and lately also the role of autophagy in muscle postmortem development. This review thus, focus on how systems-wide integrated investigations (metabolomics, transcriptomics, interactomics, phosphoproteomics, mathematical modeling), which have emerged as complementary tools to proteomics, have helped establishing a few milestones in our understanding of the events leading from muscle to meat conversion.

Long-term effects of lactocrine-deficiency on the global porcine endometrial transcriptome and the microRNA-mRNA interactome at pregnancy day 13

USDA-ARS?s Scientific Manuscript database

Through lactocrine mechanisms, bioactive factors are transferred from mother to offspring as a specific consequence of nursing to support development. A large, long-term study in pigs showed that minimal colostrum consumption on the day of birth [postnatal day (PND) 0], reflected by low serum immuno...

Plant peptides in defense and signaling.

PubMed

Marmiroli, Nelson; Maestri, Elena

2014-06-01

This review focuses on plant peptides involved in defense against pathogen infection and those involved in the regulation of growth and development. Defense peptides, defensins, cyclotides and anti-microbial peptides are compared and contrasted. Signaling peptides are classified according to their major sites of activity. Finally, a network approach to creating an interactomic peptide map is described. Copyright © 2014 Elsevier Inc. All rights reserved.

Lysine methylation modulates the protein-protein interactions of yeast cytochrome C Cyc1p.

PubMed

Winter, Daniel L; Abeygunawardena, Dhanushi; Hart-Smith, Gene; Erce, Melissa A; Wilkins, Marc R

2015-07-01

In recent years, protein methylation has been established as a major intracellular PTM. It has also been proposed to modulate protein-protein interactions (PPIs) in the interactome. To investigate the effect of PTMs on PPIs, we recently developed the conditional two-hybrid (C2H) system. With this, we demonstrated that arginine methylation can modulate PPIs in the yeast interactome. Here, we used the C2H system to investigate the effect of lysine methylation. Specifically, we asked whether Ctm1p-mediated trimethylation of yeast cytochrome c Cyc1p, on lysine 78, modulates its interactions with Erv1p, Ccp1p, Cyc2p and Cyc3p. We show that the interactions between Cyc1p and Erv1p, and between Cyc1p and Cyc3p, are significantly increased upon trimethylation of lysine 78. This increase of interaction helps explain the reported facilitation of Cyc1p import into the mitochondrial intermembrane space upon methylation. This first application of the C2H system to the study of methyllysine-modulated interactions further confirms its robustness and flexibility. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Two-pore channel (TPC) interactome unmasks isoform-specific roles for TPCs in endolysosomal morphology and cell pigmentation

PubMed Central

Lin-Moshier, Yaping; Keebler, Michael V.; Hooper, Robert; Boulware, Michael J.; Liu, Xiaolong; Churamani, Dev; Abood, Mary E.; Walseth, Timothy F.; Brailoiu, Eugen; Patel, Sandip; Marchant, Jonathan S.

2014-01-01

The two-pore channels (TPC1 and TPC2) belong to an ancient family of intracellular ion channels expressed in the endolysosomal system. Little is known about how regulatory inputs converge to modulate TPC activity, and proposed activation mechanisms are controversial. Here, we compiled a proteomic characterization of the human TPC interactome, which revealed that TPCs complex with many proteins involved in Ca2+ homeostasis, trafficking, and membrane organization. Among these interactors, TPCs were resolved to scaffold Rab GTPases and regulate endomembrane dynamics in an isoform-specific manner. TPC2, but not TPC1, caused a proliferation of endolysosomal structures, dysregulating intracellular trafficking, and cellular pigmentation. These outcomes required both TPC2 and Rab activity, as well as their interactivity, because TPC2 mutants that were inactive, or rerouted away from their endogenous expression locale, or deficient in Rab binding, failed to replicate these outcomes. Nicotinic acid adenine dinucleotide phosphate (NAADP)-evoked Ca2+ release was also impaired using either a Rab binding-defective TPC2 mutant or a Rab inhibitor. These data suggest a fundamental role for the ancient TPC complex in trafficking that holds relevance for lysosomal proliferative scenarios observed in disease. PMID:25157141

The Two-pore channel (TPC) interactome unmasks isoform-specific roles for TPCs in endolysosomal morphology and cell pigmentation.

PubMed

Lin-Moshier, Yaping; Keebler, Michael V; Hooper, Robert; Boulware, Michael J; Liu, Xiaolong; Churamani, Dev; Abood, Mary E; Walseth, Timothy F; Brailoiu, Eugen; Patel, Sandip; Marchant, Jonathan S

2014-09-09

The two-pore channels (TPC1 and TPC2) belong to an ancient family of intracellular ion channels expressed in the endolysosomal system. Little is known about how regulatory inputs converge to modulate TPC activity, and proposed activation mechanisms are controversial. Here, we compiled a proteomic characterization of the human TPC interactome, which revealed that TPCs complex with many proteins involved in Ca(2+) homeostasis, trafficking, and membrane organization. Among these interactors, TPCs were resolved to scaffold Rab GTPases and regulate endomembrane dynamics in an isoform-specific manner. TPC2, but not TPC1, caused a proliferation of endolysosomal structures, dysregulating intracellular trafficking, and cellular pigmentation. These outcomes required both TPC2 and Rab activity, as well as their interactivity, because TPC2 mutants that were inactive, or rerouted away from their endogenous expression locale, or deficient in Rab binding, failed to replicate these outcomes. Nicotinic acid adenine dinucleotide phosphate (NAADP)-evoked Ca(2+) release was also impaired using either a Rab binding-defective TPC2 mutant or a Rab inhibitor. These data suggest a fundamental role for the ancient TPC complex in trafficking that holds relevance for lysosomal proliferative scenarios observed in disease.

TrypsNetDB: An integrated framework for the functional characterization of trypanosomatid proteins

PubMed Central

Gazestani, Vahid H.; Yip, Chun Wai; Nikpour, Najmeh; Berghuis, Natasha

2017-01-01

Trypanosomatid parasites cause serious infections in humans and production losses in livestock. Due to the high divergence from other eukaryotes, such as humans and model organisms, the functional roles of many trypanosomatid proteins cannot be predicted by homology-based methods, rendering a significant portion of their proteins as uncharacterized. Recent technological advances have led to the availability of multiple systematic and genome-wide datasets on trypanosomatid parasites that are informative regarding the biological role(s) of their proteins. Here, we report TrypsNetDB (http://trypsNetDB.org), a web-based resource for the functional annotation of 16 different species/strains of trypanosomatid parasites. The database not only visualizes the network context of the queried protein(s) in an intuitive way but also examines the response of the represented network in more than 50 different biological contexts and its enrichment for various biological terms and pathways, protein sequence signatures, and potential RNA regulatory elements. The interactome core of the database, as of Jan 23, 2017, contains 101,187 interactions among 13,395 trypanosomatid proteins inferred from 97 genome-wide and focused studies on the interactome of these organisms. PMID:28158179

An HDAC3-PROX1 corepressor module acts on HNF4α to control hepatic triglycerides.

PubMed

Armour, Sean M; Remsberg, Jarrett R; Damle, Manashree; Sidoli, Simone; Ho, Wesley Y; Li, Zhenghui; Garcia, Benjamin A; Lazar, Mitchell A

2017-09-15

The histone deacetylase HDAC3 is a critical mediator of hepatic lipid metabolism, and liver-specific deletion of HDAC3 leads to fatty liver. To elucidate the underlying mechanism, here we report a method of cross-linking followed by mass spectrometry to define a high-confidence HDAC3 interactome in vivo that includes the canonical NCoR-HDAC3 complex as well as Prospero-related homeobox 1 protein (PROX1). HDAC3 and PROX1 co-localize extensively on the mouse liver genome, and are co-recruited by hepatocyte nuclear factor 4α (HNF4α). The HDAC3-PROX1 module controls the expression of a gene program regulating lipid homeostasis, and hepatic-specific ablation of either component increases triglyceride content in liver. These findings underscore the importance of specific combinations of transcription factors and coregulators in the fine tuning of organismal metabolism.HDAC3 is a critical mediator of hepatic lipid metabolism and its loss leads to fatty liver. Here, the authors characterize the liver HDAC3 interactome in vivo, provide evidence that HDAC3 interacts with PROX1, and show that HDAC3 and PROX1 control expression of genes regulating lipid homeostasis.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-06-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed Central

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-01-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777

The amyloid interactome: Exploring protein aggregation

PubMed Central

Mastrokalou, Chara V.; Hamodrakas, Stavros J.

2017-01-01

Protein-protein interactions are the quintessence of physiological activities, but also participate in pathological conditions. Amyloid formation, an abnormal protein-protein interaction process, is a widespread phenomenon in divergent proteins and peptides, resulting in a variety of aggregation disorders. The complexity of the mechanisms underlying amyloid formation/amyloidogenicity is a matter of great scientific interest, since their revelation will provide important insight on principles governing protein misfolding, self-assembly and aggregation. The implication of more than one protein in the progression of different aggregation disorders, together with the cited synergistic occurrence between amyloidogenic proteins, highlights the necessity for a more universal approach, during the study of these proteins. In an attempt to address this pivotal need we constructed and analyzed the human amyloid interactome, a protein-protein interaction network of amyloidogenic proteins and their experimentally verified interactors. This network assembled known interconnections between well-characterized amyloidogenic proteins and proteins related to amyloid fibril formation. The consecutive extended computational analysis revealed significant topological characteristics and unraveled the functional roles of all constituent elements. This study introduces a detailed protein map of amyloidogenicity that will aid immensely towards separate intervention strategies, specifically targeting sub-networks of significant nodes, in an attempt to design possible novel therapeutics for aggregation disorders. PMID:28249044

Towards Inferring Protein Interactions: Challenges and Solutions

NASA Astrophysics Data System (ADS)

Zhang, Ya; Zha, Hongyuan; Chu, Chao-Hsien; Ji, Xiang

2006-12-01

Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.

The nuclear F-actin interactome of Xenopus oocytes reveals an actin-bundling kinesin that is essential for meiotic cytokinesis

PubMed Central

Samwer, Matthias; Dehne, Heinz-Jürgen; Spira, Felix; Kollmar, Martin; Gerlich, Daniel W; Urlaub, Henning; Görlich, Dirk

2013-01-01

Nuclei of Xenopus laevis oocytes grow 100 000-fold larger in volume than a typical somatic nucleus and require an unusual intranuclear F-actin scaffold for mechanical stability. We now developed a method for mapping F-actin interactomes and identified a comprehensive set of F-actin binders from the oocyte nuclei. Unexpectedly, the most prominent interactor was a novel kinesin termed NabKin (Nuclear and meiotic actin-bundling Kinesin). NabKin not only binds microtubules but also F-actin structures, such as the intranuclear actin bundles in prophase and the contractile actomyosin ring during cytokinesis. The interaction between NabKin and F-actin is negatively regulated by Importin-β and is responsive to spatial information provided by RanGTP. Disconnecting NabKin from F-actin during meiosis caused cytokinesis failure and egg polyploidy. We also found actin-bundling activity in Nabkin's somatic paralogue KIF14, which was previously shown to be essential for somatic cell division. Our data are consistent with the notion that NabKin/KIF14 directly link microtubules with F-actin and that such link is essential for cytokinesis. PMID:23727888

Rapid Profile: A Second Language Screening Procedure.

ERIC Educational Resources Information Center

Mackey, Alison; And Others

1991-01-01

Rapid Profile, developed by Manfred Pienemann of National Languages Institute of Australia/Language Acquisition Research Centre, is a computer-based procedure for screening speech samples collected from language learners to assess their level of language development as compared to standard patterns in the acquisition of the target language. Rapid…

Validation of a rapid DNA process with the RapidHIT® ID system using GlobalFiler® Express chemistry, a platform optimized for decentralized testing environments.

PubMed

Salceda, Susana; Barican, Arnaldo; Buscaino, Jacklyn; Goldman, Bruce; Klevenberg, Jim; Kuhn, Melissa; Lehto, Dennis; Lin, Frank; Nguyen, Phong; Park, Charles; Pearson, Francesca; Pittaro, Rick; Salodkar, Sayali; Schueren, Robert; Smith, Corey; Troup, Charles; Tsou, Dean; Vangbo, Mattias; Wunderle, Justus; King, David

2017-05-01

The RapidHIT ® ID is a fully automated sample-to-answer system for short tandem repeat (STR)-based human identification. The RapidHIT ID has been optimized for use in decentralized environments and processes presumed single source DNA samples, generating Combined DNA Index System (CODIS)-compatible DNA profiles in less than 90min. The system is easy to use, requiring less than one minute of hands-on time. Profiles are reviewed using centralized linking software, RapidLINK™ (IntegenX, Pleasanton, CA), a software tool designed to collate DNA profiles from single or multiple RapidHIT ID systems at different geographic locations. The RapidHIT ID has been designed to employ GlobalFiler ® Express and AmpFLSTR ® NGMSElect™, Thermo Fisher Scientific (Waltham, MA) STR chemistries. The Developmental Validation studies were performed using GlobalFiler ® Express with single source reference samples according to Scientific Working Group for DNA Analysis Methods guidelines. These results show that multiple RapidHIT ID systems networked with RapidLINK software form a highly reliable system for wide-scale deployment in locations such as police booking stations and border crossings enabling real-time testing of arrestees, potential human trafficking victims, and other instances where rapid turnaround is essential. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Internal validation of the RapidHIT® ID system.

PubMed

Wiley, Rachel; Sage, Kelly; LaRue, Bobby; Budowle, Bruce

2017-11-01

Traditionally, forensic DNA analysis has required highly skilled forensic geneticists in a dedicated laboratory to generate short tandem repeat (STR) profiles. STR profiles are routinely used either to associate or exclude potential donors of forensic biological evidence. The typing of forensic reference samples has become more demanding, especially with the requirement in some jurisdictions to DNA profile arrestees. The Rapid DNA (RDNA) platform, the RapidHIT ® ID (IntegenX ® , Pleasanton, CA), is a fully automated system capable of processing reference samples in approximately 90min with minimal human intervention. Thus, the RapidHIT ID instrument can be deployed to non-laboratory environments (e.g., booking stations) and run by trained atypical personnel such as law enforcement. In order to implement the RapidHIT ID platform, validation studies are needed to define the performance and limitations of the system. Internal validation studies were undertaken with four early-production RapidHIT ID units. Reliable and concordant STR profiles were obtained from reference buccal swabs. Throughout the study, no contamination was observed. The overall first-pass success rate with an "expert-like system" was 72%, which is comparable to another current RDNA platform commercially available. The system's second-pass success rate (involving manual interpretation on first-pass inconclusive results) increased to 90%. Inhibitors (i.e., coffee, smoking tobacco, and chewing tobacco) did not appear to affect typing by the instrument system; however, substrate (i.e., swab type) did impact typing success. Additionally, one desirable feature not available with other Rapid systems is that in the event of a system failed run, a swab can be recovered and subsequently re-analyzed in a new sample cartridge. Therefore, rarely should additional sampling or swab consumption be necessary. The RapidHIT ID system is a robust and reliable tool capable of generating complete STR profiles within the forensic DNA typing laboratory or with proper training in decentralized environments by non-laboratory personnel. Copyright © 2017 Elsevier B.V. All rights reserved.

The Last Enzyme of the De Novo Purine Synthesis Pathway 5-aminoimidazole-4-carboxamide Ribonucleotide Formyltransferase/IMP Cyclohydrolase (ATIC) Plays a Central Role in Insulin Signaling and the Golgi/Endosomes Protein Network*

PubMed Central

Boutchueng-Djidjou, Martial; Collard-Simard, Gabriel; Fortier, Suzanne; Hébert, Sébastien S.; Kelly, Isabelle; Landry, Christian R.; Faure, Robert L.

2015-01-01

Insulin is internalized with its cognate receptor into the endosomal apparatus rapidly after binding to hepatocytes. We performed a bioinformatic screen of Golgi/endosome hepatic protein fractions and found that ATIC, which is a rate-limiting enzyme in the de novo purine biosynthesis pathway, and PTPLAD1 are associated with insulin receptor (IR) internalization. The IR interactome (IRGEN) connects ATIC to AMPK within the Golgi/endosome protein network (GEN). Forty-five percent of the IR Golgi/endosome protein network have common heritable variants associated with type 2 diabetes, including ATIC and AMPK. We show that PTPLAD1 and AMPK are rapidly compartmentalized within the plasma membrane (PM) and Golgi/endosome fractions after insulin stimulation and that ATIC later accumulates in the Golgi/endosome fraction. Using an in vitro reconstitution system and siRNA-mediated partial knockdown of ATIC and PTPLAD1 in HEK293 cells, we show that both ATIC and PTPLAD1 affect IR tyrosine phosphorylation and endocytosis. We further show that insulin stimulation and ATIC knockdown readily increase the level of AMPK-Thr172 phosphorylation in IR complexes. We observed that IR internalization was markedly decreased after AMPKα2 knockdown, and treatment with the ATIC substrate AICAR, which is an allosteric activator of AMPK, increased IR endocytosis in cultured cells and in the liver. These results suggest the presence of a signaling mechanism that senses adenylate synthesis, ATP levels, and IR activation states and that acts in regulating IR autophosphorylation and endocytosis. PMID:25687571

The Ties that Bind (the Igh Locus).

PubMed

Krangel, Michael S

2016-05-01

Immunoglobulin heavy-chain locus V(D)J recombination requires a 3D chromatin organization which permits widely distributed variable (V) gene segments to contact distant diversity (D) and joining (J) gene segments. A recent study has identified key nodes in the locus interactome, paving the way for new molecular insights into how the locus is configured for recombination. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Ties That Bind: Mapping the Dynamic Enhancer-Promoter Interactome

DOE PAGES

Spurrell, Cailyn H.; Dickel, Diane E.; Visel, Axel

2016-11-17

Coupling chromosome conformation capture to molecular enrichment for promoter-containing DNA fragments enables the systematic mapping of interactions between individual distal regulatory sequences and their target genes. Here in this Minireview, we describe recent progress in the application of this technique and related complementary approaches to gain insight into the lineage- and cell-type-specific dynamics of interactions between regulators and gene promoters.

Prediction of scaffold proteins based on protein interaction and domain architectures.

PubMed

Oh, Kimin; Yi, Gwan-Su

2016-07-28

Scaffold proteins are known for being crucial regulators of various cellular functions by assembling multiple proteins involved in signaling and metabolic pathways. Identification of scaffold proteins and the study of their molecular mechanisms can open a new aspect of cellular systemic regulation and the results can be applied in the field of medicine and engineering. Despite being highlighted as the regulatory roles of dozens of scaffold proteins, there was only one known computational approach carried out so far to find scaffold proteins from interactomes. However, there were limitations in finding diverse types of scaffold proteins because their criteria were restricted to the classical scaffold proteins. In this paper, we will suggest a systematic approach to predict massive scaffold proteins from interactomes and to characterize the roles of scaffold proteins comprehensively. From a total of 10,419 basic scaffold protein candidates in protein interactomes, we classified them into three classes according to the structural evidences for scaffolding, such as domain architectures, domain interactions and protein complexes. Finally, we could define 2716 highly reliable scaffold protein candidates and their characterized functional features. To assess the accuracy of our prediction, the gold standard positive and negative data sets were constructed. We prepared 158 gold standard positive data and 844 gold standard negative data based on the functional information from Gene Ontology consortium. The precision, sensitivity and specificity of our testing was 80.3, 51.0, and 98.5 % respectively. Through the function enrichment analysis of highly reliable scaffold proteins, we could confirm the significantly enriched functions that are related to scaffold protein binding. We also identified functional association between scaffold proteins and their recruited proteins. Furthermore, we checked that the disease association of scaffold proteins is higher than kinases. In conclusion, we could predict larger volume of scaffold proteins and analyzed their functional characteristics. Deeper understandings about the roles of scaffold proteins from this study will provide a higher opportunity to find therapeutic or engineering applications of scaffold proteins using their functional characteristics.

Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

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

Park, Sung-Dong; Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749; Cheon, So Yeong

Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did notmore » inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model.« less

Striatal Transcriptome and Interactome Analysis of Shank3-overexpressing Mice Reveals the Connectivity between Shank3 and mTORC1 Signaling

PubMed Central

Lee, Yeunkum; Kim, Sun Gyun; Lee, Bokyoung; Zhang, Yinhua; Kim, Yoonhee; Kim, Shinhyun; Kim, Eunjoon; Kang, Hyojin; Han, Kihoon

2017-01-01

Mania causes symptoms of hyperactivity, impulsivity, elevated mood, reduced anxiety and decreased need for sleep, which suggests that the dysfunction of the striatum, a critical component of the brain motor and reward system, can be causally associated with mania. However, detailed molecular pathophysiology underlying the striatal dysfunction in mania remains largely unknown. In this study, we aimed to identify the molecular pathways showing alterations in the striatum of SH3 and multiple ankyrin repeat domains 3 (Shank3)-overexpressing transgenic (TG) mice that display manic-like behaviors. The results of transcriptome analysis suggested that mammalian target of rapamycin complex 1 (mTORC1) signaling may be the primary molecular signature altered in the Shank3 TG striatum. Indeed, we found that striatal mTORC1 activity, as measured by mTOR S2448 phosphorylation, was significantly decreased in the Shank3 TG mice compared to wild-type (WT) mice. To elucidate the potential underlying mechanism, we re-analyzed previously reported protein interactomes, and detected a high connectivity between Shank3 and several upstream regulators of mTORC1, such as tuberous sclerosis 1 (TSC1), TSC2 and Ras homolog enriched in striatum (Rhes), via 94 common interactors that we denominated “Shank3-mTORC1 interactome”. We noticed that, among the 94 common interactors, 11 proteins were related to actin filaments, the level of which was increased in the dorsal striatum of Shank3 TG mice. Furthermore, we could co-immunoprecipitate Shank3, Rhes and Wiskott-Aldrich syndrome protein family verprolin-homologous protein 1 (WAVE1) proteins from the striatal lysate of Shank3 TG mice. By comparing with the gene sets of psychiatric disorders, we also observed that the 94 proteins of Shank3-mTORC1 interactome were significantly associated with bipolar disorder (BD). Altogether, our results suggest a protein interaction-mediated connectivity between Shank3 and certain upstream regulators of mTORC1 that might contribute to the abnormal striatal mTORC1 activity and to the manic-like behaviors of Shank3 TG mice. PMID:28701918

Demonstration of protein-fragment complementation assay using purified firefly luciferase fragments

PubMed Central

2013-01-01

Background Human interactome is predicted to contain 150,000 to 300,000 protein-protein interactions, (PPIs). Protein-fragment complementation assay (PCA) is one of the most widely used methods to detect PPI, as well as Förster resonance energy transfer (FRET). To date, successful applications of firefly luciferase (Fluc)-based PCA have been reported in vivo, in cultured cells and in cell-free lysate, owing to its high sensitivity, high signal-to-background (S/B) ratio, and reversible response. Here we show the assay also works with purified proteins with unexpectedly rapid kinetics. Results Split Fluc fragments both fused with a rapamycin-dependently interacting protein pair were made and expressed in E. coli system, and purified to homogeneity. When the proteins were used for PCA to detect rapamycin-dependent PPI, they enabled a rapid detection (~1 s) of PPI with high S/B ratio. When Fn7-8 domains (7 nm in length) that was shown to abrogate GFP mutant-based FRET was inserted between split Fluc and FKBP12 as a rigid linker, it still showed some response, suggesting less limitation in interacting partner’s size. Finally, the stability of the probe was investigated. Preincubation of the probes at 37 degreeC up to 1 h showed marked decrease of the luminescent signal to 1.5%, showing the limited stability of this system. Conclusion Fluc PCA using purified components will enable a rapid and handy detection of PPIs with high S/B ratio, avoiding the effects of concomitant components. Although the system might not be suitable for large-scale screening due to its limited stability, it can detect an interaction over larger distance than by FRET. This would be the first demonstration of Fluc PCA in vitro, which has a distinct advantage over other PPI assays. Our system enables detection of direct PPIs without risk of perturbation by PPI mediators in the complex cellular milieu. PMID:23536995

Optimization and quality control of genome-wide Hi-C library preparation.

