Next generation of network medicine: interdisciplinary signaling approaches.

PubMed

Korcsmaros, Tamas; Schneider, Maria Victoria; Superti-Furga, Giulio

2017-02-20

In the last decade, network approaches have transformed our understanding of biological systems. Network analyses and visualizations have allowed us to identify essential molecules and modules in biological systems, and improved our understanding of how changes in cellular processes can lead to complex diseases, such as cancer, infectious and neurodegenerative diseases. "Network medicine" involves unbiased large-scale network-based analyses of diverse data describing interactions between genes, diseases, phenotypes, drug targets, drug transport, drug side-effects, disease trajectories and more. In terms of drug discovery, network medicine exploits our understanding of the network connectivity and signaling system dynamics to help identify optimal, often novel, drug targets. Contrary to initial expectations, however, network approaches have not yet delivered a revolution in molecular medicine. In this review, we propose that a key reason for the limited impact, so far, of network medicine is a lack of quantitative multi-disciplinary studies involving scientists from different backgrounds. To support this argument, we present existing approaches from structural biology, 'omics' technologies (e.g., genomics, proteomics, lipidomics) and computational modeling that point towards how multi-disciplinary efforts allow for important new insights. We also highlight some breakthrough studies as examples of the potential of these approaches, and suggest ways to make greater use of the power of interdisciplinarity. This review reflects discussions held at an interdisciplinary signaling workshop which facilitated knowledge exchange from experts from several different fields, including in silico modelers, computational biologists, biochemists, geneticists, molecular and cell biologists as well as cancer biologists and pharmacologists.

Conditions for duality between fluxes and concentrations in biochemical networks

PubMed Central

Fleming, Ronan M.T.; Vlassis, Nikos; Thiele, Ines; Saunders, Michael A.

2016-01-01

Mathematical and computational modelling of biochemical networks is often done in terms of either the concentrations of molecular species or the fluxes of biochemical reactions. When is mathematical modelling from either perspective equivalent to the other? Mathematical duality translates concepts, theorems or mathematical structures into other concepts, theorems or structures, in a one-to-one manner. We present a novel stoichiometric condition that is necessary and sufficient for duality between unidirectional fluxes and concentrations. Our numerical experiments, with computational models derived from a range of genome-scale biochemical networks, suggest that this flux-concentration duality is a pervasive property of biochemical networks. We also provide a combinatorial characterisation that is sufficient to ensure flux-concentration duality. The condition prescribes that, for every two disjoint sets of molecular species, there is at least one reaction complex that involves species from only one of the two sets. When unidirectional fluxes and molecular species concentrations are dual vectors, this implies that the behaviour of the corresponding biochemical network can be described entirely in terms of either concentrations or unidirectional fluxes. PMID:27345817

Conditions for duality between fluxes and concentrations in biochemical networks

DOE PAGES

Fleming, Ronan M. T.; Vlassis, Nikos; Thiele, Ines; ...

2016-06-23

Mathematical and computational modelling of biochemical networks is often done in terms of either the concentrations of molecular species or the fluxes of biochemical reactions. When is mathematical modelling from either perspective equivalent to the other? Mathematical duality translates concepts, theorems or mathematical structures into other concepts, theorems or structures, in a one-to-one manner. We present a novel stoichiometric condition that is necessary and sufficient for duality between unidirectional fluxes and concentrations. Our numerical experiments, with computational models derived from a range of genome-scale biochemical networks, suggest that this flux-concentration duality is a pervasive property of biochemical networks. We alsomore » provide a combinatorial characterisation that is sufficient to ensure flux-concentration duality.The condition prescribes that, for every two disjoint sets of molecular species, there is at least one reaction complex that involves species from only one of the two sets. When unidirectional fluxes and molecular species concentrations are dual vectors, this implies that the behaviour of the corresponding biochemical network can be described entirely in terms of either concentrations or unidirectional fluxes« less

Conditions for duality between fluxes and concentrations in biochemical networks

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

Fleming, Ronan M. T.; Vlassis, Nikos; Thiele, Ines

Mathematical and computational modelling of biochemical networks is often done in terms of either the concentrations of molecular species or the fluxes of biochemical reactions. When is mathematical modelling from either perspective equivalent to the other? Mathematical duality translates concepts, theorems or mathematical structures into other concepts, theorems or structures, in a one-to-one manner. We present a novel stoichiometric condition that is necessary and sufficient for duality between unidirectional fluxes and concentrations. Our numerical experiments, with computational models derived from a range of genome-scale biochemical networks, suggest that this flux-concentration duality is a pervasive property of biochemical networks. We alsomore » provide a combinatorial characterisation that is sufficient to ensure flux-concentration duality.The condition prescribes that, for every two disjoint sets of molecular species, there is at least one reaction complex that involves species from only one of the two sets. When unidirectional fluxes and molecular species concentrations are dual vectors, this implies that the behaviour of the corresponding biochemical network can be described entirely in terms of either concentrations or unidirectional fluxes« less

Using graph-based assessments within socratic tutorials to reveal and refine students' analytical thinking about molecular networks.

PubMed

Trujillo, Caleb; Cooper, Melanie M; Klymkowsky, Michael W

2012-01-01

Biological systems, from the molecular to the ecological, involve dynamic interaction networks. To examine student thinking about networks we used graphical responses, since they are easier to evaluate for implied, but unarticulated assumptions. Senior college level molecular biology students were presented with simple molecular level scenarios; surprisingly, most students failed to articulate the basic assumptions needed to generate reasonable graphical representations; their graphs often contradicted their explicit assumptions. We then developed a tiered Socratic tutorial based on leading questions designed to provoke metacognitive reflection. The activity is characterized by leading questions (prompts) designed to provoke meta-cognitive reflection. When applied in a group or individual setting, there was clear improvement in targeted areas. Our results highlight the promise of using graphical responses and Socratic prompts in a tutorial context as both a formative assessment for students and an informative feedback system for instructors, in part because graphical responses are relatively easy to evaluate for implied, but unarticulated assumptions. Copyright © 2011 Wiley Periodicals, Inc.

Formation of hydroxyl-functionalized stilbenoid molecular sieves at the liquid/solid interface on top of a 1-decanol monolayer.

PubMed

Bellec, Amandine; Arrigoni, Claire; Douillard, Ludovic; Fiorini-Debuisschert, Céline; Mathevet, Fabrice; Kreher, David; Attias, André-Jean; Charra, Fabrice

2014-10-31

Specific molecular tectons can be designed to form molecular sieves through self-assembly at the solid-liquid interface. After demonstrating a model tecton bearing apolar alkyl chains, we then focus on a modified structure involving asymmetric functionalization of some alkyl chains with polar hydroxyl groups in order to get chemical selectivity in the sieving. As the formation of supramolecular self-assembled networks strongly depends on molecule-molecule, molecule-substrate and molecule-solvent interactions, we compared the tectons' self-assembly on graphite for two types of solvent. We demonstrate the possibility to create hydroxylated stilbenoid molecular sieves by using 1-decanol as a solvent. Interestingly, with this solvent, the porous network is developed on top of a 1-decanol monolayer.

Host-pathogen interaction in Fusarium oxysporum infections: where do we stand?

PubMed

Husaini, Amjad M; Sakina, Aafreen; Cambay, Souliha R

2018-03-16

Fusarium oxysporum, a ubiquitous soil-borne pathogen causes devastating vascular wilt in more than 100 plant species and ranks fifth among top ten fungal plant pathogens. It has emerged as a human pathogen too, causing infections in immune-compromised patients. It is, therefore, important to gain insight into the molecular processes involved in the pathogenesis of this trans-kingdom pathogen. A complex network comprising of interconnected and over lapping signal pathways; mitogen-activated protein kinase (MAPK) signaling pathways, Ras proteins, G-protein signaling components and their downstream pathways, components of the velvet (LaeA/VeA/VelB) complex and cAMP pathways, is involved in perceiving the host. This network regulates the expression of various pathogenicity genes. Plants have however evolved an elaborate protection system to combat this attack. They too possess intricate mechanisms at molecular level, which once triggered by pathogen attack transduce signals to activate defense response. This review focuses on understanding and presenting a wholistic picture of the molecular mechanisms of F. oxysporum-host interactions in plant immunity.

Bioinformatic prediction of leader genes in human periodontitis.

PubMed

Covani, Ugo; Marconcini, Simone; Giacomelli, Luca; Sivozhelevov, Victor; Barone, Antonio; Nicolini, Claudio

2008-10-01

Genes involved in different biologic processes form complex interaction networks. However, only a few have a high number of interactions with the other genes in the network. In previous bioinformatics and experimental studies concerning the T lymphocyte cell cycle, these genes were identified and termed "leader genes." In this work, genes involved in human periodontitis were tentatively identified and ranked according to their number of interactions to obtain a preliminary, broader view of molecular mechanisms of periodontitis and plan targeted experimentation. Genes were identified with interrelated queries of several databases. The interactions among these genes were mapped and given a significance score. The weighted number of links (weighted sum of scores for every interaction in which the given gene is involved) was calculated for each gene. Genes were clustered according to this parameter. The genes in the highest cluster were termed leader genes. Sixty-one genes involved or potentially involved in periodontitis were identified. Only five were identified as leader genes, whereas 12 others were ranked in an immediately lower cluster. For 10 of 17 genes there is evidence of involvement in periodontitis; seven new genes that are potentially involved in this disease were identified. The involvement in periodontitis has been completely established for only two leader genes. We applied a validated bioinformatics algorithm to increase our knowledge of molecular mechanisms of periodontitis. Even with the limitations of this ab initio analysis, this theoretical study can suggest ad hoc experimentation targeted on significant genes and, therefore, simpler than mass-scale molecular genomics. Moreover, the identification of leader genes might suggest new potential risk factors and therapeutic targets.

Flipping the NF-κB Switch in Macrophages | Center for Cancer Research

Cancer.gov

A critical component of the innate immune system, macrophages respond to diverse microbes by recognizing certain molecular patterns, such as the Gram-negative bacteria product lipopolysaccharide (LPS), via Toll-like receptors. Receptor activation stimulates a complex signaling network that involves, among others, the NF-κB pathway. The complexity of this network has hampered

Diverse types of genetic variation converge on functional gene networks involved in schizophrenia.

PubMed

Gilman, Sarah R; Chang, Jonathan; Xu, Bin; Bawa, Tejdeep S; Gogos, Joseph A; Karayiorgou, Maria; Vitkup, Dennis

2012-12-01

Despite the successful identification of several relevant genomic loci, the underlying molecular mechanisms of schizophrenia remain largely unclear. We developed a computational approach (NETBAG+) that allows an integrated analysis of diverse disease-related genetic data using a unified statistical framework. The application of this approach to schizophrenia-associated genetic variations, obtained using unbiased whole-genome methods, allowed us to identify several cohesive gene networks related to axon guidance, neuronal cell mobility, synaptic function and chromosomal remodeling. The genes forming the networks are highly expressed in the brain, with higher brain expression during prenatal development. The identified networks are functionally related to genes previously implicated in schizophrenia, autism and intellectual disability. A comparative analysis of copy number variants associated with autism and schizophrenia suggests that although the molecular networks implicated in these distinct disorders may be related, the mutations associated with each disease are likely to lead, at least on average, to different functional consequences.

Tumor Necrosis Factor-α Regulates Distinct Molecular Pathways and Gene Networks in Cultured Skeletal Muscle Cells

PubMed Central

Gupta, Sanjay K.; Dahiya, Saurabh; Lundy, Robert F.; Kumar, Ashok

2010-01-01

Background Skeletal muscle wasting is a debilitating consequence of large number of disease states and conditions. Tumor necrosis factor-α (TNF-α) is one of the most important muscle-wasting cytokine, elevated levels of which cause significant muscular abnormalities. However, the underpinning molecular mechanisms by which TNF-α causes skeletal muscle wasting are less well-understood. Methodology/Principal Findings We have used microarray, quantitative real-time PCR (QRT-PCR), Western blot, and bioinformatics tools to study the effects of TNF-α on various molecular pathways and gene networks in C2C12 cells (a mouse myoblastic cell line). Microarray analyses of C2C12 myotubes treated with TNF-α (10 ng/ml) for 18h showed differential expression of a number of genes involved in distinct molecular pathways. The genes involved in nuclear factor-kappa B (NF-kappaB) signaling, 26s proteasome pathway, Notch1 signaling, and chemokine networks are the most important ones affected by TNF-α. The expression of some of the genes in microarray dataset showed good correlation in independent QRT-PCR and Western blot assays. Analysis of TNF-treated myotubes showed that TNF-α augments the activity of both canonical and alternative NF-κB signaling pathways in myotubes. Bioinformatics analyses of microarray dataset revealed that TNF-α affects the activity of several important pathways including those involved in oxidative stress, hepatic fibrosis, mitochondrial dysfunction, cholesterol biosynthesis, and TGF-β signaling. Furthermore, TNF-α was found to affect the gene networks related to drug metabolism, cell cycle, cancer, neurological disease, organismal injury, and abnormalities in myotubes. Conclusions TNF-α regulates the expression of multiple genes involved in various toxic pathways which may be responsible for TNF-induced muscle loss in catabolic conditions. Our study suggests that TNF-α activates both canonical and alternative NF-κB signaling pathways in a time-dependent manner in skeletal muscle cells. The study provides novel insight into the mechanisms of action of TNF-α in skeletal muscle cells. PMID:20967264

Forensic interpretation of molecular variation on networks of disease transmission and genetic inheritance.

PubMed

Velsko, Stephan P; Osburn, Joanne; Allen, Jonathan

2014-11-01

This paper describes the inference-on-networks (ION) framework for forensic interpretat ION of molecular typing data in cases involving allegations of infectious microbial transmission, association of disease outbreaks with alleged sources, and identifying familial relationships using mitochondrial or Y chromosomal DNA. The framework is applicable to molecular typing data obtained using any technique, including those based on electrophoretic separations. A key insight is that the networks associated with disease transmission or DNA inheritance can be used to define specific testable relationships and avoid the ambiguity and subjectivity associated with the criteria used for inferring genetic relatedness now in use. We discuss specific applications of the framework to the 2003 severe acute respiratory syndrome (SARS) outbreak in Singapore and the 2001 foot-and-mouth disease virus (FMDV) outbreak in Great Britain. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Identification of Neurodegenerative Factors Using Translatome-Regulatory Network Analysis

PubMed Central

Brichta, Lars; Shin, William; Jackson-Lewis, Vernice; Blesa, Javier; Yap, Ee-Lynn; Walker, Zachary; Zhang, Jack; Roussarie, Jean-Pierre; Alvarez, Mariano J.; Califano, Andrea; Przedborski, Serge; Greengard, Paul

2016-01-01

For degenerative disorders of the central nervous system, the major obstacle to therapeutic advancement has been the challenge of identifying the key molecular mechanisms underlying neuronal loss. We developed a combinatorial approach including translational profiling and brain regulatory network analysis to search for key determinants of neuronal survival or death. Following the generation of transgenic mice for cell type-specific profiling of midbrain dopaminergic neurons, we established and compared translatome libraries reflecting the molecular signature of these cells at baseline or under degenerative stress. Analysis of these libraries by interrogating a context-specific brain regulatory network led to the identification of a repertoire of intrinsic upstream regulators that drive the dopaminergic stress response. The altered activity of these regulators was not associated with changes in their expression levels. This strategy can be generalized for the elucidation of novel molecular determinants involved in the degeneration of other classes of neurons. PMID:26214373

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

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

Weighill, Deborah; Jones, Piet; Shah, Manesh

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

DOE PAGES

Weighill, Deborah; Jones, Piet; Shah, Manesh; ...

2018-05-11

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.

PubMed

Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo

2015-07-01

In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.

A Look Inside HIV Resistance through Retroviral Protease Interaction Maps

PubMed Central

Kontijevskis, Aleksejs; Prusis, Peteris; Petrovska, Ramona; Yahorava, Sviatlana; Mutulis, Felikss; Mutule, Ilze; Komorowski, Jan; Wikberg, Jarl E. S

2007-01-01

Retroviruses affect a large number of species, from fish and birds to mammals and humans, with global socioeconomic negative impacts. Here the authors report and experimentally validate a novel approach for the analysis of the molecular networks that are involved in the recognition of substrates by retroviral proteases. Using multivariate analysis of the sequence-based physiochemical descriptions of 61 retroviral proteases comprising wild-type proteases, natural mutants, and drug-resistant forms of proteases from nine different viral species in relation to their ability to cleave 299 substrates, the authors mapped the physicochemical properties and cross-dependencies of the amino acids of the proteases and their substrates, which revealed a complex molecular interaction network of substrate recognition and cleavage. The approach allowed a detailed analysis of the molecular–chemical mechanisms involved in substrate cleavage by retroviral proteases. PMID:17352531

Molecular and Genetic Inflammation Networks in Major Human Diseases

PubMed Central

Zhao, Yongzhong; Forst, Christian V.; Sayegh, Camil E.; Wang, I-Ming; Yang, Xia; Zhang, Bin

2016-01-01

It has been well-recognized that inflammation alongside tissue repair and damage maintaining tissue homeostasis determines the initiation and progression of complex diseases. Albeit with the accomplishment of having captured most critical inflammation involved molecules, genetic susceptibilities, epigenetic factors, and environmental exposures, our schemata on role of inflammation in complex disease, remain largely patchy, in part due to the success of reductionism in terms of research methodology per se. Omics data alongside the advances in data integration technologies have enabled reconstruction of molecular and genetic inflammation networks which shed light on the underlying pathophysiology of complex diseases or clinical conditions. Given the proven beneficial role of anti-inflammation in coronary heart disease as well as other complex diseases and immunotherapy as a revolutionary transition in oncology, it becomes timely to review our current understanding of the inflammation molecular and genetic networks underlying major human diseases. In this Review, we first briefly discuss the complexity of infectious diseases and then highlight recently uncovered molecular and genetic inflammation networks in other major human diseases including obesity, type II diabetes, coronary heart disease, late onset Alzheimer Disease, Parkinson disease, and sporadic cancer. The commonality and specificity of these molecular networks are addressed in the context of genetics based on genome-wide association study (GWAS). The double-sword role of inflammation, such as how the aberrant type 1 and/or type 2immunity leads to chronic and severe clinical conditions, remains open in terms of the inflammasome and the core inflammatome network features. Increasingly available large Omics and clinical data in tandem with systems biology approaches have offered an exciting yet challenging opportunity toward reconstruction of more comprehensive and dynamic molecular and genetic inflammation networks, which hold a great promise in transiting network snapshots to video-style multi-scale interplays of disease mechanisms, in turn leading to effective clinical intervening. PMID:27303926

A Computational Network Biology Approach to Uncover Novel Genes Related to Alzheimer's Disease.

PubMed

Zanzoni, Andreas

2016-01-01

Recent advances in the fields of genetics and genomics have enabled the identification of numerous Alzheimer's disease (AD) candidate genes, although for many of them the role in AD pathophysiology has not been uncovered yet. Concomitantly, network biology studies have shown a strong link between protein network connectivity and disease. In this chapter I describe a computational approach that, by combining local and global network analysis strategies, allows the formulation of novel hypotheses on the molecular mechanisms involved in AD and prioritizes candidate genes for further functional studies.

Loss surface of XOR artificial neural networks

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; Zhao, Xiaojun; Bernal, Edgar A.; Wales, David J.

2018-05-01

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters. We explore these landscapes using optimization tools developed for potential energy landscapes in molecular science. The number of local minima and transition states (saddle points of index one), as well as the ratio of transition states to minima, grow rapidly with the number of nodes in the network. There is also a strong dependence on the regularization parameter, with the landscape becoming more convex (fewer minima) as the regularization term increases. We demonstrate that in our formulation, stationary points for networks with Nh hidden nodes, including the minimal network required to fit the XOR data, are also stationary points for networks with Nh+1 hidden nodes when all the weights involving the additional node are zero. Hence, smaller networks trained on XOR data are embedded in the landscapes of larger networks. Our results clarify certain aspects of the classification and sensitivity (to perturbations in the input data) of minima and saddle points for this system, and may provide insight into dropout and network compression.

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

PubMed Central

Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar

2012-01-01

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187

Mapping Cellular Polarity Networks Using Mass Spectrometry-based Strategies.

PubMed

Daulat, Avais M; Puvirajesinghe, Tania M; Camoin, Luc; Borg, Jean-Paul

2018-05-18

Cell polarity is a vital biological process involved in the building, maintenance and normal functioning of tissues in invertebrates and vertebrates. Unsurprisingly, molecular defects affecting polarity organization and functions have a strong impact on tissue homeostasis, embryonic development and adult life, and may directly or indirectly lead to diseases. Genetic studies have demonstrated the causative effect of several polarity genes in diseases; however, much remains to be clarified before a comprehensive view of the molecular organization and regulation of the protein networks associated with polarity proteins is obtained. This challenge can be approached head-on using proteomics to identify protein complexes involved in cell polarity and their modifications in a spatio-temporal manner. We review the fundamental basics of mass spectrometry techniques and provide an in-depth analysis of how mass spectrometry has been instrumental in understanding the complex and dynamic nature of some cell polarity networks at the tissue (apico-basal and planar cell polarities) and cellular (cell migration, ciliogenesis) levels, with the fine dissection of the interconnections between prototypic cell polarity proteins and signal transduction cascades in normal and pathological situations. This review primarily focuses on epithelial structures which are the fundamental building blocks for most metazoan tissues, used as the archetypal model to study cellular polarity. This field offers broad perspectives thanks to the ever-increasing sensitivity of mass spectrometry and its use in combination with recently developed molecular strategies able to probe in situ proteomic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mutation-induced protein interaction kinetics changes affect apoptotic network dynamic properties and facilitate oncogenesis

PubMed Central

Zhao, Linjie; Sun, Tanlin; Pei, Jianfeng; Ouyang, Qi

2015-01-01

It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation. PMID:26170328

How does the molecular network structure influence PDMS elastomer wettability?

NASA Astrophysics Data System (ADS)

Melillo, Matthew; Genzer, Jan

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from medical devices to absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into PDMS networks is of critical importance for the design and use of another application - microfluidic devices. We have systematically studied the effects of polymer molecular weight, loading of tetra-functional crosslinker, end-group chemical functionality, and the extent of dilution of the curing mixture on the mechanical and surface properties of end-linked PDMS networks. The gel and sol fractions, storage and loss moduli, liquid swelling ratios, and water contact angles have all been shown to vary greatly based on the aforementioned variables. Similar trends were observed for the commercial PDMS material, Sylgard-184. Our results have confirmed theories predicting the relationships between modulus and swelling. Furthermore, we have provided new evidence for the strong influence that substrate modulus and molecular network structure have on the wettability of PDMS elastomers. These findings will aid in the design and implementation of efficient microfluidics and other PDMS-based materials that involve the transport of liquids.

Evaluation of hydrogen bond networks in cellulose Iβ and II crystals using density functional theory and Car-Parrinello molecular dynamics.

PubMed

Hayakawa, Daichi; Nishiyama, Yoshiharu; Mazeau, Karim; Ueda, Kazuyoshi

2017-09-08

Crystal models of cellulose Iβ and II, which contain various hydrogen bonding (HB) networks, were analyzed using density functional theory and Car-Parrinello molecular dynamics (CPMD) simulations. From the CPMD trajectories, the power spectra of the velocity correlation functions of hydroxyl groups involved in hydrogen bonds were calculated. For the Iβ allomorph, HB network A, which is dominant according to the neutron diffraction data, was stable, and the power spectrum represented the essential features of the experimental IR spectra. In contrast, network B, which is a minor structure, was unstable because its hydroxymethyl groups reoriented during the CPMD simulation, yielding a different crystal structure to that determined by experiments. For the II allomorph, a HB network A is proposed based on diffraction data, whereas molecular modeling identifies an alternative network B. Our simulations showed that the interaction energies of the cellulose II (B) model are slightly more favorable than model II(A). However, the evaluation of the free energy should be waited for the accurate determination from the energy point of view. For the IR calculation, cellulose II (B) model reproduces the spectra better than model II (A). Copyright © 2017 Elsevier Ltd. All rights reserved.

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

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

2013-01-01

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

[Prediction of the molecular response to pertubations from single cell measurements].

PubMed

Remacle, Françoise; Levine, Raphael D

2014-12-01

The response of protein signalization networks to perturbations is analysed from single cell measurements. This experimental approach allows characterizing the fluctuations in protein expression levels from cell to cell. The analysis is based on an information theoretic approach grounded in thermodynamics leading to a quantitative version of Le Chatelier principle which allows to predict the molecular response. Two systems are investigated: human macrophages subjected to lipopolysaccharide challenge, analogous to the immune response against Gram-negative bacteria and the response of the proteins involved in the mTOR signalizing network of GBM cancer cells to changes in partial oxygen pressure. © 2014 médecine/sciences – Inserm.

Bioinformatics and expressional analysis of cDNA clones from floral buds

NASA Astrophysics Data System (ADS)

Pawełkowicz, Magdalena Ewa; Skarzyńska, Agnieszka; Cebula, Justyna; Hincha, Dirck; ZiÄ bska, Karolina; PlÄ der, Wojciech; Przybecki, Zbigniew

2017-08-01

The application of genomic approaches may serve as an initial step in understanding the complexity of biochemical network and cellular processes responsible for regulation and execution of many developmental tasks. The molecular mechanism of sex expression in cucumber is still not elucidated. A study of differential expression was conducted to identify genes involved in sex determination and floral organ morphogenesis. Herein, we present generation of expression sequence tags (EST) obtained by differential hybridization (DH) and subtraction technique (cDNA-DSC) and their characteristic features such as molecular function, involvement in biology processes, expression and mapping position on the genome.

Biological network extraction from scientific literature: state of the art and challenges.

PubMed

Li, Chen; Liakata, Maria; Rebholz-Schuhmann, Dietrich

2014-09-01

Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical entities. It is necessary to be able to combine data from all available resources to judge the functionality, complexity and completeness of any given network overall, but especially the full integration of relevant information from the scientific literature is still an ongoing and complex task. Currently, the text-mining research community is steadily moving towards processing the full body of the scientific literature by making use of rich linguistic features such as full text parsing, to extract biological interactions. The next step will be to combine these with information from scientific databases to support hypothesis generation for the discovery of new knowledge and the extension of biological networks. The generation of comprehensive networks requires technologies such as entity grounding, coordination resolution and co-reference resolution, which are not fully solved and are required to further improve the quality of results. Here, we analyse the state of the art for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora, discuss challenges involved and identify directions for future research. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

PubMed

Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

2013-12-01

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

Combined analysis of mRNA and miRNA identifies dehydration and salinity responsive key molecular players in citrus roots.

PubMed

Xie, Rangjin; Zhang, Jin; Ma, Yanyan; Pan, Xiaoting; Dong, Cuicui; Pang, Shaoping; He, Shaolan; Deng, Lie; Yi, Shilai; Zheng, Yongqiang; Lv, Qiang

2017-02-06

Citrus is one of the most economically important fruit crops around world. Drought and salinity stresses adversely affected its productivity and fruit quality. However, the genetic regulatory networks and signaling pathways involved in drought and salinity remain to be elucidated. With RNA-seq and sRNA-seq, an integrative analysis of miRNA and mRNA expression profiling and their regulatory networks were conducted using citrus roots subjected to dehydration and salt treatment. Differentially expressed (DE) mRNA and miRNA profiles were obtained according to fold change analysis and the relationships between miRNAs and target mRNAs were found to be coherent and incoherent in the regulatory networks. GO enrichment analysis revealed that some crucial biological processes related to signal transduction (e.g. 'MAPK cascade'), hormone-mediated signaling pathways (e.g. abscisic acid- activated signaling pathway'), reactive oxygen species (ROS) metabolic process (e.g. 'hydrogen peroxide catabolic process') and transcription factors (e.g., 'MYB, ZFP and bZIP') were involved in dehydration and/or salt treatment. The molecular players in response to dehydration and salt treatment were partially overlapping. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-seq and sRNA-seq analysis. This study provides new insights into the molecular mechanisms how citrus roots respond to dehydration and salt treatment.

Combined analysis of mRNA and miRNA identifies dehydration and salinity responsive key molecular players in citrus roots

PubMed Central

Xie, Rangjin; Zhang, Jin; Ma, Yanyan; Pan, Xiaoting; Dong, Cuicui; Pang, Shaoping; He, Shaolan; Deng, Lie; Yi, Shilai; Zheng, Yongqiang; Lv, Qiang

2017-01-01

Citrus is one of the most economically important fruit crops around world. Drought and salinity stresses adversely affected its productivity and fruit quality. However, the genetic regulatory networks and signaling pathways involved in drought and salinity remain to be elucidated. With RNA-seq and sRNA-seq, an integrative analysis of miRNA and mRNA expression profiling and their regulatory networks were conducted using citrus roots subjected to dehydration and salt treatment. Differentially expressed (DE) mRNA and miRNA profiles were obtained according to fold change analysis and the relationships between miRNAs and target mRNAs were found to be coherent and incoherent in the regulatory networks. GO enrichment analysis revealed that some crucial biological processes related to signal transduction (e.g. ‘MAPK cascade’), hormone-mediated signaling pathways (e.g. abscisic acid- activated signaling pathway’), reactive oxygen species (ROS) metabolic process (e.g. ‘hydrogen peroxide catabolic process’) and transcription factors (e.g., ‘MYB, ZFP and bZIP’) were involved in dehydration and/or salt treatment. The molecular players in response to dehydration and salt treatment were partially overlapping. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-seq and sRNA-seq analysis. This study provides new insights into the molecular mechanisms how citrus roots respond to dehydration and salt treatment. PMID:28165059

Transcription Profiles Reveal Sugar and Hormone Signaling Pathways Mediating Flower Induction in Apple (Malus domestica Borkh.).

PubMed

Xing, Li-Bo; Zhang, Dong; Li, You-Mei; Shen, Ya-Wen; Zhao, Cai-Ping; Ma, Juan-Juan; An, Na; Han, Ming-Yu

2015-10-01

Flower induction in apple (Malus domestica Borkh.) is regulated by complex gene networks that involve multiple signal pathways to ensure flower bud formation in the next year, but the molecular determinants of apple flower induction are still unknown. In this research, transcriptomic profiles from differentiating buds allowed us to identify genes potentially involved in signaling pathways that mediate the regulatory mechanisms of flower induction. A hypothetical model for this regulatory mechanism was obtained by analysis of the available transcriptomic data, suggesting that sugar-, hormone- and flowering-related genes, as well as those involved in cell-cycle induction, participated in the apple flower induction process. Sugar levels and metabolism-related gene expression profiles revealed that sucrose is the initiation signal in flower induction. Complex hormone regulatory networks involved in cytokinin (CK), abscisic acid (ABA) and gibberellic acid pathways also induce apple flower formation. CK plays a key role in the regulation of cell formation and differentiation, and in affecting flowering-related gene expression levels during these processes. Meanwhile, ABA levels and ABA-related gene expression levels gradually increased, as did those of sugar metabolism-related genes, in developing buds, indicating that ABA signals regulate apple flower induction by participating in the sugar-mediated flowering pathway. Furthermore, changes in sugar and starch deposition levels in buds can be affected by ABA content and the expression of the genes involved in the ABA signaling pathway. Thus, multiple pathways, which are mainly mediated by crosstalk between sugar and hormone signals, regulate the molecular network involved in bud growth and flower induction in apple trees. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

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

PubMed

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

2015-02-01

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

A simultaneous multi-slice selective J-resolved experiment for fully resolved scalar coupling information

NASA Astrophysics Data System (ADS)

Zeng, Qing; Lin, Liangjie; Chen, Jinyong; Lin, Yanqin; Barker, Peter B.; Chen, Zhong

2017-09-01

Proton-proton scalar coupling plays an important role in molecular structure elucidation. Many methods have been proposed for revealing scalar coupling networks involving chosen protons. However, determining all JHH values within a fully coupled network remains as a tedious process. Here, we propose a method termed as simultaneous multi-slice selective J-resolved spectroscopy (SMS-SEJRES) for simultaneously measuring JHH values out of all coupling networks in a sample within one experiment. In this work, gradient-encoded selective refocusing, PSYCHE decoupling and echo planar spectroscopic imaging (EPSI) detection module are adopted, resulting in different selective J-edited spectra extracted from different spatial positions. The proposed pulse sequence can facilitate the analysis of molecular structures. Therefore, it will interest scientists who would like to efficiently address the structural analysis of molecules.

Communication: Fitting potential energy surfaces with fundamental invariant neural network

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

Shao, Kejie; Chen, Jun; Zhao, Zhiqiang

A more flexible neural network (NN) method using the fundamental invariants (FIs) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. Mathematically, FIs finitely generate the permutation invariant polynomial (PIP) ring. In combination with NN, fundamental invariant neural network (FI-NN) can approximate any function to arbitrary accuracy. Because FI-NN minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. In this work, we provide the FIs for all possible molecular systems up to five atoms. Potential energymore » surfaces for OH{sub 3} and CH{sub 4} were constructed with FI-NN, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations.« less

Spectroscopic study of uracil, 1-methyluracil and 1-methyl-4-thiouracil: Hydrogen bond interactions in crystals and ab-initio molecular dynamics

NASA Astrophysics Data System (ADS)

Brela, Mateusz Z.; Boczar, Marek; Malec, Leszek M.; Wójcik, Marek J.; Nakajima, Takahito

2018-05-01

Hydrogen bond networks in uracil, 1-methyluracil and 1-methyl-4-thiouracil were studied by ab initio molecular dynamics as well as analysis of the orbital interactions. The power spectra calculated by ab initio molecular dynamics for atoms involved in hydrogen bonds were analyzed. We calculated spectra by using anharmonic approximation based on the autocorrelation function of the atom positions obtained from the Born-Oppenheimer simulations. Our results show the differences between hydrogen bond networks in uracil and its methylated derivatives. The studied methylated derivatives, 1-methyluracil as well as 1-methyl-4-thiouracil, form dimeric structures in the crystal phase, while uracil does not form that kind of structures. The presence of sulfur atom instead oxygen atom reflects weakness of the hydrogen bonds that build dimers.

[Motivation and Emotional States: Structural Systemic, Neurochemical, Molecular and Cellular Mechanisms].

PubMed

Bazyan, A S

2016-01-01

The structural, systemic, neurochemical, molecular and cellular mechanisms of organization and coding motivation and emotional states are describe. The GABA and glutamatergic synaptic systems of basal ganglia form a neural network and participate in the implementation of voluntary behavior. Neuropeptides, neurohormones and paracrine neuromodulators involved in the organization of motivation and emotional states, integrated with synaptic systems, controlled by neural networks and organizing goal-directed behavior. Structural centers for united and integrated of information in voluntary and goal-directed behavior are globus pallidus. Substantia nigra pars reticulata switches the information from corticobasal networks to thalamocortical networks, induces global dopaminergic (DA) signal and organize interaction of mesolimbic and nigostriatnoy DA systems controlled by prefrontal and motor cortex. Together with the motor cortex, substantia nigra displays information in the brainstem and spinal cord to implementation of behavior. Motivation states are formed in the interaction of neurohormonal and neuropeptide systems by monoaminergic systems of brain. Emotional states are formed by monoaminergic systems of the mid-brain, where the leading role belongs to the mesolimbic DA system. The emotional and motivation state of the encoded specific epigenetic molecular and chemical pattern of neuron.

Suppressed Expression of T-Box Transcription Factors is Involved in Senescence in Chronic Obstructive Pulmonary Disease

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

Acquaah-Mensah, George; Malhotra, Deepti; Vulimiri, Madhulika

2012-06-19

Chronic obstructive pulmonary disease (COPD) is a major global health problem. The etiology of COPD has been associated with apoptosis, oxidative stress, and inflammation. However, understanding of the molecular interactions that modulate COPD pathogenesis remains only partly resolved. We conducted an exploratory study on COPD etiology to identify the key molecular participants. We used information-theoretic algorithms including Context Likelihood of Relatedness (CLR), Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE), and Inferelator. We captured direct functional associations among genes, given a compendium of gene expression profiles of human lung epithelial cells. A set of genes differentially expressed in COPD,more » as reported in a previous study were superposed with the resulting transcriptional regulatory networks. After factoring in the properties of the networks, an established COPD susceptibility locus and domain-domain interactions involving protein products of genes in the generated networks, several molecular candidates were predicted to be involved in the etiology of COPD. These include COL4A3, CFLAR, GULP1, PDCD1, CASP10, PAX3, BOK, HSPD1, PITX2, and PML. Furthermore, T-box (TBX) genes and cyclin-dependent kinase inhibitor 2A (CDKN2A), which are in a direct transcriptional regulatory relationship, emerged as preeminent participants in the etiology of COPD by means of senescence. Contrary to observations in neoplasms, our study reveals that the expression of genes and proteins in the lung samples from patients with COPD indicate an increased tendency towards cellular senescence. The expression of the anti-senescence mediators TBX transcription factors, chromatin modifiers histone deacetylases, and sirtuins was suppressed; while the expression of TBX-regulated cellular senescence markers such as CDKN2A, CDKN1A, and CAV1 was elevated in the peripheral lung tissue samples from patients with COPD. The critical balance between senescence and anti-senescence factors is disrupted towards senescence in COPD lungs.« less

Neural Plasticity and Memory: Is Memory Encoded in Hydrogen Bonding Patterns?

PubMed

Amtul, Zareen; Rahman, Atta-Ur

2016-02-01

Current models of memory storage recognize posttranslational modification vital for short-term and mRNA translation for long-lasting information storage. However, at the molecular level things are quite vague. A comprehensive review of the molecular basis of short and long-lasting synaptic plasticity literature leads us to propose that the hydrogen bonding pattern at the molecular level may be a permissive, vital step of memory storage. Therefore, we propose that the pattern of hydrogen bonding network of biomolecules (glycoproteins and/or DNA template, for instance) at the synapse is the critical edifying mechanism essential for short- and long-term memories. A novel aspect of this model is that nonrandom impulsive (or unplanned) synaptic activity functions as a synchronized positive-feedback rehearsal mechanism by revising the configurations of the hydrogen bonding network by tweaking the earlier tailored hydrogen bonds. This process may also maintain the elasticity of the related synapses involved in memory storage, a characteristic needed for such networks to alter intricacy and revise endlessly. The primary purpose of this review is to stimulate the efforts to elaborate the mechanism of neuronal connectivity both at molecular and chemical levels. © The Author(s) 2014.

Flipping the NF-κB Switch in Macrophages | Center for Cancer Research

Cancer.gov

A critical component of the innate immune system, macrophages respond to diverse microbes by recognizing certain molecular patterns, such as the Gram-negative bacteria product lipopolysaccharide (LPS), via Toll-like receptors. Receptor activation stimulates a complex signaling network that involves, among others, the NF-κB pathway. The complexity of this network has hampered researchers’ understanding of how macrophages resolve conflicting signals to determine when to mount an immune response.

A Computational and Theoretical Study of Conductance in Hydrogen-bonded Molecular Junctions

NASA Astrophysics Data System (ADS)

Wimmer, Michael

This thesis is devoted to the theoretical and computational study of electron transport in molecular junctions where one or more hydrogen bonds are involved in the process. While electron transport through covalent bonds has been extensively studied, in recent work the focus has been shifted towards hydrogen-bonded systems due to their ubiquitous presence in biological systems and their potential in forming nano-junctions between molecular electronic devices and biological systems. This analysis allows us to significantly expand our comprehension of the experimentally observed result that the inclusion of hydrogen bonding in a molecular junction significantly impacts its transport properties, a fact that has important implications for our understanding of transport through DNA, and nano-biological interfaces in general. In part of this work I have explored the implications of quasiresonant transport in short chains of weakly-bonded molecular junctions involving hydrogen bonds. I used theoretical and computational analysis to interpret recent experiments and explain the role of Fano resonances in the transmission properties of the junction. In a different direction, I have undertaken the study of the transversal conduction through nucleotide chains that involve a variable number of different hydrogen bonds, e.g. NH˙˙˙O, OH˙˙˙O, and NH˙˙˙N, which are the three most prevalent hydrogen bonds in biological systems and organic electronics. My effort here has focused on the analysis of electronic descriptors that allow a simplified conceptual and computational understanding of transport properties. Specifically, I have expanded our previous work where the molecular polarizability was used as a conductance descriptor to include the possibility of atomic and bond partitions of the molecular polarizability. This is important because it affords an alternative molecular description of conductance that is not based on the conventional view of molecular orbitals as transport channels. My findings suggest that the hydrogen-bond networks are crucial in understanding the conductance of these junctions. A broader impact of this work pertains the fact that characterizing transport through hydrogen bonding networks may help in developing faster and cost-effective approaches to personalized medicine, to advance DNA sequencing and implantable electronics, and to progress in the design and application of new drugs.

Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins.

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2015-01-01

Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations across diverse chaperone functions. This study reconciles a wide spectrum of structural and functional experiments by demonstrating how integration of molecular simulations and network-centric modeling may explain thermodynamic and mechanistic aspects of allosteric regulation in chaperones.

Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins

PubMed Central

Stetz, Gabrielle; Verkhivker, Gennady M.

2015-01-01

Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations across diverse chaperone functions. This study reconciles a wide spectrum of structural and functional experiments by demonstrating how integration of molecular simulations and network-centric modeling may explain thermodynamic and mechanistic aspects of allosteric regulation in chaperones. PMID:26619280

Molecular networks discriminating mouse bladder responses to intravesical bacillus Calmette-Guerin (BCG), LPS, and TNF-α

PubMed Central

Saban, Marcia R; O'Donnell, Michael A; Hurst, Robert E; Wu, Xue-Ru; Simpson, Cindy; Dozmorov, Igor; Davis, Carole; Saban, Ricardo

2008-01-01

Background Despite being a mainstay for treating superficial bladder carcinoma and a promising agent for interstitial cystitis, the precise mechanism of Bacillus Calmette-Guerin (BCG) remains poorly understood. It is particularly unclear whether BCG is capable of altering gene expression in the bladder target organ beyond its well-recognized pro-inflammatory effects and how this relates to its therapeutic efficacy. The objective of this study was to determine differentially expressed genes in the mouse bladder following chronic intravesical BCG therapy and to compare the results to non-specific pro inflammatory stimuli (LPS and TNF-α). For this purpose, C57BL/6 female mice received four weekly instillations of BCG, LPS, or TNF-α. Seven days after the last instillation, the urothelium along with the submucosa was removed from detrusor muscle and the RNA was extracted from both layers for cDNA array experiments. Microarray results were normalized by a robust regression analysis and only genes with an expression above a conditional threshold of 0.001 (3SD above background) were selected for analysis. Next, genes presenting a 3-fold ratio in regard to the control group were entered in Ingenuity Pathway Analysis (IPA) for a comparative analysis in order to determine genes specifically regulated by BCG, TNF-α, and LPS. In addition, the transcriptome was precipitated with an antibody against RNA polymerase II and real-time polymerase chain reaction assay (Q-PCR) was used to confirm some of the BCG-specific transcripts. Results Molecular networks of treatment-specific genes generated several hypotheses regarding the mode of action of BCG. BCG-specific genes involved small GTPases and BCG-specific networks overlapped with the following canonical signaling pathways: axonal guidance, B cell receptor, aryl hydrocarbon receptor, IL-6, PPAR, Wnt/β-catenin, and cAMP. In addition, a specific detrusor network expressed a high degree of overlap with the development of the lymphatic system. Interestingly, TNF-α-specific networks overlapped with the following canonical signaling pathways: PPAR, death receptor, and apoptosis. Finally, LPS-specific networks overlapped with the LPS/IL-1 mediated inhibition of RXR. Because NF-kappaB occupied a central position in several networks, we further determined whether this transcription factor was part of the responses to BCG. Electrophoretic mobility shift assays confirmed the participation of NF-kappaB in the mouse bladder responses to BCG. In addition, BCG treatment of a human urothelial cancer cell line (J82) also increased the binding activity of NF-kappaB, as determined by precipitation of the chromatin by a NF-kappaB-p65 antibody and Q-PCR of genes bearing a NF-kappaB consensus sequence. Next, we tested the hypothesis of whether small GTPases such as LRG-47 are involved in the uptake of BCG by the bladder urothelium. Conclusion As expected, BCG treatment induces the transcription of genes belonging to common pro-inflammatory networks. However, BCG also induces unique genes belonging to molecular networks involved in axonal guidance and lymphatic system development within the bladder target organ. In addition, NF-kappaB seems to play a predominant role in the bladder responses to BCG therapy. Finally, in intact urothelium, BCG-GFP internalizes in LRG-47-positive vesicles. These results provide a molecular framework for the further study of the involvement of immune and nervous systems in the bladder responses to BCG therapy. PMID:18267009

INVOLVEMENT OF MULTIPLE MOLECULAR PATHWAYS IN THE GENETICS OF OCULAR REFRACTION AND MYOPIA.

PubMed

Wojciechowski, Robert; Cheng, Ching-Yu

2018-01-01

The prevalence of myopia has increased dramatically worldwide within the last three decades. Recent studies have shown that refractive development is influenced by environmental, behavioral, and inherited factors. This review aims to analyze recent progress in the genetics of refractive error and myopia. A comprehensive literature search of PubMed and OMIM was conducted to identify relevant articles in the genetics of refractive error. Genome-wide association and sequencing studies have increased our understanding of the genetics involved in refractive error. These studies have identified interesting candidate genes. All genetic loci discovered to date indicate that refractive development is a heterogeneous process mediated by a number of overlapping biological processes. The exact mechanisms by which these biological networks regulate eye growth are poorly understood. Although several individual genes and/or molecular pathways have been investigated in animal models, a systematic network-based approach in modeling human refractive development is necessary to understand the complex interplay between genes and environment in refractive error. New biomedical technologies and better-designed studies will continue to refine our understanding of the genetics and molecular pathways of refractive error, and may lead to preventative and therapeutic measures to combat the myopia epidemic.

PDF Signaling Is an Integral Part of the Drosophila Circadian Molecular Oscillator.

PubMed

Mezan, Shaul; Feuz, Jean Daniel; Deplancke, Bart; Kadener, Sebastian

2016-10-11

Circadian clocks generate 24-hr rhythms in physiology and behavior. Despite numerous studies, it is still uncertain how circadian rhythms emerge from their molecular and neural constituents. Here, we demonstrate a tight connection between the molecular and neuronal circadian networks. Using fluorescent transcriptional reporters in a Drosophila ex vivo brain culture system, we identified a reciprocal negative regulation between the master circadian regulator CLK and expression of pdf, the main circadian neuropeptide. We show that PDF feedback is required for maintaining normal oscillation pattern in CLK-driven transcription. Interestingly, we found that CLK and neuronal firing suppresses pdf transcription, likely through a common pathway involving the transcription factors DHR38 and SR, establishing a direct link between electric activity and the circadian system. In sum, our work provides evidence for the existence of an uncharacterized CLK-PDF feedback loop that tightly wraps together the molecular oscillator with the circadian neuronal network in Drosophila. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Penalized differential pathway analysis of integrative oncogenomics studies.

PubMed

van Wieringen, Wessel N; van de Wiel, Mark A

2014-04-01

Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (L1) penalty to obtain a sparse pathway topology. Simulations show that the inclusion of DNA copy number data benefits the discovery of gene-gene interactions. In addition, the simulations reveal that cis-effects tend to be over-estimated in a univariate (single gene) analysis. In the application to real data from integrative oncogenomic studies we show that inclusion of prior information on the regulatory network architecture benefits the reproducibility of all edges. Furthermore, analyses of the TP53 and TGFb signaling pathways between ER+ and ER- samples from an integrative genomics breast cancer study identify reproducible differential regulatory patterns that corroborate with existing literature.

Alzheimer's disease master regulators analysis: search for potential molecular targets and drug repositioning candidates.

PubMed

Vargas, D M; De Bastiani, M A; Zimmer, E R; Klamt, F

2018-06-23

Alzheimer's disease (AD) is a multifactorial and complex neuropathology that involves impairment of many intricate molecular mechanisms. Despite recent advances, AD pathophysiological characterization remains incomplete, which hampers the development of effective treatments. In fact, currently, there are no effective pharmacological treatments for AD. Integrative strategies such as transcription regulatory network and master regulator analyses exemplify promising new approaches to study complex diseases and may help in the identification of potential pharmacological targets. In this study, we used transcription regulatory network and master regulator analyses on transcriptomic data of human hippocampus to identify transcription factors (TFs) that can potentially act as master regulators in AD. All expression profiles were obtained from the Gene Expression Omnibus database using the GEOquery package. A normal hippocampus transcription factor-centered regulatory network was reconstructed using the ARACNe algorithm. Master regulator analysis and two-tail gene set enrichment analysis were employed to evaluate the inferred regulatory units in AD case-control studies. Finally, we used a connectivity map adaptation to prospect new potential therapeutic interventions by drug repurposing. We identified TFs with already reported involvement in AD, such as ATF2 and PARK2, as well as possible new targets for future investigations, such as CNOT7, CSRNP2, SLC30A9, and TSC22D1. Furthermore, Connectivity Map Analysis adaptation suggested the repositioning of six FDA-approved drugs that can potentially modulate master regulator candidate regulatory units (Cefuroxime, Cyproterone, Dydrogesterone, Metrizamide, Trimethadione, and Vorinostat). Using a transcription factor-centered regulatory network reconstruction we were able to identify several potential molecular targets and six drug candidates for repositioning in AD. Our study provides further support for the use of bioinformatics tools as exploratory strategies in neurodegenerative diseases research, and also provides new perspectives on molecular targets and drug therapies for future investigation and validation in AD.

Quantum and semiclassical spin networks: from atomic and molecular physics to quantum computing and gravity

NASA Astrophysics Data System (ADS)

Aquilanti, Vincenzo; Bitencourt, Ana Carla P.; Ferreira, Cristiane da S.; Marzuoli, Annalisa; Ragni, Mirco

2008-11-01

The mathematical apparatus of quantum-mechanical angular momentum (re)coupling, developed originally to describe spectroscopic phenomena in atomic, molecular, optical and nuclear physics, is embedded in modern algebraic settings which emphasize the underlying combinatorial aspects. SU(2) recoupling theory, involving Wigner's 3nj symbols, as well as the related problems of their calculations, general properties, asymptotic limits for large entries, nowadays plays a prominent role also in quantum gravity and quantum computing applications. We refer to the ingredients of this theory—and of its extension to other Lie and quantum groups—by using the collective term of 'spin networks'. Recent progress is recorded about the already established connections with the mathematical theory of discrete orthogonal polynomials (the so-called Askey scheme), providing powerful tools based on asymptotic expansions, which correspond on the physical side to various levels of semi-classical limits. These results are useful not only in theoretical molecular physics but also in motivating algorithms for the computationally demanding problems of molecular dynamics and chemical reaction theory, where large angular momenta are typically involved. As for quantum chemistry, applications of these techniques include selection and classification of complete orthogonal basis sets in atomic and molecular problems, either in configuration space (Sturmian orbitals) or in momentum space. In this paper, we list and discuss some aspects of these developments—such as for instance the hyperquantization algorithm—as well as a few applications to quantum gravity and topology, thus providing evidence of a unifying background structure.

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

The autophagy interaction network of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Osiewacz, Heinz D; Koch, Ina

2017-03-27

Autophagy is a conserved molecular pathway involved in the degradation and recycling of cellular components. It is active either as response to starvation or molecular damage. Evidence is emerging that autophagy plays a key role in the degradation of damaged cellular components and thereby affects aging and lifespan control. In earlier studies, it was found that autophagy in the aging model Podospora anserina acts as a longevity assurance mechanism. However, only little is known about the individual components controlling autophagy in this aging model. Here, we report a biochemical and bioinformatics study to detect the protein-protein interaction (PPI) network of P. anserina combining experimental and theoretical methods. We constructed the PPI network of autophagy in P. anserina based on the corresponding networks of yeast and human. We integrated PaATG8 interaction partners identified in an own yeast two-hybrid analysis using ATG8 of P. anserina as bait. Additionally, we included age-dependent transcriptome data. The resulting network consists of 89 proteins involved in 186 interactions. We applied bioinformatics approaches to analyze the network topology and to prove that the network is not random, but exhibits biologically meaningful properties. We identified hub proteins which play an essential role in the network as well as seven putative sub-pathways, and interactions which are likely to be evolutionary conserved amongst species. We confirmed that autophagy-associated genes are significantly often up-regulated and co-expressed during aging of P. anserina. With the present study, we provide a comprehensive biological network of the autophagy pathway in P. anserina comprising PPI and gene expression data. It is based on computational prediction as well as experimental data. We identified sub-pathways, important hub proteins, and evolutionary conserved interactions. The network clearly illustrates the relation of autophagy to aging processes and enables further specific studies to understand autophagy and aging in P. anserina as well as in other systems.

Spectroscopic study of uracil, 1-methyluracil and 1-methyl-4-thiouracil: Hydrogen bond interactions in crystals and ab-initio molecular dynamics.

PubMed

Brela, Mateusz Z; Boczar, Marek; Malec, Leszek M; Wójcik, Marek J; Nakajima, Takahito

2018-05-15

Hydrogen bond networks in uracil, 1-methyluracil and 1-methyl-4-thiouracil were studied by ab initio molecular dynamics as well as analysis of the orbital interactions. The power spectra calculated by ab initio molecular dynamics for atoms involved in hydrogen bonds were analyzed. We calculated spectra by using anharmonic approximation based on the autocorrelation function of the atom positions obtained from the Born-Oppenheimer simulations. Our results show the differences between hydrogen bond networks in uracil and its methylated derivatives. The studied methylated derivatives, 1-methyluracil as well as 1-methyl-4-thiouracil, form dimeric structures in the crystal phase, while uracil does not form that kind of structures. The presence of sulfur atom instead oxygen atom reflects weakness of the hydrogen bonds that build dimers. Copyright © 2018 Elsevier B.V. All rights reserved.

Screening the molecular targets of ovarian cancer based on bioinformatics analysis.

PubMed

Du, Lei; Qian, Xiaolei; Dai, Chenyang; Wang, Lihua; Huang, Ding; Wang, Shuying; Shen, Xiaowei

2015-01-01

Ovarian cancer (OC) is the most lethal gynecologic malignancy. This study aims to explore the molecular mechanisms of OC and identify potential molecular targets for OC treatment. Microarray gene expression data (GSE14407) including 12 normal ovarian surface epithelia samples and 12 OC epithelia samples were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) between 2 kinds of ovarian tissue were identified by using limma package in R language (|log2 fold change| gt;1 and false discovery rate [FDR] lt;0.05). Protein-protein interactions (PPIs) and known OC-related genes were screened from COXPRESdb and GenBank database, respectively. Furthermore, PPI network of top 10 upregulated DEGs and top 10 downregulated DEGs was constructed and visualized through Cytoscape software. Finally, for the genes involved in PPI network, functional enrichment analysis was performed by using DAVID (FDR lt;0.05). In total, 1136 DEGs were identified, including 544 downregulated and 592 upregulated DEGs. Then, PPI network was constructed, and DEGs CDKN2A, MUC1, OGN, ZIC1, SOX17, and TFAP2A interacted with known OC-related genes CDK4, EGFR/JUN, SRC, CLI1, CTNNB1, and TP53, respectively. Moreover, functions about oxygen transport and embryonic development were enriched by the genes involved in the network of downregulated DEGs. We propose that 4 DEGs (OGN, ZIC1, SOX17, and TFAP2A) and 2 functions (oxygen transport and embryonic development) might play a role in the development of OC. These 4 DEGs and known OC-related genes might serve as therapeutic targets for OC. Further studies are required to validate these predictions.

Identification of control targets in Boolean molecular network models via computational algebra.

PubMed

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe

PubMed Central

Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

2016-01-01

Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies. PMID:27014338

Bone Marrow Derived Myeloid Cells Orchestrate Antiangiogenic Resistance in Glioblastoma through Coordinated Molecular Networks

PubMed Central

Achyut, B.R.; Shankar, Adarsh; Iskander, ASM; Ara, Roxan; Angara, Kartik; Zeng, Peng; Knight, Robert A.; Scicli, Alfonso G; Arbab, Ali S.

2015-01-01

Glioblastoma (GBM) is a hypervascular and malignant form of brain tumors. Anti-angiogenic therapies (AAT) were used as an adjuvant against VEGF-VEGFR pathway to normalize blood vessels in clinical and preclinical studies, which resulted into marked hypoxia and recruited bone marrow derived cells (BMDCs) to the tumor microenvironment (TME). In vivo animal models to track BMDCs and investigate molecular mechanisms in AAT resistance are rare. We exploited recently established chimeric mouse to develop orthotopic U251 tumor, which uses as low as 5×106 GFP+ BM cells in athymic nude mice and engrafted >70% GFP+ cells within 14 days. Our unpublished data and published studies have indicated the involvement of immunosuppressive myeloid cells in therapeutic resistance in glioma. Similarly, in the present study, vatalanib significantly increased CD68+ myeloid cells, and CD133+, CD34+ and Tie2+ endothelial cell signatures. Therefore, we tested inhibition of CSF1R+ myeloid cells using GW2580 that reduced tumor growth by decreasing myeloid (Gr1+ CD11b+ and F4/80+) and angiogenic (CD202b+ and VEGFR2+) cell signatures in TME. CSF1R blockade significantly decreased inflammatory, proangiogenic and immunosuppressive molecular signatures compared to vehicle, vatalanib or combination. TCK1 or CXCL7, a potent chemoattractant and activator of neutrophils, was observed as most significantly decreased cytokine in CSF1R blockade. ERK MAPK pathway was involved in cytokine network regulation. In conclusion, present study confirmed the contribution of myeloid cells in GBM development and therapeutic resistance using chimeric mouse model. We identified novel molecular networks including CXCL7 chemokine as a promising target for future studies. Nonetheless, survival studies are required to assess the beneficial effect of CSF1R blockade. PMID:26404753

Dataset generated for Dissection of mechanisms of Trypanothione Reductase and Tryparedoxin Peroxidase through dynamic network analysis and simulations in leishmaniasis.

PubMed

Kumar, Anurag; Saha, Bhaskar; Singh, Shailza

2017-12-01

Leishmaniasis is the second largest parasitic killer disease caused by the protozoan parasite Leishmania , transmitted by the bite of sand flies. It's endemic in the eastern India with 165.4 million populations at risk with the current drug regimen. Three forms of leishmaniasis exist in which cutaneous is the most common form caused by Leishmania major . Trypanothione Reductase (TryR), a flavoprotein oxidoreductase, unique to thiol redox system, is considered as a potential target for chemotherapy for trypanosomatids infection. It is involved in the NADPH dependent reduction of Trypanothione disulphide to Trypanothione. Similarly, is Tryparedoxin Peroxidase (Txnpx), for detoxification of peroxides, an event pivotal for survival of Leishmania in two disparate biological environment. Fe-S plays a major role in regulating redox balance. To check for the closeness between human homologs of these proteins, we have carried the molecular clock analysis followed by molecular modeling of 3D structure of this protein, enabling us to design and test the novel drug like molecules. Molecular clock analysis suggests that human homologs of TryR i.e. Glutathione Reductase and Txnpx respectively are highly diverged in phylogenetic tree, thus, they serve as good candidates for chemotherapy of leishmaniasis. Furthermore, we have done the homology modeling of TryR using template of same protein from Leishmania infantum (PDB ID: 2JK6). This was done using Modeller 9.18 and the resultant models were validated. To inhibit this target, molecular docking was done with various screened inhibitors in which we found Taxifolin acts as common inhibitors for both TryR and Txnpx. We constructed the protein-protein interaction network for the proteins that are involved in the redox metabolism from various Interaction databases and the network was statistically analysed.

Genes and Experience in the Development of Executive Attention and Effortful Control

ERIC Educational Resources Information Center

Rothbart, Mary K.; Posner, Michael I.

2005-01-01

The executive attention network is involved in regulating emotions and cognitions, forming a neural basis for temperamental self-regulation. New brain imaging and molecular genetics methods can enhance our understanding of common mechanisms of self-regulation and individual differences in their expression.

The role of effectors and host immunity in plant-necrotrophic fungal interactions.

PubMed

Wang, Xuli; Jiang, Nan; Liu, Jinling; Liu, Wende; Wang, Guo-Liang

2014-01-01

Fungal diseases pose constant threats to the global economy and food safety. As the largest group of plant fungal pathogens, necrotrophic fungi cause heavy crop losses worldwide. The molecular mechanisms of the interaction between necrotrophic fungi and plants are complex and involve sophisticated recognition and signaling networks. Here, we review recent findings on the roles of phytotoxin and proteinaceous effectors, pathogen-associated molecular patterns (PAMPs), and small RNAs from necrotrophic fungi. We also consider the functions of damage-associated molecular patterns (DAMPs), the receptor-like protein kinase BIK1, and epigenetic regulation in plant immunity to necrotrophic fungi.

Construction and analysis of circular RNA molecular regulatory networks in liver cancer.

PubMed

Ren, Shuangchun; Xin, Zhuoyuan; Xu, Yinyan; Xu, Jianting; Wang, Guoqing

2017-01-01

Liver cancer is the sixth most prevalent cancer, and the third most frequent cause of cancer-related deaths. Circular RNAs (circRNAs), a kind of special endogenous ncRNAs, have been coming back to the forefront of cancer genomics research. In this study, we used a systems biology approach to construct and analyze the circRNA molecular regulatory networks in the context of liver cancer. We detected a total of 127 differentially expressed circRNAs and 3,235 differentially expressed mRNAs. We selected the top-5 upregulated circRNAs to construct a circRNA-miRNA-mRNA network. We enriched the pathways and gene ontology items and determined their participation in cancer-related pathways such as p53 signaling pathway and pathways involved in angiogenesis and cell cycle. Quantitative real-time PCR was performed to verify the top-five circRNAs. ROC analysis showed circZFR, circFUT8, circIPO11 could significantly distinguish the cancer samples, with an AUC of 0.7069, 0.7575, and 0.7103, respectively. Our results suggest the circRNA-miRNA-mRNA network may help us further understand the molecular mechanisms of tumor progression in liver cancer, and reveal novel biomarkers and therapeutic targets.

Long-Term Oil Contamination Alters the Molecular Ecological Networks of Soil Microbial Functional Genes

PubMed Central

Liang, Yuting; Zhao, Huihui; Deng, Ye; Zhou, Jizhong; Li, Guanghe; Sun, Bo

2016-01-01

With knowledge on microbial composition and diversity, investigation of within-community interactions is a further step to elucidate microbial ecological functions, such as the biodegradation of hazardous contaminants. In this work, microbial functional molecular ecological networks were studied in both contaminated and uncontaminated soils to determine the possible influences of oil contamination on microbial interactions and potential functions. Soil samples were obtained from an oil-exploring site located in South China, and the microbial functional genes were analyzed with GeoChip, a high-throughput functional microarray. By building random networks based on null model, we demonstrated that overall network structures and properties were significantly different between contaminated and uncontaminated soils (P < 0.001). Network connectivity, module numbers, and modularity were all reduced with contamination. Moreover, the topological roles of the genes (module hub and connectors) were altered with oil contamination. Subnetworks of genes involved in alkane and polycyclic aromatic hydrocarbon degradation were also constructed. Negative co-occurrence patterns prevailed among functional genes, thereby indicating probable competition relationships. The potential “keystone” genes, defined as either “hubs” or genes with highest connectivities in the network, were further identified. The network constructed in this study predicted the potential effects of anthropogenic contamination on microbial community co-occurrence interactions. PMID:26870020

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.

Interconnectivity of human cellular metabolism and disease prevalence

NASA Astrophysics Data System (ADS)

Lee, Deok-Sun

2010-12-01

Fluctuations of metabolic reaction fluxes may cause abnormal concentrations of toxic or essential metabolites, possibly leading to metabolic diseases. The mutual binding of enzymatic proteins and ones involving common metabolites enforces distinct coupled reactions, by which local perturbations may spread through the cellular network. Such network effects at the molecular interaction level in human cellular metabolism can reappear in the patterns of disease occurrence. Here we construct the enzyme-reaction network and the metabolite-reaction network, capturing the flux coupling of metabolic reactions caused by the interacting enzymes and the shared metabolites, respectively. Diseases potentially caused by the failure of individual metabolic reactions can be identified by using the known disease-gene association, which allows us to derive the probability of an inactivated reaction causing diseases from the disease records at the population level. We find that the greater the number of proteins that catalyze a reaction, the higher the mean prevalence of its associated diseases. Moreover, the number of connected reactions and the mean size of the avalanches in the networks constructed are also shown to be positively correlated with the disease prevalence. These findings illuminate the impact of the cellular network topology on disease development, suggesting that the global organization of the molecular interaction network should be understood to assist in disease diagnosis, treatment, and drug discovery.

An integrated molecular dynamics, principal component analysis and residue interaction network approach reveals the impact of M184V mutation on HIV reverse transcriptase resistance to lamivudine.

PubMed

Bhakat, Soumendranath; Martin, Alberto J M; Soliman, Mahmoud E S

2014-08-01

The emergence of different drug resistant strains of HIV-1 reverse transcriptase (HIV RT) remains of prime interest in relation to viral pathogenesis as well as drug development. Amongst those mutations, M184V was found to cause a complete loss of ligand fitness. In this study, we report the first account of the molecular impact of M184V mutation on HIV RT resistance to 3TC (lamivudine) using an integrated computational approach. This involved molecular dynamics simulation, binding free energy analysis, principle component analysis (PCA) and residue interaction networks (RINs). Results clearly confirmed that M184V mutation leads to steric conflict between 3TC and the beta branched side chain of valine, decreases the ligand (3TC) binding affinity by ∼7 kcal mol(-1) when compared to the wild type, changes the overall conformational landscape of the protein and distorts the native enzyme residue-residue interaction network. The comprehensive molecular insight gained from this study should be of great importance in understanding drug resistance against HIV RT as well as assisting in the design of novel reverse transcriptase inhibitors with high ligand efficacy on resistant strains.

Impaired clock output by altered connectivity in the circadian network.

PubMed

Fernández, María de la Paz; Chu, Jessie; Villella, Adriana; Atkinson, Nigel; Kay, Steve A; Ceriani, María Fernanda

2007-03-27

Substantial progress has been made in elucidating the molecular processes that impart a temporal control to physiology and behavior in most eukaryotes. In Drosophila, dorsal and ventral neuronal networks act in concert to convey rhythmicity. Recently, the hierarchical organization among the different circadian clusters has been addressed, but how molecular oscillations translate into rhythmic behavior remains unclear. The small ventral lateral neurons can synchronize certain dorsal oscillators likely through the release of pigment dispersing factor (PDF), a neuropeptide central to the control of rhythmic rest-activity cycles. In the present study, we have taken advantage of flies exhibiting a distinctive arrhythmic phenotype due to mutation of the potassium channel slowpoke (slo) to examine the relevance of specific neuronal populations involved in the circadian control of behavior. We show that altered neuronal function associated with the null mutation specifically impaired PDF accumulation in the dorsal protocerebrum and, in turn, desynchronized molecular oscillations in the dorsal clusters. However, molecular oscillations in the small ventral lateral neurons are properly running in the null mutant, indicating that slo is acting downstream of these core pacemaker cells, most likely in the output pathway. Surprisingly, disrupted PDF signaling by slo dysfunction directly affects the structure of the underlying circuit. Our observations demonstrate that subtle structural changes within the circadian network are responsible for behavioral arrhythmicity.

Astrochemistry at the Cryogenic Storage Ring

NASA Astrophysics Data System (ADS)

Kreckel, Holger; Becker, Arno; Blaum, Klaus; Breitenfeldt, Christian; George, Sebastian; Göck, Jürgen; Grieser, Manfred; Grussie, Florian; Guerin, Elisabeth; Heber, Oded; Karthein, Jonas; Krantz, Claude; Meyer, Christian; Mishra, Preeti; Novotny, Oldrich; O'Connor, Aodh; Saurabh, Sunny; Schippers, Stefan; Spruck, Kaija; Kumar, S. Sunil; Urbain, Xavier; Vogel, Stephen; von Hahn, Robert; Wilhelm, Patrick; Wolf, Andreas; Zajfman, Daniel

2017-01-01

Almost 200 different molecular species have been identified in space, and this number continues to grow steadily. This surprising molecular diversity bears witness to an active reaction network, in which molecular ions are the main drivers of chemistry in the gas phase. To study these reactions under controlled conditions in the laboratory is a major experimental challenge. The new Cryogenic Storage Ring (CSR) that has recently been commissioned at the Max Planck Institute for Nuclear Physics in Heidelberg will serve as an ideal testbed to study cold molecular ions in the gas phase. With residual gas densities of <140 cm-3 and temperatures below 10K, the CSR will allow for merged beams collision studies involving molecular ions, neutral atoms, free electrons and photons under true interstellar conditions.

Gene expression networks underlying ovarian development in wild largemouth bass (Micropterus salmoides).