PubMed

Zhang, Xiang-Yuan; He, Chao; Ye, Bing-Yu; Xie, De-Jian; Shi, Ming-Lei; Zhang, Yan; Shen, Wen-Long; Li, Ping; Zhao, Zhi-Hu

2017-09-20

Highest-throughput chromosome conformation capture (Hi-C) is one of the key assays for genome- wide chromatin interaction studies. It is a time-consuming process that involves many steps and many different kinds of reagents, consumables, and equipments. At present, the reproducibility is unsatisfactory. By optimizing the key steps of the Hi-C experiment, such as crosslinking, pretreatment of digestion, inactivation of restriction enzyme, and in situ ligation etc., we established a robust Hi-C procedure and prepared two biological replicates of Hi-C libraries from the GM12878 cells. After preliminary quality control by Sanger sequencing, the two replicates were high-throughput sequenced. The bioinformatics analysis of the raw sequencing data revealed the mapping-ability and pair-mate rate of the raw data were around 90% and 72%, respectively. Additionally, after removal of self-circular ligations and dangling-end products, more than 96% of the valid pairs were reached. Genome-wide interactome profiling shows clear topological associated domains (TADs), which is consistent with previous reports. Further correlation analysis showed that the two biological replicates strongly correlate with each other in terms of both bin coverage and all bin pairs. All these results indicated that the optimized Hi-C procedure is robust and stable, which will be very helpful for the wide applications of the Hi-C assay.

Repositioning of drugs using open-access data portal DTome: A test case with probenecid (Review).

PubMed

Ahmed, Mohammad U; Bennett, Dylan J; Hsieh, Tze-Chen; Doonan, Barbara B; Ahmed, Saba; Wu, Joseph M

2016-01-01

The one gene-one enzyme hypothesis, first introduced by Beadle and Tatum in the 1940s and based on their genetic analysis and observation of phenotype changes in Neurospora crassa challenged by various experimental conditions, has witnessed significant advances in recent decades. Much of our understanding of the association between genes and their phenotype expression has benefited from the completion of the human genome project, and has shown continual transformation guided by the effort directed at the annotation and characterization of human genes. Similarly, the idea of one drug‑one primary disease indication that traditionally has been the benchmark for the labeling and usage of drugs has also undergone evident progressive refinements; in recent years the science and practice of pharmaceutical development has notable success in the strategy of drug repurposing. Drug repurposing is an innovative approach where, instead of de novo synthesis and discovery of new drugs with novel indications, drug candidates with the desired usage are identified by a process of re‑profiling using an open‑source database or knowledge of known or failed drugs already in existence. In the present study, the repurposing drug strategy employing open‑access data portal drug‑target interactome (DTome) is applied to the uncovering of new clinical usage for probenecid.

Geraniol suppresses prostate cancer growth through down-regulation of E2F8.

PubMed

Lee, Sanghoon; Park, Yu Rang; Kim, Su-Hwa; Park, Eun-Jung; Kang, Min Ji; So, Insuk; Chun, Jung Nyeo; Jeon, Ju-Hong

2016-10-01

Geraniol, an acyclic dietary monoterpene, has been found to suppress cancer survival and growth. However, the molecular mechanism underlying the antitumor action of geraniol has not been investigated at the genome-wide level. In this study, we analyzed the microarray data obtained from geraniol-treated prostate cancer cells. Geraniol potently altered a gene expression profile and primarily down-regulated cell cycle-related gene signatures, compared to linalool, another structurally similar monoterpene that induces no apparent phenotypic changes. Master regulator analysis using the prostate cancer-specific regulatory interactome identified that the transcription factor E2F8 as a specific target molecule regulates geraniol-specific cell cycle signatures. Subsequent experiments confirmed that geraniol down-regulated E2F8 expression and the knockdown of E2F8 was sufficient to suppress cell growth by inducing G 2 /M arrest. Epidemiological analysis showed that E2F8 is up-regulated in metastatic prostate cancer and associated with poor prognosis. These results indicate that E2F8 is a crucial transcription regulator controlling cell cycle and survival in prostate cancer cells. Therefore, our study provides insight into the role of E2F8 in prostate cancer biology and therapeutics. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

LncSubpathway: a novel approach for identifying dysfunctional subpathways associated with risk lncRNAs by integrating lncRNA and mRNA expression profiles and pathway topologies.

PubMed

Xu, Yanjun; Li, Feng; Wu, Tan; Xu, Yingqi; Yang, Haixiu; Dong, Qun; Zheng, Meiyu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Li, Xia

2017-02-28

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including the development of many diseases. Pathway analysis is a valuable aid for understanding the cellular functions of these transcripts. We have developed and characterized LncSubpathway, a novel method that integrates lncRNA and protein coding gene (PCG) expression with interactome data to identify disease risk subpathways that functionally associated with risk lncRNAs. LncSubpathway identifies the most relevance regions which are related with risk lncRNA set and implicated with study conditions through simultaneously considering the dysregulation extent of lncRNAs, PCGs and their correlations. Simulation studies demonstrated that the sensitivity and false positive rates of LncSubpathway were within acceptable ranges, and that LncSubpathway could accurately identify dysregulated regions that related with disease risk lncRNAs within pathways. When LncSubpathway was applied to colorectal carcinoma and breast cancer subtype datasets, it identified cancer type- and breast cancer subtype-related meaningful subpathways. Further, analysis of its robustness and reproducibility indicated that LncSubpathway was a reliable means of identifying subpathways that functionally associated with lncRNAs. LncSubpathway is freely available at http://www.bio-bigdata.com/lncSubpathway/.

LncSubpathway: a novel approach for identifying dysfunctional subpathways associated with risk lncRNAs by integrating lncRNA and mRNA expression profiles and pathway topologies

PubMed Central

Wu, Tan; Xu, Yingqi; Yang, Haixiu; Dong, Qun; Zheng, Meiyu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Li, Xia

2017-01-01

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including the development of many diseases. Pathway analysis is a valuable aid for understanding the cellular functions of these transcripts. We have developed and characterized LncSubpathway, a novel method that integrates lncRNA and protein coding gene (PCG) expression with interactome data to identify disease risk subpathways that functionally associated with risk lncRNAs. LncSubpathway identifies the most relevance regions which are related with risk lncRNA set and implicated with study conditions through simultaneously considering the dysregulation extent of lncRNAs, PCGs and their correlations. Simulation studies demonstrated that the sensitivity and false positive rates of LncSubpathway were within acceptable ranges, and that LncSubpathway could accurately identify dysregulated regions that related with disease risk lncRNAs within pathways. When LncSubpathway was applied to colorectal carcinoma and breast cancer subtype datasets, it identified cancer type- and breast cancer subtype-related meaningful subpathways. Further, analysis of its robustness and reproducibility indicated that LncSubpathway was a reliable means of identifying subpathways that functionally associated with lncRNAs. LncSubpathway is freely available at http://www.bio-bigdata.com/lncSubpathway/. PMID:28152521

The Breast Cancer DNA Interactome

DTIC Science & Technology

2014-12-01

Research and Education 8. PERFORMING ORGANIZATION REPORT NUMBER Palo Alto, CA 94304 9 . SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10...act as a growth modulator (7- 9 ). While correlations between serum levels of IGFBP3 and breast cancer have yielded contradictory results (3-5, 10...receptor (EGFR), another breast cancer related gene. EGFR is located approximately 9 Mb from IGFBP3 on chromosome 7. To examine this long-range

The TRiC/CCT chaperone is implicated in Alzheimer's disease based on patient GWAS and an RNAi screen in Aβ-expressing Caenorhabditis elegans.

PubMed

Khabirova, Eleonora; Moloney, Aileen; Marciniak, Stefan J; Williams, Julie; Lomas, David A; Oliver, Stephen G; Favrin, Giorgio; Sattelle, David B; Crowther, Damian C

2014-01-01

The human Aβ peptide causes progressive paralysis when expressed in the muscles of the nematode worm, C. elegans. We have exploited this model of Aβ toxicity by carrying out an RNAi screen to identify genes whose reduced expression modifies the severity of this locomotor phenotype. Our initial finding was that none of the human orthologues of these worm genes is identical with the genome-wide significant GWAS genes reported to date (the "white zone"); moreover there was no identity between worm screen hits and the longer list of GWAS genes which included those with borderline levels of significance (the "grey zone"). This indicates that Aβ toxicity should not be considered as equivalent to sporadic AD. To increase the sensitivity of our analysis, we then considered the physical interactors (+1 interactome) of the products of the genes in both the worm and the white+grey zone lists. When we consider these worm and GWAS gene lists we find that 4 of the 60 worm genes have a +1 interactome overlap that is larger than expected by chance. Two of these genes form a chaperonin complex, the third is closely associated with this complex and the fourth gene codes for actin, the major substrate of the same chaperonin.

Triangular Alignment (TAME). A Tensor-based Approach for Higher-order Network Alignment

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

Mohammadi, Shahin; Gleich, David F.; Kolda, Tamara G.

2015-11-01

Network alignment is an important tool with extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-order structures and provide a new objective function that maximizes the number of aligned substructures. This objective function corresponds to an integer programming problem, which is NP-hard. Consequently, we approximate this objective function as a surrogate function whose maximization results in a tensor eigenvalue problem. Based on this formulation, we present an algorithm called Triangularmore » AlignMEnt (TAME), which attempts to maximize the number of aligned triangles across networks. We focus on alignment of triangles because of their enrichment in complex networks; however, our formulation and resulting algorithms can be applied to general motifs. Using a case study on the NAPABench dataset, we show that TAME is capable of producing alignments with up to 99% accuracy in terms of aligned nodes. We further evaluate our method by aligning yeast and human interactomes. Our results indicate that TAME outperforms the state-of-art alignment methods both in terms of biological and topological quality of the alignments.« less

Interactome analyses identify ties of PrP and its mammalian paralogs to oligomannosidic N-glycans and endoplasmic reticulum-derived chaperones.

PubMed

Watts, Joel C; Huo, Hairu; Bai, Yu; Ehsani, Sepehr; Jeon, Amy Hye Won; Won, Amy Hye; Shi, Tujin; Daude, Nathalie; Lau, Agnes; Young, Rebecca; Xu, Lei; Carlson, George A; Williams, David; Westaway, David; Schmitt-Ulms, Gerold

2009-10-01

The physiological environment which hosts the conformational conversion of the cellular prion protein (PrP(C)) to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrP(C) interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd) and Shadoo (Sprn), two mammalian PrP(C) paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrP(C) and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI) were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrP(C) with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrP(Sc). A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrP(C) organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins.

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

PubMed

Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida

2017-04-01

Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Chemokine interactome mapping enables tailored intervention in acute and chronic inflammation.

PubMed

von Hundelshausen, Philipp; Agten, Stijn M; Eckardt, Veit; Blanchet, Xavier; Schmitt, Martin M; Ippel, Hans; Neideck, Carlos; Bidzhekov, Kiril; Leberzammer, Julian; Wichapong, Kanin; Faussner, Alexander; Drechsler, Maik; Grommes, Jochen; van Geffen, Johanna P; Li, He; Ortega-Gomez, Almudena; Megens, Remco T A; Naumann, Ronald; Dijkgraaf, Ingrid; Nicolaes, Gerry A F; Döring, Yvonne; Soehnlein, Oliver; Lutgens, Esther; Heemskerk, Johan W M; Koenen, Rory R; Mayo, Kevin H; Hackeng, Tilman M; Weber, Christian

2017-04-05

Chemokines orchestrate leukocyte trafficking and function in health and disease. Heterophilic interactions between chemokines in a given microenvironment may amplify, inhibit, or modulate their activity; however, a systematic evaluation of the chemokine interactome has not been performed. We used immunoligand blotting and surface plasmon resonance to obtain a comprehensive map of chemokine-chemokine interactions and to confirm their specificity. Structure-function analyses revealed that chemokine activity can be enhanced by CC-type heterodimers but inhibited by CXC-type heterodimers. Functional synergism was achieved through receptor heteromerization induced by CCL5-CCL17 or receptor retention at the cell surface via auxiliary proteoglycan binding of CCL5-CXCL4. In contrast, inhibitory activity relied on conformational changes (in CXCL12), affecting receptor signaling. Obligate CC-type heterodimers showed high efficacy and potency and drove acute lung injury and atherosclerosis, processes abrogated by specific CCL5-derived peptide inhibitors or knock-in of an interaction-deficient CXCL4 variant. Atheroprotective effects of CCL17 deficiency were phenocopied by a CCL5-derived peptide disrupting CCL5-CCL17 heterodimers, whereas a CCL5 α-helix peptide mimicked inhibitory effects on CXCL12-driven platelet aggregation. Thus, formation of specific chemokine heterodimers differentially dictates functional activity and can be exploited for therapeutic targeting. Copyright © 2017, American Association for the Advancement of Science.

Examining the Interactome of Huperzine A by Magnetic Biopanning

PubMed Central

Guo, Wei; Liu, Shupeng; Peng, Jinliang; Wei, Xiaohui; Sun, Ye; Qiu, Yangsheng; Gao, Guangwei; Wang, Peng; Xu, Yuhong

2012-01-01

Huperzine A is a bioactive compound derived from traditional Chinese medicine plant Qian Ceng Ta (Huperzia serrata), and was found to have multiple neuroprotective effects. In addition to being a potent acetylcholinesterase inhibitor, it was thought to act through other mechanisms such as antioxidation, antiapoptosis, etc. However, the molecular targets involved with these mechanisms were not identified. In this study, we attempted to exam the interactome of Huperzine A using a cDNA phage display library and also mammalian brain tissue extracts. The drugs were chemically linked on the surface of magnetic particles and the interactive phages or proteins were collected and analyzed. Among the various cDNA expressing phages selected, one was identified to encode the mitochondria NADH dehydrogenase subunit 1. Specific bindings between the drug and the target phages and target proteins were confirmed. Another enriched phage clone was identified as mitochondria ATP synthase, which was also panned out from the proteome of mouse brain tissue lysate. These data indicated the possible involvement of mitochondrial respiratory chain matrix enzymes in Huperzine A's pharmacological effects. Such involvement had been suggested by previous studies based on enzyme activity changes. Our data supported the new mechanism. Overall we demonstrated the feasibility of using magnetic biopanning as a simple and viable method for investigating the complex molecular mechanisms of bioactive molecules. PMID:22615909

Split luciferase complementation assay to detect regulated protein-protein interactions in rice protoplasts in a large-scale format

PubMed Central

2014-01-01

Background The rice interactome, in which a network of protein-protein interactions has been elucidated in rice, is a useful resource to identify functional modules of rice signal transduction pathways. Protein-protein interactions occur in cells in two ways, constitutive and regulative. While a yeast-based high-throughput method has been widely used to identify the constitutive interactions, a method to detect the regulated interactions is rarely developed for a large-scale analysis. Results A split luciferase complementation assay was applied to detect the regulated interactions in rice. A transformation method of rice protoplasts in a 96-well plate was first established for a large-scale analysis. In addition, an antibody that specifically recognizes a carboxyl-terminal fragment of Renilla luciferase was newly developed. A pair of antibodies that recognize amino- and carboxyl- terminal fragments of Renilla luciferase, respectively, was then used to monitor quality and quantity of interacting recombinant-proteins accumulated in the cells. For a proof-of-concept, the method was applied to detect the gibberellin-dependent interaction between GIBBERELLIN INSENSITIVE DWARF1 and SLENDER RICE 1. Conclusions A method to detect regulated protein-protein interactions was developed towards establishment of the rice interactome. PMID:24987490

Proteomic analyses of signalling complexes associated with receptor tyrosine kinase identify novel members of fibroblast growth factor receptor 3 interactome.

PubMed

Balek, Lukas; Nemec, Pavel; Konik, Peter; Kunova Bosakova, Michaela; Varecha, Miroslav; Gudernova, Iva; Medalova, Jirina; Krakow, Deborah; Krejci, Pavel

2018-01-01

Receptor tyrosine kinases (RTKs) form multiprotein complexes that initiate and propagate intracellular signals and determine the RTK-specific signalling patterns. Unravelling the full complexity of protein interactions within the RTK-associated complexes is essential for understanding of RTK functions, yet it remains an understudied area of cell biology. We describe a comprehensive approach to characterize RTK interactome. A single tag immunoprecipitation and phosphotyrosine protein isolation followed by mass-spectrometry was used to identify proteins interacting with fibroblast growth factor receptor 3 (FGFR3). A total of 32 experiments were carried out in two different cell types and identified 66 proteins out of which only 20 (30.3%) proteins were already known FGFR interactors. Using co-immunoprecipitations, we validated FGFR3 interaction with adapter protein STAM1, transcriptional regulator SHOX2, translation elongation factor eEF1A1, serine/threonine kinases ICK, MAK and CCRK, and inositol phosphatase SHIP2. We show that unappreciated signalling mediators exist for well-studied RTKs, such as FGFR3, and may be identified via proteomic approaches described here. These approaches are easily adaptable to other RTKs, enabling identification of novel signalling mediators for majority of the known human RTKs. Copyright © 2017 Elsevier Inc. All rights reserved.

Network topological analysis reveals the functional cohesiveness for the newly discovered links by Yeast 2 Hybrid approach

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Pevzner, Sam; Rolland, Thomas; Tassan, Murat; Barabasi, Albert Laszlo; Vidal, Mark; CCNR, Northeastern University Collaboration; Dana Farber Cancer Institute Collaboration

2014-03-01

Protein-protein interaction maps and interactomes are the blueprint of Network Medicine and systems biology and are being experimentally studied by different groups. Despite the wide usage of Literature Curated Interactome (LCI), these sources are biased towards different parameters such as highly studied proteins. Yeast two hybrid method is a high throughput experimental setup which screens proteins in an unbiased fashion. Current knowledge of protein interactions is far from complete. In fact the previous offered data from Y2H method (2005), is estimated to offer only 5% of all potential protein interactions. Currently this coverage has increased to 20% of what is known as reference HI In this work we study the topological properties of Y2H protein-protein interactions network with LCI and show although they both agree on some properties, LCI shows a clear unbiased nature of interaction selections. Most importantly, we assess the properties of PPI as it evolves with increasing the coverage. We show that, the newly discovered interactions tend to connect proteins that have been closer than average in the previous PPI release. reinforcing the modular structure of PPI. Furthermore, we show, some unseen effects on PPI (as opposed to LCI) can be explained by its incompleteness.

The SSU processome interactome in Saccharomyces cerevisiae reveals novel protein subcomplexes.

PubMed

Vincent, Nicholas G; Charette, J Michael; Baserga, Susan J

2018-01-01

Ribosome assembly is an evolutionarily conserved and energy intensive process required for cellular growth, proliferation, and maintenance. In yeast, assembly of the small ribosomal subunit (SSU) requires approximately 75 assembly factors that act in coordination to form the SSU processome, a 6 MDa ribonucleoprotein complex. The SSU processome is required for processing, modifying, and folding the preribosomal RNA (rRNA) to prepare it for incorporation into the mature SSU. Although the protein composition of the SSU processome has been known for some time, the interaction network of the proteins required for its assembly has remained poorly defined. Here, we have used a semi-high-throughput yeast two-hybrid (Y2H) assay and coimmunoprecipitation validation method to produce a high-confidence interactome of SSU processome assembly factors (SPAFs), providing essential insight into SSU assembly and ribosome biogenesis. Further, we used glycerol density-gradient sedimentation to reveal the presence of protein subcomplexes that have not previously been observed. Our work not only provides essential insight into SSU assembly and ribosome biogenesis, but also serves as an important resource for future investigations into how defects in biogenesis and assembly cause congenital disorders of ribosomes known as ribosomopathies. © 2018 Vincent et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Elucidation of the Ebola virus VP24 cellular interactome and disruption of virus biology through targeted inhibition of host-cell protein function.

PubMed

García-Dorival, Isabel; Wu, Weining; Dowall, Stuart; Armstrong, Stuart; Touzelet, Olivier; Wastling, Jonathan; Barr, John N; Matthews, David; Carroll, Miles; Hewson, Roger; Hiscox, Julian A

2014-11-07

Viral pathogenesis in the infected cell is a balance between antiviral responses and subversion of host-cell processes. Many viral proteins specifically interact with host-cell proteins to promote virus biology. Understanding these interactions can lead to knowledge gains about infection and provide potential targets for antiviral therapy. One such virus is Ebola, which has profound consequences for human health and causes viral hemorrhagic fever where case fatality rates can approach 90%. The Ebola virus VP24 protein plays a critical role in the evasion of the host immune response and is likely to interact with multiple cellular proteins. To map these interactions and better understand the potential functions of VP24, label-free quantitative proteomics was used to identify cellular proteins that had a high probability of forming the VP24 cellular interactome. Several known interactions were confirmed, thus placing confidence in the technique, but new interactions were also discovered including one with ATP1A1, which is involved in osmoregulation and cell signaling. Disrupting the activity of ATP1A1 in Ebola-virus-infected cells with a small molecule inhibitor resulted in a decrease in progeny virus, thus illustrating how quantitative proteomics can be used to identify potential therapeutic targets.

Making connections for life: an in vivo map of the yeast interactome.

PubMed

Kast, Juergen

2008-10-01

Proteins are the true workhorses of any cell. To carry out specific tasks, they frequently bind other molecules in their surroundings. Due to their structural complexity and flexibility, the most diverse array of interactions is seen with other proteins. The different geometries and affinities available for such interactions typically bestow specific functions on proteins. Having available a map of protein-protein interactions is therefore of enormous importance for any researcher interested in gaining insight into biological systems at the level of cells and organisms. In a recent report, a novel approach has been employed that relies on the spontaneous folding of complementary enzyme fragments fused to two different proteins to test whether these interact in their actual cellular context [Tarassov et al., Science 320, 1465-1470 (2008)]. Genome-wide application of this protein-fragment complementation assay has resulted in the first map of the in vivo interactome of Saccharomyces cerevisiae. The current data show striking similarities but also significant differences to those obtained using other large-scale approaches for the same task. This warrants a general discussion of the current state of affairs of protein-protein interaction studies and foreseeable future trends, highlighting their significance for a variety of applications and their potential to revolutionize our understanding of the architecture and dynamics of biological systems.

Making connections for life: an in vivo map of the yeast interactome

PubMed Central

Kast, Juergen

2008-01-01

Proteins are the true workhorses of any cell. To carry out specific tasks, they frequently bind other molecules in their surroundings. Due to their structural complexity and flexibility, the most diverse array of interactions is seen with other proteins. The different geometries and affinities available for such interactions typically bestow specific functions on proteins. Having available a map of protein–protein interactions is therefore of enormous importance for any researcher interested in gaining insight into biological systems at the level of cells and organisms. In a recent report, a novel approach has been employed that relies on the spontaneous folding of complementary enzyme fragments fused to two different proteins to test whether these interact in their actual cellular context [Tarassov et al., Science 320, 1465–1470 (2008)]. Genome-wide application of this protein-fragment complementation assay has resulted in the first map of the in vivo interactome of Saccharomyces cerevisiae. The current data show striking similarities but also significant differences to those obtained using other large-scale approaches for the same task. This warrants a general discussion of the current state of affairs of protein–protein interaction studies and foreseeable future trends, highlighting their significance for a variety of applications and their potential to revolutionize our understanding of the architecture and dynamics of biological systems. PMID:19404434

Strategic camouflage treatment of skeletal Class III malocclusion (mandibular prognathism) using bone-borne rapid maxillary expansion and mandibular anterior subapical osteotomy.