PubMed

Martyniuk, Christopher J; Prucha, Melinda S; Doperalski, Nicholas J; Antczak, Philipp; Kroll, Kevin J; Falciani, Francesco; Barber, David S; Denslow, Nancy D

2013-01-01

Oocyte maturation in fish involves numerous cell signaling cascades that are activated or inhibited during specific stages of oocyte development. The objectives of this study were to characterize molecular pathways and temporal gene expression patterns throughout a complete breeding cycle in wild female largemouth bass to improve understanding of the molecular sequence of events underlying oocyte maturation. Transcriptomic analysis was performed on eight morphologically diverse stages of the ovary, including primary and secondary stages of oocyte growth, ovulation, and atresia. Ovary histology, plasma vitellogenin, 17β-estradiol, and testosterone were also measured to correlate with gene networks. Global expression patterns revealed dramatic differences across ovarian development, with 552 and 2070 genes being differentially expressed during both ovulation and atresia respectively. Gene set enrichment analysis (GSEA) revealed that early primary stages of oocyte growth involved increases in expression of genes involved in pathways of B-cell and T-cell receptor-mediated signaling cascades and fibronectin regulation. These pathways as well as pathways that included adrenergic receptor signaling, sphingolipid metabolism and natural killer cell activation were down-regulated at ovulation. At atresia, down-regulated pathways included gap junction and actin cytoskeleton regulation, gonadotrope and mast cell activation, and vasopressin receptor signaling and up-regulated pathways included oxidative phosphorylation and reactive oxygen species metabolism. Expression targets for luteinizing hormone signaling were low during vitellogenesis but increased 150% at ovulation. Other networks found to play a significant role in oocyte maturation included those with genes regulated by members of the TGF-beta superfamily (activins, inhibins, bone morphogenic protein 7 and growth differentiation factor 9), neuregulin 1, retinoid X receptor, and nerve growth factor family. This study offers novel insight into the gene networks underlying vitellogenesis, ovulation and atresia and generates new hypotheses about the cellular pathways regulating oocyte maturation.

Rapid neutral-neutral reactions at low temperatures: a new network and first results for TMC-1

NASA Astrophysics Data System (ADS)

Smith, Ian W. M.; Herbst, Eric; Chang, Qiang

2004-05-01

There is now ample evidence from an assortment of experiments, especially those involving the CRESU (Cinétique de Réaction en Ecoulement Supersonique Uniforme) technique, that a variety of neutral-neutral reactions possess no activation energy barrier and are quite rapid at very low temperatures. These reactions include both radical-radical systems and, more surprisingly, systems involving an atom or a radical and one `stable' species. Generalizing from the small but growing number of systems studied in the laboratory, we estimate reaction rate coefficients for a larger number of such reactions and include these estimates in a new network of gas-phase reactions for use in low-temperature interstellar chemistry. Designated osu.2003, the new network is available on the World Wide Web and will be continually updated. A table of new results for molecular abundances in the dark cloud TMC-1 (CP) is provided and compared with results from an older (new standard model; nsm) network.

Coexpression network analysis of the genes regulated by two types of resistance responses to powdery mildew in wheat

PubMed Central

Zhang, Juncheng; Zheng, Hongyuan; Li, Yiwen; Li, Hongjie; Liu, Xin; Qin, Huanju; Dong, Lingli; Wang, Daowen

2016-01-01

Powdery mildew disease caused by Blumeria graminis f. sp. tritici (Bgt) inflicts severe economic losses in wheat crops. A systematic understanding of the molecular mechanisms involved in wheat resistance to Bgt is essential for effectively controlling the disease. Here, using the diploid wheat Triticum urartu as a host, the genes regulated by immune (IM) and hypersensitive reaction (HR) resistance responses to Bgt were investigated through transcriptome sequencing. Four gene coexpression networks (GCNs) were developed using transcriptomic data generated for 20 T. urartu accessions showing IM, HR or susceptible responses. The powdery mildew resistance regulated (PMRR) genes whose expression was significantly correlated with Bgt resistance were identified, and they tended to be hubs and enriched in six major modules. A wide occurrence of negative regulation of PMRR genes was observed. Three new candidate immune receptor genes (TRIUR3_13045, TRIUR3_01037 and TRIUR3_06195) positively associated with Bgt resistance were discovered. Finally, the involvement of TRIUR3_01037 in Bgt resistance was tentatively verified through cosegregation analysis in a F2 population and functional expression assay in Bgt susceptible leaf cells. This research provides insights into the global network properties of PMRR genes. Potential molecular differences between IM and HR resistance responses to Bgt are discussed. PMID:27033636

Td4IN2: A drought-responsive durum wheat (Triticum durum Desf.) gene coding for a resistance like protein with serine/threonine protein kinase, nucleotide binding site and leucine rich domains.

PubMed

Rampino, Patrizia; De Pascali, Mariarosaria; De Caroli, Monica; Luvisi, Andrea; De Bellis, Luigi; Piro, Gabriella; Perrotta, Carla

2017-11-01

Wheat, the main food source for a third of world population, appears strongly under threat because of predicted increasing temperatures coupled to drought. Plant complex molecular response to drought stress relies on the gene network controlling cell reactions to abiotic stress. In the natural environment, plants are subjected to the combination of abiotic and biotic stresses. Also the response of plants to biotic stress, to cope with pathogens, involves the activation of a molecular network. Investigations on combination of abiotic and biotic stresses indicate the existence of cross-talk between the two networks and a kind of overlapping can be hypothesized. In this work we describe the isolation and characterization of a drought-related durum wheat (Triticum durum Desf.) gene, identified in a previous study, coding for a protein combining features of NBS-LRR type resistance protein with a S/TPK domain, involved in drought stress response. This is one of the few examples reported where all three domains are present in a single protein and, to our knowledge, it is the first report on a gene specifically induced by drought stress and drought-related conditions, with this particular structure. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

MOLSIM: A modular molecular simulation software

PubMed Central

Jurij, Reščič

2015-01-01

The modular software MOLSIM for all‐atom molecular and coarse‐grained simulations is presented with focus on the underlying concepts used. The software possesses four unique features: (1) it is an integrated software for molecular dynamic, Monte Carlo, and Brownian dynamics simulations; (2) simulated objects are constructed in a hierarchical fashion representing atoms, rigid molecules and colloids, flexible chains, hierarchical polymers, and cross‐linked networks; (3) long‐range interactions involving charges, dipoles and/or anisotropic dipole polarizabilities are handled either with the standard Ewald sum, the smooth particle mesh Ewald sum, or the reaction‐field technique; (4) statistical uncertainties are provided for all calculated observables. In addition, MOLSIM supports various statistical ensembles, and several types of simulation cells and boundary conditions are available. Intermolecular interactions comprise tabulated pairwise potentials for speed and uniformity and many‐body interactions involve anisotropic polarizabilities. Intramolecular interactions include bond, angle, and crosslink potentials. A very large set of analyses of static and dynamic properties is provided. The capability of MOLSIM can be extended by user‐providing routines controlling, for example, start conditions, intermolecular potentials, and analyses. An extensive set of case studies in the field of soft matter is presented covering colloids, polymers, and crosslinked networks. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:25994597

The PluriNetWork: An Electronic Representation of the Network Underlying Pluripotency in Mouse, and Its Applications

PubMed Central

Greber, Boris; Siatkowski, Marcin; Paudel, Yogesh; Warsow, Gregor; Cap, Clemens; Schöler, Hans; Fuellen, Georg

2010-01-01

Background Analysis of the mechanisms underlying pluripotency and reprogramming would benefit substantially from easy access to an electronic network of genes, proteins and mechanisms. Moreover, interpreting gene expression data needs to move beyond just the identification of the up-/downregulation of key genes and of overrepresented processes and pathways, towards clarifying the essential effects of the experiment in molecular terms. Methodology/Principal Findings We have assembled a network of 574 molecular interactions, stimulations and inhibitions, based on a collection of research data from 177 publications until June 2010, involving 274 mouse genes/proteins, all in a standard electronic format, enabling analyses by readily available software such as Cytoscape and its plugins. The network includes the core circuit of Oct4 (Pou5f1), Sox2 and Nanog, its periphery (such as Stat3, Klf4, Esrrb, and c-Myc), connections to upstream signaling pathways (such as Activin, WNT, FGF, BMP, Insulin, Notch and LIF), and epigenetic regulators as well as some other relevant genes/proteins, such as proteins involved in nuclear import/export. We describe the general properties of the network, as well as a Gene Ontology analysis of the genes included. We use several expression data sets to condense the network to a set of network links that are affected in the course of an experiment, yielding hypotheses about the underlying mechanisms. Conclusions/Significance We have initiated an electronic data repository that will be useful to understand pluripotency and to facilitate the interpretation of high-throughput data. To keep up with the growth of knowledge on the fundamental processes of pluripotency and reprogramming, we suggest to combine Wiki and social networking software towards a community curation system that is easy to use and flexible, and tailored to provide a benefit for the scientist, and to improve communication and exchange of research results. A PluriNetWork tutorial is available at http://www.ibima.med.uni-rostock.de/IBIMA/PluriNetWork/. PMID:21179244

Novel transcriptional networks regulated by CLOCK in human neurons.

PubMed

Fontenot, Miles R; Berto, Stefano; Liu, Yuxiang; Werthmann, Gordon; Douglas, Connor; Usui, Noriyoshi; Gleason, Kelly; Tamminga, Carol A; Takahashi, Joseph S; Konopka, Genevieve

2017-11-01

The molecular mechanisms underlying human brain evolution are not fully understood; however, previous work suggested that expression of the transcription factor CLOCK in the human cortex might be relevant to human cognition and disease. In this study, we investigated this novel transcriptional role for CLOCK in human neurons by performing chromatin immunoprecipitation sequencing for endogenous CLOCK in adult neocortices and RNA sequencing following CLOCK knockdown in differentiated human neurons in vitro. These data suggested that CLOCK regulates the expression of genes involved in neuronal migration, and a functional assay showed that CLOCK knockdown increased neuronal migratory distance. Furthermore, dysregulation of CLOCK disrupts coexpressed networks of genes implicated in neuropsychiatric disorders, and the expression of these networks is driven by hub genes with human-specific patterns of expression. These data support a role for CLOCK-regulated transcriptional cascades involved in human brain evolution and function. © 2017 Fontenot et al.; Published by Cold Spring Harbor Laboratory Press.

MicroRNAs in Palatogenesis and Cleft Palate

PubMed Central

Schoen, Christian; Aschrafi, Armaz; Thonissen, Michelle; Poelmans, Geert; Von den Hoff, Johannes W.; Carels, Carine E. L.

2017-01-01

Palatogenesis requires a precise spatiotemporal regulation of gene expression, which is controlled by an intricate network of transcription factors and their corresponding DNA motifs. Even minor perturbations of this network may cause cleft palate, the most common congenital craniofacial defect in humans. MicroRNAs (miRNAs), a class of small regulatory non-coding RNAs, have elicited strong interest as key regulators of embryological development, and as etiological factors in disease. MiRNAs function as post-transcriptional repressors of gene expression and are therefore able to fine-tune gene regulatory networks. Several miRNAs are already identified to be involved in congenital diseases. Recent evidence from research in zebrafish and mice indicates that miRNAs are key factors in both normal palatogenesis and cleft palate formation. Here, we provide an overview of recently identified molecular mechanisms underlying palatogenesis involving specific miRNAs, and discuss how dysregulation of these miRNAs may result in cleft palate. PMID:28420997

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.

Constructing Smart Protocells with Built-In DNA Computational Core to Eliminate Exogenous Challenge.

PubMed

Lyu, Yifan; Wu, Cuichen; Heinke, Charles; Han, Da; Cai, Ren; Teng, I-Ting; Liu, Yuan; Liu, Hui; Zhang, Xiaobing; Liu, Qiaoling; Tan, Weihong

2018-06-06

A DNA reaction network is like a biological algorithm that can respond to "molecular input signals", such as biological molecules, while the artificial cell is like a microrobot whose function is powered by the encapsulated DNA reaction network. In this work, we describe the feasibility of using a DNA reaction network as the computational core of a protocell, which will perform an artificial immune response in a concise way to eliminate a mimicked pathogenic challenge. Such a DNA reaction network (RN)-powered protocell can realize the connection of logical computation and biological recognition due to the natural programmability and biological properties of DNA. Thus, the biological input molecules can be easily involved in the molecular computation and the computation process can be spatially isolated and protected by artificial bilayer membrane. We believe the strategy proposed in the current paper, i.e., using DNA RN to power artificial cells, will lay the groundwork for understanding the basic design principles of DNA algorithm-based nanodevices which will, in turn, inspire the construction of artificial cells, or protocells, that will find a place in future biomedical research.

The molecular mechanism of plant gravitropism.

PubMed

Wu, Di; Huang, Lin-zhou; Gao, Jin; Wang, Yong-hong

2016-07-20

Gravity is an important environmental factor that regulates plant growth and morphogenesis. In response to gravity stimulus, plants can set the optimum angle between the organs and the gravity vector. Plant gravitropism is divided into four sequential steps, including gravity perception, signal transduction, asymmetrical distribution of auxin, and organ curvature. In recent years, large numbers of mutants with defective gravitropism have been identified and genes involved in the regulation of gravitropism have been functionally characterized. In particular, progress has been achieved on elucidating the molecular mechanisms of gravity perception and asymmetrical distribution of auxin. As one of the most important strategies for plant to adapt environmental changes, gravitropism is also involved in the regulation of rice plant architecture and grain yield through modulating rice tiller angle. Therefore, the investigation of plant gravitropism not only contributes to decipher the regulatory mechanisms of plant growth and development, but also helps to guide the genetic improvement of crop architecture. However, the molecular mechanisms and regulatory network of gravitropism remain to be elusive. In this review, we focus on recent progress on elucidating molecular mechanisms underlying gravitropism and its involvement in regulating rice tiller angle, which is an important agronomic trait that determines rice plant architecture and thus grain yields.

Molecular codes for neuronal individuality and cell assembly in the brain

PubMed Central

Yagi, Takeshi

2012-01-01

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain. PMID:22518100

Computational analysis of multimorbidity between asthma, eczema and rhinitis

PubMed Central

Aguilar, Daniel; Pinart, Mariona; Koppelman, Gerard H.; Saeys, Yvan; Nawijn, Martijn C.; Postma, Dirkje S.; Akdis, Mübeccel; Auffray, Charles; Ballereau, Stéphane; Benet, Marta; García-Aymerich, Judith; González, Juan Ramón; Guerra, Stefano; Keil, Thomas; Kogevinas, Manolis; Lambrecht, Bart; Lemonnier, Nathanael; Melen, Erik; Sunyer, Jordi; Valenta, Rudolf; Valverde, Sergi; Wickman, Magnus; Bousquet, Jean; Oliva, Baldo; Antó, Josep M.

2017-01-01

Background The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. Methods An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Results Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. Conclusions These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases. PMID:28598986

Computational analysis of multimorbidity between asthma, eczema and rhinitis.

PubMed

Aguilar, Daniel; Pinart, Mariona; Koppelman, Gerard H; Saeys, Yvan; Nawijn, Martijn C; Postma, Dirkje S; Akdis, Mübeccel; Auffray, Charles; Ballereau, Stéphane; Benet, Marta; García-Aymerich, Judith; González, Juan Ramón; Guerra, Stefano; Keil, Thomas; Kogevinas, Manolis; Lambrecht, Bart; Lemonnier, Nathanael; Melen, Erik; Sunyer, Jordi; Valenta, Rudolf; Valverde, Sergi; Wickman, Magnus; Bousquet, Jean; Oliva, Baldo; Antó, Josep M

2017-01-01

The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases.

The Developmental Regulator SEEDSTICK Controls Structural and Mechanical Properties of the Arabidopsis Seed Coat

PubMed Central

Beauzamy, Léna; Caporali, Elisabetta; Koroney, Abdoul-Salam

2016-01-01

Although many transcription factors involved in cell wall morphogenesis have been identified and studied, it is still unknown how genetic and molecular regulation of cell wall biosynthesis is integrated into developmental programs. We demonstrate by molecular genetic studies that SEEDSTICK (STK), a transcription factor controlling ovule and seed integument identity, directly regulates PMEI6 and other genes involved in the biogenesis of the cellulose-pectin matrix of the cell wall. Based on atomic force microscopy, immunocytochemistry, and chemical analyses, we propose that structural modifications of the cell wall matrix in the stk mutant contribute to defects in mucilage release and seed germination under water-stress conditions. Our studies reveal a molecular network controlled by STK that regulates cell wall properties of the seed coat, demonstrating that developmental regulators controlling organ identity also coordinate specific aspects of cell wall characteristics. PMID:27624758

Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network.

PubMed

Martínez-Romero, Marcos; Vázquez-Naya, José M; Rabuñal, Juan R; Pita-Fernández, Salvador; Macenlle, Ramiro; Castro-Alvariño, Javier; López-Roses, Leopoldo; Ulla, José L; Martínez-Calvo, Antonio V; Vázquez, Santiago; Pereira, Javier; Porto-Pazos, Ana B; Dorado, Julián; Pazos, Alejandro; Munteanu, Cristian R

2010-05-01

Colorectal cancer is one of the most frequent types of cancer in the world and generates important social impact. The understanding of the specific metabolism of this disease and the transformations of the specific drugs will allow finding effective prevention, diagnosis and treatment of the colorectal cancer. All the terms that describe the drug metabolism contribute to the construction of ontology in order to help scientists to link the correlated information and to find the most useful data about this topic. The molecular components involved in this metabolism are included in complex network such as metabolic pathways in order to describe all the molecular interactions in the colorectal cancer. The graphical method of processing biological information such as graphs and complex networks leads to the numerical characterization of the colorectal cancer drug metabolic network by using invariant values named topological indices. Thus, this method can help scientists to study the most important elements in the metabolic pathways and the dynamics of the networks during mutations, denaturation or evolution for any type of disease. This review presents the last studies regarding ontology and complex networks of the colorectal cancer drug metabolism and a basic topology characterization of the drug metabolic process sub-ontology from the Gene Ontology.

Parameter space exploration within dynamic simulations of signaling networks.

PubMed

De Ambrosi, Cristina; Barla, Annalisa; Tortolina, Lorenzo; Castagnino, Nicoletta; Pesenti, Raffaele; Verri, Alessandro; Ballestrero, Alberto; Patrone, Franco; Parodi, Silvio

2013-02-01

We started offering an introduction to very basic aspects of molecular biology, for the reader coming from computer sciences, information technology, mathematics. Similarly we offered a minimum of information about pathways and networks in graph theory, for a reader coming from the bio-medical sector. At the crossover about the two different types of expertise, we offered some definition about Systems Biology. The core of the article deals with a Molecular Interaction Map (MIM), a network of biochemical interactions involved in a small signaling-network sub-region relevant in breast cancer. We explored robustness/sensitivity to random perturbations. It turns out that our MIM is a non-isomorphic directed graph. For non physiological directions of propagation of the signal the network is quite resistant to perturbations. The opposite happens for biologically significant directions of signal propagation. In these cases we can have no signal attenuation, and even signal amplification. Signal propagation along a given pathway is highly unidirectional, with the exception of signal-feedbacks, that again have a specific biological role and significance. In conclusion, even a relatively small network like our present MIM reveals the preponderance of specific biological functions over unspecific isomorphic behaviors. This is perhaps the consequence of hundreds of millions of years of biological evolution.

The role of effectors and host immunity in plant–necrotrophic fungal interactions

PubMed Central

Wang, Xuli; Jiang, Nan; Liu, Jinling; Liu, Wende; Wang, Guo-Liang

2014-01-01

Fungal diseases pose constant threats to the global economy and food safety. As the largest group of plant fungal pathogens, necrotrophic fungi cause heavy crop losses worldwide. The molecular mechanisms of the interaction between necrotrophic fungi and plants are complex and involve sophisticated recognition and signaling networks. Here, we review recent findings on the roles of phytotoxin and proteinaceous effectors, pathogen-associated molecular patterns (PAMPs), and small RNAs from necrotrophic fungi. We also consider the functions of damage-associated molecular patterns (DAMPs), the receptor-like protein kinase BIK1, and epigenetic regulation in plant immunity to necrotrophic fungi. PMID:25513773

KEGG Bioinformatics Resource for Plant Genomics and Metabolomics.

PubMed

Kanehisa, Minoru

2016-01-01

In the era of high-throughput biology it is necessary to develop not only elaborate computational methods but also well-curated databases that can be used as reference for data interpretation. KEGG ( http://www.kegg.jp/ ) is such a reference knowledge base with two specific aims. One is to compile knowledge on high-level functions of the cell and the organism in terms of the molecular interaction and reaction networks, which is implemented in KEGG pathway maps, BRITE functional hierarchies, and KEGG modules. The other is to expand knowledge on genes and proteins involved in the molecular networks from experimentally observed organisms to other organisms using the concept of orthologs, which is implemented in the KEGG Orthology (KO) system. Thus, KEGG is a generic resource applicable to all organisms and enables interpretation of high-level functions from genomic and molecular data. Here we first present a brief overview of the entire KEGG resource, and then give an introduction of how to use KEGG in plant genomics and metabolomics research.

A Systematic Analysis of Candidate Genes Associated with Nicotine Addiction

PubMed Central

Liu, Meng; Li, Xia; Fan, Rui; Liu, Xinhua; Wang, Ju

2015-01-01

Nicotine, as the major psychoactive component of tobacco, has broad physiological effects within the central nervous system, but our understanding of the molecular mechanism underlying its neuronal effects remains incomplete. In this study, we performed a systematic analysis on a set of nicotine addiction-related genes to explore their characteristics at network levels. We found that NAGenes tended to have a more moderate degree and weaker clustering coefficient and to be less central in the network compared to alcohol addiction-related genes or cancer genes. Further, clustering of these genes resulted in six clusters with themes in synaptic transmission, signal transduction, metabolic process, and apoptosis, which provided an intuitional view on the major molecular functions of the genes. Moreover, functional enrichment analysis revealed that neurodevelopment, neurotransmission activity, and metabolism related biological processes were involved in nicotine addiction. In summary, by analyzing the overall characteristics of the nicotine addiction related genes, this study provided valuable information for understanding the molecular mechanisms underlying nicotine addiction. PMID:26097843

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

PubMed

Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

2018-06-01

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

Genetic interaction networks: better understand to better predict

PubMed Central

Boucher, Benjamin; Jenna, Sarah

2013-01-01

A genetic interaction (GI) between two genes generally indicates that the phenotype of a double mutant differs from what is expected from each individual mutant. In the last decade, genome scale studies of quantitative GIs were completed using mainly synthetic genetic array technology and RNA interference in yeast and Caenorhabditis elegans. These studies raised questions regarding the functional interpretation of GIs, the relationship of genetic and molecular interaction networks, the usefulness of GI networks to infer gene function and co-functionality, the evolutionary conservation of GI, etc. While GIs have been used for decades to dissect signaling pathways in genetic models, their functional interpretations are still not trivial. The existence of a GI between two genes does not necessarily imply that these two genes code for interacting proteins or that the two genes are even expressed in the same cell. In fact, a GI only implies that the two genes share a functional relationship. These two genes may be involved in the same biological process or pathway; or they may also be involved in compensatory pathways with unrelated apparent function. Considering the powerful opportunity to better understand gene function, genetic relationship, robustness and evolution, provided by a genome-wide mapping of GIs, several in silico approaches have been employed to predict GIs in unicellular and multicellular organisms. Most of these methods used weighted data integration. In this article, we will review the later knowledge acquired on GI networks in metazoans by looking more closely into their relationship with pathways, biological processes and molecular complexes but also into their modularity and organization. We will also review the different in silico methods developed to predict GIs and will discuss how the knowledge acquired on GI networks can be used to design predictive tools with higher performances. PMID:24381582

Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks

NASA Astrophysics Data System (ADS)

Raff, L. M.; Malshe, M.; Hagan, M.; Doughan, D. I.; Rockley, M. G.; Komanduri, R.

2005-02-01

A neural network/trajectory approach is presented for the development of accurate potential-energy hypersurfaces that can be utilized to conduct ab initio molecular dynamics (AIMD) and Monte Carlo studies of gas-phase chemical reactions, nanometric cutting, and nanotribology, and of a variety of mechanical properties of importance in potential microelectromechanical systems applications. The method is sufficiently robust that it can be applied to a wide range of polyatomic systems. The overall method integrates ab initio electronic structure calculations with importance sampling techniques that permit the critical regions of configuration space to be determined. The computed ab initio energies and gradients are then accurately interpolated using neural networks (NN) rather than arbitrary parametrized analytical functional forms, moving interpolation or least-squares methods. The sampling method involves a tight integration of molecular dynamics calculations with neural networks that employ early stopping and regularization procedures to improve network performance and test for convergence. The procedure can be initiated using an empirical potential surface or direct dynamics. The accuracy and interpolation power of the method has been tested for two cases, the global potential surface for vinyl bromide undergoing unimolecular decomposition via four different reaction channels and nanometric cutting of silicon. The results show that the sampling methods permit the important regions of configuration space to be easily and rapidly identified, that convergence of the NN fit to the ab initio electronic structure database can be easily monitored, and that the interpolation accuracy of the NN fits is excellent, even for systems involving five atoms or more. The method permits a substantial computational speed and accuracy advantage over existing methods, is robust, and relatively easy to implement.

Cholecystokinin: A multi-functional molecular switch of neuronal circuits

PubMed Central

Lee, Soo Yeun; Soltesz, Ivan

2010-01-01

Cholecystokinin (CCK), a peptide originally discovered in the gastrointestinal tract, is one of the most the abundant and widely distributed neuropeptides in the brain. In spite of its abundance, recent data indicate that that CCK modulates intrinsic neuronal excitability and synaptic transmission in a surprisingly cell-type specific manner, acting as a key molecular switch to regulate the functional output of neuronal circuits. The central importance of CCK in neuronal networks is also reflected in its involvement in a variety of neuropsychiatric and neurological disorders including panic attacks and epilepsy. PMID:21154912

A network approach to predict pathogenic genes for Fusarium graminearum.

PubMed

Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

2010-10-04

Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which demonstrate the effectiveness of the proposed method. The results presented in this paper not only can provide guidelines for future experimental verification, but also shed light on the pathogenesis of the destructive fungus F. graminearum.

Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

PubMed

Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

2013-12-01

To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advanced Polymer Network Structures

DTIC Science & Technology

2016-02-01

double networks in a single step was identified from coarse-grained molecular dynamics simulations of polymer solvents bearing rigid side chains dissolved...in a polymer network. Coarse-grained molecular dynamics simulations also explored the mechanical behavior of traditional double networks and...DRI), polymer networks, polymer gels, molecular dynamics simulations , double networks 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

The study on serum and urine of renal interstitial fibrosis rats induced by unilateral ureteral obstruction based on metabonomics and network analysis methods.

PubMed

Xiang, Zheng; Sun, Hao; Cai, Xiaojun; Chen, Dahui

2016-04-01

Transmission of biological information is a biochemical process of multistep cascade from genes/proteins to metabolites. However, because most metabolites reflect the terminal information of the biochemical process, it is difficult to describe the transmission process of disease information in terms of the metabolomics strategy. In this paper, by incorporating network and metabolomics methods, an integrated approach was proposed to systematically investigate and explain the molecular mechanism of renal interstitial fibrosis. Through analysis of the network, the cascade transmission process of disease information starting from genes/proteins to metabolites was putatively identified and uncovered. The results indicated that renal fibrosis was involved in metabolic pathways of glycerophospholipid metabolism, biosynthesis of unsaturated fatty acids and arachidonic acid metabolism, riboflavin metabolism, tyrosine metabolism, and sphingolipid metabolism. These pathways involve kidney disease genes such as TGF-β1 and P2RX7. Our results showed that combining metabolomics and network analysis can provide new strategies and ideas for the interpretation of pathogenesis of disease with full consideration of "gene-protein-metabolite."

Network Analysis Implicates Alpha-Synuclein (Snca) in the Regulation of Ovariectomy-Induced Bone Loss

PubMed Central

Calabrese, Gina; Mesner, Larry D.; Foley, Patricia L.; Rosen, Clifford J.; Farber, Charles R.

2016-01-01

The postmenopausal period in women is associated with decreased circulating estrogen levels, which accelerate bone loss and increase the risk of fracture. Here, we gained novel insight into the molecular mechanisms mediating bone loss in ovariectomized (OVX) mice, a model of human menopause, using co-expression network analysis. Specifically, we generated a co-expression network consisting of 53 gene modules using expression profiles from intact and OVX mice from a panel of inbred strains. The expression of four modules was altered by OVX, including module 23 whose expression was decreased by OVX across all strains. Module 23 was enriched for genes involved in the response to oxidative stress, a process known to be involved in OVX-induced bone loss. Additionally, module 23 homologs were co-expressed in human bone marrow. Alpha synuclein (Snca) was one of the most highly connected “hub” genes in module 23. We characterized mice deficient in Snca and observed a 40% reduction in OVX-induced bone loss. Furthermore, protection was associated with the altered expression of specific network modules, including module 23. In summary, the results of this study suggest that Snca regulates bone network homeostasis and ovariectomy-induced bone loss. PMID:27378017

Prospects of engineering thermotolerance in crops through modulation of heat stress transcription factor and heat shock protein networks.

PubMed

Fragkostefanakis, Sotirios; Röth, Sascha; Schleiff, Enrico; Scharf, Klaus-Dieter

2015-09-01

Cell survival under high temperature conditions involves the activation of heat stress response (HSR), which in principle is highly conserved among different organisms, but shows remarkable complexity and unique features in plant systems. The transcriptional reprogramming at higher temperatures is controlled by the activity of the heat stress transcription factors (Hsfs). Hsfs allow the transcriptional activation of HSR genes, among which heat shock proteins (Hsps) are best characterized. Hsps belong to multigene families encoding for molecular chaperones involved in various processes including maintenance of protein homeostasis as a requisite for optimal development and survival under stress conditions. Hsfs form complex networks to activate downstream responses, but are concomitantly subjected to cell-type-dependent feedback regulation through factor-specific physical and functional interactions with chaperones belonging to Hsp90, Hsp70 and small Hsp families. There is increasing evidence that the originally assumed specialized function of Hsf/chaperone networks in the HSR turns out to be a complex central stress response system that is involved in the regulation of a broad variety of other stress responses and may also have substantial impact on various developmental processes. Understanding in detail the function of such regulatory networks is prerequisite for sustained improvement of thermotolerance in important agricultural crops. © 2014 John Wiley & Sons Ltd.

Designing heavy metal oxide glasses with threshold properties from network rigidity

NASA Astrophysics Data System (ADS)

Chakraborty, Shibalik; Boolchand, P.; Malki, M.; Micoulaut, M.

2014-01-01

Here, we show that a new class of glasses composed of heavy metal oxides involving transition metals (V2O5-TeO2) can surprisingly be designed from very basic tools using topology and rigidity of their underlying molecular networks. When investigated as a function of composition, such glasses display abrupt changes in network packing and enthalpy of relaxation at Tg, underscoring presence of flexible to rigid elastic phase transitions. We find that these elastic phases are fully consistent with polaronic nature of electronic conductivity at high V2O5 content. Such observations have new implications for designing electronic glasses which differ from the traditional amorphous electrolytes having only mobile ions as charge carriers.

Designing heavy metal oxide glasses with threshold properties from network rigidity.

PubMed

Chakraborty, Shibalik; Boolchand, P; Malki, M; Micoulaut, M

2014-01-07

Here, we show that a new class of glasses composed of heavy metal oxides involving transition metals (V2O5-TeO2) can surprisingly be designed from very basic tools using topology and rigidity of their underlying molecular networks. When investigated as a function of composition, such glasses display abrupt changes in network packing and enthalpy of relaxation at Tg, underscoring presence of flexible to rigid elastic phase transitions. We find that these elastic phases are fully consistent with polaronic nature of electronic conductivity at high V2O5 content. Such observations have new implications for designing electronic glasses which differ from the traditional amorphous electrolytes having only mobile ions as charge carriers.

Gene expression, signal transduction pathways and functional networks associated with growth of sporadic vestibular schwannomas.

PubMed

Sass, Hjalte C R; Borup, Rehannah; Alanin, Mikkel; Nielsen, Finn Cilius; Cayé-Thomasen, Per

2017-01-01

The objective of this study was to determine global gene expression in relation to Vestibular schwannomas (VS) growth rate and to identify signal transduction pathways and functional molecular networks associated with growth. Repeated magnetic resonance imaging (MRI) prior to surgery determined tumor growth rate. Following tissue sampling during surgery, mRNA was extracted from 16 sporadic VS. Double stranded cDNA was synthesized from the mRNA and used as template for in vitro transcription reaction to synthesize biotin-labeled antisense cRNA, which was hybridized to Affymetrix HG-U133A arrays and analyzed by dChip software. Differential gene expression was defined as a 1.5-fold difference between fast and slow growing tumors (><0.5 ccm/year), employing a p-value <0.01. Deregulated transcripts were matched against established gene ontology. Ingenuity Pathway Analysis was used for identification of signal transduction pathways and functional molecular networks associated with tumor growth. In total 109 genes were deregulated in relation to tumor growth rate. Genes associated with apoptosis, growth and cell proliferation were deregulated. Gene ontology included regulation of the cell cycle, cell differentiation and proliferation, among other functions. Fourteen pathways were associated with tumor growth. Five functional molecular networks were generated. This first study on global gene expression in relation to vestibular schwannoma growth rate identified several genes, signal transduction pathways and functional networks associated with tumor progression. Specific genes involved in apoptosis, cell growth and proliferation were deregulated in fast growing tumors. Fourteen pathways were associated with tumor growth. Generated functional networks underlined the importance of the PI3K family, among others.

Glomerular pathology in Alport syndrome: a molecular perspective

PubMed Central

Cosgrove, Dominic

2012-01-01

We have known for some time that mutations in the genes encoding 3 of the 6 type IV collagen chains are the underlying defect responsible for both X-linked (where the COL4A5 gene is involved) and autosomal (where either COL4A3 or COL4A4 genes are involved) Alport syndrome. The result of these mutations is the absence of the sub-epithelial network of all three chains in the glomerular basement membrane (GBM) resulting, at maturity, in a type IV collagen GBM network comprised of only α1(IV) and α2(IV) chains. The altered GBM functions adequately in early life. Eventually there is onset of proteinuria associated with the classic and progressive irregular thickening, thinning, and splitting of the GBM, which culminates in end stage renal failure. We have learned much about the molecular events associated with disease onset and progression through the study of animal models for Alport syndrome, and have identified some potential therapeutic approaches that may serve to delay the onset or slow the progression of the disease. This review focuses on where we are in our understanding of the disease, where we need to go to understand the molecular triggers that set the process in motion, and what emergent therapeutic approaches show promise for ameliorating disease progression in the clinic. PMID:21455721

Organization of cis-acting regulatory elements in osmotic- and cold-stress-responsive promoters.

PubMed

Yamaguchi-Shinozaki, Kazuko; Shinozaki, Kazuo

2005-02-01

cis-Acting regulatory elements are important molecular switches involved in the transcriptional regulation of a dynamic network of gene activities controlling various biological processes, including abiotic stress responses, hormone responses and developmental processes. In particular, understanding regulatory gene networks in stress response cascades depends on successful functional analyses of cis-acting elements. The ever-improving accuracy of transcriptome expression profiling has led to the identification of various combinations of cis-acting elements in the promoter regions of stress-inducible genes involved in stress and hormone responses. Here we discuss major cis-acting elements, such as the ABA-responsive element (ABRE) and the dehydration-responsive element/C-repeat (DRE/CRT), that are a vital part of ABA-dependent and ABA-independent gene expression in osmotic and cold stress responses.

Networks and tuberculosis: an undetected community outbreak involving public places.

PubMed

Klovdahl, A S; Graviss, E A; Yaganehdoost, A; Ross, M W; Wanger, A; Adams, G J; Musser, J M

2001-03-01

After decades of decline in developed countries, there was a resurgence of tuberculosis in the mid-1980s accompanied by increased recognition that this infectious disease has long remained a major public health problem at the global level. New methods from molecular biology, in particular DNA 'fingerprinting' (of Mycobacterium tuberculosis), made it clear that current transmission and recent infection (in contrast to reactivation of earlier, latent infection) were much more significant than previously believed. Studies of tuberculosis outbreaks using these new tools pointed to complex networks through which infection was spreading and highlighted the need for new approaches to outbreak investigation and disease control. In the study reported here a new approach--combining methods from molecular biology, epidemiology and network analysis--was used to examine an outbreak of tuberculosis in Houston, Texas. Initial investigation using conventional strategies revealed few contacts among 37 patients with identical (six-band) DNA (IS6110-based) fingerprints but subsequent research uncovered over 40 places (including many gay bars) to which patients in this outbreak could be linked. Network methods were used to reconstruct an outbreak network and to quantify the relative importance (here, 'betweenness' centrality) of different actors (persons and places) playing a role in the outbreak. The multidisciplinary work provides the basis for a new approach to outbreak investigation and disease control.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

Influence of Bulk PDMS Network Properties on Water Wettability

NASA Astrophysics Data System (ADS)

Melillo, Matthew; Walker, Edwin; Klein, Zoe; Efimenko, Kirill; Genzer, Jan

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine antifouling coatings to absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into PDMS networks is of critical importance for the design and use of another application - medical devices. We have systematically studied the effects of polymer molecular weight, loading of tetra-functional crosslinker, and end-group chemical functionality on the mechanical and surface properties of end-linked PDMS networks. Wettability was investigated through the sessile drop technique, wherein a DI water droplet was placed on the bulk network surface and droplet volume, shape, surface area, and contact angle were monitored as a function of time. Various silicone substrates ranging from incredibly soft and flexible materials (E' 50 kPa) to highly rigid networks (E' 5 MPa) were tested. The dynamic behavior of the droplet on the surfaces demonstrated equilibration times between the droplet and surface on the order of 5 minutes. Similar trends were observed for the commercial PDMS material, Sylgard-184. Our results have provided new evidence for the strong influence that substrate modulus and molecular network structure have on the wettability of PDMS elastomers. These findings will aid in the design and implementation of efficient, accurate, and safe PDMS-based medical devices and microfluidic materials that involve aqueous media.

The Brassinosteroid Signaling Pathway—New Key Players and Interconnections with Other Signaling Networks Crucial for Plant Development and Stress Tolerance

PubMed Central

Gruszka, Damian

2013-01-01

Brassinosteroids (BRs) are a class of steroid hormones regulating a wide range of physiological processes during the plant life cycle from seed development to the modulation of flowering and senescence. The last decades, and recent years in particular, have witnessed a significant advance in the elucidation of the molecular mechanisms of BR signaling from perception by the transmembrane receptor complex to the regulation of transcription factors influencing expression of the target genes. Application of the new approaches shed light on the molecular functions of the key players regulating the BR signaling cascade and allowed identification of new factors. Recent studies clearly indicated that some of the components of BR signaling pathway act as multifunctional proteins involved in other signaling networks regulating diverse physiological processes, such as photomorphogenesis, cell death control, stomatal development, flowering, plant immunity to pathogens and metabolic responses to stress conditions, including salinity. Regulation of some of these processes is mediated through a crosstalk between BR signalosome and the signaling cascades of other hormones, including auxin, abscisic acid, ethylene and salicylic acid. Unravelling the complicated mechanisms of BR signaling and its interconnections with other molecular networks may be of great importance for future practical applications in agriculture. PMID:23615468

Elements of the cellular metabolic structure

PubMed Central

De la Fuente, Ildefonso M.

2015-01-01

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell. PMID:25988183

Network based transcription factor analysis of regenerating axolotl limbs

PubMed Central

2011-01-01

Background Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. Results We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF) pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets). Network analysis showed that TGF-β1 and fibronectin (FN) lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1. Conclusions Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem cell markers in regeneration. PMID:21418574

Gene Expression Networks Underlying Ovarian Development in Wild Largemouth Bass (Micropterus salmoides)

PubMed Central

Martyniuk, Christopher J.; Prucha, Melinda S.; Doperalski, Nicholas J.; Antczak, Philipp; Kroll, Kevin J.; Falciani, Francesco; Barber, David S.; Denslow, Nancy D.

2013-01-01

Background Oocyte maturation in fish involves numerous cell signaling cascades that are activated or inhibited during specific stages of oocyte development. The objectives of this study were to characterize molecular pathways and temporal gene expression patterns throughout a complete breeding cycle in wild female largemouth bass to improve understanding of the molecular sequence of events underlying oocyte maturation. Methods Transcriptomic analysis was performed on eight morphologically diverse stages of the ovary, including primary and secondary stages of oocyte growth, ovulation, and atresia. Ovary histology, plasma vitellogenin, 17β-estradiol, and testosterone were also measured to correlate with gene networks. Results Global expression patterns revealed dramatic differences across ovarian development, with 552 and 2070 genes being differentially expressed during both ovulation and atresia respectively. Gene set enrichment analysis (GSEA) revealed that early primary stages of oocyte growth involved increases in expression of genes involved in pathways of B-cell and T-cell receptor-mediated signaling cascades and fibronectin regulation. These pathways as well as pathways that included adrenergic receptor signaling, sphingolipid metabolism and natural killer cell activation were down-regulated at ovulation. At atresia, down-regulated pathways included gap junction and actin cytoskeleton regulation, gonadotrope and mast cell activation, and vasopressin receptor signaling and up-regulated pathways included oxidative phosphorylation and reactive oxygen species metabolism. Expression targets for luteinizing hormone signaling were low during vitellogenesis but increased 150% at ovulation. Other networks found to play a significant role in oocyte maturation included those with genes regulated by members of the TGF-beta superfamily (activins, inhibins, bone morphogenic protein 7 and growth differentiation factor 9), neuregulin 1, retinoid X receptor, and nerve growth factor family. Conclusions This study offers novel insight into the gene networks underlying vitellogenesis, ovulation and atresia and generates new hypotheses about the cellular pathways regulating oocyte maturation. PMID:23527095

Investigation of naphthofuran moiety as potential dual inhibitor against BACE-1 and GSK-3β: molecular dynamics simulations, binding energy, and network analysis to identify first-in-class dual inhibitors against Alzheimer's disease.

PubMed

Kumar, Akhil; Srivastava, Gaurava; Srivastava, Swati; Verma, Seema; Negi, Arvind S; Sharma, Ashok

2017-08-01

BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.

Self-repairable polyurethane networks by atmospheric carbon dioxide and water.

PubMed

Yang, Ying; Urban, Marek W

2014-11-03

Sugar moieties were incorporated into cross-linked polyurethane (PUR) networks in an effort to achieve self-repairing in the presence of atmospheric carbon dioxide (CO2) and water (H2O). When methyl-α-D-glucopyranoside (MGP) molecules are reacted with hexamethylene diisocyanate trimer (HDI) and polyethylene glycol (PEG) to form cross-linked MGP-polyurethane (PUR) networks, these materials are capable of self-repairing in air. This process requires atmospheric amounts of CO2 and H2O, thus resembling plant behavior of carbon fixation during the photosynthesis cycle. Molecular processes responsible for this unique self-repair process involve physical diffusion of cleaved network segments as well as the formation of carbonate and urethane linkages. Unlike plants, MGP-PUR networks require no photo-initiated reactions, and they are thus capable of repair in darkness under atmospheric conditions. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly Conductive Ionic-Liquid Gels Prepared with Orthogonal Double Networks of a Low-Molecular-Weight Gelator and Cross-Linked Polymer.

PubMed

Kataoka, Toshikazu; Ishioka, Yumi; Mizuhata, Minoru; Minami, Hideto; Maruyama, Tatsuo

2015-10-21

We prepared a heterogeneous double-network (DN) ionogel containing a low-molecular-weight gelator network and a polymer network that can exhibit high ionic conductivity and high mechanical strength. An imidazolium-based ionic liquid was first gelated by the molecular self-assembly of a low-molecular-weight gelator (benzenetricarboxamide derivative), and methyl methacrylate was polymerized with a cross-linker to form a cross-linked poly(methyl methacrylate) (PMMA) network within the ionogel. Microscopic observation and calorimetric measurement revealed that the fibrous network of the low-molecular-weight gelator was maintained in the DN ionogel. The PMMA network strengthened the ionogel of the low-molecular-weight gelator and allowed us to handle the ionogel using tweezers. The orthogonal DNs produced ionogels with a broad range of storage elastic moduli. DN ionogels with low PMMA concentrations exhibited high ionic conductivity that was comparable to that of a neat ionic liquid. The present study demonstrates that the ionic conductivities of the DN and single-network, low-molecular-weight gelator or polymer ionogels strongly depended on their storage elastic moduli.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

NASA Astrophysics Data System (ADS)

Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Plasticity of gene-regulatory networks controlling sex determination: of masters, slaves, usual suspects, newcomers, and usurpators.

PubMed

Herpin, Amaury; Schartl, Manfred

2015-10-01

Sexual dimorphism is one of the most pervasive and diverse features of animal morphology, physiology, and behavior. Despite the generality of the phenomenon itself, the mechanisms controlling how sex is determined differ considerably among various organismic groups, have evolved repeatedly and independently, and the underlying molecular pathways can change quickly during evolution. Even within closely related groups of organisms for which the development of gonads on the morphological, histological, and cell biological level is undistinguishable, the molecular control and the regulation of the factors involved in sex determination and gonad differentiation can be substantially different. The biological meaning of the high molecular plasticity of an otherwise common developmental program is unknown. While comparative studies suggest that the downstream effectors of sex-determining pathways tend to be more stable than the triggering mechanisms at the top, it is still unclear how conserved the downstream networks are and how all components work together. After many years of stasis, when the molecular basis of sex determination was amenable only in the few classical model organisms (fly, worm, mouse), recently, sex-determining genes from several animal species have been identified and new studies have elucidated some novel regulatory interactions and biological functions of the downstream network, particularly in vertebrates. These data have considerably changed our classical perception of a simple linear developmental cascade that makes the decision for the embryo to develop as male or female, and how it evolves. © 2015 The Authors.

Semi-Automated Curation Allows Causal Network Model Building for the Quantification of Age-Dependent Plaque Progression in ApoE-/- Mouse.

PubMed

Szostak, Justyna; Martin, Florian; Talikka, Marja; Peitsch, Manuel C; Hoeng, Julia

2016-01-01

The cellular and molecular mechanisms behind the process of atherosclerotic plaque destabilization are complex, and molecular data from aortic plaques are difficult to interpret. Biological network models may overcome these difficulties and precisely quantify the molecular mechanisms impacted during disease progression. The atherosclerosis plaque destabilization biological network model was constructed with the semiautomated curation pipeline, BELIEF. Cellular and molecular mechanisms promoting plaque destabilization or rupture were captured in the network model. Public transcriptomic data sets were used to demonstrate the specificity of the network model and to capture the different mechanisms that were impacted in ApoE -/- mouse aorta at 6 and 32 weeks. We concluded that network models combined with the network perturbation amplitude algorithm provide a sensitive, quantitative method to follow disease progression at the molecular level. This approach can be used to investigate and quantify molecular mechanisms during plaque progression.

Cellular and synaptic network defects in autism

PubMed Central

Peça, João; Feng, Guoping

2012-01-01

Many candidate genes are now thought to confer susceptibility to autism spectrum disorder (ASD). Here we review four interrelated complexes, each composed of multiple families of genes that functionally coalesce on common cellular pathways. We illustrate a common thread in the organization of glutamatergic synapses and suggest a link between genes involved in Tuberous Sclerosis Complex, Fragile X syndrome, Angelman syndrome and several synaptic ASD candidate genes. When viewed in this context, progress in deciphering the molecular architecture of cellular protein-protein interactions together with the unraveling of synaptic dysfunction in neural networks may prove pivotal to advancing our understanding of ASDs. PMID:22440525

The Hedgehog-GLI pathway in embryonic development and cancer: implications for pulmonary oncology therapy

PubMed Central

Armas-López, Leonel; Zúñiga, Joaquín; Arrieta, Oscar; Ávila-Moreno, Federico

2017-01-01

Transcriptional regulation and epigenetic mechanisms closely control gene expression through diverse physiological and pathophysiological processes. These include the development of germ layers and post-natal epithelial cell-tissue differentiation, as well as, involved with the induction, promotion and/or progression of human malignancies. Diverse studies have shed light on the molecular similarities and differences involved in the stages of embryological epithelial development and dedifferentiation processes in malignant tumors of epithelial origin, of which many focus on lung carcinomas. In lung cancer, several transcriptional, epigenetic and genetic aberrations have been described to partly arise from environmental risk factors, but ethnic genetic predisposition factors may also play a role. The classification of the molecular hallmarks of cancer has been essential to study and achieve a comprehensive view of the interaction networks between cell signaling pathways and functional roles of the transcriptional and epigenetic regulatory mechanisms. This has in turn increased understanding on how these molecular networks are involved in embryo-layers and malignant diseases development. Ultimately, a major biomedicine goal is to achieve a thorough understanding of their roles as diagnostic, prognostic and treatment response indicators in lung oncological patients. Recently, several notable cell-signaling pathways have been studied based on their contribution to promoting and/or regulating the engagement of different cancer hallmarks, among them genome instability, exacerbated proliferative signaling, replicative immortality, tumor invasion-metastasis, inflammation, and immune-surveillance evasion mechanisms. Of these, the Hedgehog-GLI (Hh) cell-signaling pathway has been identified as a main molecular contribution into several of the abovementioned functional embryo-malignancy processes. Nonetheless, the systematic study of the regulatory epigenetic and transcriptional mechanisms has remained mostly unexplored, which could identify the interaction networks between specific biomarkers and/or new therapeutic targets in malignant tumor progression and resistance to lung oncologic therapy. In the present work, we aimed to revise the most important up-to-date experimental and clinical findings in biology, embryology and cancer research regarding the Hh pathway. We explore the potential control of the transcriptional-epigenetic programming versus reprogramming mechanisms associated with its Hh-GLI cell signaling pathway members. Last, we present a summary of this information to systematically integrate the Hh signaling pathway to identify and propose novel compound strategies or better oncological therapeutic schemes for lung cancer patients. PMID:28948003

Innate Immune Regulations and Liver Ischemia Reperfusion Injury

PubMed Central

Lu, Ling; Zhou, Haoming; Ni, Ming; Wang, Xuehao; Busuttil, Ronald; Kupiec-Weglinski, Jerzy; Zhai, Yuan

2016-01-01

Liver ischemia reperfusion activates innate immune system to drive the full development of inflammatory hepatocellular injury. Damage-associated molecular patterns (DAMPs) stimulate myeloid and dendritic cells via pattern recognition receptors (PRRs) to initiate the immune response. Complex intracellular signaling network transduces inflammatory signaling to regulate both innate immune cell activation and parenchymal cell death. Recent studies have revealed that DAMPs may trigger not only proinflammatory, but also immune regulatory responses by activating different PRRs or distinctive intracellular signaling pathways or in special cell populations. Additionally, tissue injury milieu activates PRR-independent receptors which also regulate inflammatory disease processes. Thus, the innate immune mechanism of liver IRI involves diverse molecular and cellular interactions, subjected to both endogenous and exogenous regulation in different cells. A better understanding of these complicated regulatory pathways/network is imperative for us in designing safe and effective therapeutic strategy to ameliorate liver IRI in patients. PMID:27861288

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

PubMed

Ni, Jingchao; Koyuturk, Mehmet; Tong, Hanghang; Haines, Jonathan; Xu, Rong; Zhang, Xiang

2016-11-10

Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity network and molecular networks such as protein interaction or gene co-expression networks. Although successful, a common limitation of the existing methods is that they assume all diseases share the same molecular network and a single generic molecular network is used to predict candidate genes for all diseases. However, different diseases tend to manifest in different tissues, and the molecular networks in different tissues are usually different. An ideal method should be able to incorporate tissue-specific molecular networks for different diseases. In this paper, we develop a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization. Our method allows each disease to have its own tissue-specific network(s). We formulate the problem of candidate gene prioritization as an optimization problem based on network propagation. When there are multiple tissue-specific networks available for a disease, our method can automatically infer the relative importance of each tissue-specific network. Thus it is robust to the noisy and incomplete network data. To solve the optimization problem, we develop fast algorithms which have linear time complexities in the number of nodes in the molecular networks. We also provide rigorous theoretical foundations for our algorithms in terms of their optimality and convergence properties. Extensive experimental results show that our method can significantly improve the accuracy of candidate gene prioritization compared with the state-of-the-art methods. In our experiments, we compare our methods with 7 popular network-based disease gene prioritization algorithms on diseases from Online Mendelian Inheritance in Man (OMIM) database. The experimental results demonstrate that our methods recover true associations more accurately than other methods in terms of AUC values, and the performance differences are significant (with paired t-test p-values less than 0.05). This validates the importance to integrate tissue-specific molecular networks for studying disease gene prioritization and show the superiority of our network models and ranking algorithms toward this purpose. The source code and datasets are available at http://nijingchao.github.io/CRstar/ .

Inferring protein domains associated with drug side effects based on drug-target interaction network.

PubMed

Iwata, Hiroaki; Mizutani, Sayaka; Tabei, Yasuo; Kotera, Masaaki; Goto, Susumu; Yamanishi, Yoshihiro

2013-01-01

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.

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.

Design Principles of Regulatory Networks: Searching for the Molecular Algorithms of the Cell

PubMed Central

Lim, Wendell A.; Lee, Connie M.; Tang, Chao

2013-01-01

A challenge in biology is to understand how complex molecular networks in the cell execute sophisticated regulatory functions. Here we explore the idea that there are common and general principles that link network structures to biological functions, principles that constrain the design solutions that evolution can converge upon for accomplishing a given cellular task. We describe approaches for classifying networks based on abstract architectures and functions, rather than on the specific molecular components of the networks. For any common regulatory task, can we define the space of all possible molecular solutions? Such inverse approaches might ultimately allow the assembly of a design table of core molecular algorithms that could serve as a guide for building synthetic networks and modulating disease networks. PMID:23352241

Molecular and epigenetic regulations and functions of the LAFL transcriptional regulators that control seed development.

PubMed

Lepiniec, L; Devic, M; Roscoe, T J; Bouyer, D; Zhou, D-X; Boulard, C; Baud, S; Dubreucq, B

2018-05-24

The LAFL (i.e. LEC1, ABI3, FUS3, and LEC2) master transcriptional regulators interact to form different complexes that induce embryo development and maturation, and inhibit seed germination and vegetative growth in Arabidopsis. Orthologous genes involved in similar regulatory processes have been described in various angiosperms including important crop species. Consistent with a prominent role of the LAFL regulators in triggering and maintaining embryonic cell fate, their expression appears finely tuned in different tissues during seed development and tightly repressed in vegetative tissues by a surprisingly high number of genetic and epigenetic factors. Partial functional redundancies and intricate feedback regulations of the LAFL have hampered the elucidation of the underpinning molecular mechanisms. Nevertheless, genetic, genomic, cellular, molecular, and biochemical analyses implemented during the last years have greatly improved our knowledge of the LALF network. Here we summarize and discuss recent progress, together with current issues required to gain a comprehensive insight into the network, including the emerging function of LEC1 and possibly LEC2 as pioneer transcription factors.

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

Deep Brain Stimulation

PubMed Central

Lyketsos, Constantine G.; Pendergrass, Jo Cara; Lozano, Andres M.

2012-01-01

Recent studies have identified an association between memory deficits and defects of the integrated neuronal cortical areas known collectively as the default mode network. It is conceivable that the amyloid deposition or other molecular abnormalities seen in patients with Alzheimer’s disease may interfere with this network and disrupt neuronal circuits beyond the localized brain areas. Therefore, Alzheimer’s disease may be both a degenerative disease and a broader system-level disorder affecting integrated neuronal pathways involved in memory. In this paper, we describe the rationale and provide some evidence to support the study of deep brain stimulation of the hippocampal fornix as a novel treatment to improve neuronal circuitry within these integrated networks and thereby sustain memory function in early Alzheimer’s disease. PMID:23346514

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

Protein-Protein Interface and Disease: Perspective from Biomolecular Networks.

PubMed

Hu, Guang; Xiao, Fei; Li, Yuqian; Li, Yuan; Vongsangnak, Wanwipa

Protein-protein interactions are involved in many important biological processes and molecular mechanisms of disease association. Structural studies of interfacial residues in protein complexes provide information on protein-protein interactions. Characterizing protein-protein interfaces, including binding sites and allosteric changes, thus pose an imminent challenge. With special focus on protein complexes, approaches based on network theory are proposed to meet this challenge. In this review we pay attention to protein-protein interfaces from the perspective of biomolecular networks and their roles in disease. We first describe the different roles of protein complexes in disease through several structural aspects of interfaces. We then discuss some recent advances in predicting hot spots and communication pathway analysis in terms of amino acid networks. Finally, we highlight possible future aspects of this area with respect to both methodology development and applications for disease treatment.

2-(4-Hy-droxy-phen-yl)-1H-benzimidazol-3-ium chloride monohydrate.

PubMed

González-Padilla, Jazmin E; Rosales-Hernández, Martha Cecila; Padilla-Martínez, Itzia I; García-Báez, Efren V; Rojas-Lima, Susana

2013-01-01

The title mol-ecular salt, C13H11N2O(+)·Cl(-)·H2O, crystallizes as a monohydrate. In the cation, the phenol and benzimidazole rings are almost coplanar, making a dihedral angle of 3.18 (4)°. The chloride anion and benzimidazole cation are linked by two N(+)-H⋯Cl(-) hydrogen bonds, forming chains propagating along [010]. These chains are linked through O-H⋯Cl hydrogen bonds involving the water mol-ecule and the chloride anion, which form a diamond core, giving rise to the formation of two-dimensional networks lying parallel to (10-2). Two π-π inter-actions involving the imidazolium ring with the benzene and phenol rings [centroid-centroid distances = 3.859 (3) and 3.602 (3) Å, respectively], contribute to this second dimension. A strong O-H⋯O hydrogen bond involving the water mol-ecule and the phenol substituent on the benzimidazole unit links the networks, forming a three-dimensional structure.

Host-Guest Chemistry in Integrated Porous Space Formed by Molecular Self-Assembly at Liquid-Solid Interfaces.

PubMed

Iritani, Kohei; Tahara, Kazukuni; De Feyter, Steven; Tobe, Yoshito

2017-05-16

Host-guest chemistry in two-dimensional (2D) space, that is, physisorbed monolayers of a single atom or a single molecular thickness on surfaces, has become a subject of intense current interest because of perspectives for various applications in molecular-scale electronics, selective sensors, and tailored catalysis. Scanning tunneling microscopy has been used as a powerful tool for the visualization of molecules in real space on a conducting substrate surface. For more than a decade, we have been investigating the self-assembly of a series of triangle-shaped phenylene-ethynylene macrocycles called dehydrobenzo[12]annulenes (DBAs). These molecules are substituted with six alkyl chains and are capable of forming hexagonal porous 2D molecular networks via van der Waals interactions between interdigitated alkyl chains at the interface of organic solvents and graphite. The dimension of the nanoporous space or nanowell formed by the self-assembly of DBAs can be controlled from 1.6 to 4.7 nm by simply changing the alkyl chain length from C 6 to C 20 . Single molecules as well as homoclusters and heteroclusters are capable of coadsorbing within the host matrix using shape- and size-complementarity principles. Moreover, on the basis of the versatility of the DBA molecules that allows chemical modification of the alkyl chain terminals, we were able to decorate the interior space of the nanoporous networks with functional groups such as azobenzenedicarboxylic acid for photoresponsive guest adsorption/desorption or fluoroalkanes and tetraethylene glycol groups for selective guest binding by electrostatic interactions and zinc-porphyrin units for complexation with a guest by charge-transfer interactions. In this Feature Article, we describe the general aspects of molecular self-assembly at liquid/solid interfaces, followed by the formation of programmed porous molecular networks using rationally designed molecular building blocks. We focus on our own work involving host-guest chemistry in integrated nanoporous space that is modified for specific purposes.

Lightweight computational steering of very large scale molecular dynamics simulations

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

Beazley, D.M.; Lomdahl, P.S.

1996-09-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show howmore » this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.« less

NaviCom: a web application to create interactive molecular network portraits using multi-level omics data.

PubMed

Dorel, Mathurin; Viara, Eric; Barillot, Emmanuel; Zinovyev, Andrei; Kuperstein, Inna

2017-01-01

Human diseases such as cancer are routinely characterized by high-throughput molecular technologies, and multi-level omics data are accumulated in public databases at increasing rate. Retrieval and visualization of these data in the context of molecular network maps can provide insights into the pattern of regulation of molecular functions reflected by an omics profile. In order to make this task easy, we developed NaviCom, a Python package and web platform for visualization of multi-level omics data on top of biological network maps. NaviCom is bridging the gap between cBioPortal, the most used resource of large-scale cancer omics data and NaviCell, a data visualization web service that contains several molecular network map collections. NaviCom proposes several standardized modes of data display on top of molecular network maps, allowing addressing specific biological questions. We illustrate how users can easily create interactive network-based cancer molecular portraits via NaviCom web interface using the maps of Atlas of Cancer Signalling Network (ACSN) and other maps. Analysis of these molecular portraits can help in formulating a scientific hypothesis on the molecular mechanisms deregulated in the studied disease. NaviCom is available at https://navicom.curie.fr. © The Author(s) 2017. Published by Oxford University Press.

Bioinformatic Integration of Molecular Networks and Major Pathways Involved in Mice Cochlear and Vestibular Supporting Cells.

PubMed

Requena, Teresa; Gallego-Martinez, Alvaro; Lopez-Escamez, Jose A

2018-01-01

Background : Cochlear and vestibular epithelial non-hair cells (ENHCs) are the supporting elements of the cellular architecture in the organ of Corti and the vestibular neuroepithelium in the inner ear. Intercellular and cell-extracellular matrix interactions are essential to prevent an abnormal ion redistribution leading to hearing and vestibular loss. The aim of this study is to define the main pathways and molecular networks in the mouse ENHCs. Methods : We retrieved microarray and RNA-seq datasets from mouse epithelial sensory and non-sensory cells from gEAR portal (http://umgear.org/index.html) and obtained gene expression fold-change between ENHCs and non-epithelial cells (NECs) against HCs for each gene. Differentially expressed genes (DEG) with a log2 fold change between 1 and -1 were discarded. The remaining genes were selected to search for interactions using Ingenuity Pathway Analysis and STRING platform. Specific molecular networks for ENHCs in the cochlea and the vestibular organs were generated and significant pathways were identified. Results : Between 1723 and 1559 DEG were found in the mouse cochlear and vestibular tissues, respectively. Six main pathways showed enrichment in the supporting cells in both tissues: (1) "Inhibition of Matrix Metalloproteases"; (2) "Calcium Transport I"; (3) "Calcium Signaling"; (4) "Leukocyte Extravasation Signaling"; (5) "Signaling by Rho Family GTPases"; and (6) "Axonal Guidance Si". In the mouse cochlea, ENHCs showed a significant enrichment in 18 pathways highlighting "axonal guidance signaling (AGS)" ( p = 4.37 × 10 -8 ) and "RhoGDI Signaling" ( p = 3.31 × 10 -8 ). In the vestibular dataset, there were 20 enriched pathways in ENHCs, the most significant being "Leukocyte Extravasation Signaling" ( p = 8.71 × 10 -6 ), "Signaling by Rho Family GTPases" ( p = 1.20 × 10 -5 ) and "Calcium Signaling" ( p = 1.20 × 10 -5 ). Among the top ranked networks, the most biologically significant network contained the "auditory and vestibular system development and function" terms. We also found 108 genes showing tonotopic gene expression in the cochlear ENHCs. Conclusions : We have predicted the main pathways and molecular networks for ENHCs in the organ of Corti and vestibular neuroepithelium. These pathways will facilitate the design of molecular maps to select novel candidate genes for hearing or vestibular loss to conduct functional studies.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints.

PubMed

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D

2015-02-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

PubMed Central

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D.

2015-01-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern (“receptor fingerprint”), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. PMID:25243991

An interactive network of elastase, secretases, and PAR-2 protein regulates CXCR1 receptor surface expression on neutrophils.

PubMed

Bakele, Martina; Lotz-Havla, Amelie S; Jakowetz, Anja; Carevic, Melanie; Marcos, Veronica; Muntau, Ania C; Gersting, Soeren W; Hartl, Dominik

2014-07-25

CXCL8 (IL-8) recruits and activates neutrophils through the G protein-coupled chemokine receptor CXCR1. We showed previously that elastase cleaves CXCR1 and thereby impairs antibacterial host defense. However, the molecular intracellular machinery involved in this process remained undefined. Here we demonstrate by using flow cytometry, confocal microscopy, subcellular fractionation, co-immunoprecipitation, and bioluminescence resonance energy transfer that combined α- and γ-secretase activities are functionally involved in elastase-mediated regulation of CXCR1 surface expression on human neutrophils, whereas matrix metalloproteases are dispensable. We further demonstrate that PAR-2 is stored in mobilizable compartments in neutrophils. Bioluminescence resonance energy transfer and co-immunoprecipitation studies showed that secretases, PAR-2, and CXCR1 colocalize and physically interact in a novel protease/secretase-chemokine receptor network. PAR-2 blocking experiments provided evidence that elastase increased intracellular presenilin-1 expression through PAR-2 signaling. When viewed in combination, these studies establish a novel functional network of elastase, secretases, and PAR-2 that regulate CXCR1 expression on neutrophils. Interfering with this network could lead to novel therapeutic approaches in neutrophilic diseases, such as cystic fibrosis or rheumatoid arthritis.

An Interactive Network of Elastase, Secretases, and PAR-2 Protein Regulates CXCR1 Receptor Surface Expression on Neutrophils*

PubMed Central

Bakele, Martina; Lotz-Havla, Amelie S.; Jakowetz, Anja; Carevic, Melanie; Marcos, Veronica; Muntau, Ania C.; Gersting, Soeren W.; Hartl, Dominik

2014-01-01

CXCL8 (IL-8) recruits and activates neutrophils through the G protein-coupled chemokine receptor CXCR1. We showed previously that elastase cleaves CXCR1 and thereby impairs antibacterial host defense. However, the molecular intracellular machinery involved in this process remained undefined. Here we demonstrate by using flow cytometry, confocal microscopy, subcellular fractionation, co-immunoprecipitation, and bioluminescence resonance energy transfer that combined α- and γ-secretase activities are functionally involved in elastase-mediated regulation of CXCR1 surface expression on human neutrophils, whereas matrix metalloproteases are dispensable. We further demonstrate that PAR-2 is stored in mobilizable compartments in neutrophils. Bioluminescence resonance energy transfer and co-immunoprecipitation studies showed that secretases, PAR-2, and CXCR1 colocalize and physically interact in a novel protease/secretase-chemokine receptor network. PAR-2 blocking experiments provided evidence that elastase increased intracellular presenilin-1 expression through PAR-2 signaling. When viewed in combination, these studies establish a novel functional network of elastase, secretases, and PAR-2 that regulate CXCR1 expression on neutrophils. Interfering with this network could lead to novel therapeutic approaches in neutrophilic diseases, such as cystic fibrosis or rheumatoid arthritis. PMID:24914212

Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.

PubMed

Scarpa, Joseph R; Jiang, Peng; Losic, Bojan; Readhead, Ben; Gao, Vance D; Dudley, Joel T; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

2016-07-01

Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks, and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease. Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression, but the molecular mechanisms underlying this complex clinical presentation remain largely unknown. In the present work, we specifically examine the relationship between these psychiatric traits and Huntington's disease (HD) by identifying striatal transcriptional networks shared by HD, stress, and sleep phenotypes. First, we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD (GSE3790 from GEO) in a novel way. We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD, and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate. We validate this result in an independent HD cohort. Next, we computationally predict FOXO3 as a regulator of this network, and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis (TGFβ-FOXO3). We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large (n = 100) chronically stressed (B6xA/J)F2 mouse population that has been extensively phenotyped (328 stress- and sleep-related measurements), and we show that this striatal astrocyte network is correlated to sleep and stress traits, many of which are known to be altered in HD cohorts. We identify causal regulators of this network through Bayesian network analysis, and we highlight their relevance to motor, mood, and sleep traits through multiple in silico approaches, including an examination of their protein binding partners. Finally, we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus, a medical intervention thought to confer some therapeutic benefit to HD patients. In conclusion, we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis. Furthermore, we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD. By analyzing and integrating multiple independent datasets, we identify a point of molecular convergence between sleep, stress, and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression.

Force Exertion and Transmission in Cross-Linked Actin Networks

NASA Astrophysics Data System (ADS)

Stam, Samantha

Cells are responsive to external cues in their environment telling them to proliferate or migrate within their surrounding tissue. Sensing of cues that are mechanical in nature, such stiffness of a tissue or forces transmitted from other cells, is believed to involve the cytoskeleton of a cell. The cytoskeleton is a complex network of proteins consisting of polymers that provide structural support, motor proteins that remodel these structures, and many others. We do not yet have a complete understanding of how cytoskeletal components respond to either internal or external mechanical force and stiffness. Such an understanding should involve mechanisms by which constituent molecules, such as motor proteins, are responsive to mechanics. Additionally, physical models of how forces are transmitted through biopolymer networks are necessary. My research has focused on networks formed by the cytoskeletal filament actin and the molecular motor protein myosin II. Actin filaments form networks and bundles that form a structural framework of the cell, and myosin II slides actin filaments. In this thesis, we show that stiffness of an elastic load that opposes myosin-generated actin sliding has a very sharp effect on the myosin force output in simulations. Secondly, we show that the stiffness and connectivity of cytoskeletal filaments regulates the contractility and anisotropy of network deformations that transmit force on material length scales. Together, these results have implications for predicting and interpreting the deformations and forces in biopolymeric active materials.

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

PubMed

Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

2017-02-01

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

Topology of molecular interaction networks.