PubMed

Seo, Yu-Jin; Lin, Lu; Kim, Seong-Hun; Chung, Kyu-Rhim; Nelson, Gerald

2016-01-01

This case report presents the camouflage treatment that successfully improved the facial profile of a patient with a skeletal Class III malocclusion using bone-borne rapid maxillary expansion and mandibular anterior subapical osteotomy. The patient was an 18-year-old woman with chief complaints of crooked teeth and a protruded jaw. Camouflage treatment was chosen because she rejected orthognathic surgery under general anesthesia. A hybrid type of bone-borne rapid maxillary expander with palatal mini-implants was used to correct the transverse discrepancy, and a mandibular anterior subapical osteotomy was conducted to achieve proper overjet with normal incisal inclination and to improve her lip and chin profile. As a result, a Class I occlusion with a favorable inclination of the anterior teeth and a good esthetic profile was achieved with no adverse effects. Therefore, the hybrid type of bone-borne rapid maxillary expander and a mandibular anterior subapical osteotomy can be considered effective camouflage treatment of a skeletal Class III malocclusion, providing improved inclination of the dentition and lip profile. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Changes in the transcriptional profile in response to overexpression of the osteopontin-c splice isoform in ovarian (OvCar-3) and prostate (PC-3) cancer cell lines

PubMed Central

2014-01-01

Background Especially in human tumor cells, the osteopontin (OPN) primary transcript is subject to alternative splicing, generating three isoforms termed OPNa, OPNb and OPNc. We previously demonstrated that the OPNc splice variant activates several aspects of the progression of ovarian and prostate cancers. The goal of the present study was to develop cell line models to determine the impact of OPNc overexpression on main cancer signaling pathways and thus obtain insights into the mechanisms of OPNc pro-tumorigenic roles. Methods Human ovarian and prostate cancer cell lines, OvCar-3 and PC-3 cells, respectively, were stably transfected to overexpress OPNc. Transcriptomic profiling was performed on these cells and compared to controls, to identify OPNc overexpression-dependent changes in gene expression levels and pathways by qRT-PCR analyses. Results Among 84 genes tested by using a multiplex real-time PCR Cancer Pathway Array approach, 34 and 16, respectively, were differentially expressed between OvCar-3 and PC-3 OPNc-overexpressing cells in relation to control clones. Differentially expressed genes are included in all main hallmarks of cancer, and several interacting proteins have been identified using an interactome network analysis. Based on marked up-regulation of Vegfa transcript in response to OPNc overexpression, we partially validated the array data by demonstrating that conditioned medium (CM) secreted from OvCar-3 and PC-3 OPNc-overexpressing cells significantly induced endothelial cell adhesion, proliferation and migration, compared to CM secreted from control cells. Conclusions Overall, the present study elucidated transcriptional changes of OvCar-3 and PC-3 cancer cell lines in response to OPNc overexpression, which provides an assessment for predicting the molecular mechanisms by which this splice variant promotes tumor progression features. PMID:24928374

Unraveling the Plant-Soil Interactome

NASA Astrophysics Data System (ADS)

Lipton, M. S.; Hixson, K.; Ahkami, A. H.; HaHandkumbura, P. P.; Hess, N. J.; Fang, Y.; Fortin, D.; Stanfill, B.; Yabusaki, S.; Engbrecht, K. M.; Baker, E.; Renslow, R.; Jansson, C.

2017-12-01

Plant photosynthesis is the primary conduit of carbon fixation from the atmosphere to the terrestrial ecosystem. While more is known about plant physiology and biochemistry, the interplay between genetic and environmental factors that govern partitioning of carbon to above- and below ground plant biomass, to microbes, to the soil, and respired to the atmosphere is not well understood holistically. To address this knowledge gap there is a need to define, study, comprehend, and model the plant ecosystem as an integrated system of integrated biotic and abiotic processes and feedbacks. Local rhizosphere conditions are an important control on plant performance but are in turn affected by plant uptake and rhizodeposition processes. C3 and C4 plants have different CO2 fixation strategies and likely have differential metabolic profiles resulting in different carbon sources exuding to the rhizosphere. In this presentation, we report on an integrated capability to better understand plant-soil interactions, including modeling tools that address the spatiotemporal hydrobiogeochemistry in the rhizosphere. Comparing Brachypodium distachyon, (Brachypodium) as our C3 representative and Setaria viridis (Setaria) as our C4 representative, we designed, highly controlled single-plant experimental ecosystems based these model grasses to enable quantitative prediction of ecosystem traits and responses as a function of plant genotype and environmental variables. A metabolomics survey of 30 Brachypodium genotypes grown under control and drought conditions revealed specific metabolites that correlated with biomass production and drought tolerance. A comparison of Brachypodium and Setaria grown with control and a future predicted elevated CO2 level revealed changes in biomass accumulation and metabolite profiles between the C3 and C4 species in both leaves and roots. Finally, we are building an mechanistic modeling capability that will contribute to a better basis for modeling plant water and nutrient cycling in larger scale models.

Rapid Inhibition Profiling in Bacillus subtilis to Identify the Mechanism of Action of New Antimicrobials.

PubMed

Lamsa, Anne; Lopez-Garrido, Javier; Quach, Diana; Riley, Eammon P; Pogliano, Joe; Pogliano, Kit

2016-08-19

Increasing antimicrobial resistance has become a major public health crisis. New antimicrobials with novel mechanisms of action (MOA) are desperately needed. We previously developed a method, bacterial cytological profiling (BCP), which utilizes fluorescence microscopy to rapidly identify the MOA of antimicrobial compounds. BCP is based upon our discovery that cells treated with antibiotics affecting different metabolic pathways generate different cytological signatures, providing quantitative information that can be used to determine a compound's MOA. Here, we describe a system, rapid inhibition profiling (RIP), for creating cytological profiles of new antibiotic targets for which there are currently no chemical inhibitors. RIP consists of the fast, inducible degradation of a target protein followed by BCP. We demonstrate that degrading essential proteins in the major metabolic pathways for DNA replication, transcription, fatty acid biosynthesis, and peptidoglycan biogenesis in Bacillus subtilis rapidly produces cytological profiles closely matching that of antimicrobials targeting the same pathways. Additionally, RIP and antibiotics targeting different steps in fatty acid biosynthesis can be differentiated from each other. We utilize RIP and BCP to show that the antibacterial MOA of four nonsteroidal anti-inflammatory antibiotics differs from that proposed based on in vitro data. RIP is a versatile method that will extend our knowledge of phenotypes associated with inactivating essential bacterial enzymes and thereby allow for screening for molecules that inhibit novel essential targets.

Rapid Analysis of Corni fructus Using Paper Spray-Mass Spectrometry.

PubMed

Guo, Yuan; Gu, Zhixin; Liu, Xuemei; Liu, Jingjing; Ma, Ming; Chen, Bo; Wang, Liping

2017-07-01

Paper spray-mass spectrometry (PS-MS) is a kind of ambient MS technique for the rapid analysis of samples. Corni fructus has been widely used in traditional Chinese compound preparations and healthy food. However, a number of counterfeits of Corni fructus, such as Crataegi fructus, Lycii fructus, and grape skin are illegally sold in crude herb markets. Therefore, the development of a rapid and high-throughput quality evaluation method is important for ensuring the effectiveness and safety of the crude materials of Corni fructus. To develop PS-MS chemical profiles and a semi-quantitative method of Corni fructus for quality assessment and control, and species distinction of Corni fructus. Both positive and negative ion PS-MS chemical profiles were constructed for species distinction. The statistical analysis of the chemical profiles was accomplished by principal component analysis (PCA). Rapid semi-quantitative analysis of loganin and morroniside in the extracts of Corni fructus were accomplished by PS-MS. The profiles of the Corni fructus and Crataegi fructus samples were clearly clustered into two categories. The limit of quantification (LOQ) in the semi-quantitative analysis was 6 μg/mL and 5.6 μg/mL for loganin and morroniside, respectively. PS-MS is a simple, rapid, and high-throughput method for the quality control and species distinction of Corni fructus. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Efficient, ultra-high-affinity chromatography in a one-step purification of complex proteins

PubMed Central

Vassylyeva, Marina N.; Klyuyev, Sergiy; Vassylyev, Alexey D.; Wesson, Hunter; Zhang, Zhuo; Renfrow, Matthew B.; Wang, Hengbin; Higgins, N. Patrick; Chow, Louise T.; Vassylyev, Dmitry G.

2017-01-01

Protein purification is an essential primary step in numerous biological studies. It is particularly significant for the rapidly emerging high-throughput fields, such as proteomics, interactomics, and drug discovery. Moreover, purifications for structural and industrial applications should meet the requirement of high yield, high purity, and high activity (HHH). It is, therefore, highly desirable to have an efficient purification system with a potential to meet the HHH benchmark in a single step. Here, we report a chromatographic technology based on the ultra-high-affinity (Kd ∼ 10−14–10−17 M) complex between the Colicin E7 DNase (CE7) and its inhibitor, Immunity protein 7 (Im7). For this application, we mutated CE7 to create a CL7 tag, which retained the full binding affinity to Im7 but was inactivated as a DNase. To achieve high capacity, we developed a protocol for a large-scale production and highly specific immobilization of Im7 to a solid support. We demonstrated its utility with one-step HHH purification of a wide range of traditionally challenging biological molecules, including eukaryotic, membrane, toxic, and multisubunit DNA/RNA-binding proteins. The system is simple, reusable, and also applicable to pulldown and kinetic activity/binding assays. PMID:28607052

Dissecting the chromatin interactome of microRNA genes.

PubMed

Chen, Dijun; Fu, Liang-Yu; Zhang, Zhao; Li, Guoliang; Zhang, Hang; Jiang, Li; Harrison, Andrew P; Shanahan, Hugh P; Klukas, Christian; Zhang, Hong-Yu; Ruan, Yijun; Chen, Ling-Ling; Chen, Ming

2014-03-01

Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes. RNA polymerase II-associated ChIA-PET data reveal that many groups of MIRs and protein-coding genes are organized into functionally compartmentalized chromatin communities and undergo coordinated expression when their genomic loci are spatially colocated. We observe that MIRs display widespread communication in those transcriptionally active communities. Moreover, miRNA-target interactions are significantly enriched among communities with functional homogeneity while depleted from the same community from which they originated, suggesting MIRs coordinating function-related pathways at posttranscriptional level. Further investigation demonstrates the existence of spatial MIR-MIR chromatin interacting networks. We show that groups of spatially coordinated MIRs are frequently from the same family and involved in the same disease category. The spatial interaction network possesses both common and cell-specific subnetwork modules that result from the spatial organization of chromatin within different cell types. Together, our study unveils an entirely unexplored layer of MIR regulation throughout the human genome that links the spatial coordination of MIRs to their co-expression and function.

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

PubMed

Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

The Ties That Bind: Mapping the Dynamic Enhancer-Promoter Interactome.

PubMed

Spurrell, Cailyn H; Dickel, Diane E; Visel, Axel

2016-11-17

Coupling chromosome conformation capture to molecular enrichment for promoter-containing DNA fragments enables the systematic mapping of interactions between individual distal regulatory sequences and their target genes. In this Minireview, we describe recent progress in the application of this technique and related complementary approaches to gain insight into the lineage- and cell-type-specific dynamics of interactions between regulators and gene promoters. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantum-dot temperature profiles during laser irradiation for semiconductor-doped glasses

NASA Astrophysics Data System (ADS)

Nagpal, Swati

2002-12-01

Temperature profiles around laser irradiated CdX (X=S, Se, and Te) quantum dots in borosilicate glasses were theoretically modeled. Initially the quantum dots heat up rapidly, followed by a gradual increase of temperature. Also it is found that larger dots reach higher temperatures for the same pulse characteristics. After the pulse is turned off, the dots initially cool rapidly, followed by a gradual decrease in temperature.

MaxiK channel interactome reveals its interaction with GABA transporter 3 and heat shock protein 60 in the mammalian brain.

PubMed

Singh, H; Li, M; Hall, L; Chen, S; Sukur, S; Lu, R; Caputo, A; Meredith, A L; Stefani, E; Toro, L

2016-03-11

Large conductance voltage and calcium-activated potassium (MaxiK) channels are activated by membrane depolarization and elevated cytosolic Ca(2+). In the brain, they localize to neurons and astrocytes, where they play roles such as resetting the membrane potential during an action potential, neurotransmitter release, and neurovascular coupling. MaxiK channels are known to associate with several modulatory proteins and accessory subunits, and each of these interactions can have distinct physiological consequences. To uncover new players in MaxiK channel brain physiology, we applied a directed proteomic approach and obtained MaxiK channel pore-forming α subunit brain interactome using specific antibodies. Controls included immunoprecipitations with rabbit immunoglobulin G (IgG) and with anti-MaxiK antibodies in wild type and MaxiK channel knockout mice (Kcnma1(-/-)), respectively. We have found known and unreported interactive partners that localize to the plasma membrane, extracellular space, cytosol and intracellular organelles including mitochondria, nucleus, endoplasmic reticulum and Golgi apparatus. Localization of MaxiK channel to mitochondria was further confirmed using purified brain mitochondria colabeled with MitoTracker. Independent proof of MaxiK channel interaction with previously unidentified partners is given for GABA transporter 3 (GAT3) and heat shock protein 60 (HSP60). In human embryonic kidney 293 cells containing SV40 T-antigen (HEK293T) cells, both GAT3 and HSP60 coimmunoprecipitated and colocalized with MaxiK channel; colabeling was observed mainly at the cell periphery with GAT3 and intracellularly with HSP60 with protein proximity indices of ∼ 0.6 and ∼ 0.4, respectively. In rat primary hippocampal neurons, colocalization index was identical for GAT3 (∼ 0.6) and slightly higher for HSP60 (∼ 0.5) association with MaxiK channel. The results of this study provide a complete interactome of MaxiK channel the mouse brain, further establish the localization of MaxiK channel in the mouse brain mitochondria and demonstrate the interaction of MaxiK channel with GAT3 and HSP60 in neurons. The interaction of MaxiK channel with GAT3 opens the possibility of a role of MaxiK channel in GABA homeostasis and signaling. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Exosomes and Homeostatic Synaptic Plasticity Are Linked to Each other and to Huntington's, Parkinson's, and Other Neurodegenerative Diseases by Database-Enabled Analyses of Comprehensively Curated Datasets

PubMed Central

Wang, James K. T.; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J.

2017-01-01

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene (HTT), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases. PMID:28611571

Exosomes and Homeostatic Synaptic Plasticity Are Linked to Each other and to Huntington's, Parkinson's, and Other Neurodegenerative Diseases by Database-Enabled Analyses of Comprehensively Curated Datasets.

PubMed

Wang, James K T; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J

2017-01-01

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene ( HTT ), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases.

A bioinformatic and mechanistic study elicits the antifibrotic effect of ursolic acid through the attenuation of oxidative stress with the involvement of ERK, PI3K/Akt, and p38 MAPK signaling pathways in human hepatic stellate cells and rat liver

PubMed Central

He, Wenhua; Shi, Feng; Zhou, Zhi-Wei; Li, Bimin; Zhang, Kunhe; Zhang, Xinhua; Ouyang, Canhui; Zhou, Shu-Feng; Zhu, Xuan

2015-01-01

NADPH oxidases (NOXs) are a predominant mediator of redox homeostasis in hepatic stellate cells (HSCs), and oxidative stress plays an important role in the pathogenesis of liver fibrosis. Ursolic acid (UA) is a pentacyclic triterpenoid with various pharmacological activities, but the molecular targets and underlying mechanisms for its antifibrotic effect in the liver remain elusive. This study aimed to computationally predict the molecular interactome and mechanistically investigate the antifibrotic effect of UA on oxidative stress, with a focus on NOX4 activity and cross-linked signaling pathways in human HSCs and rat liver. Drug–drug interaction via chemical–protein interactome tool, a server that can predict drug–drug interaction via chemical–protein interactome, was used to predict the molecular targets of UA, and Database for Annotation, Visualization, and Integrated Discovery was employed to analyze the signaling pathways of the predicted targets of UA. The bioinformatic data showed that there were 611 molecular proteins possibly interacting with UA and that there were over 49 functional clusters responding to UA. The subsequential benchmarking data showed that UA significantly reduced the accumulation of type I collagen in HSCs in rat liver, increased the expression level of MMP-1, but decreased the expression level of TIMP-1 in HSC-T6 cells. UA also remarkably reduced the gene expression level of type I collagen in HSC-T6 cells. Furthermore, UA remarkably attenuated oxidative stress via negative regulation of NOX4 activity and expression in HSC-T6 cells. The employment of specific chemical inhibitors, SB203580, LY294002, PD98059, and AG490, demonstrated the involvement of ERK, PI3K/Akt, and p38 MAPK signaling pathways in the regulatory effect of UA on NOX4 activity and expression. Collectively, the antifibrotic effect of UA is partially due to the oxidative stress attenuating effect through manipulating NOX4 activity and expression. The results suggest that UA may act as a promising antifibrotic agent. More studies are warranted to evaluate the safety and efficacy of UA in the treatment of liver fibrosis. PMID:26347199

Adaptive dynamics of cuticular hydrocarbons in Drosophila

PubMed Central

Rajpurohit, Subhash; Hanus, Robert; Vrkoslav, Vladimír; Behrman, Emily L.; Bergland, Alan O.; Petrov, Dmitri; Cvačka, Josef; Schmidt, Paul S.

2016-01-01

Cuticular hydrocarbons (CHCs) are hydrophobic compounds deposited on the arthropod cuticle that are of functional significance with respect to stress tolerance, social interactions, and mating dynamics. We characterized CHC profiles in natural populations of Drosophila melanogaster at five levels: across a latitudinal transect in the eastern U.S., as a function of developmental temperature during culture, across seasonal time in replicate years, and as a function of rapid evolution in experimental mesocosms in the field. Furthermore, we also characterized spatial and temporal change in allele frequencies for SNPs in genes that are associated with the production and chemical profile of CHCs. Our data demonstrate a striking degree of parallelism for clinal and seasonal variation in CHCs in this taxon; CHC profiles also demonstrate significant plasticity in response to rearing temperature, and the observed patterns of plasticity parallel the spatiotemporal patterns observed in nature. We find that these congruent shifts in CHC profiles across time and space are also mirrored by predictable shifts in allele frequencies at SNPs associated with CHC chain length. Finally, we observed rapid and predictable evolution of CHC profiles in experimental mesocosms in the field. Together, these data strongly suggest that CHC profiles respond rapidly and adaptively to environmental parameters that covary with latitude and season, and that this response reflects the process of local adaptation in natural populations of D. melanogaster. PMID:27718537

Depth profiles of oxygen precipitates in nitride-coated silicon wafers subjected to rapid thermal annealing

NASA Astrophysics Data System (ADS)

Voronkov, V. V.; Falster, R.; Kim, TaeHyeong; Park, SoonSung; Torack, T.

2013-07-01

Silicon wafers, coated with a silicon nitride layer and subjected to high temperature Rapid Thermal Annealing (RTA) in Ar, show—upon a subsequent two-step precipitation anneal cycle (such as 800 °C + 1000 °C)—peculiar depth profiles of oxygen precipitate densities. Some profiles are sharply peaked near the wafer surface, sometimes with a zero bulk density. Other profiles are uniform in depth. The maximum density is always the same. These profiles are well reproduced by simulations assuming that precipitation starts from a uniformly distributed small oxide plates originated from RTA step and composed of oxygen atoms and vacancies ("VO2 plates"). During the first step of the precipitation anneal, an oxide layer propagates around this core plate by a process of oxygen attachment, meaning that an oxygen-only ring-shaped plate emerges around the original plate. These rings, depending on their size, then either dissolve or grow during the second part of the anneal leading to a rich variety of density profiles.

MALDI-TOF MS Profiling-Advances in Species Identification of Pests, Parasites, and Vectors.

PubMed

Murugaiyan, Jayaseelan; Roesler, Uwe

2017-01-01

Invertebrate pests and parasites of humans, animals, and plants continue to cause serious diseases and remain as a high treat to agricultural productivity and storage. The rapid and accurate species identification of the pests and parasites are needed for understanding epidemiology, monitoring outbreaks, and designing control measures. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as a rapid, cost effective, and high throughput technique of microbial species identification in modern diagnostic laboratories. The development of soft ionization techniques and the release of commercial pattern matching software platforms has resulted in the exponential growth of applications in higher organisms including parasitology. The present review discusses the proof-of-principle experiments and various methods of MALDI MS profiling in rapid species identification of both laboratory and field isolates of pests, parasites and vectors.

MALDI-TOF MS Profiling-Advances in Species Identification of Pests, Parasites, and Vectors

PubMed Central

Murugaiyan, Jayaseelan; Roesler, Uwe

2017-01-01

Invertebrate pests and parasites of humans, animals, and plants continue to cause serious diseases and remain as a high treat to agricultural productivity and storage. The rapid and accurate species identification of the pests and parasites are needed for understanding epidemiology, monitoring outbreaks, and designing control measures. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as a rapid, cost effective, and high throughput technique of microbial species identification in modern diagnostic laboratories. The development of soft ionization techniques and the release of commercial pattern matching software platforms has resulted in the exponential growth of applications in higher organisms including parasitology. The present review discusses the proof-of-principle experiments and various methods of MALDI MS profiling in rapid species identification of both laboratory and field isolates of pests, parasites and vectors. PMID:28555175

Development and validation of the RapidHIT™ 200 utilising NGMSElect™ Express for the processing of buccal swabs.

PubMed

Shackleton, David; Pagram, Jenny; Ives, Lesley; Vanhinsbergh, Des

2018-06-02

The RapidHIT™ 200 System is a fully automated sample-to-DNA profile system designed to produce high quality DNA profiles within 2h. The use of RapidHIT™ 200 System within the United Kingdom Criminal Justice System (UKCJS) has required extensive development and validation of methods with a focus on AmpFℓSTR ® NGMSElect™ Express PCR kit to comply with specific regulations for loading to the UK National DNA Database (NDNAD). These studies have been carried out using single source reference samples to simulate live reference samples taken from arrestees and victims for elimination. The studies have shown that the system is capable of generating high quality profile and has achieved the accreditations necessary to load to the NDNAD; a first for the UK. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Identification of LMO2 transcriptome and interactome in diffuse large B-cell lymphoma

PubMed Central

Cubedo, Elena; Gentles, Andrew J.; Huang, Chuanxin; Natkunam, Yasodha; Bhatt, Shruti; Lu, Xiaoqing; Jiang, Xiaoyu; Romero-Camarero, Isabel; Freud, Aharon; Zhao, Shuchun; Bacchi, Carlos E.; Martínez-Climent, Jose A.; Sánchez-García, Isidro; Melnick, Ari

2012-01-01

LMO2 regulates gene expression by facilitating the formation of multipartite DNA-binding complexes. In B cells, LMO2 is specifically up-regulated in the germinal center (GC) and is expressed in GC-derived non-Hodgkin lymphomas. LMO2 is one of the most powerful prognostic indicators in diffuse large B-cell (DLBCL) patients. However, its function in GC B cells and DLBCL is currently unknown. In this study, we characterized the LMO2 transcriptome and transcriptional complex in DLBCL cells. LMO2 regulates genes implicated in kinetochore function, chromosome assembly, and mitosis. Overexpression of LMO2 in DLBCL cell lines results in centrosome amplification. In DLBCL, the LMO2 complex contains some of the traditional partners, such as LDB1, E2A, HEB, Lyl1, ETO2, and SP1, but not TAL1 or GATA proteins. Furthermore, we identified novel LMO2 interacting partners: ELK1, nuclear factor of activated T-cells (NFATc1), and lymphoid enhancer-binding factor1 (LEF1) proteins. Reporter assays revealed that LMO2 increases transcriptional activity of NFATc1 and decreases transcriptional activity of LEF1 proteins. Overall, our studies identified a novel LMO2 transcriptome and interactome in DLBCL and provides a platform for future elucidation of LMO2 function in GC B cells and DLBCL pathogenesis. PMID:22517897

RISE: a database of RNA interactome from sequencing experiments

PubMed Central

Gong, Jing; Shao, Di; Xu, Kui

2018-01-01

Abstract We present RISE (http://rise.zhanglab.net), a database of RNA Interactome from Sequencing Experiments. RNA-RNA interactions (RRIs) are essential for RNA regulation and function. RISE provides a comprehensive collection of RRIs that mainly come from recent transcriptome-wide sequencing-based experiments like PARIS, SPLASH, LIGR-seq, and MARIO, as well as targeted studies like RIA-seq, RAP-RNA and CLASH. It also includes interactions aggregated from other primary databases and publications. The RISE database currently contains 328,811 RNA-RNA interactions mainly in human, mouse and yeast. While most existing RNA databases mainly contain interactions of miRNA targeting, notably, more than half of the RRIs in RISE are among mRNA and long non-coding RNAs. We compared different RRI datasets in RISE and found limited overlaps in interactions resolved by different techniques and in different cell lines. It may suggest technology preference and also dynamic natures of RRIs. We also analyzed the basic features of the human and mouse RRI networks and found that they tend to be scale-free, small-world, hierarchical and modular. The analysis may nominate important RNAs or RRIs for further investigation. Finally, RISE provides a Circos plot and several table views for integrative visualization, with extensive molecular and functional annotations to facilitate exploration of biological functions for any RRI of interest. PMID:29040625

Examining Myddosome Formation by Luminescence-Based Mammalian Interactome Mapping (LUMIER).

PubMed

Wolz, Olaf-Oliver; Koegl, Manfred; Weber, Alexander N R

2018-01-01

Recent structural, biochemical, and functional studies have led to the notion that many of the post-receptor signaling complexes in innate immunity have a multimeric, multi-protein architecture whose hierarchical assembly is vital for function. The Myddosome is a post-receptor complex in the cytoplasmic signaling of Toll-like receptors (TLR) and the Interleukin-1 receptor (IL-1R), involving the proteins MyD88, IL-1R-associated kinase 4 (IRAK4), and IRAK2. Its importance is strikingly illustrated by the fact that rare germline mutations in MYD88 causing high susceptibility to infections are characterized by failure to assemble Myddosomes; conversely, gain-of-function MYD88 mutations leading to oncogenic hyperactivation of NF-κB show increased Myddosome formation. Reliable methods to probe Myddosome formation experimentally are therefore vital to further study the properties of this important post-receptor complex and its role in innate immunity, such as its regulation by posttranslational modification. Compared to structural and biochemical analyses, luminescence-based mammalian interactome mapping (LUMIER) is a straightforward, automatable, quantifiable, and versatile technique to study protein-protein interactions in a physiologically relevant context. We adapted LUMIER for Myddosome analysis and provide here a basic background of this technique, suitable experimental protocols, and its potential for medium-throughput screening. The principles presented herein can be adapted to other signaling pathways.

Magnetic nanoparticles to recover cellular organelles and study the time resolved nanoparticle-cell interactome throughout uptake.

PubMed

Bertoli, Filippo; Davies, Gemma-Louise; Monopoli, Marco P; Moloney, Micheal; Gun'ko, Yurii K; Salvati, Anna; Dawson, Kenneth A

2014-08-27

Nanoparticles in contact with cells and living organisms generate quite novel interactions at the interface between the nanoparticle surface and the surrounding biological environment. However, a detailed time resolved molecular level description of the evolving interactions as nanoparticles are internalized and trafficked within the cellular environment is still missing and will certainly be required for the emerging arena of nanoparticle-cell interactions to mature. In this paper promising methodologies to map out the time resolved nanoparticle-cell interactome for nanoparticle uptake are discussed. Thus silica coated magnetite nanoparticles are presented to cells and their magnetic properties used to isolate, in a time resolved manner, the organelles containing the nanoparticles. Characterization of the recovered fractions shows that different cell compartments are isolated at different times, in agreement with imaging results on nanoparticle intracellular location. Subsequently the internalized nanoparticles can be further isolated from the recovered organelles, allowing the study of the most tightly nanoparticle-bound biomolecules, analogous to the 'hard corona' that so far has mostly been characterized in extracellular environments. Preliminary data on the recovered nanoparticles suggest that significant portion of the original corona (derived from the serum in which particles are presented to the cells) is preserved as nanoparticles are trafficked through the cells. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

PubMed Central

Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S.; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P.; Sowdhamini, Ramanathan; Chandra, Nagasuma R.; Blundell, Tom L.; Srinivasan, Narayanaswamy

2015-01-01

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding. Database URL: http://proline.biochem.iisc.ernet.in/sincre PMID:26130660

Rapid non-contact inspection of composite ailerons using air-coupled ultrasound

NASA Astrophysics Data System (ADS)

Panda, Rabi Sankar; Karpenko, Oleksii; Udpa, Lalita; Haq, Mahmoodul; Rajagopal, Prabhu; Balasubramaniam, Krishnan

2016-02-01

This paper demonstrates an approach for rapid non-contact air-coupled ultrasonic inspection of composite ailerons with complex cross-sectional profile including thickness changes, curvature and the presence of a number of stiffeners. Low-frequency plate guided ultrasonic modes are used in B-scan mode for the measurements in pitch-catch mode. Appropriate probe holder angles suitable for generating and receiving lower order guided wave modes are discussed. Different embodiments of the pitch-catch tandem positions along and across stiffener and curved regions of the test sample enable a rapid test campaign capturing the feature-rich sample profile. Techniques to distinguish special features in the stiffener are presented.

Molecular characterization and interactome analysis of Trypanosoma cruzi tryparedoxin II.

PubMed

Arias, Diego G; Piñeyro, María Dolores; Iglesias, Alberto A; Guerrero, Sergio A; Robello, Carlos

2015-04-29

Trypanosoma cruzi, the causative agent of Chagas disease, possesses two tryparedoxins (TcTXNI and TcTXNII), belonging to the thioredoxin superfamily. TXNs are oxidoreductases which mediate electron transfer between trypanothione and peroxiredoxins. This constitutes a difference with the host cells, in which these activities are mediated by thioredoxins. These differences make TXNs an attractive target for drug development. In a previous work we characterized TcTXNI, including the redox interactome. In this work we extend the study to TcTXNII. We demonstrate that TcTXNII is a transmembrane protein anchored to the surface of the mitochondria and endoplasmic reticulum, with a cytoplasmatic orientation of the redox domain. It would be expressed during the metacyclogenesis process. In order to continue with the characterization of the redox interactome of T. cruzi, we designed an active site mutant TcTXNII lacking the resolving cysteine, and through the expression of this mutant protein and incubation with T. cruzi proteins, heterodisulfide complexes were isolated by affinity chromatography and identified by mass spectrometry. This allowed us to identify sixteen TcTXNII interacting proteins, which are involved in a wide range of cellular processes, indicating the relevance of TcTXNII, and contributing to our understanding of the redox interactome of T. cruzi. T. cruzi, the causative agent of Chagas disease, constitutes a major sanitary problem in Latin America. The number of estimated infected persons is ca. 8 million, 28 million people are at risk of infection and ~20,000 deaths occur per year in endemic regions. No vaccines are available at present, and most drugs currently in use were developed decades ago and show variable efficacy with undesirable side effects. The parasite is able to live and prolipherate inside macrophage phagosomes, where it is exposed to cytotoxic reactive oxygen and nitrogen species, derived from macrophage activation. Therefore, T. cruzi antioxidant mechanisms constitute an active field of investigation, since they could provide the basis for a rational drug development. Peroxide detoxification in this parasite is achieved by ascorbate peroxidase and different thiol-dependent peroxidases. Among them, both mitochondrial and cytosolic tryparedoxin peroxidases, typical two-cysteine peroxiredoxins, were found to be important for hydrogen peroxide and peroxynitrite detoxification and their expression levels correlated with parasite infectivity and virulence. In trypanosomes tryparedoxins and not thioredoxins act as peroxiredoxin reductases, suggesting that these enzymes substitute thioredoxins in these parasites. T. cruzi possesses two tryparedoxin genes, TcTXNI and TcTXN II. Since thioredoxins are proteins with several targets actively participating of complex redox networks, we have previously investigated if this is the case also for TcTXNI, for which we described relevant partners (J Proteomics. 2011;74(9):1683-92). In this manuscript we investigated the interactions of TcTXNII. We have designed an active site mutant tryparedoxin II lacking the resolving cysteine and, through the expression of this mutant protein and its incubation with T. cruzi proteins, hetero disulfide complexes were isolated by affinity chromatography purification and identified by electrophoresis separation and MS identification. This allowed us to identify sixteen TcTXNII interacting proteins which are involved in different and relevant cellular processes. Moreover, we demonstrate that TcTXNII is a transmembrane protein anchored to the surface of the mitochondria and endoplasmic reticulum. Copyright © 2015 Elsevier B.V. All rights reserved.

Rapid Detection of Necrosis in Breast Cancer with Desorption Electrospray Ionization Mass Spectrometry

PubMed Central

Tata, Alessandra; Woolman, Michael; Ventura, Manuela; Bernards, Nicholas; Ganguly, Milan; Gribble, Adam; Shrestha, Bindesh; Bluemke, Emma; Ginsberg, Howard J.; Vitkin, Alex; Zheng, Jinzi; Zarrine-Afsar, Arash

2016-01-01

Identification of necrosis in tumors is of prognostic value in treatment planning, as necrosis is associated with aggressive forms of cancer and unfavourable outcomes. To facilitate rapid detection of necrosis with Mass Spectrometry (MS), we report the lipid MS profile of necrotic breast cancer with Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) imaging validated with statistical analysis and correlating pathology. This MS profile is characterized by (1) the presence of the ion of m/z 572.48 [Cer(d34:1) + Cl]− which is a ceramide absent from the viable cancer subregions; (2) the absence of the ion of m/z 391.25 which is present in small abundance only in viable cancer subregions; and (3) a slight increase in the relative intensity of known breast cancer biomarker ions of m/z 281.25 [FA(18:1)-H]− and 303.23 [FA(20:4)-H]−. Necrosis is accompanied by alterations in the tissue optical depolarization rate, allowing tissue polarimetry to guide DESI-MS analysis for rapid MS profiling or targeted MS imaging. This workflow, in combination with the MS profile of necrosis, may permit rapid characterization of necrotic tumors from tissue slices. Further, necrosis-specific biomarker ions are detected in seconds with single MS scans of necrotic tumor tissue smears, which further accelerates the identification workflow by avoiding tissue sectioning and slide preparation. PMID:27734938

DEVELOPMENT OF PROTEIN PROFILE TECHNOLOGY TO EVALUATE ECOLOGICAL EFFECTS OF ENVIRONMENTAL CHEMICALS USING A SMALL FISH MODEL

EPA Science Inventory

The rationale for this research is: i) Protein expression changes with life stage, disease, tissue type and environmental stressors; ii) Technology allows rapid analysis of large numbers of proteins to provide protein expression profiles; iii) Protein profiles are used as specifi...

Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data

PubMed Central

Raju, Hemalatha B.; Tsinoremas, Nicholas F.; Capobianco, Enrico

2016-01-01

Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein–protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches. PMID:27803687

Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data.

PubMed

Raju, Hemalatha B; Tsinoremas, Nicholas F; Capobianco, Enrico

2016-01-01

Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein-protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches.

A Systems Biology Approach Investigating the Effect of Probiotics on the Vaginal Microbiome and Host Responses in a Double Blind, Placebo-Controlled Clinical Trial of Post-Menopausal Women

PubMed Central

Bisanz, Jordan E.; Seney, Shannon; McMillan, Amy; Vongsa, Rebecca; Koenig, David; Wong, LungFai; Dvoracek, Barbara; Gloor, Gregory B.; Sumarah, Mark; Ford, Brenda; Herman, Dorli; Burton, Jeremy P.; Reid, Gregor

2014-01-01

A lactobacilli dominated microbiota in most pre and post-menopausal women is an indicator of vaginal health. The objective of this double blinded, placebo-controlled crossover study was to evaluate in 14 post-menopausal women with an intermediate Nugent score, the effect of 3 days of vaginal administration of probiotic L. rhamnosus GR-1 and L. reuteri RC-14 (2.5×109 CFU each) on the microbiota and host response. The probiotic treatment did not result in an improved Nugent score when compared to when placebo. Analysis using 16S rRNA sequencing and metabolomics profiling revealed that the relative abundance of Lactobacillus was increased following probiotic administration as compared to placebo, which was weakly associated with an increase in lactate levels. A decrease in Atopobium was also observed. Analysis of host responses by microarray showed the probiotics had an immune-modulatory response including effects on pattern recognition receptors such as TLR2 while also affecting epithelial barrier function. This is the first study to use an interactomic approach for the study of vaginal probiotic administration in post-menopausal women. It shows that in some cases multifaceted approaches are required to detect the subtle molecular changes induced by the host to instillation of probiotic strains. Trial Registration ClinicalTrials.gov NCT02139839 PMID:25127240

Modulation of neuronal proteome profile in response to Japanese encephalitis virus infection.

PubMed

Sengupta, Nabonita; Ghosh, Sourish; Vasaikar, Suhas V; Gomes, James; Basu, Anirban

2014-01-01

In this study we have reported the in vivo proteomic changes during Japanese Encephalitis Virus (JEV) infection in combination with in vitro studies which will help in the comprehensive characterization of the modifications in the host metabolism in response to JEV infection. We performed a 2-DE based quantitative proteomic study of JEV-infected mouse brain as well as mouse neuroblastoma (Neuro2a) cells to analyze the host response to this lethal virus. 56 host proteins were found to be differentially expressed post JEV infection (defined as exhibiting ≥ 1.5-fold change in protein abundance upon JEV infection). Bioinformatics analyses were used to generate JEV-regulated host response networks which reported that the identified proteins were found to be associated with various cellular processes ranging from intracellular protein transport, cellular metabolism and ER stress associated unfolded protein response. JEV was found to invade the host protein folding machinery to sustain its survival and replication inside the host thereby generating a vigorous unfolded protein response, subsequently triggering a number of pathways responsible for the JEV associated pathologies. The results were also validated using a human cell line to correlate them to the human response to JEV. The present investigation is the first report on JEV-host interactome in in vivo model and will be of potential interest for future antiviral research in this field.

Rapid Weight Loss vs. Slow Weight Loss: Which is More Effective on Body Composition and Metabolic Risk Factors?

PubMed

Ashtary-Larky, Damoon; Ghanavati, Matin; Lamuchi-Deli, Nasrin; Payami, Seyedeh Arefeh; Alavi-Rad, Sara; Boustaninejad, Mehdi; Afrisham, Reza; Abbasnezhad, Amir; Alipour, Meysam

2017-07-01

Achieving weight loss (WL) in a short time regardless of its consequences has always been the focus of many obese and overweight people. In this study, anthropometric and metabolic effects of two diets for rapid and slow WL and their consequences were examined. Forty-two obese and overweight individuals were randomly divided to 2 groups; rapid WL (weight loss of at least 5% in 5 weeks) and slow WL (weight loss of at least 5% in 15 weeks). To compare the effects of the rate of WL in 2 groups, the same amount of was achieved with different durations. Anthropometric indices, lipid, and glycemic profiles, and systolic and diastolic blood pressures were evaluated before and after the intervention. Both protocols of rapid WL and slow WL caused reduction in waist circumference, hip circumference, total body water, body fat mass, lean body mass, and resting metabolic rate (RMR). Further reduction in waist circumference, hip circumference, fat mass, and percentage of body fat was observed in slow WL and decreased total body water, lean body mass, fat free mass, and RMR was observed in rapid WL. Improvement in lipid and glycemic profiles was observed in both groups. Reduction of low-density lipoprotein and fasting blood sugar, improvement of insulin resistance, and sensitivity were more significant in rapid WL in comparison to slow WL. Weight Loss regardless of its severity could improve anthropometric indicators, although body composition is more favorable following a slow WL. Both diets improved lipid and glycemic profiles. In this context, rapid WL was more effective. (IRCT2016010424699N2).

The Breast Cancer DNA Interactome

DTIC Science & Technology

2013-10-01

in Gheldof et al. with minor modifications [62]. HMEC, MCF7 and MDA-MB-231 cells (26107) were fixed in 2% formaldehyde in fresh medium for 10 min at... digested with 1500 U of HindIII (New England Biolabs Ipswich, MA) overnight at 37uC with shaking at 950 rpm. 200 ml of digested nuclei were removed for...assessing digestion efficiency by qPCR. The restriction enzyme was inactivated by the addition of 1.6% SDS and was incubated at 65uC for 20 min. The

The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies* | Office of Cancer Genomics

Cancer.gov

As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein–protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes.

The Role of BRCA1 in Suppressing Epithelial Mesenchymal Transition in Mammary Gland and Tumor Development

DTIC Science & Technology

2016-11-01

2015;6:7505. doi: 10.1038/ncomms8505. PubMed PMID: 26106036; PubMed Central PMCID: PMC4491827. 19. Kalluri R, Weinberg RA. The basics of epithelial...Gupta PB, Evans KW, Hollier BG, Ram PT, Lander ES, Rosen JM, Weinberg RA, Mani SA. Core epithelial-to- mesenchymal transition interactome gene...Molecular analysis reveals heterogeneity of mouse mammary tumors conditionally mutant for Brca1. Mol Cancer 2008;7:29. 14. Kalluri R, Weinberg RA. The basics

A Proteomic Approach to Identify Phosphorylation-Dependent Targets of BRCT Domains

DTIC Science & Technology

2009-03-01

Elias, P. & de Lange, T. (1997) EMBO J. 16, 1785–1794. 45. Broccoli , D., Smogorzewska, A., Chong, L. & de Lange, T. (1997) Nat. Genet. 17, 231–235...mammalian telomere interactome: regulation and regulatory activities of telomeres. Crit. Rev. Eukaryot. Gene Expr. 16, 103–118 (2006). 13. Broccoli , D... Broccoli , D., Dai, Y., Hardy, S. & de Lange, T. p53- and ATM-dependent apoptosis induced by telomeres lacking TRF2. Science 283, 1321–1325 (1999). 30. Liu

Omics strategies for revealing Yersinia pestis virulence

PubMed Central

Yang, Ruifu; Du, Zongmin; Han, Yanping; Zhou, Lei; Song, Yajun; Zhou, Dongsheng; Cui, Yujun

2012-01-01

Omics has remarkably changed the way we investigate and understand life. Omics differs from traditional hypothesis-driven research because it is a discovery-driven approach. Mass datasets produced from omics-based studies require experts from different fields to reveal the salient features behind these data. In this review, we summarize omics-driven studies to reveal the virulence features of Yersinia pestis through genomics, trascriptomics, proteomics, interactomics, etc. These studies serve as foundations for further hypothesis-driven research and help us gain insight into Y. pestis pathogenesis. PMID:23248778

Internal validation of the DNAscan/ANDE™ Rapid DNA Analysis™ platform and its associated PowerPlex® 16 high content DNA biochip cassette for use as an expert system with reference buccal swabs.

PubMed

Moreno, Lilliana I; Brown, Alice L; Callaghan, Thomas F

2017-07-01

Rapid DNA platforms are fully integrated systems capable of producing and analyzing short tandem repeat (STR) profiles from reference sample buccal swabs in less than two hours. The technology requires minimal user interaction and experience making it possible for high quality profiles to be generated outside an accredited laboratory. The automated production of point of collection reference STR profiles could eliminate the time delay for shipment and analysis of arrestee samples at centralized laboratories. Furthermore, point of collection analysis would allow searching against profiles from unsolved crimes during the normal booking process once the infrastructure to immediately search the Combined DNA Index System (CODIS) database from the booking station is established. The DNAscan/ANDE™ Rapid DNA Analysis™ System developed by Network Biosystems was evaluated for robustness and reliability in the production of high quality reference STR profiles for database enrollment and searching applications. A total of 193 reference samples were assessed for concordance of the CODIS 13 loci. Studies to evaluate contamination, reproducibility, precision, stutter, peak height ratio, noise and sensitivity were also performed. The system proved to be robust, consistent and dependable. Results indicated an overall success rate of 75% for the 13 CODIS core loci and more importantly no incorrect calls were identified. The DNAscan/ANDE™ could be confidently used without human interaction in both laboratory and non-laboratory settings to generate reference profiles. Published by Elsevier B.V.

Autophagy activation by novel inducers prevents BECN2-mediated drug tolerance to cannabinoids

PubMed Central

Kuramoto, Kenta; Wang, Nan; Fan, Yuying; Zhang, Weiran; Schoenen, Frank J.; Frankowski, Kevin J.; Marugan, Juan; Zhou, Yifa; Huang, Sui; He, Congcong

2016-01-01

ABSTRACT Cannabinoids and related drugs generate profound behavioral effects (such as analgesic effects) through activating CNR1 (cannabinoid receptor 1 [brain]). However, repeated cannabinoid administration triggers lysosomal degradation of the receptor and rapid development of drug tolerance, limiting the medical use of marijuana in chronic diseases. The pathogenic mechanisms of cannabinoid tolerance are not fully understood, and little is known about its prevention. Here we show that a protein involved in macroautophagy/autophagy (a conserved lysosomal degradation pathway), BECN2 (beclin 2), mediates cannabinoid tolerance by preventing CNR1 recycling and resensitization after prolonged agonist exposure, and deletion of Becn2 rescues CNR1 activity in mouse brain and conveys resistance to analgesic tolerance to chronic cannabinoids. To target BECN2 therapeutically, we established a competitive recruitment model of BECN2 and identified novel synthetic, natural or physiological stimuli of autophagy that sequester BECN2 from its binding with GPRASP1, a receptor protein for CNR1 degradation. Co-administration of these autophagy inducers effectively restores the level and signaling of brain CNR1 and protects mice from developing tolerance to repeated cannabinoid usage. Overall, our findings demonstrate the functional link among autophagy, receptor signaling and animal behavior regulated by psychoactive drugs, and develop a new strategy to prevent tolerance and improve medical efficacy of cannabinoids by modulating the BECN2 interactome and autophagy activity. PMID:27305347

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D

PubMed Central

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron

2017-01-01

Abstract Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. PMID:28814063

An in vivo imaging-based assay for detecting protein interactions over a wide range of binding affinities

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

Fowlkes, Jason Davidson; Owens, Elizabeth T; Standaert, Robert F

2009-01-01

Identifying and characterizing protein interactions are fundamental steps towards understanding and modeling biological networks. Methods that detect protein interactions in intact cells rather than buffered solutions are likely more relevant to natural systems since molecular crowding events in the cytosol can influence the diffusion and reactivity of individual proteins. One in vivo, imaging-based method relies on the co-localization of two proteins of interest fused to DivIVA, a cell division protein from Bacillus subtilis, and green fluorescent protein (GFP). We have modified this imaging-based assay to facilitate rapid cloning by constructing new vectors encoding N- and C-terminal DivIVA or GFP molecularmore » tag fusions based on site-specific recombination technology. The sensitivity of the assay was defined using a well-characterized protein interaction system involving the eukaryotic nuclear import receptor subunit, Importin (Imp ) and variant nuclear localization signals (NLS) representing a range of binding affinities. These data demonstrate that the modified co-localization assay is sensitive enough to detect protein interactions with Kd values that span over four orders of magnitude (1nM to 15 M). Lastly, this assay was used to confirm numerous protein interactions identified from mass spectrometry-based analyses of affinity isolates as part of an interactome mapping project in Rhodopseudomonas palustris« less

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D.

PubMed

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron; Gümüs, Zeynep H

2017-08-01

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. © The Authors 2017. Published by Oxford University Press.

The most common technologies and tools for functional genome analysis.

PubMed

Gasperskaja, Evelina; Kučinskas, Vaidutis

2017-01-01

Since the sequence of the human genome is complete, the main issue is how to understand the information written in the DNA sequence. Despite numerous genome-wide studies that have already been performed, the challenge to determine the function of genes, gene products, and also their interaction is still open. As changes in the human genome are highly likely to cause pathological conditions, functional analysis is vitally important for human health. For many years there have been a variety of technologies and tools used in functional genome analysis. However, only in the past decade there has been rapid revolutionizing progress and improvement in high-throughput methods, which are ranging from traditional real-time polymerase chain reaction to more complex systems, such as next-generation sequencing or mass spectrometry. Furthermore, not only laboratory investigation, but also accurate bioinformatic analysis is required for reliable scientific results. These methods give an opportunity for accurate and comprehensive functional analysis that involves various fields of studies: genomics, epigenomics, proteomics, and interactomics. This is essential for filling the gaps in the knowledge about dynamic biological processes at both cellular and organismal level. However, each method has both advantages and limitations that should be taken into account before choosing the right method for particular research in order to ensure successful study. For this reason, the present review paper aims to describe the most frequent and widely-used methods for the comprehensive functional analysis.