PubMed

Winterbach, Wynand; Van Mieghem, Piet; Reinders, Marcel; Wang, Huijuan; de Ridder, Dick

2013-09-16

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks.Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs.Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes.Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further.

Topology of molecular interaction networks

PubMed Central

2013-01-01

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks. Initial studies suggested that molecular interaction network topology is related to biological function and evolution. However, further whole-network analyses did not lead to a unified view on what this relation may look like, with conclusions highly dependent on the type of molecular interactions considered and the metrics used to study them. It is unclear whether global network topology drives function, as suggested by some researchers, or whether it is simply a byproduct of evolution or even an artefact of representing complex molecular interaction networks as graphs. Nevertheless, network biology has progressed significantly over the last years. We review the literature, focusing on two major developments. First, realizing that molecular interaction networks can be naturally decomposed into subsystems (such as modules and pathways), topology is increasingly studied locally rather than globally. Second, there is a move from a descriptive approach to a predictive one: rather than correlating biological network topology to generic properties such as robustness, it is used to predict specific functions or phenotypes. Taken together, this change in focus from globally descriptive to locally predictive points to new avenues of research. In particular, multi-scale approaches are developments promising to drive the study of molecular interaction networks further. PMID:24041013

Mapping biological process relationships and disease perturbations within a pathway network.

PubMed

Stoney, Ruth; Robertson, David L; Nenadic, Goran; Schwartz, Jean-Marc

2018-01-01

Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network. Pathways represent spatial and temporal sets of context-dependent interactions, generating a high-level network when linked together, which incorporates contextual information without the need for molecular interaction data. Analysis of the pathway network revealed linked communities representing functional relationships, comparable to those found in molecular networks, including metabolism, signaling, immunity, and the cell cycle. We mapped a range of diseases onto this network and find that pathways associated with diseases tend to be functionally connected, highlighting the perturbed functions that result in disease phenotypes. We demonstrated that disease pathways cluster within the network. We then examined the distribution of cancer pathways and showed that cancer pathways tend to localize within the signaling, DNA processes and immune modules, although some cancer-associated nodes are found in other network regions. Altogether, we generated a high-confidence functional network, which avoids some of the shortcomings faced by conventional molecular models. Our representation provides an intuitive functional interpretation of cellular organization, which relies only on high-quality pathway and Gene Ontology data. The network is available at https://data.mendeley.com/datasets/3pbwkxjxg9/1.

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

PubMed Central

Mäkinen, Ville-Petteri; Civelek, Mete; Meng, Qingying; Zhang, Bin; Zhu, Jun; Levian, Candace; Huan, Tianxiao; Segrè, Ayellet V.; Ghosh, Sujoy; Vivar, Juan; Nikpay, Majid; Stewart, Alexandre F. R.; Nelson, Christopher P.; Willenborg, Christina; Erdmann, Jeanette; Blakenberg, Stefan; O'Donnell, Christopher J.; März, Winfried; Laaksonen, Reijo; Epstein, Stephen E.; Kathiresan, Sekar; Shah, Svati H.; Hazen, Stanley L.; Reilly, Muredach P.; Lusis, Aldons J.; Samani, Nilesh J.; Schunkert, Heribert; Quertermous, Thomas; McPherson, Ruth; Yang, Xia; Assimes, Themistocles L.

2014-01-01

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions. PMID:25033284

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.

Preparation Details for Making Silicones: Influence of Molecular Network Architecture on Mechanical and Surface Properties of PDMS Elastomers

NASA Astrophysics Data System (ADS)

Melillo, Matthew; Walker, Edwin; Klein, Zoe; Efimenko, Kirill; Genzer, Jan

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from medical devices to absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into PDMS networks is of critical importance for the design and use of another application - microfluidic devices. We have systematically studied the effects of polymer molecular weight, loading of tetra-functional crosslinker, end-group chemical functionality, the extent of dilution of the curing mixture, and gelation kinetics on the mechanical and surface properties of end-linked PDMS networks. The gel and sol fractions, storage and loss moduli, liquid swelling ratios, and water contact angles have all been shown to vary greatly based on the aforementioned variables. Similar trends were observed for the commercial PDMS material, Sylgard-184. Our results have confirmed theories predicting the relationships between modulus and swelling and we've also applied the theory of Macosko-Miller to estimate extent of reaction of crosslinker and polymer groups. Methods for determining the molecular weight between crosslinks from swelling, mechanical, and gelation theories were applied to ascertain their similarities and differences in an effort to identify the most accurate method. These findings will aid in the design and implementation of efficient microfluidics and other PDMS-based materials that involve the transport of liquids.

Molecular mechanisms of aging and immune system regulation in Drosophila.

PubMed

Eleftherianos, Ioannis; Castillo, Julio Cesar

2012-01-01

Aging is a complex process that involves the accumulation of deleterious changes resulting in overall decline in several vital functions, leading to the progressive deterioration in physiological condition of the organism and eventually causing disease and death. The immune system is the most important host-defense mechanism in humans and is also highly conserved in insects. Extensive research in vertebrates has concluded that aging of the immune function results in increased susceptibility to infectious disease and chronic inflammation. Over the years, interest has grown in studying the molecular interaction between aging and the immune response to pathogenic infections. The fruit fly Drosophila melanogaster is an excellent model system for dissecting the genetic and genomic basis of important biological processes, such as aging and the innate immune system, and deciphering parallel mechanisms in vertebrate animals. Here, we review the recent advances in the identification of key players modulating the relationship between molecular aging networks and immune signal transduction pathways in the fly. Understanding the details of the molecular events involved in aging and immune system regulation will potentially lead to the development of strategies for decreasing the impact of age-related diseases, thus improving human health and life span.

Molecular Mechanisms of Aging and Immune System Regulation in Drosophila

PubMed Central

Eleftherianos, Ioannis; Castillo, Julio Cesar

2012-01-01

Aging is a complex process that involves the accumulation of deleterious changes resulting in overall decline in several vital functions, leading to the progressive deterioration in physiological condition of the organism and eventually causing disease and death. The immune system is the most important host-defense mechanism in humans and is also highly conserved in insects. Extensive research in vertebrates has concluded that aging of the immune function results in increased susceptibility to infectious disease and chronic inflammation. Over the years, interest has grown in studying the molecular interaction between aging and the immune response to pathogenic infections. The fruit fly Drosophila melanogaster is an excellent model system for dissecting the genetic and genomic basis of important biological processes, such as aging and the innate immune system, and deciphering parallel mechanisms in vertebrate animals. Here, we review the recent advances in the identification of key players modulating the relationship between molecular aging networks and immune signal transduction pathways in the fly. Understanding the details of the molecular events involved in aging and immune system regulation will potentially lead to the development of strategies for decreasing the impact of age-related diseases, thus improving human health and life span. PMID:22949833

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

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP.

PubMed

Twig, Gilad; Graf, Solomon A; Wikstrom, Jakob D; Mohamed, Hibo; Haigh, Sarah E; Elorza, Alvaro; Deutsch, Motti; Zurgil, Naomi; Reynolds, Nicole; Shirihai, Orian S

2006-07-01

Assembly of mitochondria into networks supports fuel metabolism and calcium transport and is involved in the cellular response to apoptotic stimuli. A mitochondrial network is defined as a continuous matrix lumen whose boundaries limit molecular diffusion. Observation of individual networks has proven challenging in live cells that possess dense populations of mitochondria. Investigation into the electrical and morphological properties of mitochondrial networks has therefore not yielded consistent conclusions. In this study we used matrix-targeted, photoactivatable green fluorescent protein to tag single mitochondrial networks. This approach, coupled with real-time monitoring of mitochondrial membrane potential, permitted the examination of matrix lumen continuity and fusion and fission events over time. We found that adjacent and intertwined mitochondrial structures often represent a collection of distinct networks. We additionally found that all areas of a single network are invariably equipotential, suggesting that a heterogeneous pattern of membrane potential within a cell's mitochondria represents differences between discrete networks. Interestingly, fission events frequently occurred without any gross morphological changes and particularly without fragmentation. These events, which are invisible under standard confocal microscopy, redefine the mitochondrial network boundaries and result in electrically disconnected daughter units.

Water Molecules and Hydrogen-Bonded Networks in Bacteriorhodopsin—Molecular Dynamics Simulations of the Ground State and the M-Intermediate

PubMed Central

Grudinin, Sergei; Büldt, Georg; Gordeliy, Valentin; Baumgaertner, Artur

2005-01-01

Protein crystallography provides the structure of a protein, averaged over all elementary cells during data collection time. Thus, it has only a limited access to diffusive processes. This article demonstrates how molecular dynamics simulations can elucidate structure-function relationships in bacteriorhodopsin (bR) involving water molecules. The spatial distribution of water molecules and their corresponding hydrogen-bonded networks inside bR in its ground state (G) and late M intermediate conformations were investigated by molecular dynamics simulations. The simulations reveal a much higher average number of internal water molecules per monomer (28 in the G and 36 in the M) than observed in crystal structures (18 and 22, respectively). We found nine water molecules trapped and 19 diffusive inside the G-monomer, and 13 trapped and 23 diffusive inside the M-monomer. The exchange of a set of diffusive internal water molecules follows an exponential decay with a 1/e time in the order of 340 ps for the G state and 460 ps for the M state. The average residence time of a diffusive water molecule inside the protein is ∼95 ps for the G state and 110 ps for the M state. We have used the Grotthuss model to describe the possible proton transport through the hydrogen-bonded networks inside the protein, which is built up in the picosecond-to-nanosecond time domains. Comparing the water distribution and hydrogen-bonded networks of the two different states, we suggest possible pathways for proton hopping and water movement inside bR. PMID:15731388

A physical sciences network characterization of non-tumorigenic and metastatic cells

PubMed Central

Agus, David B.; Alexander, Jenolyn F.; Arap, Wadih; Ashili, Shashanka; Aslan, Joseph E.; Austin, Robert H.; Backman, Vadim; Bethel, Kelly J.; Bonneau, Richard; Chen, Wei-Chiang; Chen-Tanyolac, Chira; Choi, Nathan C.; Curley, Steven A.; Dallas, Matthew; Damania, Dhwanil; Davies, Paul C. W.; Decuzzi, Paolo; Dickinson, Laura; Estevez-Salmeron, Luis; Estrella, Veronica; Ferrari, Mauro; Fischbach, Claudia; Foo, Jasmine; Fraley, Stephanie I.; Frantz, Christian; Fuhrmann, Alexander; Gascard, Philippe; Gatenby, Robert A.; Geng, Yue; Gerecht, Sharon; Gillies, Robert J.; Godin, Biana; Grady, William M.; Greenfield, Alex; Hemphill, Courtney; Hempstead, Barbara L.; Hielscher, Abigail; Hillis, W. Daniel; Holland, Eric C.; Ibrahim-Hashim, Arig; Jacks, Tyler; Johnson, Roger H.; Joo, Ahyoung; Katz, Jonathan E.; Kelbauskas, Laimonas; Kesselman, Carl; King, Michael R.; Konstantopoulos, Konstantinos; Kraning-Rush, Casey M.; Kuhn, Peter; Kung, Kevin; Kwee, Brian; Lakins, Johnathon N.; Lambert, Guillaume; Liao, David; Licht, Jonathan D.; Liphardt, Jan T.; Liu, Liyu; Lloyd, Mark C.; Lyubimova, Anna; Mallick, Parag; Marko, John; McCarty, Owen J. T.; Meldrum, Deirdre R.; Michor, Franziska; Mumenthaler, Shannon M.; Nandakumar, Vivek; O’Halloran, Thomas V.; Oh, Steve; Pasqualini, Renata; Paszek, Matthew J.; Philips, Kevin G.; Poultney, Christopher S.; Rana, Kuldeepsinh; Reinhart-King, Cynthia A.; Ros, Robert; Semenza, Gregg L.; Senechal, Patti; Shuler, Michael L.; Srinivasan, Srimeenakshi; Staunton, Jack R.; Stypula, Yolanda; Subramanian, Hariharan; Tlsty, Thea D.; Tormoen, Garth W.; Tseng, Yiider; van Oudenaarden, Alexander; Verbridge, Scott S.; Wan, Jenny C.; Weaver, Valerie M.; Widom, Jonathan; Will, Christine; Wirtz, Denis; Wojtkowiak, Jonathan; Wu, Pei-Hsun

2013-01-01

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences–Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis. PMID:23618955

A physical sciences network characterization of non-tumorigenic and metastatic cells.

PubMed

Agus, David B; Alexander, Jenolyn F; Arap, Wadih; Ashili, Shashanka; Aslan, Joseph E; Austin, Robert H; Backman, Vadim; Bethel, Kelly J; Bonneau, Richard; Chen, Wei-Chiang; Chen-Tanyolac, Chira; Choi, Nathan C; Curley, Steven A; Dallas, Matthew; Damania, Dhwanil; Davies, Paul C W; Decuzzi, Paolo; Dickinson, Laura; Estevez-Salmeron, Luis; Estrella, Veronica; Ferrari, Mauro; Fischbach, Claudia; Foo, Jasmine; Fraley, Stephanie I; Frantz, Christian; Fuhrmann, Alexander; Gascard, Philippe; Gatenby, Robert A; Geng, Yue; Gerecht, Sharon; Gillies, Robert J; Godin, Biana; Grady, William M; Greenfield, Alex; Hemphill, Courtney; Hempstead, Barbara L; Hielscher, Abigail; Hillis, W Daniel; Holland, Eric C; Ibrahim-Hashim, Arig; Jacks, Tyler; Johnson, Roger H; Joo, Ahyoung; Katz, Jonathan E; Kelbauskas, Laimonas; Kesselman, Carl; King, Michael R; Konstantopoulos, Konstantinos; Kraning-Rush, Casey M; Kuhn, Peter; Kung, Kevin; Kwee, Brian; Lakins, Johnathon N; Lambert, Guillaume; Liao, David; Licht, Jonathan D; Liphardt, Jan T; Liu, Liyu; Lloyd, Mark C; Lyubimova, Anna; Mallick, Parag; Marko, John; McCarty, Owen J T; Meldrum, Deirdre R; Michor, Franziska; Mumenthaler, Shannon M; Nandakumar, Vivek; O'Halloran, Thomas V; Oh, Steve; Pasqualini, Renata; Paszek, Matthew J; Philips, Kevin G; Poultney, Christopher S; Rana, Kuldeepsinh; Reinhart-King, Cynthia A; Ros, Robert; Semenza, Gregg L; Senechal, Patti; Shuler, Michael L; Srinivasan, Srimeenakshi; Staunton, Jack R; Stypula, Yolanda; Subramanian, Hariharan; Tlsty, Thea D; Tormoen, Garth W; Tseng, Yiider; van Oudenaarden, Alexander; Verbridge, Scott S; Wan, Jenny C; Weaver, Valerie M; Widom, Jonathan; Will, Christine; Wirtz, Denis; Wojtkowiak, Jonathan; Wu, Pei-Hsun

2013-01-01

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.

A systems biology-based investigation into the therapeutic effects of Gansui Banxia Tang on reversing the imbalanced network of hepatocellular carcinoma

NASA Astrophysics Data System (ADS)

Zhang, Yanqiong; Guo, Xiaodong; Wang, Danhua; Li, Ruisheng; Li, Xiaojuan; Xu, Ying; Liu, Zhenli; Song, Zhiqian; Lin, Ya; Li, Zhiyan; Lin, Na

2014-02-01

Several complex molecular events are involved in tumorigenesis of hepatocellular carcinoma (HCC). The interactions of these molecules may constitute the HCC imbalanced network. Gansui Banxia Tang (GSBXT), as a classic Chinese herbal formula, is a popular complementary and alternative medicine modality for treating HCC. In order to investigate the therapeutic effects and the pharmacological mechanisms of GSBXT on reversing HCC imbalanced network, we in the current study developed a comprehensive systems approach of integrating disease-specific and drug-specific networks, and successfully revealed the relationships of the ingredients in GSBXT with their putative targets, and with HCC significant molecules and HCC related pathway systems for the first time. Meanwhile, further experimental validation also demonstrated the preventive effects of GSBXT on tumor growth in mice and its regulatory effects on potential targets.

Cell-cell recognition and social networking in bacteria

PubMed Central

Troselj, Vera; Cao, Pengbo; Wall, Daniel

2018-01-01

SUMMARY The ability to recognize self and to recognize partnering cells allows microorganisms to build social networks that perform functions beyond the capabilities of the individual. In bacteria, recognition typically involves genetic determinants that provide cell surface receptors or diffusible signaling chemicals to identify proximal cells at the molecular level that can participate in cooperative processes. Social networks also rely on discriminating mechanisms to exclude competing cells from joining and exploiting their groups. In addition to their appropriate genotypes, cell-cell recognition also requires compatible phenotypes, which vary according to environmental cues or exposures as well as stochastic processes that leads to heterogeneity and potential disharmony in the population. Understanding how bacteria identify their social partners and how they synchronize their behaviors to conduct multicellular functions is an expanding field of research. Here we review recent progress in the field and contrast the various strategies used in recognition and behavioral networking. PMID:29194914

A physical sciences network characterization of non-tumorigenic and metastatic cells

NASA Astrophysics Data System (ADS)

Physical Sciences-Oncology Centers Network; Agus, David B.; Alexander, Jenolyn F.; Arap, Wadih; Ashili, Shashanka; Aslan, Joseph E.; Austin, Robert H.; Backman, Vadim; Bethel, Kelly J.; Bonneau, Richard; Chen, Wei-Chiang; Chen-Tanyolac, Chira; Choi, Nathan C.; Curley, Steven A.; Dallas, Matthew; Damania, Dhwanil; Davies, Paul C. W.; Decuzzi, Paolo; Dickinson, Laura; Estevez-Salmeron, Luis; Estrella, Veronica; Ferrari, Mauro; Fischbach, Claudia; Foo, Jasmine; Fraley, Stephanie I.; Frantz, Christian; Fuhrmann, Alexander; Gascard, Philippe; Gatenby, Robert A.; Geng, Yue; Gerecht, Sharon; Gillies, Robert J.; Godin, Biana; Grady, William M.; Greenfield, Alex; Hemphill, Courtney; Hempstead, Barbara L.; Hielscher, Abigail; Hillis, W. Daniel; Holland, Eric C.; Ibrahim-Hashim, Arig; Jacks, Tyler; Johnson, Roger H.; Joo, Ahyoung; Katz, Jonathan E.; Kelbauskas, Laimonas; Kesselman, Carl; King, Michael R.; Konstantopoulos, Konstantinos; Kraning-Rush, Casey M.; Kuhn, Peter; Kung, Kevin; Kwee, Brian; Lakins, Johnathon N.; Lambert, Guillaume; Liao, David; Licht, Jonathan D.; Liphardt, Jan T.; Liu, Liyu; Lloyd, Mark C.; Lyubimova, Anna; Mallick, Parag; Marko, John; McCarty, Owen J. T.; Meldrum, Deirdre R.; Michor, Franziska; Mumenthaler, Shannon M.; Nandakumar, Vivek; O'Halloran, Thomas V.; Oh, Steve; Pasqualini, Renata; Paszek, Matthew J.; Philips, Kevin G.; Poultney, Christopher S.; Rana, Kuldeepsinh; Reinhart-King, Cynthia A.; Ros, Robert; Semenza, Gregg L.; Senechal, Patti; Shuler, Michael L.; Srinivasan, Srimeenakshi; Staunton, Jack R.; Stypula, Yolanda; Subramanian, Hariharan; Tlsty, Thea D.; Tormoen, Garth W.; Tseng, Yiider; van Oudenaarden, Alexander; Verbridge, Scott S.; Wan, Jenny C.; Weaver, Valerie M.; Widom, Jonathan; Will, Christine; Wirtz, Denis; Wojtkowiak, Jonathan; Wu, Pei-Hsun

2013-04-01

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.

Heat acclimation and cross-tolerance against novel stressors: genomic-physiological linkage.

PubMed

Horowitz, Michal

2007-01-01

Heat acclimation (AC) is a "within lifetime" reversible phenotypic adaptation, enhancing thermotolerance and heat endurance via a transition to "efficient" cellular performance when acclimatory homeostasis is reached. An inseparable outcome of AC is the development of cross-tolerance (C-T) against novel stressors. This chapter focuses on central plasticity and the molecular-physiological linkage of acclimatory and C-T responses. A drop in temperature thresholds (T-Tsh) for activation of heat-dissipation mechanisms and an elevated T-Tsh for thermal injury development imply autonomic nervous system (ANS) and cytoprotective network involvement in these processes. During acclimation, the changes in T-Tsh for heat dissipation are biphasic. Initially T-Tsh drops, signifying the early autonomic response, and is associated with perturbed peripheral effector cellular performance. Pre-acclimation values return when acclimatory homeostasis is achieved. The changes in the ANS suggest that acclimatory plasticity involves molecular and cellular changes. These changes are manifested by the activation of central peripheral molecular networks and post-translational modifications. Sympathetic induction of elevated HSP 72 reservoirs, with faster heat shock response, is only one example of this. The global genomic response, detected using gene-chips and cluster analyses imply upregulation of genes encoding ion channels, pumps, and transporters (markers for neuronal excitability) in the hypothalamus at the onset of AC and down regulation of metabotrophic genes upon long term AC. Peripherally, the transcriptional program indicates a two-tier defense strategy. The immediate transient response is associated with the maintenance of DNA and cellular integrity. The sustained response correlates with long-lasting cytoprotective-signaling networks. C-T is recorded against cerebral hypoxia, hyperoxia, and traumatic brain injury. Using the highly developed ischemic/reperfused heart model as a baseline, it is evident that C-T stems via protective shared pathways developed with AC. These comprise constitutive elevation of HIF 1alpha and associated target pathways, HSPs, anti-apoptosis, and antioxidative pathways. Collectively the master regulators of AC and C-T are still enigmatic; however, cutting-edge investigative techniques, using a broad molecular approach, challenge current ideas, and the data accumulated will pinpoint novel pathways and provide new perspectives.

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

Could ecosystem management provide a new framework for Alzheimer's disease?

PubMed

Hubin, Ellen; Vanschoenwinkel, Bram; Broersen, Kerensa; De Deyn, Peter P; Koedam, Nico; van Nuland, Nico A; Pauwels, Kris

2016-01-01

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder that involves a plethora of molecular pathways. In the context of therapeutic treatment and biomarker profiling, the amyloid-beta (Aβ) peptide constitutes an interesting research avenue that involves interactions within a complex mixture of Aβ alloforms and other disease-modifying factors. Here, we explore the potential of an ecosystem paradigm as a novel way to consider AD and Aβ dynamics in particular. We discuss the example that the complexity of the Aβ network not only exhibits interesting parallels with the functioning of complex systems such as ecosystems but that this analogy can also provide novel insights into the neurobiological phenomena in AD and serve as a communication tool. We propose that combining network medicine with general ecosystem management principles could be a new and holistic approach to understand AD pathology and design novel therapies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Experimental evolution of protein–protein interaction networks

PubMed Central

Kaçar, Betül; Gaucher, Eric A.

2013-01-01

The modern synthesis of evolutionary theory and genetics has enabled us to discover underlying molecular mechanisms of organismal evolution. We know that in order to maximize an organism's fitness in a particular environment, individual interactions among components of protein and nucleic acid networks need to be optimized by natural selection, or sometimes through random processes, as the organism responds to changes and/or challenges in the environment. Despite the significant role of molecular networks in determining an organism's adaptation to its environment, we still do not know how such inter- and intra-molecular interactions within networks change over time and contribute to an organism's evolvability while maintaining overall network functions. One way to address this challenge is to identify connections between molecular networks and their host organisms, to manipulate these connections, and then attempt to understand how such perturbations influence molecular dynamics of the network and thus influence evolutionary paths and organismal fitness. In the present review, we discuss how integrating evolutionary history with experimental systems that combine tools drawn from molecular evolution, synthetic biology and biochemistry allow us to identify the underlying mechanisms of organismal evolution, particularly from the perspective of protein interaction networks. PMID:23849056

Integration of Structural Dynamics and Molecular Evolution via Protein Interaction Networks: A New Era in Genomic Medicine

PubMed Central

Kumar, Avishek; Butler, Brandon M.; Kumar, Sudhir; Ozkan, S. Banu

2016-01-01

Summary Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. PMID:26684487

Early brain response to low-dose radiation exposure involves molecular networks and pathways associated with cognitive functions, advanced aging and Alzheimer's disease.

PubMed

Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J

2009-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy and environmental nuclear contamination as well as for Earth-orbit and space missions. Analyses of transcriptome profiles of mouse brain tissue after whole-body irradiation showed that low-dose exposures (10 cGy) induced genes not affected by high-dose radiation (2 Gy) and that low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues and pathways that were specific for brain tissue. Low-dose genes clustered into a saturated network (P < 10(-53)) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified nine neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose irradiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down-regulated in normal human aging and Alzheimer's disease.

Differential proteome profiling in the hippocampus of amnesic mice.

PubMed

Baghel, Meghraj Singh; Thakur, Mahendra Kumar

2017-08-01

Amnesia or memory loss is associated with brain aging and several neurodegenerative pathologies including Alzheimer's disease (AD). This can be induced by a cholinergic antagonist scopolamine but the underlying molecular mechanism is poorly understood. This study of proteome profiling in the hippocampus could provide conceptual insights into the molecular mechanisms involved in amnesia. To reveal this, mice were administered scopolamine to induce amnesia and memory impairment was validated by novel object recognition test. Using two-dimensional gel electrophoresis coupled with MALDI-MS/MS, we have analyzed the hippocampal proteome and identified 18 proteins which were differentially expressed. Out of these proteins, 11 were downregulated and 7 were upregulated in scopolamine-treated mice as compared to control. In silico analysis showed that the majority of identified proteins are involved in metabolism, catalytic activity, and cytoskeleton architectural functions. STRING interaction network analysis revealed that majority of identified proteins exhibit common association with Actg1 cytoskeleton and Vdac1 energy transporter protein. Furthermore, interaction map analysis showed that Fascin1 and Coronin 1b individually interact with Actg1 and regulate the actin filament dynamics. Vdac1 was significantly downregulated in amnesic mice and showed interaction with other proteins in interaction network. Therefore, we silenced Vdac1 in the hippocampus of normal young mice and found similar impairment in recognition memory of Vdac1 silenced and scopolamine-treated mice. Thus, these findings suggest that Vdac1-mediated disruption of energy metabolism and cytoskeleton architecture might be involved in scopolamine-induced amnesia. © 2017 Wiley Periodicals, Inc.

Neuropathic pain promotes adaptive changes in gene expression in brain networks involved in stress and depression.

PubMed

Descalzi, Giannina; Mitsi, Vasiliki; Purushothaman, Immanuel; Gaspari, Sevasti; Avrampou, Kleopatra; Loh, Yong-Hwee Eddie; Shen, Li; Zachariou, Venetia

2017-03-21

Neuropathic pain is a complex chronic condition characterized by various sensory, cognitive, and affective symptoms. A large percentage of patients with neuropathic pain are also afflicted with depression and anxiety disorders, a pattern that is also seen in animal models. Furthermore, clinical and preclinical studies indicate that chronic pain corresponds with adaptations in several brain networks involved in mood, motivation, and reward. Chronic stress is also a major risk factor for depression. We investigated whether chronic pain and stress affect similar molecular mechanisms and whether chronic pain can affect gene expression patterns that are involved in depression. Using two mouse models of neuropathic pain and depression [spared nerve injury (SNI) and chronic unpredictable stress (CUS)], we performed next-generation RNA sequencing and pathway analysis to monitor changes in gene expression in the nucleus accumbens (NAc), the medial prefrontal cortex (mPFC), and the periaqueductal gray (PAG). In addition to finding unique transcriptome profiles across these regions, we identified a substantial number of signaling pathway-associated genes with similar changes in expression in both SNI and CUS mice. Many of these genes have been implicated in depression, anxiety, and chronic pain in patients. Our study provides a resource of the changes in gene expression induced by long-term neuropathic pain in three distinct brain regions and reveals molecular connections between pain and chronic stress. Copyright © 2017, American Association for the Advancement of Science.

Weak Long-Range Correlated Motions in a Surface Patch of Ubiquitin Involved in Molecular Recognition

PubMed Central

2011-01-01

Long-range correlated motions in proteins are candidate mechanisms for processes that require information transfer across protein structures, such as allostery and signal transduction. However, the observation of backbone correlations between distant residues has remained elusive, and only local correlations have been revealed using residual dipolar couplings measured by NMR spectroscopy. In this work, we experimentally identified and characterized collective motions spanning four β-strands separated by up to 15 Å in ubiquitin. The observed correlations link molecular recognition sites and result from concerted conformational changes that are in part mediated by the hydrogen-bonding network. PMID:21634390

Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

PubMed Central

Engin, H. Billur; Guney, Emre; Keskin, Ozlem; Oliva, Baldo; Gursoy, Attila

2013-01-01

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the “guilt-by-association” principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis. PMID:24278371

Identification of the key regulating genes of diminished ovarian reserve (DOR) by network and gene ontology analysis.

PubMed

Pashaiasl, Maryam; Ebrahimi, Mansour; Ebrahimie, Esmaeil

2016-09-01

Diminished ovarian reserve (DOR) is one of the reasons for infertility that not only affects both older and young women. Ovarian reserve assessment can be used as a new prognostic tool for infertility treatment decision making. Here, up- and down-regulated gene expression profiles of granulosa cells were analysed to generate a putative interaction map of the involved genes. In addition, gene ontology (GO) analysis was used to get insight intol the biological processes and molecular functions of involved proteins in DOR. Eleven up-regulated genes and nine down-regulated genes were identified and assessed by constructing interaction networks based on their biological processes. PTGS2, CTGF, LHCGR, CITED, SOCS2, STAR and FSTL3 were the key nodes in the up-regulated networks, while the IGF2, AMH, GREM, and FOXC1 proteins were key in the down-regulated networks. MIRN101-1, MIRN153-1 and MIRN194-1 inhibited the expression of SOCS2, while CSH1 and BMP2 positively regulated IGF1 and IGF2. Ossification, ovarian follicle development, vasculogenesis, sequence-specific DNA binding transcription factor activity, and golgi apparatus are the major differential groups between up-regulated and down-regulated genes in DOR. Meta-analysis of publicly available transcriptomic data highlighted the high coexpression of CTGF, connective tissue growth factor, with the other key regulators of DOR. CTGF is involved in organ senescence and focal adhesion pathway according to GO analysis. These findings provide a comprehensive system biology based insight into the aetiology of DOR through network and gene ontology analyses.

Hydrogen Bond Networks and Hydrophobic Effects in the Amyloid β30-35 Chain in Water: A Molecular Dynamics Study.

PubMed

Jong, KwangHyok; Grisanti, Luca; Hassanali, Ali

2017-07-24

We have studied the conformational landscape of the C-terminal fragment of the amyloid protein Aβ 30-35 in water using well-tempered metadynamics simulations and found that it resembles an intrinsically disordered protein. The conformational fluctuations of the protein are facilitated by a collective reorganization of both protein and water hydrogen bond networks, combined with electrostatic interactions between termini as well as hydrophobic interactions of the side chains. The stabilization of hydrophobic interactions in one of the conformers involves a collective collapse of the side chains along with a squeeze-out of water sandwiched between them. The charged N- and C-termini play a critical role in stabilizing different types of protein conformations, including those involving contact-ion salt bridges as well as solvent-mediated interactions of the termini and the amide backbone. We have examined this by probing the distribution of directed water wires forming the hydrogen bond network enveloping the polypeptide. Water wires and their fluctuations form an integral part of structural signature of the protein conformation.

Role of Silicon on Plant–Pathogen Interactions

PubMed Central

Wang, Min; Gao, Limin; Dong, Suyue; Sun, Yuming; Shen, Qirong; Guo, Shiwei

2017-01-01

Although silicon (Si) is not recognized as an essential element for general higher plants, it has beneficial effects on the growth and production of a wide range of plant species. Si is known to effectively mitigate various environmental stresses and enhance plant resistance against both fungal and bacterial pathogens. In this review, the effects of Si on plant–pathogen interactions are analyzed, mainly on physical, biochemical, and molecular aspects. In most cases, the Si-induced biochemical/molecular resistance during plant–pathogen interactions were dominated as joint resistance, involving activating defense-related enzymes activates, stimulating antimicrobial compound production, regulating the complex network of signal pathways, and activating of the expression of defense-related genes. The most previous studies described an independent process, however, the whole plant resistances were rarely considered, especially the interaction of different process in higher plants. Si can act as a modulator influencing plant defense responses and interacting with key components of plant stress signaling systems leading to induced resistance. Priming of plant defense responses, alterations in phytohormone homeostasis, and networking by defense signaling components are all potential mechanisms involved in Si-triggered resistance responses. This review summarizes the roles of Si in plant–microbe interactions, evaluates the potential for improving plant resistance by modifying Si fertilizer inputs, and highlights future research concerning the role of Si in agriculture. PMID:28529517

Poly[[aqua­(μ2-oxalato)(μ2-2-oxido­pyridinium-3-carboxylato)holmium(III)] monohydrate

PubMed Central

Zhu, Hui-Lan; Lai, Hui-Ling; Han, Lu; Luo, Yi-Fan; Zeng, Rong-Hua

2009-01-01

In the title complex, {[Ho(C2O4)(C6H4NO3)(H2O)]·(H2O)}n, the HoIII ion is coordinated by three O atoms from two 2-oxidopyridinium-3-carboxylate ligands, four O atoms from two oxalate ligands and one water mol­ecule in a distorted bicapped trigonal-prismatic geometry. The 2-oxidopyridin­ium-3-carboxylate and oxalate ligands link the HoIII ions into a layer in (100). These layers are further connected by inter­molecular O—H⋯O hydrogen bonds involving the coordinated water mol­ecules to assemble a three-dimensional supra­molecular network. The uncoordin­ated water mol­ecule is involved in N—H⋯O and O—H⋯O hydrogen bonds within the layer. PMID:21577741

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study.