Gene Scanning of an Internalin B Gene Fragment Using High-Resolution Melting Curve Analysis as a Tool for Rapid Typing of Listeria monocytogenes

PubMed Central

Pietzka, Ariane T.; Stöger, Anna; Huhulescu, Steliana; Allerberger, Franz; Ruppitsch, Werner

2011-01-01

The ability to accurately track Listeria monocytogenes strains involved in outbreaks is essential for control and prevention of listeriosis. Because current typing techniques are time-consuming, cost-intensive, technically demanding, and difficult to standardize, we developed a rapid and cost-effective method for typing of L. monocytogenes. In all, 172 clinical L. monocytogenes isolates and 20 isolates from culture collections were typed by high-resolution melting (HRM) curve analysis of a specific locus of the internalin B gene (inlB). All obtained HRM curve profiles were verified by sequence analysis. The 192 tested L. monocytogenes isolates yielded 15 specific HRM curve profiles. Sequence analysis revealed that these 15 HRM curve profiles correspond to 18 distinct inlB sequence types. The HRM curve profiles obtained correlated with the five phylogenetic groups I.1, I.2, II.1, II.2, and III. Thus, HRM curve analysis constitutes an inexpensive assay and represents an improvement in typing relative to classical serotyping or multiplex PCR typing protocols. This method provides a rapid and powerful screening tool for simultaneous preliminary typing of up to 384 samples in approximately 2 hours. PMID:21227395

An Accelerated Analytical Process for the Development of STR Profiles for Casework Samples.

PubMed

Laurin, Nancy; Frégeau, Chantal J

2015-07-01

Significant efforts are being devoted to the development of methods enabling rapid generation of short tandem repeat (STR) profiles in order to reduce turnaround times for the delivery of human identification results from biological evidence. Some of the proposed solutions are still costly and low throughput. This study describes the optimization of an analytical process enabling the generation of complete STR profiles (single-source or mixed profiles) for human identification in approximately 5 h. This accelerated process uses currently available reagents and standard laboratory equipment. It includes a 30-min lysis step, a 27-min DNA extraction using the Promega Maxwell(®) 16 System, DNA quantification in <1 h using the Qiagen Investigator(®) Quantiplex HYres kit, fast amplification (<26 min) of the loci included in AmpFℓSTR(®) Identifiler(®), and analysis of the profiles on the 3500-series Genetic Analyzer. This combination of fast individual steps produces high-quality profiling results and offers a cost-effective alternative approach to rapid DNA analysis. © 2015 American Academy of Forensic Sciences.

Identification on Membrane and Characterization of Phosphoproteins Using an Alkoxide-Bridged Dinuclear Metal Complex as a Phosphate-Binding Tag Molecule

PubMed Central

Nakanishi, Tsuyoshi; Ando, Eiji; Furuta, Masaru; Kinoshita, Eiji; Kinoshita-Kikuta, Emiko; Koike, Tohru; Tsunasawa, Susumu; Nishimura, Osamu

2007-01-01

We have developed a method for on-membrane direct identification of phosphoproteins, which are detected by a phosphate-binding tag (Phos-tag) that has an affinity to phosphate groups with a chelated Zn2+ ion. This rapid profiling approach for phosphoproteins combines chemical inkjet technology for microdispensing of reagents onto a tiny region of target proteins with mass spectrometry for on-membrane digested peptides. Using this method, we analyzed human epidermoid carcinoma cell lysates of A-431 cells stimulated with epidermal growth factor, and identified six proteins with intense signals upon affinity staining with the phosphate-binding tag. It was already known that these proteins are phosphorylated, and our new approach proved to be effective at rapid profiling of phosphoproteins. Furthermore, we tried to determine their phosphorylation sites by MS/MS analysis after in-gel digestion of the corresponding spots on the 2DE gel to the rapid on-membrane identifications. As one example of use of information gained from the rapid-profiling approach, we successfully characterized a phosphorylation site at Ser-113 on prostaglandin E synthase 3. PMID:18166671

BEAP profiles as rapid test system for status analysis and early detection of process incidents in biogas plants.

PubMed

Refai, Sarah; Berger, Stefanie; Wassmann, Kati; Hecht, Melanie; Dickhaus, Thomas; Deppenmeier, Uwe

2017-03-01

A method was developed to quantify the performance of microorganisms involved in different digestion levels in biogas plants. The test system was based on the addition of butyrate (BCON), ethanol (ECON), acetate (ACON) or propionate (PCON) to biogas sludge samples and the subsequent analysis of CH 4 formation in comparison to control samples. The combination of the four values was referred to as BEAP profile. Determination of BEAP profiles enabled rapid testing of a biogas plant's metabolic state within 24 h and an accurate mapping of all degradation levels in a lab-scale experimental setup. Furthermore, it was possible to distinguish between specific BEAP profiles for standard biogas plants and for biogas reactors with process incidents (beginning of NH 4 + -N inhibition, start of acidification, insufficient hydrolysis and potential mycotoxin effects). Finally, BEAP profiles also functioned as a warning system for the early prediction of critical NH 4 + -N concentrations leading to a drop of CH 4 formation.

Shock loading and release behavior of silicon nitride

NASA Astrophysics Data System (ADS)

Kawai, N.; Tsuru, T.; Hidaka, N.; Liu, X.; Mashimo, T.

2017-01-01

Shock-reshock and shock-release experiments were performed on silicon nitride ceramics above and below its phase transition pressure. Experimental results clearly show the occurrence of elastic-plastic transition and phase transition during initial shock loading. The HEL and phase transition stress are determined as 11.6 and 34.5 GPa, respectively. Below the phase transition stress, the reshock profile consists of the single shock with short rise time, while the release profile shows the gradual release followed by rapid one. Above phase transition stress, reshock and release behavior varies with the initial shock stress. In the case of reshock and release from about 40 GPa, the reshock structure is considerably dispersed, while the release structure shows rapid release. In the reshock profile from about 50 GPa, the formation of the shock wave with the small ramped precursor is observed. And, the release response from same shocked condition shows initial gradual release and subsequent quite rapid one. These results would provide the information about how phase transformation kinetics effects on the reshock and release behavior.

Rapid Weight Loss vs. Slow Weight Loss: Which is More Effective on Body Composition and Metabolic Risk Factors?

PubMed Central

Ashtary-Larky, Damoon; Ghanavati, Matin; Lamuchi-Deli, Nasrin; Payami, Seyedeh Arefeh; Alavi-Rad, Sara; Boustaninejad, Mehdi; Afrisham, Reza; Abbasnezhad, Amir; Alipour, Meysam

2017-01-01

Background Achieving weight loss (WL) in a short time regardless of its consequences has always been the focus of many obese and overweight people. In this study, anthropometric and metabolic effects of two diets for rapid and slow WL and their consequences were examined. Methods Forty-two obese and overweight individuals were randomly divided to 2 groups; rapid WL (weight loss of at least 5% in 5 weeks) and slow WL (weight loss of at least 5% in 15 weeks). To compare the effects of the rate of WL in 2 groups, the same amount of was achieved with different durations. Anthropometric indices, lipid, and glycemic profiles, and systolic and diastolic blood pressures were evaluated before and after the intervention. Results Both protocols of rapid WL and slow WL caused reduction in waist circumference, hip circumference, total body water, body fat mass, lean body mass, and resting metabolic rate (RMR). Further reduction in waist circumference, hip circumference, fat mass, and percentage of body fat was observed in slow WL and decreased total body water, lean body mass, fat free mass, and RMR was observed in rapid WL. Improvement in lipid and glycemic profiles was observed in both groups. Reduction of low-density lipoprotein and fasting blood sugar, improvement of insulin resistance, and sensitivity were more significant in rapid WL in comparison to slow WL. Conclusions Weight Loss regardless of its severity could improve anthropometric indicators, although body composition is more favorable following a slow WL. Both diets improved lipid and glycemic profiles. In this context, rapid WL was more effective. (IRCT2016010424699N2) PMID:29201070

Comparative analysis of human tissue interactomes reveals factors leading to tissue-specific manifestation of hereditary diseases.

PubMed

Barshir, Ruth; Shwartz, Omer; Smoly, Ilan Y; Yeger-Lotem, Esti

2014-06-01

An open question in human genetics is what underlies the tissue-specific manifestation of hereditary diseases, which are caused by genomic aberrations that are present in cells across the human body. Here we analyzed this phenomenon for over 300 hereditary diseases by using comparative network analysis. We created an extensive resource of protein expression and interactions in 16 main human tissues, by integrating recent data of gene and protein expression across tissues with data of protein-protein interactions (PPIs). The resulting tissue interaction networks (interactomes) shared a large fraction of their proteins and PPIs, and only a small fraction of them were tissue-specific. Applying this resource to hereditary diseases, we first show that most of the disease-causing genes are widely expressed across tissues, yet, enigmatically, cause disease phenotypes in few tissues only. Upon testing for factors that could lead to tissue-specific vulnerability, we find that disease-causing genes tend to have elevated transcript levels and increased number of tissue-specific PPIs in their disease tissues compared to unaffected tissues. We demonstrate through several examples that these tissue-specific PPIs can highlight disease mechanisms, and thus, owing to their small number, provide a powerful filter for interrogating disease etiologies. As two thirds of the hereditary diseases are associated with these factors, comparative tissue analysis offers a meaningful and efficient framework for enhancing the understanding of the molecular basis of hereditary diseases.

Bacteriophage Protein–Protein Interactions

PubMed Central

Häuser, Roman; Blasche, Sonja; Dokland, Terje; Haggård-Ljungquist, Elisabeth; von Brunn, Albrecht; Salas, Margarita; Casjens, Sherwood; Molineux, Ian

2012-01-01

Bacteriophages T7, λ, P22, and P2/P4 (from Escherichia coli), as well as ϕ29 (from Bacillus subtilis), are among the best-studied bacterial viruses. This chapter summarizes published protein interaction data of intraviral protein interactions, as well as known phage–host protein interactions of these phages retrieved from the literature. We also review the published results of comprehensive protein interaction analyses of Pneumococcus phages Dp-1 and Cp-1, as well as coliphages λ and T7. For example, the ≈55 proteins encoded by the T7 genome are connected by ≈43 interactions with another ≈15 between the phage and its host. The chapter compiles published interactions for the well-studied phages λ (33 intra-phage/22 phage-host), P22 (38/9), P2/P4 (14/3), and ϕ29 (20/2). We discuss whether different interaction patterns reflect different phage lifestyles or whether they may be artifacts of sampling. Phages that infect the same host can interact with different host target proteins, as exemplified by E. coli phage λ and T7. Despite decades of intensive investigation, only a fraction of these phage interactomes are known. Technical limitations and a lack of depth in many studies explain the gaps in our knowledge. Strategies to complete current interactome maps are described. Although limited space precludes detailed overviews of phage molecular biology, this compilation will allow future studies to put interaction data into the context of phage biology. PMID:22748812

Sequence- and Interactome-Based Prediction of Viral Protein Hotspots Targeting Host Proteins: A Case Study for HIV Nef

PubMed Central

Sarmady, Mahdi; Dampier, William; Tozeren, Aydin

2011-01-01

Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk. PMID:21738584

Identification and characterization of moonlighting long non-coding RNAs based on RNA and protein interactome.

PubMed

Cheng, Lixin; Leung, Kwong-Sak

2018-05-16

Moonlighting proteins are a class of proteins having multiple distinct functions, which play essential roles in a variety of cellular and enzymatic functioning systems. Although there have long been calls for computational algorithms for the identification of moonlighting proteins, research on approaches to identify moonlighting long non-coding RNAs (lncRNAs) has never been undertaken. Here, we introduce a novel methodology, MoonFinder, for the identification of moonlighting lncRNAs. MoonFinder is a statistical algorithm identifying moonlighting lncRNAs without a priori knowledge through the integration of protein interactome, RNA-protein interactions, and functional annotation of proteins. We identify 155 moonlighting lncRNA candidates and uncover that they are a distinct class of lncRNAs characterized by specific sequence and cellular localization features. The non-coding genes that transcript moonlighting lncRNAs tend to have shorter but more exons and the moonlighting lncRNAs have a variable localization pattern with a high chance of residing in the cytoplasmic compartment in comparison to the other lncRNAs. Moreover, moonlighting lncRNAs and moonlighting proteins are rather mutually exclusive in terms of both their direct interactions and interacting partners. Our results also shed light on how the moonlighting candidates and their interacting proteins implicated in the formation and development of cancers and other diseases. The code implementing MoonFinder is supplied as an R package in the supplementary material. lxcheng@cse.cuhk.edu.hk or ksleung@cse.cuhk.edu.hk. Supplementary data are available at Bioinformatics online.

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy

PubMed Central

Matkovich, Scot J.; Dorn, Gerald W.

2018-01-01

Summary MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicates purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses. PMID:25836573

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

PubMed

Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.

AF4 and AF4N protein complexes: recruitment of P-TEFb kinase, their interactome and potential functions

PubMed Central

Scholz, Bastian; Kowarz, Eric; Rössler, Tanja; Ahmad, Khalil; Steinhilber, Dieter; Marschalek, Rolf

2015-01-01

AF4/AFF1 and AF5/AFF4 are the molecular backbone to assemble “super-elongation complexes” (SECs) that have two main functions: (1) control of transcriptional elongation by recruiting the positive transcription elongation factor b (P-TEFb = CyclinT1/CDK9) that is usually stored in inhibitory 7SK RNPs; (2) binding of different histone methyltransferases, like DOT1L, NSD1 and CARM1. This way, transcribed genes obtain specific histone signatures (e.g. H3K79me2/3, H3K36me2) to generate a transcriptional memory system. Here we addressed several questions: how is P-TEFb recruited into SEC, how is the AF4 interactome composed, and what is the function of the naturally occuring AF4N protein variant which exhibits only the first 360 amino acids of the AF4 full-length protein. Noteworthy, shorter protein variants are a specific feature of all AFF protein family members. Here, we demonstrate that full-length AF4 and AF4N are both catalyzing the transition of P-TEFb from 7SK RNP to their N-terminal domain. We have also mapped the protein-protein interaction network within both complexes. In addition, we have first evidence that the AF4N protein also recruits TFIIH and the tumor suppressor MEN1. This indicate that AF4N may have additional functions in transcriptional initiation and in MEN1-dependend transcriptional processes. PMID:26171280

Bioinformatics Analysis Reveals Distinct Molecular Characteristics of Hepatitis B-Related Hepatocellular Carcinomas from Very Early to Advanced Barcelona Clinic Liver Cancer Stages.

PubMed

Kong, Fan-Yun; Wei, Xiao; Zhou, Kai; Hu, Wei; Kou, Yan-Bo; You, Hong-Juan; Liu, Xiao-Mei; Zheng, Kui-Yang; Tang, Ren-Xian

2016-01-01

Hepatocellular carcinoma (HCC)is the fifth most common malignancy associated with high mortality. One of the risk factors for HCC is chronic hepatitis B virus (HBV) infection. The treatment strategy for the disease is dependent on the stage of HCC, and the Barcelona clinic liver cancer (BCLC) staging system is used in most HCC cases. However, the molecular characteristics of HBV-related HCC in different BCLC stages are still unknown. Using GSE14520 microarray data from HBV-related HCC cases with BCLC stages from 0 (very early stage) to C (advanced stage) in the gene expression omnibus (GEO) database, differentially expressed genes (DEGs), including common DEGs and unique DEGs in different BCLC stages, were identified. These DEGs were located on different chromosomes. The molecular functions and biology pathways of DEGs were identified by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the interactome networks of DEGs were constructed using the NetVenn online tool. The results revealed that both common DEGs and stage-specific DEGs were associated with various molecular functions and were involved in special biological pathways. In addition, several hub genes were found in the interactome networks of DEGs. The identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of HBV-related HCC through the different BCLC stages, and might be used as staging biomarkers or molecular targets for the treatment of HCC with HBV infection.

“Stop Ne(c)king around”: How interactomics contributes to functionally characterize Nek family kinases

PubMed Central

Meirelles, Gabriela Vaz; Perez, Arina Marina; de Souza, Edmárcia Elisa; Basei, Fernanda Luisa; Papa, Priscila Ferreira; Melo Hanchuk, Talita Diniz; Cardoso, Vanessa Bomfim; Kobarg, Jörg

2014-01-01

Aside from Polo and Aurora, a third but less studied kinase family involved in mitosis regulation is the never in mitosis-gene A (NIMA)-related kinases (Neks). The founding member of this family is the sole member NIMA of Aspergillus nidulans, which is crucial for the initiation of mitosis in that organism. All 11 human Neks have been functionally assigned to one of the three core functions established for this family in mammals: (1) centrioles/mitosis; (2) primary ciliary function/ciliopathies; and (3) DNA damage response (DDR). Recent findings, especially on Nek 1 and 8, showed however, that several Neks participate in parallel in at least two of these contexts: primary ciliary function and DDR. In the core section of this in-depth review, we report the current detailed functional knowledge on each of the 11 Neks. In the discussion, we return to the cross-connections among Neks and point out how our and other groups’ functional and interactomics studies revealed that most Neks interact with protein partners associated with two if not all three of the functional contexts. We then raise the hypothesis that Neks may be the connecting regulatory elements that allow the cell to fine tune and synchronize the cellular events associated with these three core functions. The new and exciting findings on the Nek family open new perspectives and should allow the Neks to finally claim the attention they deserve in the field of kinases and cell cycle biology. PMID:24921005

What model organisms and interactomics can reveal about the genetics of human obesity.

PubMed

Williams, Michael J; Almén, Markus S; Fredriksson, Robert; Schiöth, Helgi B

2012-11-01

Genome-wide association studies have identified a number of genes associated with human body weight. While some of these genes are large fields within obesity research, such as MC4R, POMC, FTO and BDNF, the majority do not have a clearly defined functional role explaining why they may affect body weight. Here, we searched biological databases and discovered 33 additional genes associated with human obesity (CADM2, GIPR, GPCR5B, LRP1B, NEGR1, NRXN3, SH2B1, FANCL, GNPDA2, HMGCR, MAP2K5, NUDT3, PRKD1, QPCTL, TNNI3K, MTCH2, DNAJC27, SLC39A8, MTIF3, RPL27A, SEC16B, ETV5, HMGA1, TFAP2B, TUB, ZNF608, FAIM2, KCTD15, LINGO2, POC5, PTBP2, TMEM18, TMEM160). We find that the majority have orthologues in distant species, such as D. melanogaster and C. elegans, suggesting that they are important for the biology of most bilateral species. Intriguingly, signalling cascade genes and transcription factors are enriched among these obesity genes, and several of the genes show properties that could be useful for potential drug discovery. In this review, we demonstrate how information from several distant model species, interactomics and signalling pathway analysis represents an important way to better understand the functional diversity of the surprisingly high number of molecules that seem to be important for human obesity.

Dislocated Worker Human Capital Depreciation and Recovery. Upjohn Institute Staff Working Paper 90-04.

ERIC Educational Resources Information Center

Hollenbeck, Kevin

This study examined the characteristics of dislocated workers' wage profiles upon reemployment. In particular, it related these profiles to the model developed by Mincer and Ofek (1982). An inference from this model was that workers recovered wage losses relatively rapidly. Explanations for a steeply sloped reentry wage profile were as follows:…

Effects of Temperature and Air Density Profiles on Ozone Lidar Retrievals

NASA Astrophysics Data System (ADS)

Kirgis, G.; Langford, A. O.; Senff, C. J.; Alvarez, R. J. _II, II

2017-12-01

The recent reduction in the primary U.S. National Ambient Air Quality Standard (NAAQS) for ozone (O3) from 75 to 70 parts-per-billion by volume (ppbv) adds urgency to the need for better understanding of the processes that control ground-level concentrations in the United States. While ground-based in situ sensors are capable of measuring ozone levels, they don't give any insight into upper air transport and mixing. Differential absorption lidars such as the NOAA/ESRL Tunable Optical Profiler for Aerosol and oZone (TOPAZ) measure continuous vertical ozone profiles with high spatial and temporal resolution. However, the retrieved ozone mixing ratios depend on the temperature and air density profiles used in the analysis. This study analyzes the ozone concentrations for seven field campaigns from 2013 to 2016 to evaluate the impact of the assumed pressure and temperature profiles on the ozone mixing ratio retrieval. Pressure and temperature profiles from various spatial and temporal resolution models (Modern Era Retrospective-Analysis for Research and Applications, NCEP/NCAR Reanalysis, NCEP North American Regional Reanalysis, Rapid Refresh, and High-Resolution Rapid Refresh) are compared to reference ozone profiles created with pressure and temperature profiles from ozonesondes launched close to the TOPAZ measurement site. The results show significant biases with respect to time of day and season, altitude, and location of the model-extracted profiles. Limitations and advantages of all datasets used will also be discussed.

Comparative proteomic analysis of normal and collagen IX null mouse cartilage reveals altered extracellular matrix composition and novel components of the collagen IX interactome.

PubMed

Brachvogel, Bent; Zaucke, Frank; Dave, Keyur; Norris, Emma L; Stermann, Jacek; Dayakli, Münire; Koch, Manuel; Gorman, Jeffrey J; Bateman, John F; Wilson, Richard

2013-05-10

Collagen IX is an integral cartilage extracellular matrix component important in skeletal development and joint function. Proteomic analysis and validation studies revealed novel alterations in collagen IX null cartilage. Matrilin-4, collagen XII, thrombospondin-4, fibronectin, βig-h3, and epiphycan are components of the in vivo collagen IX interactome. We applied a proteomics approach to advance our understanding of collagen IX ablation in cartilage. The cartilage extracellular matrix is essential for endochondral bone development and joint function. In addition to the major aggrecan/collagen II framework, the interacting complex of collagen IX, matrilin-3, and cartilage oligomeric matrix protein (COMP) is essential for cartilage matrix stability, as mutations in Col9a1, Col9a2, Col9a3, Comp, and Matn3 genes cause multiple epiphyseal dysplasia, in which patients develop early onset osteoarthritis. In mice, collagen IX ablation results in severely disturbed growth plate organization, hypocellular regions, and abnormal chondrocyte shape. This abnormal differentiation is likely to involve altered cell-matrix interactions but the mechanism is not known. To investigate the molecular basis of the collagen IX null phenotype we analyzed global differences in protein abundance between wild-type and knock-out femoral head cartilage by capillary HPLC tandem mass spectrometry. We identified 297 proteins in 3-day cartilage and 397 proteins in 21-day cartilage. Components that were differentially abundant between wild-type and collagen IX-deficient cartilage included 15 extracellular matrix proteins. Collagen IX ablation was associated with dramatically reduced COMP and matrilin-3, consistent with known interactions. Matrilin-1, matrilin-4, epiphycan, and thrombospondin-4 levels were reduced in collagen IX null cartilage, providing the first in vivo evidence for these proteins belonging to the collagen IX interactome. Thrombospondin-4 expression was reduced at the mRNA level, whereas matrilin-4 was verified as a novel collagen IX-binding protein. Furthermore, changes in TGFβ-induced protein βig-h3 and fibronectin abundance were found in the collagen IX knock-out but not associated with COMP ablation, indicating specific involvement in the abnormal collagen IX null cartilage. In addition, the more widespread expression of collagen XII in the collagen IX-deficient cartilage suggests an attempted compensatory response to the absence of collagen IX. Our differential proteomic analysis of cartilage is a novel approach to identify candidate matrix protein interactions in vivo, underpinning further analysis of mutant cartilage lacking other matrix components or harboring disease-causing mutations.

hPDI: a database of experimental human protein-DNA interactions.

PubMed

Xie, Zhi; Hu, Shaohui; Blackshaw, Seth; Zhu, Heng; Qian, Jiang

2010-01-15

The human protein DNA Interactome (hPDI) database holds experimental protein-DNA interaction data for humans identified by protein microarray assays. The unique characteristics of hPDI are that it contains consensus DNA-binding sequences not only for nearly 500 human transcription factors but also for >500 unconventional DNA-binding proteins, which are completely uncharacterized previously. Users can browse, search and download a subset or the entire data via a web interface. This database is freely accessible for any academic purposes. http://bioinfo.wilmer.jhu.edu/PDI/.

Principles of Protein Recognition and Properties of Protein-protein Interfaces

NASA Astrophysics Data System (ADS)

Keskin, Ozlem; Gursoy, Attila; Nussinov, Ruth

In this chapter we address two aspects - the static physical interactions which allow the information transfer for the function to be performed; and the dynamic, i.e. how the information is transmitted between the binding sites in the single protein molecule and in the network. We describe the single protein molecules and their complexes; and the analogy between protein folding and protein binding. Eventually, to fully understand the interactome and how it performs the essential cellular functions, we have to put all together - and hierarchically progress through the system.