PubMed

Städler, Nicolas; Dondelinger, Frank; Hill, Steven M; Akbani, Rehan; Lu, Yiling; Mills, Gordon B; Mukherjee, Sach

2017-09-15

Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging. Furthermore, since network differences could provide important and biologically interpretable information to identify molecular subgroups, there is a need to consider the unsupervised task of learning subgroups and networks that define them. This is a nontrivial clustering problem, with neither subgroups nor subgroup-specific networks known at the outset. We leverage recent ideas from high-dimensional statistics for testing and clustering in the network biology setting. The methods we describe can be applied directly to most continuous molecular measurements and networks do not need to be specified beforehand. We illustrate the ideas and methods in a case study using protein data from The Cancer Genome Atlas (TCGA). This provides evidence that patterns of interplay between signalling proteins differ significantly between cancer types. Furthermore, we show how the proposed approaches can be used to learn subtypes and the molecular networks that define them. As the Bioconductor package nethet. staedler.n@gmail.com or sach.mukherjee@dzne.de. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Investigating Molecular Level Stress-Strain Relationships in Entangled F-Actin Networks by Combined Force-Measuring Optical Tweezers and Fluorescence Microscopy

NASA Astrophysics Data System (ADS)

Lee, Kent; Henze, Dean; Robertson-Anderson, Rae

2013-03-01

Actin is an important cytoskeletal protein involved in cell structure and motility, cancer invasion and metastasis, and muscle contraction. The intricate viscoelastic properties of filamentous actin (F-actin) networks allow for the many dynamic roles of actin, thus warranting investigation. Exploration of this unique stress-strain/strain-rate relationship in complex F-actin networks can also improve biomimetic materials engineering. Here, we use optical tweezers with fluorescence microscopy to study the viscoelastic properties of F-actin networks on the microscopic level. Optically trapped microspheres embedded in various F-actin networks are moved through the network using a nanoprecision piezoelectric stage. The force exerted on the microspheres by the F-actin network and subsequent force relaxation are measured, while a fraction of the filaments in the network are fluorescent-labeled to observe filament deformation in real-time. The dependence of the viscoelastic properties of the network on strain rates and amplitudes as well as F-actin concentration is quantified. This approach provides the much-needed link between induced force and deformation over localized regimes (tens of microns) and down to the single molecule level.

Metamorphosis in solitary ascidians.

PubMed

Karaiskou, Anthi; Swalla, Billie J; Sasakura, Yasunori; Chambon, Jean-Philippe

2015-01-01

Embryonic and postembryonic development in ascidians have been studied for over a century, but it is only in the last 10 years that the complex molecular network involved in coordinating postlarval development and metamorphosis has started to emerge. In most ascidians, the transition from the larval to the sessile juvenile/adult stage, or metamorphosis, requires a combination of environmental and endogenous signals and is characterized by coordinated global morphogenetic changes that are initiated by the adhesion of the larvae. Cloney was the first to describe cellular events of ascidians' metamorphosis in 1978 and only recently elements of the molecular regulation of this crucial developmental step have been revealed. This review aims to present a thorough view of this crucial developmental step by combining recent molecular data to the already established cellular events. © 2014 Wiley Periodicals, Inc.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

The Consequences of Surface Confinement on Free Radical Chemistry

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

Birtt, P.F.; Buchanan, A.C., III

1999-08-22

Mass transport limitations impact the thermochemical processing of fossil and renewable energy resources, which involves the breakdown of cross-linked, macromolecular networks. To Investigate the molecular level details of the consequences of molecular confinement on high temperature (275-500°C) free-radical reaction pathways, we have been examining the pyrolysis of model compounds attached to the surface of non-porous silica nanoparticles through a thermally robust Si-O-C aryl, tetha. Pyrolysis of silica-immobilized diphenylalkanes and related ethers have been studied in detail and compared with the corresponding behavior in fluid phases. The diffusional constraints can lead to reduced rates of radical termination on the surface, andmore » enhancement of neophyl-like rearrangements, cyclization-dehydrogenation pathways, and ipso- aromatic substitutions. Furthermore, studies of two-component surfaces have revealed the importance of a radical relay mechanism involving rapid serial hydrogen transfer steps resulting from the molecular pre-organization on the low fractal dimension silica surface. Key findings are reviewed in this paper, and the implications of these results for fuel processing are described.« less

NaviCell Web Service for network-based data visualization.

PubMed

Bonnet, Eric; Viara, Eric; Kuperstein, Inna; Calzone, Laurence; Cohen, David P A; Barillot, Emmanuel; Zinovyev, Andrei

2015-07-01

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of 'omics' data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Inferring protein domains associated with drug side effects based on drug-target interaction network

PubMed Central

2013-01-01

Background Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. PMID:24565527

In vivo genome-wide analysis of multiple tissues identifies gene regulatory networks, novel functions and downstream regulatory genes for Bapx1 and its co-regulation with Sox9 in the mammalian vertebral column.

PubMed

Chatterjee, Sumantra; Sivakamasundari, V; Yap, Sook Peng; Kraus, Petra; Kumar, Vibhor; Xing, Xing; Lim, Siew Lan; Sng, Joel; Prabhakar, Shyam; Lufkin, Thomas

2014-12-05

Vertebrate organogenesis is a highly complex process involving sequential cascades of transcription factor activation or repression. Interestingly a single developmental control gene can occasionally be essential for the morphogenesis and differentiation of tissues and organs arising from vastly disparate embryological lineages. Here we elucidated the role of the mammalian homeobox gene Bapx1 during the embryogenesis of five distinct organs at E12.5 - vertebral column, spleen, gut, forelimb and hindlimb - using expression profiling of sorted wildtype and mutant cells combined with genome wide binding site analysis. Furthermore we analyzed the development of the vertebral column at the molecular level by combining transcriptional profiling and genome wide binding data for Bapx1 with similarly generated data sets for Sox9 to assemble a detailed gene regulatory network revealing genes previously not reported to be controlled by either of these two transcription factors. The gene regulatory network appears to control cell fate decisions and morphogenesis in the vertebral column along with the prevention of premature chondrocyte differentiation thus providing a detailed molecular view of vertebral column development.

2D-HB-Network at the air-water interface: A structural and dynamical characterization by means of ab initio and classical molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Pezzotti, Simone; Serva, Alessandra; Gaigeot, Marie-Pierre

2018-05-01

Following our previous work where the existence of a special 2-Dimensional H-Bond (2D-HB)-Network was revealed at the air-water interface [S. Pezzotti et al., J. Phys. Chem. Lett. 8, 3133 (2017)], we provide here a full structural and dynamical characterization of this specific arrangement by means of both Density Functional Theory based and Force Field based molecular dynamics simulations. We show in particular that water at the interface with air reconstructs to maximize H-Bonds formed between interfacial molecules, which leads to the formation of an extended and non-interrupted 2-Dimensional H-Bond structure involving on average ˜90% of water molecules at the interface. We also show that the existence of such an extended structure, composed of H-Bonds all oriented parallel to the surface, constrains the reorientional dynamics of water that is hence slower at the interface than in the bulk. The structure and dynamics of the 2D-HB-Network provide new elements to possibly rationalize several specific properties of the air-water interface, such as water surface tension, anisotropic reorientation of interfacial water under an external field, and proton hopping.

Excavation of attractor modules for nasopharyngeal carcinoma via integrating systemic module inference with attract method.

PubMed

Jiang, T; Jiang, C-Y; Shu, J-H; Xu, Y-J

2017-07-10

The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively. Among them, 8 pairs of modules with similar gene composition were selected, and 2 attractor modules were identified via the attract method. Functional analysis indicated that these two attractor modules participate in one common bioprocess of cell division. Based on the strategy of integrating systemic module inference with the attract method, we successfully identified 2 attractor modules. These attractor modules might play important roles in the molecular pathogenesis of NPC via affecting the bioprocess of cell division in a conjunct way. Further research is needed to explore the correlations between cell division and NPC.

Disruption of a Regulatory Network Consisting of Neutrophils and Platelets Fosters Persisting Inflammation in Rheumatic Diseases.

PubMed

Maugeri, Norma; Rovere-Querini, Patrizia; Manfredi, Angelo A

2016-01-01

A network of cellular interactions that involve blood leukocytes and platelets maintains vessel homeostasis. It plays a critical role in the response to invading microbes by recruiting intravascular immunity and through the generation of neutrophil extracellular traps (NETs) and immunothrombosis. Moreover, it enables immune cells to respond to remote chemoattractants by crossing the endothelial barrier and reaching sites of infection. Once the network operating under physiological conditions is disrupted, the reciprocal activation of cells in the blood and the vessel walls determines the vascular remodeling via inflammatory signals delivered to stem/progenitor cells. A deregulated leukocyte/mural cell interaction is an early critical event in the natural history of systemic inflammation. Despite intense efforts, the signals that initiate and sustain the immune-mediated vessel injury, or those that enforce the often-prolonged phases of clinical quiescence in patients with vasculitis, have only been partially elucidated. Here, we discuss recent evidence that implicates the prototypic damage-associated molecular pattern/alarmin, the high mobility group box 1 (HMGB1) protein in systemic vasculitis and in the vascular inflammation associated with systemic sclerosis. HMGB1 could represent a player in the pathogenesis of rheumatic diseases and an attractive target for molecular interventions.

NaviCell Web Service for network-based data visualization

PubMed Central

Bonnet, Eric; Viara, Eric; Kuperstein, Inna; Calzone, Laurence; Cohen, David P. A.; Barillot, Emmanuel; Zinovyev, Andrei

2015-01-01

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of ‘omics’ data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases. PMID:25958393

Biological network motif detection and evaluation

PubMed Central

2011-01-01

Background Molecular level of biological data can be constructed into system level of data as biological networks. Network motifs are defined as over-represented small connected subgraphs in networks and they have been used for many biological applications. Since network motif discovery involves computationally challenging processes, previous algorithms have focused on computational efficiency. However, we believe that the biological quality of network motifs is also very important. Results We define biological network motifs as biologically significant subgraphs and traditional network motifs are differentiated as structural network motifs in this paper. We develop five algorithms, namely, EDGEGO-BNM, EDGEBETWEENNESS-BNM, NMF-BNM, NMFGO-BNM and VOLTAGE-BNM, for efficient detection of biological network motifs, and introduce several evaluation measures including motifs included in complex, motifs included in functional module and GO term clustering score in this paper. Experimental results show that EDGEGO-BNM and EDGEBETWEENNESS-BNM perform better than existing algorithms and all of our algorithms are applicable to find structural network motifs as well. Conclusion We provide new approaches to finding network motifs in biological networks. Our algorithms efficiently detect biological network motifs and further improve existing algorithms to find high quality structural network motifs, which would be impossible using existing algorithms. The performances of the algorithms are compared based on our new evaluation measures in biological contexts. We believe that our work gives some guidelines of network motifs research for the biological networks. PMID:22784624

Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.

PubMed

van Helden, Jacques; Toussaint, Ariane; Thieffry, Denis

2012-01-01

This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

Flower Development

PubMed Central

Alvarez-Buylla, Elena R.; Benítez, Mariana; Corvera-Poiré, Adriana; Chaos Cador, Álvaro; de Folter, Stefan; Gamboa de Buen, Alicia; Garay-Arroyo, Adriana; García-Ponce, Berenice; Jaimes-Miranda, Fabiola; Pérez-Ruiz, Rigoberto V.; Piñeyro-Nelson, Alma; Sánchez-Corrales, Yara E.

2010-01-01

Flowers are the most complex structures of plants. Studies of Arabidopsis thaliana, which has typical eudicot flowers, have been fundamental in advancing the structural and molecular understanding of flower development. The main processes and stages of Arabidopsis flower development are summarized to provide a framework in which to interpret the detailed molecular genetic studies of genes assigned functions during flower development and is extended to recent genomics studies uncovering the key regulatory modules involved. Computational models have been used to study the concerted action and dynamics of the gene regulatory module that underlies patterning of the Arabidopsis inflorescence meristem and specification of the primordial cell types during early stages of flower development. This includes the gene combinations that specify sepal, petal, stamen and carpel identity, and genes that interact with them. As a dynamic gene regulatory network this module has been shown to converge to stable multigenic profiles that depend upon the overall network topology and are thus robust, which can explain the canalization of flower organ determination and the overall conservation of the basic flower plan among eudicots. Comparative and evolutionary approaches derived from Arabidopsis studies pave the way to studying the molecular basis of diverse floral morphologies. PMID:22303253

Trapping proton transfer intermediates in the disordered hydrogen-bonded network of cryogenic hydrofluoric acid solutions.

PubMed

Ayotte, Patrick; Plessis, Sylvain; Marchand, Patrick

2008-08-28

A molecular-level description of the structural and dynamical aspects that are responsible for the weak acid behaviour of dilute hydrofluoric acid solutions and their unusual increased acidity at near equimolar concentrations continues to elude us. We address this problem by reporting reflection-absorption infrared spectra (RAIRS) of cryogenic HF-H(2)O binary mixtures at various compositions prepared as nanoscopic films using molecular beam techniques. Optical constants for these cryogenic solutions [n(omega) and k(omega)] are obtained by iteratively solving Fresnel equations for stratified media. Modeling of the experimental RAIRS spectra allow for a quantitative interpretation of the complex interplay between multiple reflections, optical interference and absorption effects. The evolution of the strong absorption features in the intermediate 1000-3000 cm(-1) range with increasing HF concentration reveals the presence of various ionic dissociation intermediates that are trapped in the disordered H-bonded network of cryogenic hydrofluoric acid solutions. Our findings are discussed in light of the conventional interpretation of why hydrofluoric acid is a weak acid revealing molecular-level details of the mechanism for HF ionization that may be relevant to analogous elementary processes involved in the ionization of weak acids in aqueous solutions.

A systems biology approach to detect key pathways and interaction networks in gastric cancer on the basis of microarray analysis.

PubMed

Guo, Leilei; Song, Chunhua; Wang, Peng; Dai, Liping; Zhang, Jianying; Wang, Kaijuan

2015-11-01

The aim of the present study was to explore key molecular pathways contributing to gastric cancer (GC) and to construct an interaction network between significant pathways and potential biomarkers. Publicly available gene expression profiles of GSE29272 for GC, and data for the corresponding normal tissue, were downloaded from Gene Expression Omnibus. Pre‑processing and differential analysis were performed with R statistical software packages, and a number of differentially expressed genes (DEGs) were obtained. A functional enrichment analysis was performed for all the DEGs with a BiNGO plug‑in in Cytoscape. Their correlation was analyzed in order to construct a network. The modularity analysis and pathway identification operations were used to identify graph clusters and associated pathways. The underlying molecular mechanisms involving these DEGs were also assessed by data mining. A total of 249 DEGs, which were markedly upregulated and downregulated, were identified. The extracellular region contained the most significantly over‑represented functional terms, with respect to upregulated and downregulated genes, and the closest topological matches were identified for taste transduction and regulation of autophagy. In addition, extracellular matrix‑receptor interactions were identified as the most relevant pathway associated with the progression of GC. The genes for fibronectin 1, secreted phosphoprotein 1, collagen type 4 variant α‑1/2 and thrombospondin 1, which are involved in the pathways, may be considered as potential therapeutic targets for GC. A series of associations between candidate genes and key pathways were also identified for GC, and their correlation may provide novel insights into the pathogenesis of GC.

Conformational transitions of uracil transporter UraA from Escherichia coli: a molecular simulation study.

PubMed

Yang, Liu; Yang, Lianjuan; Yu, Hui; Liu, Lu; Zhao, Xi; Huang, Xuri

2017-10-26

The Escherichia coli uracil/H + symporter UraA, known as the representative nucleobase/cation symporter 2(NCS2) protein, gets involved in several crucial physiological processes for most living organisms on Earth, such as the uptake of nucleobases and transport of vitamin C. Some experiments proposed a working model to explain proton-coupling and uracil transporting process of UraA on the basis of the crystal structure of NCS2 protein, but the details of conformational changes remained unknown. Thus, in order to make clear conformational changes caused by the protonation and deprotonation process of some conserved proton-coupled residues, the molecular dynamics simulation was used to study the conformation of UraA complexes in different protonation states. The results demonstrated that the protonation of residue Glu241 and Glu290 resulted in the whole conformational transition from the inward-open to the outward-open state. It can be concluded that Glu290 was crucial in a network of hydrogen-bonds in the middle of the core domain involving another essential residue, mainly including tyr288 in TM8, Tyr342, Ser338 in TM12, and the network of hydrogen-bonds was the key to maintain the stability of conformation. Protonation of Glu290 affects the stability of network of H-bond and changed the domains TM3 TM10 TM12. Thus, Glu290 may play a vital role as a 'proton trigger' that affects spatial structural of amino and residues near substrate binding side leading to an outward-open conformation transition.

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study | Office of Cancer Genomics

Cancer.gov

Motivation: Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging.

Structural and Functional Characterization of a Caenorhabditis elegans Genetic Interaction Network within Pathways

PubMed Central

Boucher, Benjamin; Lee, Anna Y.; Hallett, Michael; Jenna, Sarah

2016-01-01

A genetic interaction (GI) is defined when the mutation of one gene modifies the phenotypic expression associated with the mutation of a second gene. Genome-wide efforts to map GIs in yeast revealed structural and functional properties of a GI network. This provided insights into the mechanisms underlying the robustness of yeast to genetic and environmental insults, and also into the link existing between genotype and phenotype. While a significant conservation of GIs and GI network structure has been reported between distant yeast species, such a conservation is not clear between unicellular and multicellular organisms. Structural and functional characterization of a GI network in these latter organisms is consequently of high interest. In this study, we present an in-depth characterization of ~1.5K GIs in the nematode Caenorhabditis elegans. We identify and characterize six distinct classes of GIs by examining a wide-range of structural and functional properties of genes and network, including co-expression, phenotypical manifestations, relationship with protein-protein interaction dense subnetworks (PDS) and pathways, molecular and biological functions, gene essentiality and pleiotropy. Our study shows that GI classes link genes within pathways and display distinctive properties, specifically towards PDS. It suggests a model in which pathways are composed of PDS-centric and PDS-independent GIs coordinating molecular machines through two specific classes of GIs involving pleiotropic and non-pleiotropic connectors. Our study provides the first in-depth characterization of a GI network within pathways of a multicellular organism. It also suggests a model to understand better how GIs control system robustness and evolution. PMID:26871911

Signaling Network of Environmental Sensing and Adaptation in Plants:. Key Roles of Calcium Ion

NASA Astrophysics Data System (ADS)

Kurusu, Takamitsu; Kuchitsu, Kazuyuki

2011-01-01

Considering the important issues concerning food, environment, and energy that humans are facing in the 21st century, humans mostly depend on plants. Unlike animals which move from an inappropriate environment, plants do not move, but rapidly sense diverse environmental changes or invasion by other organisms such as pathogens and insects in the place they root, and adapt themselves by changing their own bodies, through which they developed adaptability. Whole genetic information corresponding to the blueprints of many biological systems has recently been analyzed, and comparative genomic studies facilitated tracing strategies of each organism in their evolutional processes. Comparison of factors involved in intracellular signal transduction between animals and plants indicated diversification of different gene sets. Reversible binding of Ca2+ to sensor proteins play key roles as a molecular switch both in animals and plants. Molecular mechanisms for signaling network of environmental sensing and adaptation in plants will be discussed with special reference to Ca2+ as a key element in information processing.

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

PubMed

Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Guidance of vascular development: lessons from the nervous system.

PubMed

Larrivée, Bruno; Freitas, Catarina; Suchting, Steven; Brunet, Isabelle; Eichmann, Anne

2009-02-27

The vascular system of vertebrates consists of an organized, branched network of arteries, veins, and capillaries that penetrates all the tissues of the body. One of the most striking features of the vascular system is that its branching pattern is highly stereotyped, with major and secondary branches forming at specific sites and developing highly conserved organ-specific vascular patterns. The factors controlling vascular patterning are not yet completely understood. Recent studies have highlighted the anatomic and structural similarities between blood vessels and nerves. The 2 networks are often aligned, with nerve fibers and blood vessels following parallel routes. Furthermore, both systems require precise control over their guidance and growth. Several molecules with attractive and repulsive properties have been found to modulate the proper guidance of both nerves and blood vessels. These include the Semaphorins, the Slits, and the Netrins and their receptors. In this review, we describe the molecular mechanisms by which blood vessels and axons achieve proper path finding and the molecular cues that are involved in their guidance.

The 20th anniversary of EMBnet: 20 years of bioinformatics for the Life Sciences community

PubMed Central

D'Elia, Domenica; Gisel, Andreas; Eriksson, Nils-Einar; Kossida, Sophia; Mattila, Kimmo; Klucar, Lubos; Bongcam-Rudloff, Erik

2009-01-01

The EMBnet Conference 2008, focusing on 'Leading Applications and Technologies in Bioinformatics', was organized by the European Molecular Biology network (EMBnet) to celebrate its 20th anniversary. Since its foundation in 1988, EMBnet has been working to promote collaborative development of bioinformatics services and tools to serve the European community of molecular biology laboratories. This conference was the first meeting organized by the network that was open to the international scientific community outside EMBnet. The conference covered a broad range of research topics in bioinformatics with a main focus on new achievements and trends in emerging technologies supporting genomics, transcriptomics and proteomics analyses such as high-throughput sequencing and data managing, text and data-mining, ontologies and Grid technologies. Papers selected for publication, in this supplement to BMC Bioinformatics, cover a broad range of the topics treated, providing also an overview of the main bioinformatics research fields that the EMBnet community is involved in. PMID:19534734

Multifaceted Leptin network: the molecular connection between obesity and breast cancer

PubMed Central

Saxena, Neeraj K.; Sharma, Dipali

2016-01-01

High plasma levels of leptin, a major adipocytokine produced by adipocytes, are correlated with increased fat mass in obese state. Leptin is emerging as a key candidate molecule linking obesity with breast cancer. Acting via endocrine, paracrine, and autocrine manner, leptin impacts various stages of breast tumorigenesis from initiation and primary tumor growth to metastatic progression. Leptin also modulates the tumor microenvironment mainly through supporting migration of endothelial cells, neo-angiogenesis and sustaining recruitment of macrophage and monocytes. Various studies have shown that hyperactive leptin-signaling network leads to concurrent activation of multiple oncogenic pathways resulting in enhanced proliferation, decreased apoptosis, acquisition of mesenchymal phenotype, potentiated migration and enhanced invasion potential of tumor cells. Furthermore, the capability of leptin to interact with other molecular effectors of obese state including, estrogen, IGF-1, insulin, VEGF and inflammatory cytokines further increases its impact on breast tumor progression in obese state. This article presents an overview of the studies investigating the involvement of leptin in breast cancer. PMID:24214584

WONOEP appraisal: new genetic approaches to study epilepsy

PubMed Central

Rossignol, Elsa; Kobow, Katja; Simonato, Michele; Loeb, Jeffrey A.; Grisar, Thierry; Gilby, Krista L.; Vinet, Jonathan; Kadam, Shilpa D.; Becker, Albert J.

2014-01-01

Objective New genetic investigation techniques, including next-generation sequencing, epigenetic profiling, cell lineage mapping, targeted genetic manipulation of specific neuronal cell types, stem cell reprogramming and optogenetic manipulations within epileptic networks are progressively unravelling the mysteries of epileptogenesis and ictogenesis. These techniques have opened new avenues to discover the molecular basis of epileptogenesis and to study the physiological impacts of mutations in epilepsy-associated genes on a multilayer level, from cells to circuits. Methods This manuscript reviews recently published applications of these new genetic technologies in the study of epilepsy, as well as work presented by the authors at the genetic session of the XII Workshop on the Neurobiology of Epilepsy in Quebec, Canada. Results Next-generation sequencing is providing investigators with an unbiased means to assess the molecular causes of sporadic forms of epilepsy and have revealed the complexity and genetic heterogeneity of sporadic epilepsy disorders. To assess the functional impact of mutations in these newly identified genes on specific neuronal cell-types during brain development, new modeling strategies in animals, including conditional genetics in mice and in utero knockdown approaches, are enabling functional validation with exquisite cell-type and temporal specificity. In addition, optogenetics, using cell-type specific Cre recombinase driver lines, is enabling investigators to dissect networks involved in epilepsy. Genetically-encoded cell-type labeling is also providing new means to assess the role of the non-neuronal components of epileptic networks such as glial cells. Furthermore, beyond its role in revealing coding variants involved in epileptogenesis, next-generation sequencing can be used to assess the epigenetic modifications that lead to sustained network hyperexcitability in epilepsy, including methylation changes in gene promoters and non-coding RNAs involved in modifying gene expression following seizures. In addition, genetically-based bioluminescent reporters are providing new opportunities to assess neuronal activity and neurotransmitter levels both in vitro and in vivo in the context of epilepsy. Finally, genetically rederived neurons generated from patient iPS cells and genetically-modified zebrafish have become high-throughput means to investigate disease mechanisms and potential new therapies. Significance Genetics has considerably changed the field of epilepsy research and is paving the way for better diagnosis and therapies for patients with epilepsy. PMID:24965021

Towards chiral distributions of dopants in microporous frameworks: helicoidal supramolecular arrangement of (1R,2S)-ephedrine and transfer of chirality.

PubMed

Gómez-Hortigüela, Luis; Álvaro-Muñoz, Teresa; Bernardo-Maestro, Beatriz; Pérez-Pariente, Joaquín

2015-01-07

A molecular-mechanics computational study is performed in order to analyze the arrangement of (1R,2S)-(-)-ephedrine molecules within the 12-MR channels of the AFI aluminophosphate microporous framework and the influence on the spatial distribution of dopants embedded in the tetrahedral network. Results showed that ephedrine molecules arrange exclusively as dimers by π-π stacking of the aromatic rings within the AFI channels. Interestingly, the asymmetric nature of ephedrine and the presence of H-bond-forming groups (NH2 and OH) involve a preferential orientation where consecutive dimers within the channels are rotated by an angle of +30°; this is driven by the establishment of inter-dimer H-bonds. This preferential orientation leads to the development of a supramolecular enantiomerically-pure helicoidal (chiral) arrangement of ephedrine dimers. In addition, the computational results demonstrate that the particular molecular structure of ephedrine imparts a strong trend to attract negative charges to the vicinity of the NH2(+) positively-charged groups. Hence divalent dopants such as Mg, whose replacement by trivalent Al in the aluminophosphate network involves the generation of a negative charge, will tend to locate close to the NH2(+) molecular groups, suggesting that an imprinting of the organic arrangement to the spatial distribution of dopants would be feasible. Combined with the trend of ephedrine to arrange in a helicoidal fashion, an enantiomerically-pure helicoidal distribution of dopants would be expected, thus inducing a new type of chirality in microporous materials.

Degradation behavior of, and tissue response to photo-crosslinked poly(trimethylene carbonate) networks.

PubMed

Rongen, Jan J; van Bochove, Bas; Hannink, Gerjon; Grijpma, Dirk W; Buma, Pieter

2016-11-01

Photo-crosslinked networks prepared from three-armed methacrylate functionalized PTMC oligomers (PTMC-tMA macromers) are attractive materials for developing an anatomically correct meniscus scaffold. In this study, we evaluated cell specific biocompatibility, in vitro and in vivo degradation behavior of, and tissue response to, such PTMC networks. By evaluating PTMC networks prepared from PTMC-tMA macromers of different molecular weights, we were able to assess the effect of macromer molecular weight on the degradation rate of the PTMC network obtained after photo-crosslinking. Three photo-crosslinked networks with different crosslinking densities were prepared using PTMC-tMA macromers with molecular weights 13.3, 17.8, and 26.7 kg/mol. Good cell biocompatibility was demonstrated in a proliferation assay with synovium derived cells. PTMC networks degraded slowly, but statistically significant, both in vitro as well as subcutaneously in rats. Networks prepared from macromers with higher molecular weights demonstrated increased degradation rates compared to networks prepared from initial macromers of lowest molecular weight. The degradation process took place via surface erosion. The PTMC networks showed good tissue tolerance during subcutaneous implantation, to which the tissue response was characterized by the presence of fibrous tissue and encapsulation of the implants. Concluding, we developed cell and tissue biocompatible, photo-crosslinked PTMC networks using PTMC-tMA macromers with relatively high molecular weights. These photo-crosslinked PTMC networks slowly degrade by a surface erosion process. Increasing the crosslinking density of these networks decreases the rate of surface degradation. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2823-2832, 2016. © 2016 Wiley Periodicals, Inc.

A Quantitative Systems Pharmacology Approach to Infer Pathways Involved in Complex Disease Phenotypes.

PubMed

Schurdak, Mark E; Pei, Fen; Lezon, Timothy R; Carlisle, Diane; Friedlander, Robert; Taylor, D Lansing; Stern, Andrew M

2018-01-01

Designing effective therapeutic strategies for complex diseases such as cancer and neurodegeneration that involve tissue context-specific interactions among multiple gene products presents a major challenge for precision medicine. Safe and selective pharmacological modulation of individual molecular entities associated with a disease often fails to provide efficacy in the clinic. Thus, development of optimized therapeutic strategies for individual patients with complex diseases requires a more comprehensive, systems-level understanding of disease progression. Quantitative systems pharmacology (QSP) is an approach to drug discovery that integrates computational and experimental methods to understand the molecular pathogenesis of a disease at the systems level more completely. Described here is the chemogenomic component of QSP for the inference of biological pathways involved in the modulation of the disease phenotype. The approach involves testing sets of compounds of diverse mechanisms of action in a disease-relevant phenotypic assay, and using the mechanistic information known for the active compounds, to infer pathways and networks associated with the phenotype. The example used here is for monogenic Huntington's disease (HD), which due to the pleiotropic nature of the mutant phenotype has a complex pathogenesis. The overall approach, however, is applicable to any complex disease.

Continuous time Bayesian networks identify Prdm1 as a negative regulator of TH17 cell differentiation in humans

PubMed Central

Acerbi, Enzo; Viganò, Elena; Poidinger, Michael; Mortellaro, Alessandra; Zelante, Teresa; Stella, Fabio

2016-01-01

T helper 17 (TH17) cells represent a pivotal adaptive cell subset involved in multiple immune disorders in mammalian species. Deciphering the molecular interactions regulating TH17 cell differentiation is particularly critical for novel drug target discovery designed to control maladaptive inflammatory conditions. Using continuous time Bayesian networks over a time-course gene expression dataset, we inferred the global regulatory network controlling TH17 differentiation. From the network, we identified the Prdm1 gene encoding the B lymphocyte-induced maturation protein 1 as a crucial negative regulator of human TH17 cell differentiation. The results have been validated by perturbing Prdm1 expression on freshly isolated CD4+ naïve T cells: reduction of Prdm1 expression leads to augmentation of IL-17 release. These data unravel a possible novel target to control TH17 polarization in inflammatory disorders. Furthermore, this study represents the first in vitro validation of continuous time Bayesian networks as gene network reconstruction method and as hypothesis generation tool for wet-lab biological experiments. PMID:26976045

Postischemic revascularization: from cellular and molecular mechanisms to clinical applications.

PubMed

Silvestre, Jean-Sébastien; Smadja, David M; Lévy, Bernard I

2013-10-01

After the onset of ischemia, cardiac or skeletal muscle undergoes a continuum of molecular, cellular, and extracellular responses that determine the function and the remodeling of the ischemic tissue. Hypoxia-related pathways, immunoinflammatory balance, circulating or local vascular progenitor cells, as well as changes in hemodynamical forces within vascular wall trigger all the processes regulating vascular homeostasis, including vasculogenesis, angiogenesis, arteriogenesis, and collateral growth, which act in concert to establish a functional vascular network in ischemic zones. In patients with ischemic diseases, most of the cellular (mainly those involving bone marrow-derived cells and local stem/progenitor cells) and molecular mechanisms involved in the activation of vessel growth and vascular remodeling are markedly impaired by the deleterious microenvironment characterized by fibrosis, inflammation, hypoperfusion, and inhibition of endogenous angiogenic and regenerative programs. Furthermore, cardiovascular risk factors, including diabetes, hypercholesterolemia, hypertension, diabetes, and aging, constitute a deleterious macroenvironment that participates to the abrogation of postischemic revascularization and tissue regeneration observed in these patient populations. Thus stimulation of vessel growth and/or remodeling has emerged as a new therapeutic option in patients with ischemic diseases. Many strategies of therapeutic revascularization, based on the administration of growth factors or stem/progenitor cells from diverse sources, have been proposed and are currently tested in patients with peripheral arterial disease or cardiac diseases. This review provides an overview from our current knowledge regarding molecular and cellular mechanisms involved in postischemic revascularization, as well as advances in the clinical application of such strategies of therapeutic revascularization.

Chromatin dynamics in plants.

PubMed

Fransz, Paul F; de Jong, J Hans

2002-12-01

Recent studies in yeast, animals and plants have provided major breakthroughs in unraveling the molecular mechanism of higher-order gene regulation. In conjunction with the DNA code, proteins that are involved in chromatin remodeling, histone modification and epigenetic imprinting form a large network of interactions that control the nuclear programming of cell identity. New insight into how chromatin conformations are regulated in plants sheds light on the relationships between chromosome function, cell differentiation and developmental patterns.

Expansion of the E138A mutation in newly diagnosed HIV-infected patients in Gran Canaria.

PubMed

Chamizo, Francisco; Gilarranz, Raúl; Tosco, Tomás; Carrillo, Deyanira; Holguín, África; Santana, Évora; Pérez-Arellano, Jose Luís; Hernández, Michele; Francés, Adela; Cárdenes, Miguel Ángel; Zarzalejos, Jose María; Pena-López, María José

2016-09-01

Molecular epidemiology allows us to know local HIV transmission and to design strategies of prevention. We studied 25 HIV newly diagnosed patients with the E138A mutation since the year 2010. Most transmission networks involved young and promiscuous men who have sex with men. Recent infection was only documented in patients grouped into the smaller clusters. Copyright © 2016 Elsevier Inc. All rights reserved.

Systematical analysis of lncRNA-mRNA competing endogenous RNA network in breast cancer subtypes.

PubMed

Zhou, Shunheng; Wang, Lihong; Yang, Qian; Liu, Haizhou; Meng, Qianqian; Jiang, Leiming; Wang, Shuyuan; Jiang, Wei

2018-06-01

Breast cancer is one of the most common solid tumors in women involving multiple subtypes. However, the mechanism for subtypes of breast cancer is still complicated and unclear. Recently, several studies indicated that long non-coding RNAs (lncRNAs) could act as sponges to compete miRNAs with mRNAs, participating in various biological processes. We concentrated on the competing interactions between lncRNAs and mRNAs in four subtypes of breast cancer (basal-like, HER2+, luminal A and luminal B), and analyzed the impacts of competing endogenous RNAs (ceRNAs) on each subtype systematically. We constructed four breast cancer subtype-related lncRNA-mRNA ceRNA networks by integrating the miRNA target information and the expression data of lncRNAs, miRNAs and mRNAs. We constructed the ceRNA network for each breast cancer subtype. Functional analysis revealed that the subtype-related ceRNA networks were enriched in cancer-related pathways in KEGG, such as pathways in cancer, miRNAs in cancer, and PI3k-Akt signaling pathway. In addition, we found three common lncRNAs across the four subtype-related ceRNA networks, NEAT1, OPI5-AS1 and AC008124.1, which played specific roles in each subtype through competing with diverse mRNAs. Finally, the potential drugs for treatment of basal-like subtype could be predicted through reversing the differentially expressed lncRNA in the ceRNA network. This study provided a novel perspective of lncRNA-involved ceRNA network to dissect the molecular mechanism for breast cancer.