Big Data Analytics in Medicine and Healthcare.

PubMed

Ristevski, Blagoj; Chen, Ming

2018-05-10

This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.

The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome.

PubMed

Kronewitter, Scott R; An, Hyun Joo; de Leoz, Maria Lorna; Lebrilla, Carlito B; Miyamoto, Suzanne; Leiserowitz, Gary S

2009-06-01

Annotation of the human serum N-linked glycome is a formidable challenge but is necessary for disease marker discovery. A new theoretical glycan library was constructed and proposed to provide all possible glycan compositions in serum. It was developed based on established glycobiology and retrosynthetic state-transition networks. We find that at least 331 compositions are possible in the serum N-linked glycome. By pairing the theoretical glycan mass library with a high mass accuracy and high-resolution MS, human serum glycans were effectively profiled. Correct isotopic envelope deconvolution to monoisotopic masses and the high mass accuracy instruments drastically reduced the amount of false composition assignments. The high throughput capacity enabled by this library permitted the rapid glycan profiling of large control populations. With the use of the library, a human serum glycan mass profile was developed from 46 healthy individuals. This paper presents a theoretical N-linked glycan mass library that was used for accurate high-throughput human serum glycan profiling. Rapid methods for evaluating a patient's glycome are instrumental for studying glycan-based markers.

Principal component analysis of TOF-SIMS spectra, images and depth profiles: an industrial perspective

NASA Astrophysics Data System (ADS)

Pacholski, Michaeleen L.

2004-06-01

Principal component analysis (PCA) has been successfully applied to time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra, images and depth profiles. Although SIMS spectral data sets can be small (in comparison to datasets typically discussed in literature from other analytical techniques such as gas or liquid chromatography), each spectrum has thousands of ions resulting in what can be a difficult comparison of samples. Analysis of industrially-derived samples means the identity of most surface species are unknown a priori and samples must be analyzed rapidly to satisfy customer demands. PCA enables rapid assessment of spectral differences (or lack there of) between samples and identification of chemically different areas on sample surfaces for images. Depth profile analysis helps define interfaces and identify low-level components in the system.

Frequency-agile, rapid scanning cavity ring-down spectroscopy (FARS-CRDS) measurements of the (30012)←(00001) near-infrared carbon dioxide band

NASA Astrophysics Data System (ADS)

Long, D. A.; Wójtewicz, S.; Miller, C. E.; Hodges, J. T.

2015-08-01

We present new high accuracy measurements of the (30012)←(00001) CO2 band near 1575 nm recorded with a frequency-agile, rapid scanning cavity ring-down spectrometer. The resulting spectra were fit with the partially correlated, quadratic-speed-dependent Nelkin-Ghatak profile with line mixing. Significant differences were observed between the fitted line shape parameters and those found in existing databases, which are based upon more simplistic line profiles. Absolute transition frequencies, which were referenced to an optical frequency comb, are given, as well as the other line shape parameters needed to model this line profile. These high accuracy measurements should allow for improved atmospheric retrievals of greenhouse gas concentrations by current and future remote sensing missions.

Shock loading and release behavior of silicon nitride

NASA Astrophysics Data System (ADS)

Kawai, Nobuaki; Tsuru, Taiki; Hidaka, Naoto; Liu, Xun; Mashimo, Tsutomu

2015-06-01

Shock-reshock and shock-release experiments were performed on silicon nitride ceramics above and below its phase transition pressure. Experimental results clearly show the occurrence of elastic-plastic transition and phase transition during initial shock loading. The HEL and phase transition stress are determined as 11.6 GPa and 34.5 GPa, respectively. Below the phase transition point, the reshock profile consists of the single shock with short rise time, while the release profile shows the gradual release followed by more rapid one. Above the phase transition point, reshock and release behavior varies with the initial shock stress. In the case of reshock and release from about 40 GPa, the reshock structure is considerably dispersed, while the release structure shows rapid release. In the reshock profile from about 50 GPa, the formation of the shock wave with the small ramped precursor is observed. And, the release response from same condition shows initial gradual release and subsequent quite rapid one. These results would provide the information about how phase transformation kinetics effects on the reshock and release behavior.

A rapid method for hydraulic profiling in unconsolidated formations

USGS Publications Warehouse

Dietrich, P.; Butler, J.J.; Faiss, K.

2008-01-01

Information on vertical variations in hydraulic conductivity (K) can often shed much light on how a contaminant will move in the subsurface. The direct-push injection logger has been developed to rapidly obtain such information in shallow unconsolidated settings. This small-diameter tool consists of a short screen located just behind a drive point. The tool is advanced into the subsurface while water is injected through the screen to keep it clear. Upon reaching a depth at which information about K is desired, advancement ceases and the injection rate and pressure are measured on the land surface. The rate and pressure values are used in a ratio that serves as a proxy for K. A vertical profile of this ratio can be transformed into a K profile through regressions with K estimates determined using other techniques. The viability of the approach was assessed at an extensively studied field site in eastern Germany. The assessment demonstrated that this tool can rapidly identify zones that may serve as conduits for or barriers to contaminant movement. ?? 2007 The Author(s).

Effects of propranolol on time of useful function (TUF) in rats.

DOT National Transportation Integrated Search

1979-02-01

To assess the effects of propranolol on tolerance to rapid decompression, a series of experiments was conducted measuring time of useful function (TUF) in rats exposed to a rapid decompression profile in an altitude chamber. In other experiments TUF ...

Interaction Network of Proteins Associated with Human Cytomegalovirus IE2-p86 Protein during Infection: A Proteomic Analysis

PubMed Central

Du, Guixin; Stinski, Mark F.

2013-01-01

Human cytomegalovirus protein IE2-p86 exerts its functions through interaction with other viral and cellular proteins. To further delineate its protein interaction network, we generated a recombinant virus expressing SG-tagged IE2-p86 and used tandem affinity purification coupled with mass spectrometry. A total of 9 viral proteins and 75 cellular proteins were found to associate with IE2-p86 protein during the first 48 hours of infection. The protein profile at 8, 24, and 48 h post infection revealed that UL84 tightly associated with IE2-p86, and more viral and cellular proteins came into association with IE2-p86 with the progression of virus infection. A computational analysis of the protein-protein interaction network indicated that all of the 9 viral proteins and most of the cellular proteins identified in the study are interconnected to varying degrees. Of the cellular proteins that were confirmed to associate with IE2-p86 by immunoprecipitation, C1QBP was further shown to be upregulated by HCMV infection and colocalized with IE2-p86, UL84 and UL44 in the virus replication compartment of the nucleus. The IE2-p86 interactome network demonstrated the temporal development of stable and abundant protein complexes that associate with IE2-p86 and provided a framework to benefit future studies of various protein complexes during HCMV infection. PMID:24358118

Novel signatures of cancer-associated fibroblasts.

PubMed

Bozóky, Benedek; Savchenko, Andrii; Csermely, Péter; Korcsmáros, Tamás; Dúl, Zoltán; Pontén, Fredrik; Székely, László; Klein, George

2013-07-15

Increasing evidence indicates the importance of the tumor microenvironment, in particular cancer-associated fibroblasts, in cancer development and progression. In our study, we developed a novel, visually based method to identify new immunohistochemical signatures of these fibroblasts. The method employed a protein list based on 759 protein products of genes identified by RNA profiling from our previous study, comparing fibroblasts with differential growth-modulating effect on human cancers cells, and their first neighbors in the human protein interactome. These 2,654 proteins were analyzed in the Human Protein Atlas online database by comparing their immunohistochemical expression patterns in normal versus tumor-associated fibroblasts. Twelve new proteins differentially expressed in cancer-associated fibroblasts were identified (DLG1, BHLHE40, ROCK2, RAB31, AZI2, PKM2, ARHGAP31, ARHGAP26, ITCH, EGLN1, RNF19A and PLOD2), four of them can be connected to the Rho kinase signaling pathway. They were further analyzed in several additional tumor stromata and revealed that the majority showed congruence among the different tumors. Many of them were also positive in normal myofibroblast-like cells. The new signatures can be useful in immunohistochemical analysis of different tumor stromata and may also give us an insight into the pathways activated in them in their true in vivo context. The method itself could be used for other similar analysis to identify proteins expressed in other cell types in tumors and their surrounding microenvironment. Copyright © 2013 UICC.

Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

DOE PAGES

Benton, H. Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G.; ...

2014-12-12

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometrymore » data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.« less

Diagnostic performance of the "MESACUP anti-Skin profile TEST".

PubMed

Horváth, Orsolya N; Varga, Rita; Kaneda, Makoto; Schmidt, Enno; Ruzicka, Thomas; Sárdy, Miklós

2016-01-01

The "MESACUP anti-Skin profile TEST" is a new, commercially available ELISA kit to detect circulating IgG autoantibodies against desmoglein 1, desmoglein 3, BP180, BP230, and type VII collagen, both simultaneously and more rapidly than previous assays. The aim of this study was to evaluate the diagnostic accuracy of this kit for the diagnosis of pemphigus foliaceus, pemphigus vulgaris, bullous pemphigoid and epidermolysis bullosa acquisita. Dual-centre retrospective study in which 138 patients with autoimmune blistering diseases were compared to 40 controls Using the MESACUP anti-Skin profile TEST, both sensitivities and specificities for desmoglein 1, desmoglein 3, BP180, BP230, and type VII collagen autoantibodies were similar to those obtained using previous, specific ELISA systems and 88% of the results were concordant without any significant difference. The MESACUP anti-Skin profile TEST had a similar performance to previously produced ELISA systems. The novel kit can be used for rapid diagnosis of most common autoimmune blistering diseases and is especially suitable for identifying overlapping disorders.

Combining insulins for optimal blood glucose control in type 1 and 2 diabetes: Focus on insulin glulisine

PubMed Central

Ulrich, Heather; Snyder, Benjamin; K Garg, Satish

2007-01-01

Normalization of blood glucose is essential for the prevention of diabetes mellitus (DM)-related microvascular and macrovascular complications. Despite substantial literature to support the benefits of glucose lowering and clear treatment targets, glycemic control remains suboptimal for most people with DM in the United States. Pharmacokinetic limitations of conventional insulins have been a barrier to achieving treatment targets secondary to adverse effects such as hypoglycemia and weight gain. Recombinant DNA technology has allowed modification of the insulin molecule to produce insulin analogues that overcome these pharmacokinetic limitations. With time action profiles that more closely mimic physiologic insulin secretion, rapid acting insulin analogues (RAAs) reduce post-prandial glucose excursions and hypoglycemia when compared to regular human insulin (RHI). Insulin glulisine (Apidra®) is a rapid-acting insulin analogue created by substituting lysine for asparagine at position B3 and glutamic acid for lysine at position B29 on the B chain of human insulin. The quick absorption of insulin glulisine more closely reproduces physiologic first-phase insulin secretion and its rapid acting profile is maintained across patient subtypes. Clinical trials have demonstrated comparable or greater efficacy of insulin glulisine versus insulin lispro or RHI, respectively. Efficacy is maintained even when insulin glulisine is administered post-meal. In addition, glulisine appears to have a more rapid time action profile compared with insulin lispro across various body mass indexes (BMIs). The safety and tolerability profile of insulin glulisine is also comparable to that of insulin lispro or RHI in type 1 or 2 DM and it has been shown to be as safe and effective when used in a continuous subcutaneous insulin infusion (CSII). In summary, insulin glulisine is a safe, effective, and well tolerated rapid-acting insulin analogue across all BMIs and a worthy option for prandial glucose control in type 1 or 2 DM. PMID:17703632

The Hsp90 co-chaperone p23 of Toxoplasma gondii: Identification, functional analysis and dynamic interactome determination

PubMed Central

Echeverria, Pablo C.; Figueras, Maria J.; Vogler, Malvina; Kriehuber, Thomas; de Miguel, Natalia; Deng, Bin; Dalmasso, Maria C.; Matthews, Dwight E.; Matrajt, Mariana; Haslbeck, Martin; Buchner, Johannes; Angel, Sergio O.

2010-01-01

Toxoplasma gondii is among the most successful parasites, with nearly half of the human population chronically infected. Recently a link between the T. gondii Hsp90 chaperone machinery and parasite development was observed. Here, the T. gondii Hsp90 co-chaperones p23 and Hip were identified mining the Toxoplasma- database (www.toxodb.org). Their identity was confirmed by domain structure and blast analysis. Additionally, analysis of the secondary structure and studies on the chaperone function of the purified protein verified the p23 identity. Studies of co-immunoprecipitation (co-IP) identified two different types of complexes, one comprising at least Hip-Hsp70-Hsp90 and another containing at least p23-Hsp90. Indirect immunofluorescence assays showed that Hip is localized in the cytoplasm in tachyzoites and as well in bradyzoites. For p23 in contrast, a solely cytoplasmic localization was only observed in the tachyzoite stage whereas nuclear and cytosolic distribution and colocalization with Hsp90 was observed in bradyzoites. These results indicate that the T. gondii Hsp90-heterocomplex cycle is similar to the one proposed for higher eukaryotes, further highlighting the implication of the Hsp90/p23 in parasite development. Furthermore, co-IP experiments of tachyzoite/bradyzoite lysates with anti-p23 antiserum and identification of the complexed proteins together with the use of the curated interaction data available from different source (orthologs and Plasmodium databases) allowed us to construct an interaction network (interactome) covering the dynamics of the Hsp90 chaperone machinery. PMID:20403389

Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types.

PubMed

Cornish, Alex J; Filippis, Ioannis; David, Alessia; Sternberg, Michael J E

2015-09-01

Each cell type found within the human body performs a diverse and unique set of functions, the disruption of which can lead to disease. However, there currently exists no systematic mapping between cell types and the diseases they can cause. In this study, we integrate protein-protein interaction data with high-quality cell-type-specific gene expression data from the FANTOM5 project to build the largest collection of cell-type-specific interactomes created to date. We develop a novel method, called gene set compactness (GSC), that contrasts the relative positions of disease-associated genes across 73 cell-type-specific interactomes to map genes associated with 196 diseases to the cell types they affect. We conduct text-mining of the PubMed database to produce an independent resource of disease-associated cell types, which we use to validate our method. The GSC method successfully identifies known disease-cell-type associations, as well as highlighting associations that warrant further study. This includes mast cells and multiple sclerosis, a cell population currently being targeted in a multiple sclerosis phase 2 clinical trial. Furthermore, we build a cell-type-based diseasome using the cell types identified as manifesting each disease, offering insight into diseases linked through etiology. The data set produced in this study represents the first large-scale mapping of diseases to the cell types in which they are manifested and will therefore be useful in the study of disease systems. Overall, we demonstrate that our approach links disease-associated genes to the phenotypes they produce, a key goal within systems medicine.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean.

PubMed

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla ) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein-protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

PubMed Central

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms. PMID:29666630

TPT1 (tumor protein, translationally-controlled 1) negatively regulates autophagy through the BECN1 interactome and an MTORC1-mediated pathway.

PubMed

Bae, Seong-Yeon; Byun, Sanguine; Bae, Soo Han; Min, Do Sik; Woo, Hyun Ae; Lee, Kyunglim

2017-05-04

TPT1/TCTP (tumor protein, translationally-controlled 1) is highly expressed in tumor cells, known to participate in various cellular activities including protein synthesis, growth and cell survival. In addition, TPT1 was identified as a direct target of the tumor suppressor TP53/p53 although little is known about the mechanism underlying the anti-survival function of TPT1. Here, we describe a role of TPT1 in the regulation of the MTORC1 pathway through modulating the molecular machinery of macroautophagy/autophagy. TPT1 inhibition induced cellular autophagy via the MTORC1 and AMPK pathways, which are inhibited and activated, respectively, during treatment with the MTOR inhibitor rapamycin. We also found that the depletion of TPT1 potentiated rapamycin-induced autophagy by synergizing with MTORC1 inhibition. We further demonstrated that TPT1 knockdown altered the BECN1 interactome, a representative MTOR-independent pathway, to stimulate autophagosome formation, via downregulating BCL2 expression through activating MAPK8/JNK1, and thereby enhancing BECN1-phosphatidylinositol 3-kinase (PtdIns3K)-UVRAG complex formation. Furthermore, reduced TPT1 promoted autophagic flux by modulating not only early steps of autophagy but also autophagosome maturation. Consistent with in vitro findings, in vivo organ analysis using Tpt1 heterozygote knockout mice showed that autophagy is enhanced because of haploinsufficient TPT1 expression. Overall, our study demonstrated the novel role of TPT1 as a negative regulator of autophagy that may have potential use in manipulating various diseases associated with autophagic dysfunction.

Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

PubMed

Brady, Arthur; Maxwell, Kyle; Daniels, Noah; Cowen, Lenore J

2009-01-01

As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model) motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all). We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

Fault Tolerance in Protein Interaction Networks: Stable Bipartite Subgraphs and Redundant Pathways

PubMed Central

Brady, Arthur; Maxwell, Kyle; Daniels, Noah; Cowen, Lenore J.

2009-01-01

As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model) motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all). We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair. PMID:19399174

Challenges in structural approaches to cell modeling

PubMed Central

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A.

2016-01-01

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. PMID:27255863

Fourier analysis of He 4471/Mg 4481 line profiles for separating rotational velocity and axial inclination in rapidly rotating B-type stars

NASA Astrophysics Data System (ADS)

Takeda, Y.; Kawanomoto, S.; Ohishi, N.

2017-11-01

While the effect of rotation on spectral lines is complicated in rapidly rotating stars because of the appreciable gravity-darkening effect differing from line to line, it is possible to make use of this line-dependent complexity to separately determine the equatorial rotation velocity (ve) and the inclination angle (i) of rotational axis. Although linewidths of spectral lines were traditionally used for this aim, we tried in this study to apply the Fourier method, which utilizes the unambiguously determinable first-zero frequency (σ1) in the Fourier transform of line profile. Equipped with this technique, we analysed the profiles of He I 4471 and Mg I 4481 lines of six rapidly rotating (ve sin i ∼ 150-300 km s-1) late B-type stars, while comparing them with the theoretical profiles simulated on a grid of models computed for various combination of (ve, i). According to our calculation, σ1 tends to be larger than the classical value for given ve sin i. This excess progressively grows with an increase in ve, and is larger for the He line than the Mg line, which leads to {σ} 1^He > {σ} 1^Mg. It was shown that ve and i are separately determinable from the intersection of two loci (sets of solutions reproducing the observed σ1 for each line) on the ve versus i plane. Yet, line profiles alone are not sufficient for their unique discrimination, for which photometric information (such as colours) needs to be simultaneously employed.

A rapid nuclear staining test using cationic dyes contributes to efficient STR analysis of telogen hair roots.

PubMed

Lee, So-Yeon; Ha, Eun-Ju; Woo, Seung-Kyun; Lee, So-Min; Lim, Kyung-Hee; Eom, Yong-Bin

2017-07-01

Telogen hairs presented in the crime scene are commonly encountered as trace evidence. However, short tandem repeat (STR) profiling of the hairs currently have low and limited use due to poor success rate. To increase the success rate of STR profiling of telogen hairs, we developed a rapid and cost-effective method to estimate the number of nuclei in the hair roots. Five cationic dyes, Methyl green (MG), Harris hematoxylin (HH), Methylene blue (MB), Toluidine blue (TB), and Safranin O (SO) were evaluated in this study. We conducted a screening test based on microscopy and the percentage of loss with nuclear DNA, in order to select the best dye. MG was selected based on its specific nuclei staining and low adverse effect on the hair-associated nuclear DNA. We examined 330 scalp and 100 pubic telogen hairs with MG. Stained hairs were classified into five groups and analyzed by STR. The fast staining method revealed 70% (head hair) and 33.4% (pubic hair) of full (30 alleles) and high partial (18-29 alleles) STR profiling proportion from the lowest nuclei count group (one to ten nuclei). The results of this study demonstrated a rapid, specific, nondestructive, and high yield DNA profiling method applicable for screening telogen hairs. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid In Situ Profiling of Lipid C═C Location Isomers in Tissue Using Ambient Mass Spectrometry with Photochemical Reactions.

PubMed

Tang, Fei; Guo, Chengan; Ma, Xiaoxiao; Zhang, Jian; Su, Yuan; Tian, Ran; Shi, Riyi; Xia, Yu; Wang, Xiaohao; Ouyang, Zheng

2018-05-01

Rapid and in situ profiling of lipids using ambient mass spectrometry (AMS) techniques has great potential for clinical diagnosis, biological studies, and biomarker discovery. In this study, the online photochemical reaction involving carbon-carbon double bonds was coupled with a surface sampling technique to develop a direct tissue-analysis method with specificity to lipid C═C isomers. This method enabled the in situ analysis of lipids from the surface of various tissues or tissue sections, which allowed the structural characterization of lipid isomers within 2 min. Under optimized reaction conditions, we have established a method for the relative quantitation of lipid C═C location isomers by comparing the abundances of the diagnostic ions arising from each isomer, which has been proven effective through the established linear relationship ( R 2 = 0.999) between molar ratio and diagnostic ion ratio of the FA 18:1 C═C location isomers. This method was then used for the rapid profiling of unsaturated lipid C═C isomers in the sections of rat brain, lung, liver, spleen, and kidney, as well as in normal and diseased rat tissues. Quantitative information on FA 18:1 and PC 16:0-18:1 C═C isomers was obtained, and significant differences were observed between different samples. To the best of our knowledge, this is the first study to report the direct analysis of lipid C═C isomers in tissues using AMS. Our results demonstrated that this method can serve as a rapid analytical approach for the profiling of unsaturated lipid C═C isomers in biological tissues and should contribute to functional lipidomics and clinical diagnosis.

Vitiligo blood transcriptomics provides new insights into disease mechanisms and identifies potential novel therapeutic targets.

PubMed

Dey-Rao, Rama; Sinha, Animesh A

2017-01-28

Significant gaps remain regarding the pathomechanisms underlying the autoimmune response in vitiligo (VL), where the loss of self-tolerance leads to the targeted killing of melanocytes. Specifically, there is incomplete information regarding alterations in the systemic environment that are relevant to the disease state. We undertook a genome-wide profiling approach to examine gene expression in the peripheral blood of VL patients and healthy controls in the context of our previously published VL-skin gene expression profile. We used several in silico bioinformatics-based analyses to provide new insights into disease mechanisms and suggest novel targets for future therapy. Unsupervised clustering methods of the VL-blood dataset demonstrate a "disease-state"-specific set of co-expressed genes. Ontology enrichment analysis of 99 differentially expressed genes (DEGs) uncovers a down-regulated immune/inflammatory response, B-Cell antigen receptor (BCR) pathways, apoptosis and catabolic processes in VL-blood. There is evidence for both type I and II interferon (IFN) playing a role in VL pathogenesis. We used interactome analysis to identify several key blood associated transcriptional factors (TFs) from within (STAT1, STAT6 and NF-kB), as well as "hidden" (CREB1, MYC, IRF4, IRF1, and TP53) from the dataset that potentially affect disease pathogenesis. The TFs overlap with our reported lesional-skin transcriptional circuitry, underscoring their potential importance to the disease. We also identify a shared VL-blood and -skin transcriptional "hot spot" that maps to chromosome 6, and includes three VL-blood dysregulated genes (PSMB8, PSMB9 and TAP1) described as potential VL-associated genetic susceptibility loci. Finally, we provide bioinformatics-based support for prioritizing dysregulated genes in VL-blood or skin as potential therapeutic targets. We examined the VL-blood transcriptome in context with our (previously published) VL-skin transcriptional profile to address a major gap in knowledge regarding the systemic changes underlying skin-specific manifestation of vitiligo. Several transcriptional "hot spots" observed in both environments offer prioritized targets for identifying disease risk genes. Finally, within the transcriptional framework of VL, we identify five novel molecules (STAT1, PRKCD, PTPN6, MYC and FGFR2) that lend themselves to being targeted by drugs for future potential VL-therapy.

Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study.

PubMed

Roede, James R; Uppal, Karan; Park, Youngja; Lee, Kichun; Tran, Vilinh; Walker, Douglas; Strobel, Frederick H; Rhodes, Shannon L; Ritz, Beate; Jones, Dean P

2013-01-01

Progression of Parkinson's disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.

Simple & Rapid Generation of Complex DNA Profiles for the Undergraduate Laboratory

ERIC Educational Resources Information Center

Kass, David H.

2007-01-01

Deoxyribonucleic acid (DNA) profiles can be generated by a variety of techniques incorporating different types of DNA markers. Simple methods are commonly utilized in the undergraduate laboratory, but with certain drawbacks. In this article, the author presents an advancement of the "Alu" dimorphism technique involving two tetraplex polymerase…

Emory University: High-Throughput Protein-Protein Interaction Analysis for Hippo Pathway Profiling | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University used high-throughput protein-protein interaction (PPI) mapping for Hippo signaling pathway profiling to rapidly unveil promising PPIs as potential therapeutic targets and advance functional understanding of signaling circuitry in cells. Read the abstract.

Determination of antibiotic resistance and high-performance liquid chromatography profiles for Mycobacterium species.

PubMed

Toka Özer, Türkan; Yula, Erkan; Doğan, Metin; Baskın, Hüseyin

2018-04-27

Incidence of mycobacterial infections has been increasing. However, diagnosis and treatment of mycobacterial infections can be difficult. The aim of this study was to investigate high-performance liquid chromatography (HPLC) analysis of the mycolic acids for rapid identification and dendrogram cluster analysis of mycobacterium species. Clinical specimens received for mycobacterial culture and antimicrobial susceptibility test were processed by standard laboratory protocols. Positive cultures were analyzed with HPLC method. Mycolic acid analysis with HPLC was used for diagnosis of tuberculosis and other mycobacterial infections. These reports were compared with Sherlock Library mycobacterial species, and the similarity index was analyzed. This value was formed by a software in multidimensional space that was the calculation of the average distance between the nearest library profile and unknown profile. The ninety-two samples were identified as M. tuberculosis. (similarity index between 0.593 and 0.994). One of the other strains was identified as M. avium intracellulare (strain No. 82) (SI = 0.906); one of them was identified as M. interjectum (strain no. 89) (SI = 0.644). Total 94 samples were identified, and dendrogram was applied to these samples. Profile A (10.6%), profile B (59.6%), profile C (11.7%), profile D (3.2%), and other profiles as single different profiles were identified. Rates for each as 1% (89, 94, 1, 82, 26, 42, 32, 41, 100, 43, 47, 44, 40, 35). High-performance liquid chromatography is a useful, rapid, reliable, and practical method for diagnosis of mycobacterium species. © 2018 Wiley Periodicals, Inc.

The rapids and the pools - Grand Canyon: Chapter D in The Colorado River region and John Wesley Powell (Professional Paper 669)

USGS Publications Warehouse

Leopold, Luna Bergere

1969-01-01

Through the Grand Canyon the Colorado drops in elevation about 2,200 feet in 280 miles; most of this drop occurs in rapids that account for only 10 percent of the distance. Despite the importance of rapids, there are no waterfalls. Depth measurements made at 1/10-mile intervals show that the bed profile is highly irregular, but the apparent randomness masks an organized alternation of deeps and shallows. Measurement of the age of a lava flow that once blocked the canyon near Toroweap shows that no appreciable deepening of the canyon has taken place during the last million years. It is reasoned that the river has had both the time and the ability to eliminate the rapids. The long-continued existence and the relative straightness of the longitudinal profile indicate that the river maintains a state of quasi-equilibrium which provides the hydraulic requirements for carrying the debris load brought in from upstream without continued erosion of the canyon bed. The maintenance of the alternating pools and rapids seems to be a necessary part of this poised or equilibrium condition.

CREDO: a structural interactomics database for drug discovery

PubMed Central

Schreyer, Adrian M.; Blundell, Tom L.

2013-01-01

CREDO is a unique relational database storing all pairwise atomic interactions of inter- as well as intra-molecular contacts between small molecules and macromolecules found in experimentally determined structures from the Protein Data Bank. These interactions are integrated with further chemical and biological data. The database implements useful data structures and algorithms such as cheminformatics routines to create a comprehensive analysis platform for drug discovery. The database can be accessed through a web-based interface, downloads of data sets and web services at http://www-cryst.bioc.cam.ac.uk/credo. Database URL: http://www-cryst.bioc.cam.ac.uk/credo PMID:23868908

GLS-Finder: An Automated Data-Mining System for Fast Profiling Glucosinolates and its Application in Brassica Vegetables

USDA-ARS?s Scientific Manuscript database

A rapid computer-aided program for profiling glucosinolates, “GLS-Finder", was developed. GLS-Finder is a Matlab script based expert system that is capable for qualitative and semi-quantitative analysis of glucosinolates in samples using data generated by ultra-high performance liquid chromatograph...

Exploration of Individual Study Paths of Successful First-Year Students: An Interview Study

ERIC Educational Resources Information Center

Lindblom-Ylänne, Sari; Haarala-Muhonen, Anne; Postareff, Liisa; Hailikari, Telle

2017-01-01

The aim of the present study was to explore the individual profiles of successful, rapidly progressing first-year university students. The participants numbered 38 humanities and law students, who volunteered to be interviewed. The interview data were analysed using abductive content analysis. Two student profiles were distinguished:…

Accelerated relative sea-level rise and rapid coastal erosion: Testing a causal relationship for the Louisiana barrier islands

USGS Publications Warehouse

List, J.H.; Sallenger, A.H.; Hansen, M.E.; Jaffe, B.E.

1997-01-01

The role of relative sea-level rise as a cause for the rapid erosion of Louisiana's barrier island coast is investigated through a numerical implementation of a modified Bruun rule that accounts for the low percentage of sand-sized sediment in the eroding Louisiana shoreface. Shore-normal profiles from 150 km of coastline west of the Mississippi delta are derived from bathymetric surveys conducted during the 1880s. 1930s and 1980s. An RMS difference criterion is employed to test whether an equilibrium profile form is maintained between survey years. Only about half the studied profiles meet the equilibrium Criterion this represents a significant limitation on the potential applicability of the Bruun rule. The profiles meeting the equilibrium criterion, along with measured rates of relative sea-level rise, are used to hindcast shoreline retreat rates at 37 locations within the study area. Modeled and observed shoreline retreat rates show no significant correlation. Thus in terms of the Bruun approach relative sea-level rise has no power for hindcasting (and presumably forecasting) rates of coastal erosion for the Louisiana barrier islands.

The 2001 April Burst Activation of SGR 1900+14: Pulse Properties and Torque

NASA Technical Reports Server (NTRS)

Woods, P. M.; Kouveliotou, C.; Goegues, E.; Finger, M. H.; Feroci, M.; Mereghetti, S.; Swank, J. H.; Hurley, K.; Heise, J.; Smith, D.;

In silico analysis of Mn transporters (NRAMP1) in various plant species.

PubMed

Vatansever, Recep; Filiz, Ertugrul; Ozyigit, Ibrahim Ilker

2016-03-01

Manganese (Mn) is an essential micronutrient in plant life cycle. It may be involved in photosynthesis, carbohydrate and lipid biosynthesis, and oxidative stress protection. Mn deficiency inhibits the plant growth and development, and causes the various plant symptoms such as interveinal chlorosis and tissue necrosis. Despite its importance in plant life cycle, we still have limited knowledge about Mn transporters in many plant species. Therefore, this study aimed to identify and characterize high affinity Arabidopsis Mn root transporter NRAMP1 orthologs in 17 different plant species. Various in silico methods and digital gene expression data were used in identification and characterization of NRAMP1 homologs; physico-chemical properties of sequences were calculated, putative transmembrane domains (TMDs) and conserved motif signatures were determined, phylogenetic tree was constructed, 3D models and interactome map were generated, and gene expression data was analyzed. 49 NRAMP1 homologs were identified from proteome datasets of 17 plant species using AtNRAMP1 as query. Identified sequences were characterized with a NRAMP domain structure, 10-12 putative TMDs with cytosolic N- and C-terminuses, and 10-14 exons encoding a protein of 500-588 amino acids and 53.8-64.3 kDa molecular weight with basic characteristics. Consensus transport residues, GQSSTITGTYAGQY(/F)V(/I)MQGFLD(/E/N) between TMD-8 and 9 were identified in all sequences but putative N-linked glycosylation sites were not highly conserved. In phylogeny, NRAMP1 sequences demonstrated divergence in lower and higher plants as well as in monocots and dicots. Despite divergence of lower plant Physcomitrella patens in phylogeny, it showed similarity in superposed 3D models. Phylogenetic distribution of AtNRAMP1 and 6 homologs inferred a functional relationship to NRAMP6 sequences in Mn transport, while distribution of OsNRAMP1 and 5 homologs implicated an involvement of NRAMP1 sequences in Mn transport or a cross-talk between in Fe-Mn homeostasis. Interactome analysis further confirmed this cross-talk between Mn and Fe pathways. Gene expression profile of AtNRAMP1 under Fe-, K-, P- and S-deficiencies, and cold, drought, heat and salt stresses revealed various proteins involving in transcription regulation, cofactor biosynthesis, diverse developmental roles, carbohydrate metabolism, oxidation-reduction reactions, cellular signaling and protein degradation pathways. Mn deficiency or toxicity could cause serious adverse effects in plants as well as in humans. To reduce these adversities mainly rely on understanding the molecular mechanisms underlying Mn uptake from the soil. However, we still have limited knowledge regarding the structural and functional roles of Mn transporters in many plant species. Therefore, identification and characterization of Mn root uptake transporter, NRAMP1 orthologs in various plant species will provide valuable theoretical knowledge to better understand Mn transporters as well as it may become an insight for future studies aiming to develop genetically engineered and biofortified plants.

Comparison of rapid descriptive sensory methodologies: Free-Choice Profiling, Flash Profile and modified Flash Profile.

PubMed

Liu, Jing; Bredie, Wender L P; Sherman, Emma; Harbertson, James F; Heymann, Hildegarde

2018-04-01

Rapid sensory methods have been developed as alternatives to traditional sensory descriptive analysis methods. Among them, Free-Choice Profiling (FCP) and Flash Profile (FP) are two that have been known for many years. The objectives of this work were to compare the rating-based FCP and ranking-based FP method; to evaluate the impact of adding adjustments to FP approach; to investigate the influence of the number of assessors on the outcome of modified FP. To achieve these aims, a conventional descriptive analysis (DA), FCP, FP and a modified version of FP were carried out. Red wines made by different grape maturity and ethanol concentration were used for sensory testing. This study showed that DA provided a more detailed and accurate information on products through a quantitative measure of the intensity of sensory attributes than FCP and FP. However, the panel hours for conducting DA were higher than that for rapid methods, and FP was even able to separate the samples to a higher degree than DA. When comparing FCP and FP, this study showed that the ranking-based FP provided a clearer separation of samples than rating-based FCP, but the latter was an easier task for most assessors. When restricting assessors on their use of attributes in FP, the sample space became clearer and the ranking task was simplified. The FP protocol with restricted attribute sets seems to be a promising approach for efficient screening of sensory properties in wine. When increasing the number of assessors from 10 to 20 for conducting the modified FP, the outcome tended to be slightly more stable, however, one should consider the degree of panel training when deciding the optimal number of assessors for conducting FP. Copyright © 2018 Elsevier Ltd. All rights reserved.

Undergraduate Chemistry Education in Chinese Universities: Addressing the Challenges of Rapid Growth

ERIC Educational Resources Information Center

Gou, Xiaojun; Cao, Haishi

2010-01-01

In the past 30 years, university-level chemistry education in China has been experiencing significant changes because of the rapid expansion of its university education system. These changes are reflected in improvements to the existing education goals, classroom teaching methods, textbooks, teaching facilities, teacher profiles, lab activities,…

Optimization and validation of a fast amplification protocol for AmpFlSTR® Profiler Plus® for rapid forensic human identification.

PubMed

Laurin, Nancy; Frégeau, Chantal

2012-01-01

The goal of this work was to optimize and validate a fast amplification protocol for the multiplex amplification of the STR loci included in AmpFlSTR(®) Profiler Plus(®) to expedite human DNA identification. By modifying the cycling conditions and by combining the use of a DNA polymerase optimized for high speed PCR (SpeedSTAR™ HS) and a more efficient thermal cycler instrument (Bio-RAD C1000™), we were able to reduce the amplification process from 4h to 26 min. No modification to the commercial AmpFlSTR(®) Profiler Plus(®) primer mix was required. When compared to the current Royal Canadian Mounted Police (RCMP) amplification protocol, no differences with regards to specificity, sensitivity, heterozygote peak height ratios and overall profile balance were noted. Moreover, complete concordance was obtained with profiles previously generated with the standard amplification protocol and minor alleles in mixture samples were reliably typed. An increase in n-4 stutter ratios (2.2% on average for all loci) was observed for profiles amplified with the fast protocol compared to the current procedure. Our results document the robustness of this rapid amplification protocol for STR profiling using the AmpFlSTR(®) Profiler Plus(®) primer set and demonstrate that comparable data can be obtained in substantially less time. This new approach could provide an alternative option to current multiplex STR typing amplification protocols in order to increase throughput or expedite time-sensitive cases. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Spacecraft compartment venting

NASA Astrophysics Data System (ADS)

Scialdone, John J.

1998-10-01

At various times, concerns have been expressed that rapid decompressions of compartments of gas pockets and thermal blankets during spacecraft launches may have caused pressure differentials across their walls sufficient to cause minor structural failures, separations of adhesively-joined parts, ballooning, and flapping of blankets. This paper presents a close form equation expressing the expected pressure differentials across the walls of a compartment as a function of the external to the volume pressure drops, the pressure at which the rates occur and the vent capability of the compartment. The pressure profiles measured inside the shrouds of several spacecraft propelled by several vehicles and some profiles obtained from ground vacuum systems have been included. The equation can be used to design the appropriate vent, which will preclude excessive pressure differentials. Precautions and needed approaches for the evaluations of the expected pressures have been indicated. Methods to make a rapid assessment of the response of the compartment to rapid external pressure drops have been discussed. These are based on the evaluation of the compartment vent flow conductance, the volume and the length of time during which the rapid pressure drop occurs.

Spacecraft Compartment Venting

NASA Technical Reports Server (NTRS)

Scialdone, John J.

1998-01-01

At various time concerns have been expressed that rapid decompressions of compartments of gas pockets and thermal blankets during spacecraft launches may have caused pressure differentials across their walls sufficient to cause minor structural failures, separations of adhesively-joined parts, ballooning, and flapping of blankets. This paper presents a close form equation expressing the expected pressure differentials across the walls of a compartment as a function of the external to the volume pressure drops, the pressure at which the rates occur and the vent capability of the compartment. The pressure profiles measured inside the shrouds of several spacecraft propelled by several vehicles and some profiles obtained from ground vacuum systems have been included. The equation can be used to design the appropriate vent, which will preclude excessive pressure differentials. Precautions and needed approaches for the evaluations of the expected pressures have been indicated. Methods to make a rapid assessment of the response of the compartment to rapid external pressure drops have been discussed. These are based on the evaluation of the compartment vent flow conductance, the volume and the length of time during which the rapid pressure drop occurs.

Online extraction-high performance liquid chromatography-diode array detector-quadrupole time-of-flight tandem mass spectrometry for rapid flavonoid profiling of Fructus aurantii immaturus.

PubMed

Tong, Runna; Peng, Mijun; Tong, Chaoying; Guo, Keke; Shi, Shuyun

2018-03-01

Chemical profiling of natural products by high performance liquid chromatography (HPLC) was critical for understanding of their clinical bioactivities, and sample pretreatment steps have been considered as a bottleneck for analysis. Currently, concerted efforts have been made to develop sample pretreatment methods with high efficiency, low solvent and time consumptions. Here, a simple and efficient online extraction (OLE) strategy coupled with HPLC-diode array detector-quadrupole time-of-flight tandem mass spectrometry (HPLC-DAD-QTOF-MS/MS) was developed for rapid chemical profiling. For OLE strategy, guard column inserted with ground sample (2 mg) instead of sample loop was connected with manual injection valve, in which components were directly extracted and transferred to HPLC-DAD-QTOF-MS/MS system only by mobile phase without any extra time, solvent, instrument and operation. By comparison with offline heat-reflux extraction for Fructus aurantii immaturus (Zhishi), OLE strategy presented higher extraction efficiency perhaps because of the high pressure and gradient elution mode. A total of eighteen flavonoids were detected according to their retention times, UV spectra, exact mass, and fragmentation ions in MS/MS spectra, and compound 9, natsudaidain-3-O-glucoside, was discovered in Zhishi for the first time. It is concluded that the developed OLE-HPLC-DAD-QTOF-MS/MS system offers new perspectives for rapid chemical profiling of natural products. Copyright © 2018. Published by Elsevier B.V.

Rapid profiling of Swiss cheese by attenuated total reflectance (ATR) infrared spectroscopy and descriptive sensory analysis.

PubMed

Kocaoglu-Vurma, N A; Eliardi, A; Drake, M A; Rodriguez-Saona, L E; Harper, W J

2009-08-01

The acceptability of cheese depends largely on the flavor formed during ripening. The flavor profiles of cheeses are complex and region- or manufacturer-specific which have made it challenging to understand the chemistry of flavor development and its correlation with sensory properties. Infrared spectroscopy is an attractive technology for the rapid, sensitive, and high-throughput analysis of foods, providing information related to its composition and conformation of food components from the spectra. Our objectives were to establish infrared spectral profiles to discriminate Swiss cheeses produced by different manufacturers in the United States and to develop predictive models for determination of sensory attributes based on infrared spectra. Fifteen samples from 3 Swiss cheese manufacturers were received and analyzed using attenuated total reflectance infrared spectroscopy (ATR-IR). The spectra were analyzed using soft independent modeling of class analogy (SIMCA) to build a classification model. The cheeses were profiled by a trained sensory panel using descriptive sensory analysis. The relationship between the descriptive sensory scores and ATR-IR spectra was assessed using partial least square regression (PLSR) analysis. SIMCA discriminated the Swiss cheeses based on manufacturer and production region. PLSR analysis generated prediction models with correlation coefficients of validation (rVal) between 0.69 and 0.96 with standard error of cross-validation (SECV) ranging from 0.04 to 0.29. Implementation of rapid infrared analysis by the Swiss cheese industry would help to streamline quality assurance.

Method development in high-performance liquid chromatography for high-throughput profiling and metabonomic studies of biofluid samples.

PubMed

Pham-Tuan, Hai; Kaskavelis, Lefteris; Daykin, Clare A; Janssen, Hans-Gerd

2003-06-15

"Metabonomics" has in the past decade demonstrated enormous potential in furthering the understanding of, for example, disease processes, toxicological mechanisms, and biomarker discovery. The same principles can also provide a systematic and comprehensive approach to the study of food ingredient impact on consumer health. However, "metabonomic" methodology requires the development of rapid, advanced analytical tools to comprehensively profile biofluid metabolites within consumers. Until now, NMR spectroscopy has been used for this purpose almost exclusively. Chromatographic techniques and in particular HPLC, have not been exploited accordingly. The main drawbacks of chromatography are the long analysis time, instabilities in the sample fingerprint and the rigorous sample preparation required. This contribution addresses these problems in the quest to develop generic methods for high-throughput profiling using HPLC. After a careful optimization process, stable fingerprints of biofluid samples can be obtained using standard HPLC equipment. A method using a short monolithic column and a rapid gradient with a high flow-rate has been developed that allowed rapid and detailed profiling of larger numbers of urine samples. The method can be easily translated into a slow, shallow-gradient high-resolution method for identification of interesting peaks by LC-MS/NMR. A similar approach has been applied for cell culture media samples. Due to the much higher protein content of such samples non-porous polymer-based small particle columns yielded the best results. The study clearly shows that HPLC can be used in metabonomic fingerprinting studies.

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry

PubMed Central

2010-01-01

Background Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. Results When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. Conclusion These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates. PMID:21073689

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry.

PubMed

Ayyadurai, Saravanan; Flaudrops, Christophe; Raoult, Didier; Drancourt, Michel

2010-11-12

Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates.

Pathogen profiling for disease management and surveillance.

PubMed

Sintchenko, Vitali; Iredell, Jonathan R; Gilbert, Gwendolyn L

2007-06-01

The usefulness of rapid pathogen genotyping is widely recognized, but its effective interpretation and application requires integration into clinical and public health decision-making. How can pathogen genotyping data best be translated to inform disease management and surveillance? Pathogen profiling integrates microbial genomics data into communicable disease control by consolidating phenotypic identity-based methods with DNA microarrays, proteomics, metabolomics and sequence-based typing. Sharing data on pathogen profiles should facilitate our understanding of transmission patterns and the dynamics of epidemics.

Proteomics: from hypothesis to quantitative assay on a single platform. Guidelines for developing MRM assays using ion trap mass spectrometers.

PubMed

Han, Bomie; Higgs, Richard E

2008-09-01

High-throughput HPLC-mass spectrometry (HPLC-MS) is routinely used to profile biological samples for potential protein markers of disease, drug efficacy and toxicity. The discovery technology has advanced to the point where translating hypotheses from proteomic profiling studies into clinical use is the bottleneck to realizing the full potential of these approaches. The first step in this translation is the development and analytical validation of a higher throughput assay with improved sensitivity and selectivity relative to typical profiling assays. Multiple reaction monitoring (MRM) assays are an attractive approach for this stage of biomarker development given their improved sensitivity and specificity, the speed at which the assays can be developed and the quantitative nature of the assay. While the profiling assays are performed with ion trap mass spectrometers, MRM assays are traditionally developed in quadrupole-based mass spectrometers. Development of MRM assays from the same instrument used in the profiling analysis enables a seamless and rapid transition from hypothesis generation to validation. This report provides guidelines for rapidly developing an MRM assay using the same mass spectrometry platform used for profiling experiments (typically ion traps) and reviews methodological and analytical validation considerations. The analytical validation guidelines presented are drawn from existing practices on immunological assays and are applicable to any mass spectrometry platform technology.

Interactome analysis of the lymphocytic choriomeningitis virus nucleoprotein in infected cells reveals ATPase Na+/K+ transporting subunit Alpha 1 and prohibitin as host-cell factors involved in the life cycle of mammarenaviruses

PubMed Central

Iwasaki, Masaharu; Caì, Yíngyún; de la Torre, Juan C.

2018-01-01

Several mammalian arenaviruses (mammarenaviruses) cause hemorrhagic fevers in humans and pose serious public health concerns in their endemic regions. Additionally, mounting evidence indicates that the worldwide-distributed, prototypic mammarenavirus, lymphocytic choriomeningitis virus (LCMV), is a neglected human pathogen of clinical significance. Concerns about human-pathogenic mammarenaviruses are exacerbated by of the lack of licensed vaccines, and current anti-mammarenavirus therapy is limited to off-label use of ribavirin that is only partially effective. Detailed understanding of virus/host-cell interactions may facilitate the development of novel anti-mammarenavirus strategies by targeting components of the host-cell machinery that are required for efficient virus multiplication. Here we document the generation of a recombinant LCMV encoding a nucleoprotein (NP) containing an affinity tag (rLCMV/Strep-NP) and its use to capture the NP-interactome in infected cells. Our proteomic approach combined with genetics and pharmacological validation assays identified ATPase Na+/K+ transporting subunit alpha 1 (ATP1A1) and prohibitin (PHB) as pro-viral factors. Cell-based assays revealed that ATP1A1 and PHB are involved in different steps of the virus life cycle. Accordingly, we observed a synergistic inhibitory effect on LCMV multiplication with a combination of ATP1A1 and PHB inhibitors. We show that ATP1A1 inhibitors suppress multiplication of Lassa virus and Candid#1, a live-attenuated vaccine strain of Junín virus, suggesting that the requirement of ATP1A1 in virus multiplication is conserved among genetically distantly related mammarenaviruses. Our findings suggest that clinically approved inhibitors of ATP1A1, like digoxin, could be repurposed to treat infections by mammarenaviruses pathogenic for humans. PMID:29462184

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

PubMed

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Anticancer activity of galactoxyloglucan polysaccharide-conjugated doxorubicin nanoparticles: Mechanistic insights and interactome analysis.