A model of the regulatory network involved in the control of the cell cycle and cell differentiation in the Caenorhabditis elegans vulva.

PubMed

Weinstein, Nathan; Ortiz-Gutiérrez, Elizabeth; Muñoz, Stalin; Rosenblueth, David A; Álvarez-Buylla, Elena R; Mendoza, Luis

2015-03-13

There are recent experimental reports on the cross-regulation between molecules involved in the control of the cell cycle and the differentiation of the vulval precursor cells (VPCs) of Caenorhabditis elegans. Such discoveries provide novel clues on how the molecular mechanisms involved in the cell cycle and cell differentiation processes are coordinated during vulval development. Dynamic computational models are helpful to understand the integrated regulatory mechanisms affecting these cellular processes. Here we propose a simplified model of the regulatory network that includes sufficient molecules involved in the control of both the cell cycle and cell differentiation in the C. elegans vulva to recover their dynamic behavior. We first infer both the topology and the update rules of the cell cycle module from an expected time series. Next, we use a symbolic algorithmic approach to find which interactions must be included in the regulatory network. Finally, we use a continuous-time version of the update rules for the cell cycle module to validate the cyclic behavior of the network, as well as to rule out the presence of potential artifacts due to the synchronous updating of the discrete model. We analyze the dynamical behavior of the model for the wild type and several mutants, finding that most of the results are consistent with published experimental results. Our model shows that the regulation of Notch signaling by the cell cycle preserves the potential of the VPCs and the three vulval fates to differentiate and de-differentiate, allowing them to remain completely responsive to the concentration of LIN-3 and lateral signal in the extracellular microenvironment.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

PubMed Central

Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N.; Jones, Byron C.; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses. PMID:29674951

HBVPathDB: a database of HBV infection-related molecular interaction network.

PubMed

Zhang, Yi; Bo, Xiao-Chen; Yang, Jing; Wang, Sheng-Qi

2005-03-21

To describe molecules or genes interaction between hepatitis B viruses (HBV) and host, for understanding how virus' and host's genes and molecules are networked to form a biological system and for perceiving mechanism of HBV infection. The knowledge of HBV infection-related reactions was organized into various kinds of pathways with carefully drawn graphs in HBVPathDB. Pathway information is stored with relational database management system (DBMS), which is currently the most efficient way to manage large amounts of data and query is implemented with powerful Structured Query Language (SQL). The search engine is written using Personal Home Page (PHP) with SQL embedded and web retrieval interface is developed for searching with Hypertext Markup Language (HTML). We present the first version of HBVPathDB, which is a HBV infection-related molecular interaction network database composed of 306 pathways with 1 050 molecules involved. With carefully drawn graphs, pathway information stored in HBVPathDB can be browsed in an intuitive way. We develop an easy-to-use interface for flexible accesses to the details of database. Convenient software is implemented to query and browse the pathway information of HBVPathDB. Four search page layout options-category search, gene search, description search, unitized search-are supported by the search engine of the database. The database is freely available at http://www.bio-inf.net/HBVPathDB/HBV/. The conventional perspective HBVPathDB have already contained a considerable amount of pathway information with HBV infection related, which is suitable for in-depth analysis of molecular interaction network of virus and host. HBVPathDB integrates pathway data-sets with convenient software for query, browsing, visualization, that provides users more opportunity to identify regulatory key molecules as potential drug targets and to explore the possible mechanism of HBV infection based on gene expression datasets.

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach.

PubMed

van Roekel, Hendrik W H; Rosier, Bas J H M; Meijer, Lenny H H; Hilbers, Peter A J; Markvoort, Albert J; Huck, Wilhelm T S; de Greef, Tom F A

2015-11-07

Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli. It has become apparent that these biological responses are regulated by complex chemical reaction networks (CRNs). Unravelling the function of these circuits is a key topic of both systems biology and synthetic biology. Recent progress at the interface of chemistry and biology together with the realisation that current experimental tools are insufficient to quantitatively understand the molecular logic of pathways inside living cells has triggered renewed interest in the bottom-up development of CRNs. This builds upon earlier work of physical chemists who extensively studied inorganic CRNs and showed how a system of chemical reactions can give rise to complex spatiotemporal responses such as oscillations and pattern formation. Using purified biochemical components, in vitro synthetic biologists have started to engineer simplified model systems with the goal of mimicking biological responses of intracellular circuits. Emulation and reconstruction of system-level properties of intracellular networks using simplified circuits are able to reveal key design principles and molecular programs that underlie the biological function of interest. In this Tutorial Review, we present an accessible overview of this emerging field starting with key studies on inorganic CRNs followed by a discussion of recent work involving purified biochemical components. Finally, we review recent work showing the versatility of programmable biochemical reaction networks (BRNs) in analytical and diagnostic applications.

Supramolecular self-assembly on the B-Si(111)-(√3x√3) R30° surface: From single molecules to multicomponent networks

NASA Astrophysics Data System (ADS)

Makoudi, Younes; Jeannoutot, Judicaël; Palmino, Frank; Chérioux, Frédéric; Copie, Guillaume; Krzeminski, Christophe; Cleri, Fabrizio; Grandidier, Bruno

2017-09-01

Understanding the physical and chemical processes in which local interactions lead to ordered structures is of particular relevance to the realization of supramolecular architectures on surfaces. While spectacular patterns have been demonstrated on metal surfaces, there have been fewer studies of the spontaneous organization of supramolecular networks on semiconductor surfaces, where the formation of covalent bonds between organics and adatoms usually hamper the diffusion of molecules and their subsequent interactions with each other. However, the saturation of the dangling bonds at a semiconductor surface is known to make them inert and offers a unique way for the engineering of molecular patterns on these surfaces. This review describes the physicochemical properties of the passivated B-Si(111)-(√3x√3) R30° surface, that enable the self-assembly of molecules into a rich variety of extended and regular structures on silicon. Particular attention is given to computational methods based on multi-scale simulations that allow to rationalize the relative contribution of the dispersion forces involved in the self-assembled networks observed with scanning tunneling microscopy. A summary of state of the art studies, where a fine tuning of the molecular network topology has been achieved, sheds light on new frontiers for exploiting the construction of supramolecular structures on semiconductor surfaces.

Analysis of molecular pathways in pancreatic ductal adenocarcinomas with a bioinformatics approach.

PubMed

Wang, Yan; Li, Yan

2015-01-01

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

Integration of structural dynamics and molecular evolution via protein interaction networks: a new era in genomic medicine.

PubMed

Kumar, Avishek; Butler, Brandon M; Kumar, Sudhir; Ozkan, S Banu

2015-12-01

Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

NASA Astrophysics Data System (ADS)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-01

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Astroglial metabolic networks sustain hippocampal synaptic transmission.

PubMed

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-05

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Coarse-Grained Molecular Dynamics Simulation of Ionic Polymer Networks

DTIC Science & Technology

2008-07-01

AFRL-RX-WP-TP-2009-4198 COARSE-GRAINED MOLECULAR DYNAMICS SIMULATION OF IONIC POLYMER NETWORKS (Postprint) T.E. Dirama, V. Varshney, K.L...GRAINED MOLECULAR DYNAMICS SIMULATION OF IONIC POLYMER NETWORKS (Postprint) 5a. CONTRACT NUMBER FA8650-05-D-5807-0052 5b. GRANT NUMBER 5c...We studied two types of networks which differ only by one containing ionic pairs that amount to 7% of the total number of bonds present. The stress

Intermolecular hydrogen bonded and self-assembled β-pleated sheet structures of β-sulfidocarbonyls

NASA Astrophysics Data System (ADS)

Hussain, Sahid; Das, Gopal; Chaudhuri, Mihir K.

2007-06-01

The three crystal structures of β-sulfidocarbonyls 1, 2 and 3 synthesized from the reaction of acryl amide with cystiene, 1,2-dithiol and 1,3-dithiols, respectively, in water catalyzed by borax, have been determined at 273 K. The characteristic features of the structures are self-assembly through intermolecular hydrogen bonding leading to infinite chains of molecules in one direction, in addition to the stacking of layers of such molecular chains in the perpendicular direction ultimately giving rise to β-pleated sheets of 3D molecular network involving N-H⋯O, C-H⋯O and C-H⋯S bonding in the crystal lattice.

Male sex determination: insights into molecular mechanisms

PubMed Central

McClelland, Kathryn; Bowles, Josephine; Koopman, Peter

2012-01-01

Disorders of sex development often arise from anomalies in the molecular or cellular networks that guide the differentiation of the embryonic gonad into either a testis or an ovary, two functionally distinct organs. The activation of the Y-linked gene Sry (sex-determining region Y) and its downstream target Sox9 (Sry box-containing gene 9) triggers testis differentiation by stimulating the differentiation of Sertoli cells, which then direct testis morphogenesis. Once engaged, a genetic pathway promotes the testis development while actively suppressing genes involved in ovarian development. This review focuses on the events of testis determination and the struggle to maintain male fate in the face of antagonistic pressure from the underlying female programme. PMID:22179516

Hydration of excess electrons trapped in charge pockets on molecular surfaces

NASA Astrophysics Data System (ADS)

Jalbout, Abraham F.; Del Castillo, R.; Adamowicz, Ludwik

2007-01-01

In this work we strive to design a novel electron trap located on a molecular surface. The process of electron trapping involves hydration of the trapped electron. Previous calculations on surface electron trapping revealed that clusters of OH groups can form stable hydrogen-bonded networks on one side of a hydrocarbon surface (i.e. cyclohexane sheets), while the hydrogen atoms on the opposite side of the surface form pockets of positive charge that can attract extra negative charge. The excess electron density on such surfaces can be further stabilized by interactions with water molecules. Our calculations show that these anionic systems are stable with respect to vertical electron detachment (VDE).

Self-Assembled Polystyrene Beads for Templated Covalent Functionalization of Graphitic Substrates Using Diazonium Chemistry.

PubMed

Van Gorp, Hans; Walke, Peter; Bragança, Ana M; Greenwood, John; Ivasenko, Oleksandr; Hirsch, Brandon E; De Feyter, Steven

2018-04-11

A network of self-assembled polystyrene beads was employed as a lithographic mask during covalent functionalization reactions on graphitic surfaces to create nanocorrals for confined molecular self-assembly studies. The beads were initially assembled into hexagonal arrays at the air-liquid interface and then transferred to the substrate surface. Subsequent electrochemical grafting reactions involving aryl diazonium molecules created covalently bound molecular units that were localized in the void space between the nanospheres. Removal of the bead template exposed hexagonally arranged circular nanocorrals separated by regions of chemisorbed molecules. Small molecule self-assembly was then investigated inside the resultant nanocorrals using scanning tunneling microscopy to highlight localized confinement effects. Overall, this work illustrates the utility of self-assembly principles to transcend length scale gaps in the development of hierarchically patterned molecular materials.

Utilizing Ion-Mobility Data to Estimate Molecular Masses

NASA Technical Reports Server (NTRS)

Duong, Tuan; Kanik, Isik

2008-01-01

A method is being developed for utilizing readings of an ion-mobility spectrometer (IMS) to estimate molecular masses of ions that have passed through the spectrometer. The method involves the use of (1) some feature-based descriptors of structures of molecules of interest and (2) reduced ion mobilities calculated from IMS readings as inputs to (3) a neural network. This development is part of a larger effort to enable the use of IMSs as relatively inexpensive, robust, lightweight instruments to identify, via molecular masses, individual compounds or groups of compounds (especially organic compounds) that may be present in specific environments or samples. Potential applications include detection of organic molecules as signs of life on remote planets, modeling and detection of biochemicals of interest in the pharmaceutical and agricultural industries, and detection of chemical and biological hazards in industrial, homeland-security, and industrial settings.

Sugars and plant innate immunity.

PubMed

Bolouri Moghaddam, Mohammad Reza; Van den Ende, Wim

2012-06-01

Sugars are involved in many metabolic and signalling pathways in plants. Sugar signals may also contribute to immune responses against pathogens and probably function as priming molecules leading to pathogen-associated molecular patterns (PAMP)-triggered immunity and effector-triggered immunity in plants. These putative roles also depend greatly on coordinated relationships with hormones and the light status in an intricate network. Although evidence in favour of sugar-mediated plant immunity is accumulating, more in-depth fundamental research is required to unravel the sugar signalling pathways involved. This might pave the way for the use of biodegradable sugar-(like) compounds to counteract plant diseases as cheaper and safer alternatives for toxic agrochemicals.

[Fanconi anemia: cellular and molecular features].

PubMed

Macé, G; Briot, D; Guervilly, J-H; Rosselli, F

2007-02-01

Fanconi anemia (FA) is a recessive human cancer prone syndrome featuring bone marrow failure, developmental abnormalities and hypersensitivity to DNA crosslinking agents exposure. 11 among 12 FA gene have been isolated. The biochemical functions of the FANC proteins remain poorly understood. Anyhow, to cope with DNA crosslinks a cell needs a functional FANC pathway. Moreover, the FANC proteins appear to be involved in cell protection against oxidative damage and in the control of TNF-alpha activity. In this review, we describe the current understanding of the FANC pathway and we present how it may be integrated in the complex networks of proteins involved in maintaining the cellular homeostasis.

Protein complexes and functional modules in molecular networks

NASA Astrophysics Data System (ADS)

Spirin, Victor; Mirny, Leonid A.

2003-10-01

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

Competing dynamic phases of active polymer networks

NASA Astrophysics Data System (ADS)

Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Identification of the Kelch Family Protein Nd1-L as a Novel Molecular Interactor of KRIT1

PubMed Central

Cutano, Valentina; Martino, Chiara

2012-01-01

Loss-of-function mutations of the KRIT1 gene (CCM1) have been associated with the Cerebral Cavernous Malformation (CCM) disease, which is characterized by serious alterations of brain capillary architecture. The KRIT1 protein contains multiple interaction domains and motifs, suggesting that it might act as a scaffold for the assembly of functional protein complexes involved in signaling networks. In previous work, we defined structure-function relationships underlying KRIT1 intramolecular and intermolecular interactions and nucleocytoplasmic shuttling, and found that KRIT1 plays an important role in molecular mechanisms involved in the maintenance of the intracellular Reactive Oxygen Species (ROS) homeostasis to prevent oxidative cellular damage. Here we report the identification of the Kelch family protein Nd1-L as a novel molecular interactor of KRIT1. This interaction was discovered through yeast two-hybrid screening of a mouse embryo cDNA library, and confirmed by pull-down and co-immunoprecipitation assays of recombinant proteins, as well as by co-immunoprecipitation of endogenous proteins in human endothelial cells. Furthermore, using distinct KRIT1 isoforms and mutants, we defined the role of KRIT1 domains in the Nd1-L/KRIT1 interaction. Finally, functional assays showed that Nd1-L may contribute to the regulation of KRIT1 nucleocytoplasmic shuttling and cooperate with KRIT1 in modulating the expression levels of the antioxidant protein SOD2, opening a novel avenue for future mechanistic studies. The identification of Nd1-L as a novel KRIT1 interacting protein provides a novel piece of the molecular puzzle involving KRIT1 and suggests a potential functional cooperation in cellular responses to oxidative stress, thus expanding the framework of molecular complexes and mechanisms that may underlie the pathogenesis of CCM disease. PMID:22970292

Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses.

PubMed

Mach, Núria; Ramayo-Caldas, Yuliaxis; Clark, Allison; Moroldo, Marco; Robert, Céline; Barrey, Eric; López, Jesús Maria; Le Moyec, Laurence

2017-02-17

Endurance exercise in horses requires adaptive processes involving physiological, biochemical, and cognitive-behavioral responses in an attempt to regain homeostasis. We hypothesized that the identification of the relationships between blood metabolome, transcriptome, and miRNome during endurance exercise in horses could provide significant insights into the molecular response to endurance exercise. For this reason, the serum metabolome and whole-blood transcriptome and miRNome data were obtained from ten horses before and after a 160 km endurance competition. We obtained a global regulatory network based on 11 unique metabolites, 263 metabolic genes and 5 miRNAs whose expression was significantly altered at T1 (post- endurance competition) relative to T0 (baseline, pre-endurance competition). This network provided new insights into the cross talk between the distinct molecular pathways (e.g. energy and oxygen sensing, oxidative stress, and inflammation) that were not detectable when analyzing single metabolites or transcripts alone. Single metabolites and transcripts were carrying out multiple roles and thus sharing several biochemical pathways. Using a regulatory impact factor metric analysis, this regulatory network was further confirmed at the transcription factor and miRNA levels. In an extended cohort of 31 independent animals, multiple factor analysis confirmed the strong associations between lactate, methylene derivatives, miR-21-5p, miR-16-5p, let-7 family and genes that coded proteins involved in metabolic reactions primarily related to energy, ubiquitin proteasome and lipopolysaccharide immune responses after the endurance competition. Multiple factor analysis also identified potential biomarkers at T0 for an increased likelihood for failure to finish an endurance competition. To the best of our knowledge, the present study is the first to provide a comprehensive and integrated overview of the metabolome, transcriptome, and miRNome co-regulatory networks that may have a key role in regulating the metabolic and immune response to endurance exercise in horses.

NFκB pathway analysis: An approach to analyze gene co-expression networks employing feedback cycles.

PubMed

Dillenburg, Fabiane Cristine; Zanotto-Filho, Alfeu; Fonseca Moreira, José Cláudio; Ribeiro, Leila; Carro, Luigi

2018-02-01

The genes of the NFκB pathway are involved in the control of a plethora of biological processes ranking from inhibition of apoptosis to metastasis in cancer. It has been described that Gliobastoma multiforme (GBM) patients carry aberrant NFκB activation, but the molecular mechanisms are not completely understood. Here, we present a NFκB pathway analysis in tumor specimens of GBM compared to non-neoplasic brain tissues, based on the different kind of cycles found among genes of a gene co-expression network constructed using quantized data obtained from the microarrays. A cycle is a closed walk with all vertices distinct (except the first and last). Thanks to this way of finding relations among genes, a more robust interpretation of gene correlations is possible, because the cycles are associated with feedback mechanisms that are very common in biological networks. In GBM samples, we could conclude that the stoichiometric relationship between genes involved in NFκB pathway regulation is unbalanced. This can be measured and explained by the identification of a cycle. This conclusion helps to understand more about the biology of this type of tumor. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reverse Engineering Cellular Networks with Information Theoretic Methods

PubMed Central

Villaverde, Alejandro F.; Ross, John; Banga, Julio R.

2013-01-01

Building mathematical models of cellular networks lies at the core of systems biology. It involves, among other tasks, the reconstruction of the structure of interactions between molecular components, which is known as network inference or reverse engineering. Information theory can help in the goal of extracting as much information as possible from the available data. A large number of methods founded on these concepts have been proposed in the literature, not only in biology journals, but in a wide range of areas. Their critical comparison is difficult due to the different focuses and the adoption of different terminologies. Here we attempt to review some of the existing information theoretic methodologies for network inference, and clarify their differences. While some of these methods have achieved notable success, many challenges remain, among which we can mention dealing with incomplete measurements, noisy data, counterintuitive behaviour emerging from nonlinear relations or feedback loops, and computational burden of dealing with large data sets. PMID:24709703

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

PubMed Central

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-01-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration. PMID:27241320

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

NASA Astrophysics Data System (ADS)

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-05-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

Molecular mechanisms of OLIG2 transcription factor in brain cancer

PubMed Central

Lian, Nathan; Kesari, Santosh

2016-01-01

Oligodendrocyte lineage transcription factor 2 (OLIG2) plays a pivotal role in glioma development. Here we conducted a comprehensive study of the critical gene regulatory networks involving OLIG2. These include the networks responsible for OLIG2 expression, its translocation to nucleus, cell cycle, epigenetic regulation, and Rho-pathway interactions. We described positive feedback loops including OLIG2: loops of epigenetic regulation and loops involving receptor tyrosine kinases. These loops may be responsible for the prolonged oncogenic activity of OLIG2. The proposed schemes for epigenetic regulation of the gene networks involving OLIG2 are confirmed by patient survival (Kaplan–Meier) curves based on the cancer genome atlas (TCGA) datasets. Finally, we elucidate the Coherent-Gene Modules (CGMs) networks—framework of OLIG2 involvement in cancer. We showed that genes interacting with OLIG2 formed eight CGMs having a set of intermodular connections. We showed also that among the genes involved in these modules the most connected hub is EGFR, then, on lower level, HSP90 and CALM1, followed by three lower levels including epigenetic genes KDM1A and NCOR1. The genes on the six upper levels of the hierarchy are involved in interconnections of all eight CGMs and organize functionally defined gene-signaling subnetworks having specific functions. For example, CGM1 is involved in epigenetic control. CGM2 is significantly related to cell proliferation and differentiation. CGM3 includes a number of interconnected helix–loop–helix transcription factors (bHLH) including OLIG2. Many of these TFs are partially controlled by OLIG2. The CGM4 is involved in PDGF-related: angiogenesis, tumor cell proliferation and differentiation. These analyses provide testable hypotheses and approaches to inhibit OLIG2 pathway and relevant feed-forward and feedback loops to be interrogated. This broad approach can be applied to other TFs. PMID:27447975

Nonlinear microrheology and molecular imaging to map microscale deformations of entangled DNA networks

NASA Astrophysics Data System (ADS)

Wu, Tsai-Chin; Anderson, Rae

We use active microrheology coupled to single-molecule fluorescence imaging to elucidate the microscale dynamics of entangled DNA. DNA naturally exists in a wide range of lengths and topologies, and is often confined in cell nucleui, forming highly concentrated and entangled biopolymer networks. Thus, DNA is the model polymer for understanding entangled polymer dynamics as well as the crowded environment of cells. These networks display complex viscoelastic properties that are not well understood, especially at the molecular-level and in response to nonlinear perturbations. Specifically, how microscopic stresses and strains propagate through entangled networks, and what molecular deformations lead to the network stress responses are unknown. To answer these important questions, we optically drive a microsphere through entangled DNA, perturbing the system far from equilibrium, while measuring the resistive force the DNA exerts on the bead during and after bead motion. We simultaneously image single fluorescent-labeled DNA molecules throughout the network to directly link the microscale stress response to molecular deformations. We characterize the deformation of the network from the molecular-level to the mesoscale, and map the stress propagation throughout the network. We further study the impact of DNA length (11 - 115 kbp) and topology (linear vs ring DNA) on deformation and propagation dynamics, exploring key nonlinear features such as tube dilation and power-law relaxation.

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

PubMed Central

Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

Analyzing milestoning networks for molecular kinetics: definitions, algorithms, and examples.

PubMed

Viswanath, Shruthi; Kreuzer, Steven M; Cardenas, Alfredo E; Elber, Ron

2013-11-07

Network representations are becoming increasingly popular for analyzing kinetic data from techniques like Milestoning, Markov State Models, and Transition Path Theory. Mapping continuous phase space trajectories into a relatively small number of discrete states helps in visualization of the data and in dissecting complex dynamics to concrete mechanisms. However, not only are molecular networks derived from molecular dynamics simulations growing in number, they are also getting increasingly complex, owing partly to the growth in computer power that allows us to generate longer and better converged trajectories. The increased complexity of the networks makes simple interpretation and qualitative insight of the molecular systems more difficult to achieve. In this paper, we focus on various network representations of kinetic data and algorithms to identify important edges and pathways in these networks. The kinetic data can be local and partial (such as the value of rate coefficients between states) or an exact solution to kinetic equations for the entire system (such as the stationary flux between vertices). In particular, we focus on the Milestoning method that provides fluxes as the main output. We proposed Global Maximum Weight Pathways as a useful tool for analyzing molecular mechanism in Milestoning networks. A closely related definition was made in the context of Transition Path Theory. We consider three algorithms to find Global Maximum Weight Pathways: Recursive Dijkstra's, Edge-Elimination, and Edge-List Bisection. The asymptotic efficiency of the algorithms is analyzed and numerical tests on finite networks show that Edge-List Bisection and Recursive Dijkstra's algorithms are most efficient for sparse and dense networks, respectively. Pathways are illustrated for two examples: helix unfolding and membrane permeation. Finally, we illustrate that networks based on local kinetic information can lead to incorrect interpretation of molecular mechanisms.

Effects of 5-h multimodal stress on the molecules and pathways involved in dendritic morphology and cognitive function.

PubMed

Xu, Yiran; Cheng, Xiaorui; Cui, Xiuliang; Wang, Tongxing; Liu, Gang; Yang, Ruishang; Wang, Jianhui; Bo, Xiaochen; Wang, Shengqi; Zhou, Wenxia; Zhang, Yongxiang

2015-09-01

Stress induces cognitive impairments, which are likely related to the damaged dendritic morphology in the brain. Treatments for stress-induced impairments remain limited because the molecules and pathways underlying these impairments are unknown. Therefore, the aim of this study was to find the potential molecules and pathways related to damage of the dendritic morphology induced by stress. To do this, we detected gene expression, constructed a protein-protein interaction (PPI) network, and analyzed the molecular pathways in the brains of mice exposed to 5-h multimodal stress. The results showed that stress increased plasma corticosterone concentration, decreased cognitive function, damaged dendritic morphologies, and altered APBB1, CLSTN1, KCNA4, NOTCH3, PLAU, RPS6KA1, SYP, TGFB1, KCNA1, NTRK3, and SNCA expression in the brains of mice. Further analyses found that the abnormal expressions of CLSTN1, PLAU, NOTCH3, and TGFB1 induced by stress were related to alterations in the dendritic morphology. These four genes demonstrated interactions with 55 other genes, and configured a closed PPI network. Molecular pathway analysis use the Database for Annotation, Visualization, and Integrated Discovery (DAVID), specifically the gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG), each identified three pathways that were significantly enriched in the gene list of the PPI network, with genes belonging to the Notch and transforming growth factor-beta (TGF-B) signaling pathways being the most enriched. Our results suggest that TGFB1, PLAU, NOTCH3, and CLSTN1 may be related to the alterations in dendritic morphology induced by stress, and imply that the Notch and TGF-B signaling pathways may be involved. Copyright © 2015 Elsevier Inc. All rights reserved.

Familial hypercholesterolemia: The Italian Atherosclerosis Society Network (LIPIGEN).

PubMed

Averna, Maurizio; Cefalù, Angelo B; Casula, Manuela; Noto, Davide; Arca, Marcello; Bertolini, Stefano; Calandra, Sebastiano; Catapano, Alberico L; Tarugi, Patrizia

2017-10-01

Primary dyslipidemias are a heterogeneous group of disorders characterized by abnormal levels of circulating lipoproteins. Among them, familial hypercholesterolemia is the most common lipid disorder that predisposes for premature cardiovascular disease. We set up an Italian nationwide network aimed at facilitating the clinical and genetic diagnosis of genetic dyslipidemias named LIPIGEN (LIpid TransPort Disorders Italian GEnetic Network). Observational, multicenter, retrospective and prospective study involving about 40 Italian clinical centers. Genetic testing of the appropriate candidate genes at one of six molecular diagnostic laboratories serving as nationwide DNA diagnostic centers. From 2012 to October 2016, available biochemical and clinical information of 3480 subjects with familial hypercholesterolemia identified according to the Dutch Lipid Clinic Network (DLCN) score were included in the database and genetic analysis was performed in 97.8% of subjects, with a mutation detection rate of 92.0% in patients with DLCN score ≥6. The establishment of the LIPIGEN network will have important effects on clinical management and it will improve the overall identification and treatment of primary dyslipidemias in Italy. Copyright © 2017. Published by Elsevier B.V.

Immunomediated Pan-cancer Regulation Networks are Dominant Fingerprints After Treatment of Cell Lines with Demethylation.

PubMed

El Baroudi, Mariama; Cinti, Caterina; Capobianco, Enrico

2016-01-01

Pan-cancer studies are particularly relevant not only for addressing the complexity of the inherently observed heterogeneity but also for identifying clinically relevant features that may be common to the cancer types. Immune system regulations usually reveal synergistic modulation with other cancer mechanisms and in combination provide insights on possible advances in cancer immunotherapies. Network inference is a powerful approach to decipher pan-cancer systems dynamics. The methodology proposed in this study elucidates the impacts of epigenetic treatment on the drivers of complex pan-cancer regulation circuits involving cell lines of five cancer types. These patterns were observed from differential gene expression measurements following demethylation with 5-azacytidine. Networks were built to establish associations of phenotypes at molecular level with cancer hallmarks through both transcriptional and post-transcriptional regulation mechanisms. The most prominent feature that emerges from our integrative network maps, linking pathway landscapes to disease and drug-target associations, refers primarily to a mosaic of immune-system crosslinked influences. Therefore, characteristics initially evidenced in single cancer maps become motifs well summarized by network cores and fingerprints.

Using the shared genetics of dystonia and ataxia to unravel their pathogenesis

PubMed Central

Nibbeling, Esther A.R.; Delnooz, Cathérine C.S.; de Koning, Tom J.; Sinke, Richard J.; Jinnah, Hyder A.; Tijssen, Marina A.J.; Verbeek, Dineke S.

2018-01-01

In this review we explore the similarities between spinocerebellar ataxias and dystonias, and suggest potentially shared molecular pathways using a gene co-expression network approach. The spinocerebellar ataxias are a group of neurodegenerative disorders characterized by coordination problems caused mainly by atrophy of the cerebellum. The dystonias are another group of neurological movement disorders linked to basal ganglia dysfunction, although evidence is now pointing to cerebellar involvement as well. Our gene co-expression network approach identified 99 shared genes and showed the involvement of two major pathways: synaptic transmission and neurodevelopment. These pathways overlapped in the two disorders, with a large role for GABAergic signaling in both. The overlapping pathways may provide novel targets for disease therapies. We need to prioritize variants obtained by whole exome sequencing in the genes associated with these pathways in the search for new pathogenic variants, which can than be used to help in the genetic counseling of patients and their families. PMID:28143763

Systems Biomedicine of Rabies Delineates the Affected Signaling Pathways.

PubMed

Azimzadeh Jamalkandi, Sadegh; Mozhgani, Sayed-Hamidreza; Gholami Pourbadie, Hamid; Mirzaie, Mehdi; Noorbakhsh, Farshid; Vaziri, Behrouz; Gholami, Alireza; Ansari-Pour, Naser; Jafari, Mohieddin

2016-01-01

The prototypical neurotropic virus, rabies, is a member of the Rhabdoviridae family that causes lethal encephalomyelitis. Although there have been a plethora of studies investigating the etiological mechanism of the rabies virus and many precautionary methods have been implemented to avert the disease outbreak over the last century, the disease has surprisingly no definite remedy at its late stages. The psychological symptoms and the underlying etiology, as well as the rare survival rate from rabies encephalitis, has still remained a mystery. We, therefore, undertook a systems biomedicine approach to identify the network of gene products implicated in rabies. This was done by meta-analyzing whole-transcriptome microarray datasets of the CNS infected by strain CVS-11, and integrating them with interactome data using computational and statistical methods. We first determined the differentially expressed genes (DEGs) in each study and horizontally integrated the results at the mRNA and microRNA levels separately. A total of 61 seed genes involved in signal propagation system were obtained by means of unifying mRNA and microRNA detected integrated DEGs. We then reconstructed a refined protein-protein interaction network (PPIN) of infected cells to elucidate the rabies-implicated signal transduction network (RISN). To validate our findings, we confirmed differential expression of randomly selected genes in the network using Real-time PCR. In conclusion, the identification of seed genes and their network neighborhood within the refined PPIN can be useful for demonstrating signaling pathways including interferon circumvent, toward proliferation and survival, and neuropathological clue, explaining the intricate underlying molecular neuropathology of rabies infection and thus rendered a molecular framework for predicting potential drug targets.

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

PubMed

Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.).

PubMed

Moschen, Sebastián; Di Rienzo, Julio A; Higgins, Janet; Tohge, Takayuki; Watanabe, Mutsumi; González, Sergio; Rivarola, Máximo; García-García, Francisco; Dopazo, Joaquin; Hopp, H Esteban; Hoefgen, Rainer; Fernie, Alisdair R; Paniego, Norma; Fernández, Paula; Heinz, Ruth A

2017-07-01

By integration of transcriptional and metabolic profiles we identified pathways and hubs transcription factors regulated during drought conditions in sunflower, useful for applications in molecular and/or biotechnological breeding. Drought is one of the most important environmental stresses that effects crop productivity in many agricultural regions. Sunflower is tolerant to drought conditions but the mechanisms involved in this tolerance remain unclear at the molecular level. The aim of this study was to characterize and integrate transcriptional and metabolic pathways related to drought stress in sunflower plants, by using a system biology approach. Our results showed a delay in plant senescence with an increase in the expression level of photosynthesis related genes as well as higher levels of sugars, osmoprotectant amino acids and ionic nutrients under drought conditions. In addition, we identified transcription factors that were upregulated during drought conditions and that may act as hubs in the transcriptional network. Many of these transcription factors belong to families implicated in the drought response in model species. The integration of transcriptomic and metabolomic data in this study, together with physiological measurements, has improved our understanding of the biological responses during droughts and contributes to elucidate the molecular mechanisms involved under this environmental condition. These findings will provide useful biotechnological tools to improve stress tolerance while maintaining crop yield under restricted water availability.

Molecular mechanisms of liver preconditioning

PubMed Central

Alchera, Elisa; Dal Ponte, Caterina; Imarisio, Chiara; Albano, Emanuele; Carini, Rita

2010-01-01

Ischemia/reperfusion (I/R) injury still represents an important cause of morbidity following hepatic surgery and limits the use of marginal livers in hepatic transplantation. Transient blood flow interruption followed by reperfusion protects tissues against damage induced by subsequent I/R. This process known as ischemic preconditioning (IP) depends upon intrinsic cytoprotective systems whose activation can inhibit the progression of irreversible tissue damage. Compared to other organs, liver IP has additional features as it reduces inflammation and promotes hepatic regeneration. Our present understanding of the molecular mechanisms involved in liver IP is still largely incomplete. Experimental studies have shown that the protective effects of liver IP are triggered by the release of adenosine and nitric oxide and the subsequent activation of signal networks involving protein kinases such as phosphatidylinositol 3-kinase, protein kinase C δ/ε and p38 MAP kinase, and transcription factors such as signal transducer and activator of transcription 3, nuclear factor-κB and hypoxia-inducible factor 1. This article offers an overview of the molecular events underlying the preconditioning effects in the liver and points to the possibility of developing pharmacological approaches aimed at activating the intrinsic protective systems in patients undergoing liver surgery. PMID:21182220

Transcriptional profiling of NCI/ADR-RES cells unveils a complex network of signaling pathways and molecular mechanisms of drug resistance

PubMed Central

Vert, Anna; Castro, Jessica; Ribó, Marc; Vilanova, Maria; Benito, Antoni

2018-01-01

Background Ovarian cancer has the highest mortality rate among all the gynecological cancers. This is mostly due to the resistance of ovarian cancer to current chemotherapy regimens. Therefore, it is of crucial importance to identify the molecular mechanisms associated with chemoresistance. Methods NCI/ADR-RES is a multidrug-resistant cell line that is a model for the study of drug resistance in ovarian cancer. We carried out a microarray-derived transcriptional profiling analysis of NCI/ADR-RES to identify differentially expressed genes relative to its parental OVCAR-8. Results Gene-expression profiling has allowed the identification of genes and pathways that may be important for the development of drug resistance in ovarian cancer. The NCI/ADR-RES cell line has differential expression of genes involved in drug extrusion, inactivation, and efficacy, as well as genes involved in the architectural and functional reorganization of the extracellular matrix. These genes are controlled through different signaling pathways, including MAPK–Akt, Wnt, and Notch. Conclusion Our findings highlight the importance of using orthogonal therapies that target completely independent pathways to overcome mechanisms of resistance to both classical chemotherapeutic agents and molecularly targeted drugs. PMID:29379303

Deciphering metabonomics biomarkers-targets interactions for psoriasis vulgaris by network pharmacology.