PubMed

Joseph, Manu M; Aravind, S R; George, Suraj K; Raveendran Pillai, K; Mini, S; Sreelekha, T T

2015-06-01

Toxicity associated with chemotherapeutic drugs such as doxorubicin (Dox), is one of the major obstacles that is currently affecting patients. PST-Dox (Galactoxyloglucan, PST001-conjugated Dox) nanoparticles were synthesized by encapsulating Dox with polysaccharide PST001, isolated from Tamarindus indica (Ti) by ionic gelation with tripolyphosphate (TPP). Herein, we demonstrate a detailed mechanistic and interactome network analysis that is specific to PST-Dox action in cancer cells and normal lymphocytes. Our results show that PST-Dox is superior to its parental counterparts, exhibiting a greater cytotoxicity by the induction of apoptosis against a wide variety of cancers by enhanced cellular uptake of Dox from the nanoparticle conjugates. Also, PST-Dox nanoparticles were non-toxic to normal lymphocytes with limited immunostimulatory effects up to certain doses. Elucidation of molecular mechanism by whole genome microarray in cancer cells and lymphocytes revealed that a large number of genes were dysregulated specifically in cancer cells. Specifically, a unique target gene EGR1, contextually determined translational activation of P53 in the cancerous and non-cancerous cells. Most of the key downregulated genes were tyrosine kinases, indicating the potential inhibitory action of PST-Dox on tyrosine kinase oncogenic pathways. Western blotting of proteins corresponding to the genes that were altered at the genomic level was very well correlated in the majority of them, except in a few that demonstrated post-transcriptional modifications. The important findings and highly disciplined approaches highlighted in the present study will speed up the therapeutic potential of this augmented nanoparticle formulation for more robust clinical studies and testing in several cancers. Copyright © 2015 Elsevier B.V. All rights reserved.

Integration of multiple biological features yields high confidence human protein interactome.

PubMed

Karagoz, Kubra; Sevimoglu, Tuba; Arga, Kazim Yalcin

2016-08-21

The biological function of a protein is usually determined by its physical interaction with other proteins. Protein-protein interactions (PPIs) are identified through various experimental methods and are stored in curated databases. The noisiness of the existing PPI data is evident, and it is essential that a more reliable data is generated. Furthermore, the selection of a set of PPIs at different confidence levels might be necessary for many studies. Although different methodologies were introduced to evaluate the confidence scores for binary interactions, a highly reliable, almost complete PPI network of Homo sapiens is not proposed yet. The quality and coverage of human protein interactome need to be improved to be used in various disciplines, especially in biomedicine. In the present work, we propose an unsupervised statistical approach to assign confidence scores to PPIs of H. sapiens. To achieve this goal PPI data from six different databases were collected and a total of 295,288 non-redundant interactions between 15,950 proteins were acquired. The present scoring system included the context information that was assigned to PPIs derived from eight biological attributes. A high confidence network, which included 147,923 binary interactions between 13,213 proteins, had scores greater than the cutoff value of 0.80, for which sensitivity, specificity, and coverage were 94.5%, 80.9%, and 82.8%, respectively. We compared the present scoring method with others for evaluation. Reducing the noise inherent in experimental PPIs via our scoring scheme increased the accuracy significantly. As it was demonstrated through the assessment of process and cancer subnetworks, this study allows researchers to construct and analyze context-specific networks via valid PPI sets and one can easily achieve subnetworks around proteins of interest at a specified confidence level. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Gut Microbiome and Mental Health: Implications for Anxiety- and Trauma-Related Disorders.

PubMed

Malan-Muller, Stefanie; Valles-Colomer, Mireia; Raes, Jeroen; Lowry, Christopher A; Seedat, Soraya; Hemmings, Sian M J

2018-02-01

Biological psychiatry research has long focused on the brain in elucidating the neurobiological mechanisms of anxiety- and trauma-related disorders. This review challenges this assumption and suggests that the gut microbiome and its interactome also deserve attention to understand brain disorders and develop innovative treatments and diagnostics in the 21st century. The recent, in-depth characterization of the human microbiome spurred a paradigm shift in human health and disease. Animal models strongly suggest a role for the gut microbiome in anxiety- and trauma-related disorders. The microbiota-gut-brain (MGB) axis sits at the epicenter of this new approach to mental health. The microbiome plays an important role in the programming of the hypothalamic-pituitary-adrenal (HPA) axis early in life, and stress reactivity over the life span. In this review, we highlight emerging findings of microbiome research in psychiatric disorders, focusing on anxiety- and trauma-related disorders specifically, and discuss the gut microbiome as a potential therapeutic target. 16S rRNA sequencing has enabled researchers to investigate and compare microbial composition between individuals. The functional microbiome can be studied using methods involving metagenomics, metatranscriptomics, metaproteomics, and metabolomics, as discussed in the present review. Other factors that shape the gut microbiome should be considered to obtain a holistic view of the factors at play in the complex interactome linked to the MGB. In all, we underscore the importance of microbiome science, and gut microbiota in particular, as emerging critical players in mental illness and maintenance of mental health. This new frontier of biological psychiatry and postgenomic medicine should be embraced by the mental health community as it plays an ever-increasing transformative role in integrative and holistic health research in the next decade.

In silico analysis of the amido phosphoribosyltransferase inhibition by PY873, PY899 and a derivative of isophthalic acid.

PubMed

Batool, Sidra; Nawaz, Muhammad Sulaman; Kamal, Mohammad A

2013-10-01

Selectively decreasing the availability of precursors for the de novo biosynthesis of purine nucleotides is a valid approach towards seeking a cure for leukaemia. Nucleotides and deoxynucleotides are required by living cells for syntheses of RNA, DNA, and cofactors such as NADP(+), FAD(+), coenzyme A and ATP. Nucleotides contain purine and pyrimidine bases, which can be synthesized through salvage pathway as well. Amido phosphoribosyltransferase (APRT), also known as glutamine phosphoribosylpyrophosphate amidotransferase (GPAT), is an enzyme that in humans is encoded by the PPAT (phosphoribosyl pyrophosphate amidotransferase) gene. APRT catalyzes the first committed step of the de novo pathway using its substrate, phosphoribosyl pyrophosphate (PRPP). As APRT is inhibited by many folate analogues, therefore, in this study we focused on the inhibitory effects of three folate analogues on APRT activity. This is extension of our previous wet lab work to analyze and dissect molecular interaction and inhibition mechanism using molecular modeling and docking tools in the current study. Comparative molecular docking studies were carried out for three diamino folate derivatives employing a model of the human enzyme that was built using the 3D structure of Bacillus subtilis APRT (PDB ID; 1GPH) as the template. Binding orientation of interactome indicates that all compounds having nominal cluster RMSD in same active site's deep narrow polar fissure. On the basis of comparative conformational analysis, electrostatic interaction, binding free energy and binding orientation of interactome, we support the possibility that these molecules could behave as APRT inhibitors and therefore may block purine de novo biosynthesis. Consequently, we suggest that PY899 is the most active biological compound that would be a more potent inhibitor for APRT inhibition than PY873 and DIA, which also confirms previous wet lab report.

Network analysis of the genomic basis of the placebo effect

PubMed Central

Wang, Rui-Sheng; Hall, Kathryn T.; Giulianini, Franco; Passow, Dani; Kaptchuk, Ted J.

2017-01-01

The placebo effect is a phenomenon in which patients who are given an inactive treatment (e.g., inert pill) show a perceived or actual improvement in a medical condition. Placebo effects in clinical trials have been investigated for many years especially because placebo treatments often serve as the control arm of randomized clinical trial designs. Recent observations suggest that placebo effects may be modified by genetics. This observation has given rise to the term “placebome,” which refers to a group of genome-related mediators that affect an individual’s response to placebo treatments. In this study, we conduct a network analysis of the placebome and identify a placebome module in the comprehensive human interactome using a seed-connector algorithm. The placebome module is significantly enriched with neurotransmitter signaling pathways and brain-specific proteins. We validate the placebome module using a large cohort of the Women’s Genome Health Study (WGHS) trial and demonstrate that the placebome module is significantly enriched with genes whose SNPs modify the outcome in the placebo arm of the trial. To gain insights into placebo effects in different diseases and drug treatments, we use a network proximity measure to examine the closeness of the placebome module to different disease modules and drug target modules. The results demonstrate that the network proximity of the placebome module to disease modules in the interactome significantly correlates with the strength of the placebo effect in the corresponding diseases. The proximity of the placebome module to molecular pathways affected by certain drug classes indicates the existence of placebo-drug interactions. This study is helpful for understanding the molecular mechanisms mediating the placebo response, and sets the stage for minimizing its effects in clinical trials and for developing therapeutic strategies that intentionally engage it. PMID:28570268

Clinical profiling and use of loop-mediated isothermal amplification assay for rapid detection of Mycobacterium tuberculosis from sputum.

PubMed

Poudel, A; Pandey, B D; Lekhak, B; Rijal, B; Sapkota, B R; Suzuki, Y

2009-01-01

Tuberculosis is a global health problem and the situation is worsening with newer incidences of drug resistance and HIV association. Diagnosis of tuberculosis can be done by many methods and test, culture of sputum being the ideal one. Nucleic acid amplification (NAA) assay are more time efficient one, that amplify and detect specific nucleic acid sequences allows rapid, sensitive and specific detection of M. tuberculosis in sputum samples. The present study intends to compile the clinical presentations of the pulmonary tuberculosis (PTB) patients and to evaluate the efficacy of in-house loop-mediated isothermal amplification (LAMP) in detecting Mycobacterium tuberculosis in sputum samples by comparing with microscopy and culture. Two hundred two sputum samples were collected from 202 patients at National Tuberculosis Center, Bhaktapur, Nepal. Complete clinical profiling, epidemiological data and record on BCG vaccination were noted and the samples were subjected for microscopy, culture and in-house LAMP with six primers specific for 16S RNA gene of Mycobacterium tuberculosis. Of the 176 cases of clinical profiling, productive cough was most common symptom in 147 (83.52%), followed by chest pain 136 (77.27%), fever 133 (75.56%) and haemoptysis 61 (34.66%). There was a statistically significant association between BCG vaccination and development of TB (chi(2)=5.33, P=0.02). Of 202 cases, 115 (56.93%) were chest X-ray positive, 101(50%) were direct smear-positive and 100 (49.51%) were culture positive. LAMP had a sensitivity of 97% and specificity of 94.12% while comparing with culture. In addition, its sensitivity and specificity were 91.09% and 89.11% respectively with reference to microscopy. As in our previous study, overall, the result of present study further confirms that the in-house LAMP is a simple, rapid, sensitive and specific DNA amplification technique for PTB diagnosis. Because of rapidity of microscopy and specificity of culture, in-house LAMP assay can be used as a very powerful and useful supplementary tool with complete clinical profiling of the patients for rapid diagnosis of TB in both AFB-positive and negative cases who are suspected as PTB in disease endemic country like Nepal.

Boron depth profiles and residual damage following rapid thermal annealing of low-temperature BSi molecular ion implantation in silicon

NASA Astrophysics Data System (ADS)

Liang, J. H.; Wang, S. C.

2007-08-01

The influence of substrate temperature on both the implantation and post-annealing characteristics of molecular-ion-implanted 5 × 1014 cm-2 77 keV BSi in silicon was investigated in terms of boron depth profiles and damage microstructures. The substrate temperatures under investigation consisted of room temperature (RT) and liquid nitrogen temperature (LT). Post-annealing treatments were performed using rapid thermal annealing (RTA) at 1050 °C for 25 s. Boron depth profiles and damage microstructures in both the as-implanted and as-annealed specimens were determined using secondary ion mass spectrometry (SIMS) and transmission electron microscopy (TEM), respectively. The as-implanted results revealed that, compared to the RT specimen, the LT specimen yields a shallower boron depth profile with a reduced tail into the bulk. An amorphous layer containing a smooth amorphous-to-crystalline (a/c) interface is evident in the LT specimen while just the opposite is true in the as-implanted RT one. The as-annealed results illustrated that the extension of the boron depth profile into the bulk via transient-enhanced diffusion (TED) in the LT specimen is less than it is in the RT one. Only residual defects are visible in the LT specimen while two clear bands of dislocation loops appear in the RT one.

Web-Based Analysis for Student-Generated Complex Genetic Profiles

ERIC Educational Resources Information Center

Kass, David H.; LaRoe, Robert

2007-01-01

A simple, rapid method for generating complex genetic profiles using Alu-based markers was recently developed for students primarily at the undergraduate level to learn more about forensics and paternity analysis. On the basis of the Cold Spring Harbor Allele Server, which provides an excellent tool for analyzing a single Alu variant, we present a…

Differences in transcriptional effects of 1α,25 dihydroxyvitamin D3 on fibroblasts associated to breast carcinomas and from paired normal breast tissues.

PubMed

Campos, Laura Tojeiro; Brentani, Helena; Roela, Rosimeire Aparecida; Katayama, Maria Lucia Hirata; Lima, Leandro; Rolim, Cíntia Flores; Milani, Cíntia; Folgueira, Maria Aparecida Azevedo Koike; Brentani, Maria Mitzi

2013-01-01

The effects of 1α,25 dihydroxyvitamin D3 (1,25D) on breast carcinoma associated fibroblasts (CAFs) are still unknown. This study aimed to identify genes whose expression was altered after 1,25D treatment in CAFs and matched adjacent normal mammary associated fibroblasts (NAFs). CAFs and NAFs (from 5 patients) were cultured with or without (control) 1,25D 100 nM. Both CAF and NAF expressed vitamin D receptor (VDR) and 1,25D induction of the genomic pathway was detected through up-regulation of the target gene CYP24A1. Microarray analysis showed that despite presenting 50% of overlapping genes, CAFs and NAFs exhibited distinct transcriptional profiles after 1,25D treatment (FDR<0.05). Functional analysis revealed that in CAFs, genes associated with proliferation (NRG1, WNT5A, PDGFC) were down regulated and those involved in immune modulation (NFKBIA, TREM-1) were up regulated, consistent with anti tumor activities of 1,25D in breast cancer. In NAFs, a distinct subset of genes was induced by 1,25D, involved in anti apoptosis, detoxification, antibacterial defense system and protection against oxidative stress, which may limit carcinogenesis. Co-expression network and interactome analysis of genes commonly regulated by 1,25D in NAFs and CAFs revealed differences in their co-expression values, suggesting that 1,25D effects in NAFs are distinct from those triggered in CAFs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Combining affinity proteomics and network context to identify new phosphatase substrates and adapters in growth pathways

PubMed Central

Sacco, Francesca; Boldt, Karsten; Calderone, Alberto; Panni, Simona; Paoluzi, Serena; Castagnoli, Luisa; Ueffing, Marius; Cesareni, Gianni

2014-01-01

Protein phosphorylation homoeostasis is tightly controlled and pathological conditions are caused by subtle alterations of the cell phosphorylation profile. Altered levels of kinase activities have already been associated to specific diseases. Less is known about the impact of phosphatases, the enzymes that down-regulate phosphorylation by removing the phosphate groups. This is partly due to our poor understanding of the phosphatase-substrate network. Much of phosphatase substrate specificity is not based on intrinsic enzyme specificity with the catalytic pocket recognizing the sequence/structure context of the phosphorylated residue. In addition many phosphatase catalytic subunits do not form a stable complex with their substrates. This makes the inference and validation of phosphatase substrates a non-trivial task. Here, we present a novel approach that builds on the observation that much of phosphatase substrate selection is based on the network of physical interactions linking the phosphatase to the substrate. We first used affinity proteomics coupled to quantitative mass spectrometry to saturate the interactome of eight phosphatases whose down regulations was shown to affect the activation of the RAS-PI3K pathway. By integrating information from functional siRNA with protein interaction information, we develop a strategy that aims at inferring phosphatase physiological substrates. Graph analysis is used to identify protein scaffolds that may link the catalytic subunits to their substrates. By this approach we rediscover several previously described phosphatase substrate interactions and characterize two new protein scaffolds that promote the dephosphorylation of PTPN11 and ERK by DUSP18 and DUSP26, respectively. PMID:24847354

MicroRNA Signature of Human Microvascular Endothelium Infected with Rickettsia rickettsii

PubMed Central

Sahni, Abha; Narra, Hema P.; Patel, Jignesh; Sahni, Sanjeev K.

2017-01-01

MicroRNAs (miRNAs) mediate gene silencing by destabilization and/or translational repression of target mRNA. Infection of human microvascular endothelial cells as primary targets of Rickettsia rickettsii, the etiologic agent of Rocky Mountain spotted fever, triggers host responses appertaining to alterations in cellular gene expression. Microarray-based profiling of endothelial cells infected with R. rickettsii for 3 or 24 h revealed differential expression of 33 miRNAs, of which miRNAs129-5p, 200a-3p, 297, 200b-3p, and 595 were identified as the top five up-regulated miRNAs (5 to 20-fold, p ≤ 0.01) and miRNAs 301b-3p, 548a-3p, and 377-3p were down-regulated (2 to 3-fold, p ≤ 0.01). Changes in the expression of selected miRNAs were confirmed by q-RT-PCR in both in vitro and in vivo models of infection. As potential targets, expression of genes encoding NOTCH1, SMAD2, SMAD3, RIN2, SOD1, and SOD2 was either positively or negatively regulated. Using a miRNA-specific mimic or inhibitor, NOTCH1 was determined to be a target of miRNA 200a-3p in R. rickettsii-infected human dermal microvascular endothelial cells (HMECs). Predictive interactome mapping suggested the potential for miRNA-mediated modulation of regulatory gene networks underlying important host cell signaling pathways. This first demonstration of altered endothelial miRNA expression provides new insights into regulatory elements governing mechanisms of host responses and pathogenesis during human rickettsial infections. PMID:28698491

Managing the genomic revolution in cancer diagnostics.

PubMed

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.

Use of DNA Microarrays to Identify Diagnostic Signature Transcription Profiles for Host Responses to Infectious Agents

DTIC Science & Technology

2004-10-01

informative in this regard. Key signature genes will serve as the basis for rapid diagnostic approaches that could be accessed when an outbreak is suspected...AD Award Number: DAMD17-01-1-0787 TITLE: Use of DNA Microarrays to Identify Diagnostic Signature Transcription Profiles for Host Responses to...Sep 2004) 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Use of DNA Microarrays to Identify Diagnostic Signature DAMD17-01-1-0787 Transcription Profiles for

Transcriptional Profiling of Antigen-Dependent Murine B Cell Differentiation and Memory Formation1

PubMed Central

Bhattacharya, Deepta; Cheah, Ming T.; Franco, Christopher B.; Hosen, Naoki; Pin, Christopher L.; Sha, William C.; Weissman, Irving L.

2015-01-01

Humoral immunity is characterized by the generation of Ab-secreting plasma cells and memory B cells that can more rapidly generate specific Abs upon Ag exposure than their naive counterparts. To determine the intrinsic differences that distinguish naive and memory B cells and to identify pathways that allow germinal center B cells to differentiate into memory B cells, we compared the transcriptional profiles of highly purified populations of these three cell types along with plasma cells isolated from mice immunized with a T-dependent Ag. The transcriptional profile of memory B cells is similar to that of naive B cells, yet displays several important differences, including increased expression of activation-induced deaminase and several antiapoptotic genes, chemotactic receptors, and costimulatory molecules. Retroviral expression of either Klf2 or Ski, two transcriptional regulators specifically enriched in memory B cells relative to their germinal center precursors, imparted a competitive advantage to Ag receptor and CD40-engaged B cells in vitro. These data suggest that humoral recall responses are more rapid than primary responses due to the expression of a unique transcriptional program by memory B cells that allows them to both be maintained at high frequencies and to detect and rapidly respond to antigenic re-exposure. PMID:17982071

Challenges in structural approaches to cell modeling.

PubMed

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A

2016-07-31

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial.

PubMed

Crosara, Karla Tonelli Bicalho; Moffa, Eduardo Buozi; Xiao, Yizhi; Siqueira, Walter Luiz

2018-01-16

Protein-protein interaction is a common physiological mechanism for protection and actions of proteins in an organism. The identification and characterization of protein-protein interactions in different organisms is necessary to better understand their physiology and to determine their efficacy. In a previous in vitro study using mass spectrometry, we identified 43 proteins that interact with histatin 1. Six previously documented interactors were confirmed and 37 novel partners were identified. In this tutorial, we aimed to demonstrate the usefulness of the STRING database for studying protein-protein interactions. We used an in-silico approach along with the STRING database (http://string-db.org/) and successfully performed a fast simulation of a novel constructed histatin 1 protein-protein network, including both the previously known and the predicted interactors, along with our newly identified interactors. Our study highlights the advantages and importance of applying bioinformatics tools to merge in-silico tactics with experimental in vitro findings for rapid advancement of our knowledge about protein-protein interactions. Our findings also indicate that bioinformatics tools such as the STRING protein network database can help predict potential interactions between proteins and thus serve as a guide for future steps in our exploration of the Human Interactome. Our study highlights the usefulness of the STRING protein database for studying protein-protein interactions. The STRING database can collect and integrate data about known and predicted protein-protein associations from many organisms, including both direct (physical) and indirect (functional) interactions, in an easy-to-use interface. Copyright © 2017 Elsevier B.V. All rights reserved.

Meat science: From proteomics to integrated omics towards system biology.

PubMed

D'Alessandro, Angelo; Zolla, Lello

2013-01-14

Since the main ultimate goal of farm animal raising is the production of proteins for human consumption, research tools to investigate proteins play a major role in farm animal and meat science. Indeed, proteomics has been applied to the field of farm animal science to monitor in vivo performances of livestock animals (growth performances, fertility, milk quality etc.), but also to further our understanding of the molecular processes at the basis of meat quality, which are largely dependent on the post mortem biochemistry of the muscle, often in a species-specific way. Post mortem alterations to the muscle proteome reflect the biological complexity of the process of "muscle to meat conversion," a process that, despite decades of advancements, is all but fully understood. This is mainly due to the enormous amounts of variables affecting meat tenderness per se, including biological factors, such as animal species, breed specific-characteristic, muscle under investigation. However, it is rapidly emerging that the tender meat phenotype is not only tied to genetics (livestock breeding selection), but also to extrinsic factors, such as the rearing environment, feeding conditions, physical activity, administration of hormonal growth promotants, pre-slaughter handling and stress, post mortem handling. From this intricate scenario, biochemical approaches and systems-wide integrated investigations (metabolomics, transcriptomics, interactomics, phosphoproteomics, mathematical modeling), which have emerged as complementary tools to proteomics, have helped establishing a few milestones in our understanding of the events leading from muscle to meat conversion. The growing integration of omics disciplines in the field of systems biology will soon contribute to take further steps forward. Copyright © 2012 Elsevier B.V. All rights reserved.

Convergence of Free Energy Profile of Coumarin in Lipid Bilayer

PubMed Central

2012-01-01

Atomistic molecular dynamics (MD) simulations of druglike molecules embedded in lipid bilayers are of considerable interest as models for drug penetration and positioning in biological membranes. Here we analyze partitioning of coumarin in dioleoylphosphatidylcholine (DOPC) bilayer, based on both multiple, unbiased 3 μs MD simulations (total length) and free energy profiles along the bilayer normal calculated by biased MD simulations (∼7 μs in total). The convergences in time of free energy profiles calculated by both umbrella sampling and z-constraint techniques are thoroughly analyzed. Two sets of starting structures are also considered, one from unbiased MD simulation and the other from “pulling” coumarin along the bilayer normal. The structures obtained by pulling simulation contain water defects on the lipid bilayer surface, while those acquired from unbiased simulation have no membrane defects. The free energy profiles converge more rapidly when starting frames from unbiased simulations are used. In addition, z-constraint simulation leads to more rapid convergence than umbrella sampling, due to quicker relaxation of membrane defects. Furthermore, we show that the choice of RESP, PRODRG, or Mulliken charges considerably affects the resulting free energy profile of our model drug along the bilayer normal. We recommend using z-constraint biased MD simulations based on starting geometries acquired from unbiased MD simulations for efficient calculation of convergent free energy profiles of druglike molecules along bilayer normals. The calculation of free energy profile should start with an unbiased simulation, though the polar molecules might need a slow pulling afterward. Results obtained with the recommended simulation protocol agree well with available experimental data for two coumarin derivatives. PMID:22545027