PubMed

Gu, Jiangyong; Li, Li; Wang, Dongmei; Zhu, Wei; Han, Ling; Zhao, Ruizhi; Xu, Xiaojie; Lu, Chuanjian

2018-06-01

Psoriasis vulgaris is a chronic inflammatory and immune-mediated skin disease. 44 metabonomics biomarkers were identified by high-throughput liquid chromatography coupled to mass spectrometry in our previous work, but the roles of metabonomics biomarkers in the pathogenesis of psoriasis is unclear. The metabonomics biomarker-enzyme network was constructed. The key metabonomics biomarkers and enzymes were screened out by network analysis. The binding affinity between each metabonomics biomarker and target was calculated by molecular docking. A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways. Long-chain fatty acids, phospholipids, Estradiol and NADH were the most important metabonomics biomarkers. Most key enzymes belonged hydrolase, thioesterase and acyltransferase. Six proteins (TNF-alpha, MAPK3, iNOS, eNOS, COX2 and mTOR) were extensively involved in inflammatory reaction, immune response and cell proliferation, and might be drug targets for psoriasis. PI3K-Akt signaling pathway and five other pathways had close correlation with the pathogenesis of psoriasis and could deserve further research. The inflammatory reaction, immune response and cell proliferation are mainly involved in psoriasis. Network pharmacology provide a new insight into the relationships between metabonomics biomarkers and the pathogenesis of psoriasis. KEY MESSAGES   • Network pharmacology was adopted to identify key metabonomics biomarkers and enzymes.   • Six proteins were screened out as important drug targets for psoriasis.   • A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways.

Disruption of a Regulatory Network Consisting of Neutrophils and Platelets Fosters Persisting Inflammation in Rheumatic Diseases

PubMed Central

Maugeri, Norma; Rovere-Querini, Patrizia; Manfredi, Angelo A.

2016-01-01

A network of cellular interactions that involve blood leukocytes and platelets maintains vessel homeostasis. It plays a critical role in the response to invading microbes by recruiting intravascular immunity and through the generation of neutrophil extracellular traps (NETs) and immunothrombosis. Moreover, it enables immune cells to respond to remote chemoattractants by crossing the endothelial barrier and reaching sites of infection. Once the network operating under physiological conditions is disrupted, the reciprocal activation of cells in the blood and the vessel walls determines the vascular remodeling via inflammatory signals delivered to stem/progenitor cells. A deregulated leukocyte/mural cell interaction is an early critical event in the natural history of systemic inflammation. Despite intense efforts, the signals that initiate and sustain the immune-mediated vessel injury, or those that enforce the often-prolonged phases of clinical quiescence in patients with vasculitis, have only been partially elucidated. Here, we discuss recent evidence that implicates the prototypic damage-associated molecular pattern/alarmin, the high mobility group box 1 (HMGB1) protein in systemic vasculitis and in the vascular inflammation associated with systemic sclerosis. HMGB1 could represent a player in the pathogenesis of rheumatic diseases and an attractive target for molecular interventions. PMID:27242789

Casein Kinase 1 Promotes Synchrony of the Circadian Clock Network

PubMed Central

Zheng, Xiangzhong; Sowcik, Mallory; Chen, Dechun

2014-01-01

Casein kinase 1, known as DOUBLETIME (DBT) in Drosophila melanogaster, is a critical component of the circadian clock that phosphorylates and promotes degradation of the PERIOD (PER) protein. However, other functions of DBT in circadian regulation are not clear, in part because severe reduction of dbt causes preadult lethality. Here we report the molecular and behavioral phenotype of a viable dbtEY02910 loss-of-function mutant. We found that DBT protein levels are dramatically reduced in adult dbtEY02910 flies, and the majority of mutant flies display arrhythmic behavior, with a few showing weak, long-period (∼32 h) rhythms. Peak phosphorylation of PER is delayed, and both hyper- and hypophosphorylated forms of the PER and CLOCK proteins are present throughout the day. In addition, molecular oscillations of the circadian clock are dampened. In the central brain, PER and TIM expression is heterogeneous and decoupled in the canonical clock neurons of the dbtEY02910 mutants. We also report an interaction between dbt and the signaling pathway involving pigment dispersing factor (PDF), a synchronizing peptide in the clock network. These data thus demonstrate that overall reduction of DBT causes long and arrhythmic behavior, and they reveal an unexpected role of DBT in promoting synchrony of the circadian clock network. PMID:24820422

Applications of computational models to better understand microvascular remodelling: a focus on biomechanical integration across scales

PubMed Central

Murfee, Walter L.; Sweat, Richard S.; Tsubota, Ken-ichi; Gabhann, Feilim Mac; Khismatullin, Damir; Peirce, Shayn M.

2015-01-01

Microvascular network remodelling is a common denominator for multiple pathologies and involves both angiogenesis, defined as the sprouting of new capillaries, and network patterning associated with the organization and connectivity of existing vessels. Much of what we know about microvascular remodelling at the network, cellular and molecular scales has been derived from reductionist biological experiments, yet what happens when the experiments provide incomplete (or only qualitative) information? This review will emphasize the value of applying computational approaches to advance our understanding of the underlying mechanisms and effects of microvascular remodelling. Examples of individual computational models applied to each of the scales will highlight the potential of answering specific questions that cannot be answered using typical biological experimentation alone. Looking into the future, we will also identify the needs and challenges associated with integrating computational models across scales. PMID:25844149

Evaluation of the applicability of the dual‐domain mass transfer model in porous media containing connected high‐conductivity channels

USGS Publications Warehouse

Liu, Gaisheng; Zheng, Chunmiao; Gorelick, Steven M.

2007-01-01

This paper evaluates the dual‐domain mass transfer (DDMT) model to represent transport processes when small‐scale high‐conductivity (K) preferential flow paths (PFPs) are present in a homogenous porous media matrix. The effects of PFPs upon solute transport were examined through detailed numerical experiments involving different realizations of PFP networks, PFP/matrix conductivity contrasts varying from 10:1 to 200:1, different magnitudes of effective conductivities, and a range of molecular diffusion coefficients. Results suggest that the DDMT model can reproduce both the near‐source peak and the downstream low‐concentration spreading observed in the embedded dendritic network when there are large conductivity contrasts between high‐K PFPs and the low‐K matrix. The accuracy of the DDMT model is also affected by the geometry of PFP networks and by the relative significance of the diffusion process in the network‐matrix system.

Convergent evolution and adaptation of Pseudomonas aeruginosa within patients with cystic fibrosis.

PubMed

Marvig, Rasmus Lykke; Sommer, Lea Mette; Molin, Søren; Johansen, Helle Krogh

2015-01-01

Little is known about how within-host evolution compares between genotypically different strains of the same pathogenic species. We sequenced the whole genomes of 474 longitudinally collected clinical isolates of Pseudomonas aeruginosa sampled from 34 children and young individuals with cystic fibrosis. Our analysis of 36 P. aeruginosa lineages identified convergent molecular evolution in 52 genes. This list of genes suggests a role in host adaptation for remodeling of regulatory networks and central metabolism, acquisition of antibiotic resistance and loss of extracellular virulence factors. Furthermore, we find an ordered succession of mutations in key regulatory networks. Accordingly, mutations in downstream transcriptional regulators were contingent upon mutations in upstream regulators, suggesting that remodeling of regulatory networks might be important in adaptation. The characterization of genes involved in host adaptation may help in predicting bacterial evolution in patients with cystic fibrosis and in the design of future intervention strategies.

A Module Analysis Approach to Investigate Molecular Mechanism of TCM Formula: A Trial on Shu-feng-jie-du Formula

PubMed Central

Zhang, Fangbo; Tang, Shihuan; Liu, Xi; Gao, Yibo; Wang, Yanping

2013-01-01

At the molecular level, it is acknowledged that a TCM formula is often a complex system, which challenges researchers to fully understand its underlying pharmacological action. However, module detection technique developed from complex network provides new insight into systematic investigation of the mode of action of a TCM formula from the molecule perspective. We here proposed a computational approach integrating the module detection technique into a 2-class heterogeneous network (2-HN) which models the complex pharmacological system of a TCM formula. This approach takes three steps: construction of a 2-HN, identification of primary pharmacological units, and pathway analysis. We employed this approach to study Shu-feng-jie-du (SHU) formula, which aimed at discovering its molecular mechanism in defending against influenza infection. Actually, four primary pharmacological units were identified from the 2-HN for SHU formula and further analysis revealed numbers of biological pathways modulated by the four pharmacological units. 24 out of 40 enriched pathways that were ranked in top 10 corresponding to each of the four pharmacological units were found to be involved in the process of influenza infection. Therefore, this approach is capable of uncovering the mode of action underlying a TCM formula via module analysis. PMID:24376467

VirHostNet 2.0: surfing on the web of virus/host molecular interactions data.

PubMed

Guirimand, Thibaut; Delmotte, Stéphane; Navratil, Vincent

2015-01-01

VirHostNet release 2.0 (http://virhostnet.prabi.fr) is a knowledgebase dedicated to the network-based exploration of virus-host protein-protein interactions. Since the previous VirhostNet release (2009), a second run of manual curation was performed to annotate the new torrent of high-throughput protein-protein interactions data from the literature. This resource is shared publicly, in PSI-MI TAB 2.5 format, using a PSICQUIC web service. The new interface of VirHostNet 2.0 is based on Cytoscape web library and provides a user-friendly access to the most complete and accurate resource of virus-virus and virus-host protein-protein interactions as well as their projection onto their corresponding host cell protein interaction networks. We hope that the VirHostNet 2.0 system will facilitate systems biology and gene-centered analysis of infectious diseases and will help to identify new molecular targets for antiviral drugs design. This resource will also continue to help worldwide scientists to improve our knowledge on molecular mechanisms involved in the antiviral response mediated by the cell and in the viral strategies selected by viruses to hijack the host immune system. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Silencing of karyopherin α2 inhibits cell growth and survival in human hepatocellular carcinoma

PubMed Central

Yang, Yunfeng; Guo, Jian; Hao, Yuxia; Wang, Fuhua; Li, Fengxia; Shuang, Shaomin; Wang, Junping

2017-01-01

Karyopherin α2 (KPNA2), involved in nucleocytoplasmic transport, has been reported to be upregulated in hepatocellular carcinoma and considered as a biomarker for poor prognosis. However, comprehensive studies of KPNA2 functions in hepatocellular carcinogenesis are still lacking. Our study examine the roles and related molecular mechanisms of KPNA2 in hepatocellular carcinoma development. Results show that KPNA2 knockdown inhibited the proliferation and growth of hepatocellular carcinoma cells in vitro and in vivo. KPNA2 knockdown also inhibited colony formation ability, induced cell cycle arrest and cellular apoptosis in two hepatocellular carcinoma cell lines, HepG2 and SMMC-7721. Furthermore, gene expression microarray analysis in HepG2 cells with KPNA2 knockdown revealed that critical signaling pathways involved in cell proliferation and survival were deregulated. In conclusion, this study provided systematic evidence that KPNA2 was an essential factor promoting hepatocellular carcinoma and unraveled potential molecular pathways and networks underlying KPNA2-induced hepatocellular carcinogenesis. PMID:28422734

Silencing of karyopherin α2 inhibits cell growth and survival in human hepatocellular carcinoma.

PubMed

Yang, Yunfeng; Guo, Jian; Hao, Yuxia; Wang, Fuhua; Li, Fengxia; Shuang, Shaomin; Wang, Junping

2017-05-30

Karyopherin α2 (KPNA2), involved in nucleocytoplasmic transport, has been reported to be upregulated in hepatocellular carcinoma and considered as a biomarker for poor prognosis. However, comprehensive studies of KPNA2 functions in hepatocellular carcinogenesis are still lacking. Our study examine the roles and related molecular mechanisms of KPNA2 in hepatocellular carcinoma development. Results show that KPNA2 knockdown inhibited the proliferation and growth of hepatocellular carcinoma cells in vitro and in vivo. KPNA2 knockdown also inhibited colony formation ability, induced cell cycle arrest and cellular apoptosis in two hepatocellular carcinoma cell lines, HepG2 and SMMC-7721. Furthermore, gene expression microarray analysis in HepG2 cells with KPNA2 knockdown revealed that critical signaling pathways involved in cell proliferation and survival were deregulated. In conclusion, this study provided systematic evidence that KPNA2 was an essential factor promoting hepatocellular carcinoma and unraveled potential molecular pathways and networks underlying KPNA2-induced hepatocellular carcinogenesis.

Phenotypic and Molecular Convergence of 2q23.1 Deletion Syndrome with Other Neurodevelopmental Syndromes Associated with Autism Spectrum Disorder

PubMed Central

Mullegama, Sureni V.; Alaimo, Joseph T.; Chen, Li; Elsea, Sarah H.

2015-01-01

Roughly 20% of autism spectrum disorders (ASD) are syndromic with a well-established genetic cause. Studying the genes involved can provide insight into the molecular and cellular mechanisms of ASD. 2q23.1 deletion syndrome (causative gene, MBD5) is a recently identified genetic neurodevelopmental disorder associated with ASD. Mutations in MBD5 have been found in ASD cohorts. In this study, we provide a phenotypic update on the prevalent features of 2q23.1 deletion syndrome, which include severe intellectual disability, seizures, significant speech impairment, sleep disturbance, and autistic-like behavioral problems. Next, we examined the phenotypic, molecular, and network/pathway relationships between nine neurodevelopmental disorders associated with ASD: 2q23.1 deletion Rett, Angelman, Pitt-Hopkins, 2q23.1 duplication, 5q14.3 deletion, Kleefstra, Kabuki make-up, and Smith-Magenis syndromes. We show phenotypic overlaps consisting of intellectual disability, speech delay, seizures, sleep disturbance, hypotonia, and autistic-like behaviors. Molecularly, MBD5 possibly regulates the expression of UBE3A, TCF4, MEF2C, EHMT1 and RAI1. Network analysis reveals that there could be indirect protein interactions, further implicating function for these genes in common pathways. Further, we show that when MBD5 and RAI1 are haploinsufficient, they perturb several common pathways that are linked to neuronal and behavioral development. These findings support further investigations into the molecular and pathway relationships among genes linked to neurodevelopmental disorders and ASD, which will hopefully lead to common points of regulation that may be targeted toward therapeutic intervention. PMID:25853262

A Systems Biology Approach to the Coordination of Defensive and Offensive Molecular Mechanisms in the Innate and Adaptive Host–Pathogen Interaction Networks

PubMed Central

Wu, Chia-Chou; Chen, Bor-Sen

2016-01-01

Infected zebrafish coordinates defensive and offensive molecular mechanisms in response to Candida albicans infections, and invasive C. albicans coordinates corresponding molecular mechanisms to interact with the host. However, knowledge of the ensuing infection-activated signaling networks in both host and pathogen and their interspecific crosstalk during the innate and adaptive phases of the infection processes remains incomplete. In the present study, dynamic network modeling, protein interaction databases, and dual transcriptome data from zebrafish and C. albicans during infection were used to infer infection-activated host–pathogen dynamic interaction networks. The consideration of host–pathogen dynamic interaction systems as innate and adaptive loops and subsequent comparisons of inferred innate and adaptive networks indicated previously unrecognized crosstalk between known pathways and suggested roles of immunological memory in the coordination of host defensive and offensive molecular mechanisms to achieve specific and powerful defense against pathogens. Moreover, pathogens enhance intraspecific crosstalk and abrogate host apoptosis to accommodate enhanced host defense mechanisms during the adaptive phase. Accordingly, links between physiological phenomena and changes in the coordination of defensive and offensive molecular mechanisms highlight the importance of host–pathogen molecular interaction networks, and consequent inferences of the host–pathogen relationship could be translated into biomedical applications. PMID:26881892

A Systems Biology Approach to the Coordination of Defensive and Offensive Molecular Mechanisms in the Innate and Adaptive Host-Pathogen Interaction Networks.

PubMed

Wu, Chia-Chou; Chen, Bor-Sen

2016-01-01

Infected zebrafish coordinates defensive and offensive molecular mechanisms in response to Candida albicans infections, and invasive C. albicans coordinates corresponding molecular mechanisms to interact with the host. However, knowledge of the ensuing infection-activated signaling networks in both host and pathogen and their interspecific crosstalk during the innate and adaptive phases of the infection processes remains incomplete. In the present study, dynamic network modeling, protein interaction databases, and dual transcriptome data from zebrafish and C. albicans during infection were used to infer infection-activated host-pathogen dynamic interaction networks. The consideration of host-pathogen dynamic interaction systems as innate and adaptive loops and subsequent comparisons of inferred innate and adaptive networks indicated previously unrecognized crosstalk between known pathways and suggested roles of immunological memory in the coordination of host defensive and offensive molecular mechanisms to achieve specific and powerful defense against pathogens. Moreover, pathogens enhance intraspecific crosstalk and abrogate host apoptosis to accommodate enhanced host defense mechanisms during the adaptive phase. Accordingly, links between physiological phenomena and changes in the coordination of defensive and offensive molecular mechanisms highlight the importance of host-pathogen molecular interaction networks, and consequent inferences of the host-pathogen relationship could be translated into biomedical applications.

Bioinformatics analysis on molecular mechanism of rheum officinale in treatment of jaundice

NASA Astrophysics Data System (ADS)

Shan, Si; Tu, Jun; Nie, Peng; Yan, Xiaojun

2017-01-01

Objective: To study the molecular mechanism of Rheum officinale in the treatment of Jaundice by building molecular networks and comparing canonical pathways. Methods: Target proteins of Rheum officinale and related genes of Jaundice were searched from Pubchem and Gene databases online respectively. Molecular networks and canonical pathways comparison analyses were performed by Ingenuity Pathway Analysis (IPA). Results: The molecular networks of Rheum officinale and Jaundice were complex and multifunctional. The 40 target proteins of Rheum officinale and 33 Homo sapiens genes of Jaundice were found in databases. There were 19 common pathways both related networks. Rheum officinale could regulate endothelial differentiation, Interleukin-1B (IL-1B) and Tumor Necrosis Factor (TNF) in these pathways. Conclusions: Rheum officinale treat Jaundice by regulating many effective nodes of Apoptotic pathway and cellular immunity related pathways.

HA metabolism in skin homeostasis and inflammatory disease.

PubMed

Kavasi, Rafaela-Maria; Berdiaki, Aikaterini; Spyridaki, Ioanna; Corsini, Emanuela; Tsatsakis, Aristidis; Tzanakakis, George; Nikitovic, Dragana

2017-03-01

Hyaluronan (HA), an unsulfated glycosaminoglycan, is an important component of the complex extracellular matrix network which surrounds and supports cells in tissues. HA is detected in all vertebrate tissues, but the bulk of HA is produced and deposited in the skin. In this review we focus on the role of HA in skin-associated inflammatory disease and wound healing. Properties of HA are directly dependent on its molecular weight. Thus, high molecular weight HA (HMWHA) is deposited in normal tissues during homeostasis and promotes their stability whereas low molecular weight HA fragments (LMWHA), on the other hand, may arise from enzymatic or chemical activities. The degradation of HMWHA to LMWHA fragments, often leads to the generation of biologically active oligosaccharides with different properties and postulated functions in wound scar formation and inflammation. More detailed studies of HA involvement in skin-associated inflammatory disease may result in novel treatment modalities. Copyright © 2017 Elsevier Ltd. All rights reserved.

The transcriptional regulatory network of Corynebacterium jeikeium K411 and its interaction with metabolic routes contributing to human body odor formation.

PubMed

Barzantny, Helena; Schröder, Jasmin; Strotmeier, Jasmin; Fredrich, Eugenie; Brune, Iris; Tauch, Andreas

2012-06-15

Lipophilic corynebacteria are involved in the generation of volatile odorous products in the process of human body odor formation by degrading skin lipids and specific odor precursors. Therefore, these bacteria represent appropriate model systems for the cosmetic industry to examine axillary malodor formation on the molecular level. To understand the transcriptional control of metabolic pathways involved in this process, the transcriptional regulatory network of the lipophilic axilla isolate Corynebacterium jeikeium K411 was reconstructed from the complete genome sequence. This bioinformatic approach detected a gene-regulatory repertoire of 83 candidate proteins, including 56 DNA-binding transcriptional regulators, nine two-component systems, nine sigma factors, and nine regulators with diverse physiological functions. Furthermore, a cross-genome comparison among selected corynebacterial species of the taxonomic cluster 3 revealed a common gene-regulatory repertoire of 44 transcriptional regulators, including the MarR-like regulator Jk0257, which is exclusively encoded in the genomes of this taxonomical subline. The current network reconstruction comprises 48 transcriptional regulators and 674 gene-regulatory interactions that were assigned to five interconnected functional modules. Most genes involved in lipid degradation are under the combined control of the global cAMP-sensing transcriptional regulator GlxR and the LuxR-family regulator RamA, probably reflecting the essential role of lipid degradation in C. jeikeium. This study provides the first genome-scale in silico analysis of the transcriptional regulation of metabolism in a lipophilic bacterium involved in the formation of human body odor. Copyright © 2012 Elsevier B.V. All rights reserved.

Proteomic Analysis of Gingival Tissue and Alveolar Bone during Alveolar Bone Healing*

PubMed Central

Yang, Hee-Young; Kwon, Joseph; Kook, Min-Suk; Kang, Seong Soo; Kim, Se Eun; Sohn, Sungoh; Jung, Seunggon; Kwon, Sang-Oh; Kim, Hyung-Seok; Lee, Jae Hyuk; Lee, Tae-Hoon

2013-01-01

Bone tissue regeneration is orchestrated by the surrounding supporting tissues and involves the build-up of osteogenic cells, which orchestrate remodeling/healing through the expression of numerous mediators and signaling molecules. Periodontal regeneration models have proven useful for studying the interaction and communication between alveolar bone and supporting soft tissue. We applied a quantitative proteomic approach to analyze and compare proteins with altered expression in gingival soft tissue and alveolar bone following tooth extraction. For target identification and validation, hard and soft tissue were extracted from mini-pigs at the indicated times after tooth extraction. From triplicate experiments, 56 proteins in soft tissue and 27 proteins in alveolar bone were found to be differentially expressed before and after tooth extraction. The expression of 21 of those proteins was altered in both soft tissue and bone. Comparison of the activated networks in soft tissue and alveolar bone highlighted their distinct responsibilities in bone and tissue healing. Moreover, we found that there is crosstalk between identified proteins in soft tissue and alveolar bone with respect to cellular assembly, organization, and communication. Among these proteins, we examined in detail the expression patterns and associated networks of ATP5B and fibronectin 1. ATP5B is involved in nucleic acid metabolism, small molecule biochemistry, and neurological disease, and fibronectin 1 is involved in cellular assembly, organization, and maintenance. Collectively, our findings indicate that bone regeneration is accompanied by a profound interaction among networks regulating cellular resources, and they provide novel insight into the molecular mechanisms involved in the healing of periodontal tissue after tooth extraction. PMID:23824910

Interplay between environmentally modulated feedback loops - hypoxia and circadian rhythms - two sides of the same coin?

PubMed

Depping, Reinhard; Oster, Henrik

2017-11-01

Sensing of environmental parameters is critically important for cells of metazoan organisms. Members of the superfamily of bHLH-PAS transcription factors, involved in oxygen sensing and circadian rhythm generation, are important players in such molecular pathways. The interplay between both networks includes a so far unknown factor, connecting PER2 (circadian clocks) to hypoxia sensing (HIF-1 α) to result in a more adapted state of homeostasis at the right time. © 2017 Federation of European Biochemical Societies.

Bromidotetra-kis-(2-ethyl-1H-imidazole-κN (3))copper(II) bromide.

PubMed

Godlewska, Sylwia; Kelm, Harald; Krüger, Hans-Jörg; Dołęga, Anna

2012-12-01

The Cu(II) ion in the title mol-ecular salt, [CuBr(C5H8N2)4]Br, is coordinated in a square-pyramidal geometry by four N atoms of imidazole ligands and one bromide anion in the apical position. In the crystal, the ions are linked by N-H⋯Br hydrogen bonds involving both the coordinating and the free bromide species as acceptors. A C-H⋯Br inter-action is also observed. Overall, a three-dimensional network results.

Insights into plant plasma membrane aquaporin trafficking.

PubMed

Hachez, Charles; Besserer, Arnaud; Chevalier, Adrien S; Chaumont, François

2013-06-01

Plasma membrane intrinsic proteins (PIPs) are plant aquaporins that facilitate the diffusion of water and small uncharged solutes through the cell membrane. Deciphering the network of interacting proteins that modulate PIP trafficking to and activity in the plasma membrane is essential to improve our knowledge about PIP regulation and function. This review highlights the most recent advances related to PIP subcellular routing and dynamic redistribution, identifies some key molecular interacting proteins, and indicates exciting directions for future research in this field. A better understanding of the mechanisms by which plants optimize water movement might help in identifying new molecular players of agronomical relevance involved in the control of cellular water uptake and drought tolerance. Copyright © 2012 Elsevier Ltd. All rights reserved.

Signaling Network Map of Endothelial TEK Tyrosine Kinase

PubMed Central

Sandhya, Varot K.; Singh, Priyata; Parthasarathy, Deepak; Kumar, Awinav; Gattu, Rudrappa; Mathur, Premendu Prakash; Mac Gabhann, F.; Pandey, Akhilesh

2014-01-01

TEK tyrosine kinase is primarily expressed on endothelial cells and is most commonly referred to as TIE2. TIE2 is a receptor tyrosine kinase modulated by its ligands, angiopoietins, to regulate the development and remodeling of vascular system. It is also one of the critical pathways associated with tumor angiogenesis and familial venous malformations. Apart from the vascular system, TIE2 signaling is also associated with postnatal hematopoiesis. Despite the involvement of TIE2-angiopoietin system in several diseases, the downstream molecular events of TIE2-angiopoietin signaling are not reported in any pathway repository. Therefore, carrying out a detailed review of published literature, we have documented molecular signaling events mediated by TIE2 in response to angiopoietins and developed a network map of TIE2 signaling. The pathway information is freely available to the scientific community through NetPath, a manually curated resource of signaling pathways. We hope that this pathway resource will provide an in-depth view of TIE2-angiopoietin signaling and will lead to identification of potential therapeutic targets for TIE2-angiopoietin associated disorders. PMID:25371820

Vertebrate Presynaptic Active Zone Assembly: a Role Accomplished by Diverse Molecular and Cellular Mechanisms.

PubMed

Torres, Viviana I; Inestrosa, Nibaldo C

2018-06-01

Among all the biological systems in vertebrates, the central nervous system (CNS) is the most complex, and its function depends on specialized contacts among neurons called synapses. The assembly and organization of synapses must be exquisitely regulated for a normal brain function and network activity. There has been a tremendous effort in recent decades to understand the molecular and cellular mechanisms participating in the formation of new synapses and their organization, maintenance, and regulation. At the vertebrate presynapses, proteins such as Piccolo, Bassoon, RIM, RIM-BPs, CAST/ELKS, liprin-α, and Munc13 are constant residents and participate in multiple and dynamic interactions with other regulatory proteins, which define network activity and normal brain function. Here, we review the function of these active zone (AZ) proteins and diverse factors involved in AZ assembly and maintenance, with an emphasis on axonal trafficking of precursor vesicles, protein homo- and hetero-oligomeric interactions as a mechanism of AZ trapping and stabilization, and the role of F-actin in presynaptic assembly and its modulation by Wnt signaling.

The role of CH/π interactions in the high affinity binding of streptavidin and biotin.

PubMed

Ozawa, Motoyasu; Ozawa, Tomonaga; Nishio, Motohiro; Ueda, Kazuyoshi

2017-08-01

The streptavidin-biotin complex has an extraordinarily high affinity (Ka: 10 15 mol -1 ) and contains one of the strongest non-covalent interactions known. This strong interaction is widely used in biological tools, including for affinity tags, detection, and immobilization of proteins. Although hydrogen bond networks and hydrophobic interactions have been proposed to explain this high affinity, the reasons for it remain poorly understood. Inspired by the deceased affinity of biotin observed for point mutations of streptavidin at tryptophan residues, we hypothesized that a CH/π interaction may also contribute to the strong interaction between streptavidin and biotin. CH/π interactions were explored and analyzed at the biotin-binding site and at the interface of the subunits by the fragment molecular orbital method (FMO) and extended applications: PIEDA and FMO4. The results show that CH/π interactions are involved in the high affinity for biotin at the binding site of streptavidin. We further suggest that the involvement of CH/π interactions at the subunit interfaces and an extended CH/π network play more critical roles in determining the high affinity, rather than involvement at the binding site. Copyright © 2017 Elsevier Inc. All rights reserved.

Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.

PubMed

Tian, Ye; Wang, Sean S; Zhang, Zhen; Rodriguez, Olga C; Petricoin, Emanuel; Shih, Ie-Ming; Chan, Daniel; Avantaggiati, Maria; Yu, Guoqiang; Ye, Shaozhen; Clarke, Robert; Wang, Chao; Zhang, Bai; Wang, Yue; Albanese, Chris

2014-01-01

Ever growing "omics" data and continuously accumulated biological knowledge provide an unprecedented opportunity to identify molecular biomarkers and their interactions that are responsible for cancer phenotypes that can be accurately defined by clinical measurements such as in vivo imaging. Since signaling or regulatory networks are dynamic and context-specific, systematic efforts to characterize such structural alterations must effectively distinguish significant network rewiring from random background fluctuations. Here we introduced a novel integration of network biology and imaging to study cancer phenotypes and responses to treatments at the molecular systems level. Specifically, Differential Dependence Network (DDN) analysis was used to detect statistically significant topological rewiring in molecular networks between two phenotypic conditions, and in vivo Magnetic Resonance Imaging (MRI) was used to more accurately define phenotypic sample groups for such differential analysis. We applied DDN to analyze two distinct phenotypic groups of breast cancer and study how genomic instability affects the molecular network topologies in high-grade ovarian cancer. Further, FDA-approved arsenic trioxide (ATO) and the ND2-SmoA1 mouse model of Medulloblastoma (MB) were used to extend our analyses of combined MRI and Reverse Phase Protein Microarray (RPMA) data to assess tumor responses to ATO and to uncover the complexity of therapeutic molecular biology.

Vitamins for enhancing plant resistance.

PubMed

Boubakri, Hatem; Gargouri, Mahmoud; Mliki, Ahmed; Brini, Faiçal; Chong, Julie; Jbara, Moez

2016-09-01

This paper provides an overview on vitamins with inducing activities in plants, the molecular and cellular mechanisms implicated, and the hormonal signalling-network regulating this process. Moreover, it reports how vitamins might be part of the molecular events linked to induced resistance by the conventional elicitors. Induced resistance (IR), exploiting the plant innate-defense system is a sustainable strategy for plant disease control. In the last decade, vitamins have been proven to act as inducers of disease resistance, and these findings have received an important attention owing to their safety and cost effectiveness. Vitamins, including thiamine (TH, vitamin B1), riboflavin (RF, vitamin B2), menadione sodium bisulfite (MSB, vitamin K3), Para-aminobenzoic acid (PABA, vitamin Bx), and folic acid (FA, vitamin B9) provided an efficient protection against a wide range of pathogens through the modulation of specific host-defense facets. However, other vitamins, such as ascorbic acid (AA, vitamin C) and tocopherols (vitamin E), have been shown to be a part of the molecular mechanisms associated to IR. The present review is the first to summarize what vitamins are acting as inducers of disease resistance in plants and how could they be modulated by the conventional elicitors. Thus, this report provides an overview on the protective abilities of vitamins and the molecular and cellular mechanisms underlying their activities. Moreover, it describes the hormonal-signalling network regulating vitamin-signal transduction during IR. Finally, a biochemical model describing how vitamins are involved in the establishment of IR process is discussed.

Systems Biology Methods for Alzheimer's Disease Research Toward Molecular Signatures, Subtypes, and Stages and Precision Medicine: Application in Cohort Studies and Trials.

PubMed

Castrillo, Juan I; Lista, Simone; Hampel, Harald; Ritchie, Craig W

2018-01-01

Alzheimer's disease (AD) is a complex multifactorial disease, involving a combination of genomic, interactome, and environmental factors, with essential participation of (a) intrinsic genomic susceptibility and (b) a constant dynamic interplay between impaired pathways and central homeostatic networks of nerve cells. The proper investigation of the complexity of AD requires new holistic systems-level approaches, at both the experimental and computational level. Systems biology methods offer the potential to unveil new fundamental insights, basic mechanisms, and networks and their interplay. These may lead to the characterization of mechanism-based molecular signatures, and AD hallmarks at the earliest molecular and cellular levels (and beyond), for characterization of AD subtypes and stages, toward targeted interventions according to the evolving precision medicine paradigm. In this work, an update on advanced systems biology methods and strategies for holistic studies of multifactorial diseases-particularly AD-is presented. This includes next-generation genomics, neuroimaging and multi-omics methods, experimental and computational approaches, relevant disease models, and latest genome editing and single-cell technologies. Their progressive incorporation into basic research, cohort studies, and trials is beginning to provide novel insights into AD essential mechanisms, molecular signatures, and markers toward mechanism-based classification and staging, and tailored interventions. Selected methods which can be applied in cohort studies and trials, with the European Prevention of Alzheimer's Dementia (EPAD) project as a reference example, are presented and discussed.

Molecular communication and networking: opportunities and challenges.

PubMed

Nakano, Tadashi; Moore, Michael J; Wei, Fang; Vasilakos, Athanasios V; Shuai, Jianwei

2012-06-01

The ability of engineered biological nanomachines to communicate with biological systems at the molecular level is anticipated to enable future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, we present the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. We then discuss challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications.

Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action

PubMed Central

Sun, Jingchun; Zhao, Min; Jia, Peilin; Wang, Lily; Wu, Yonghui; Iverson, Carissa; Zhou, Yubo; Bowton, Erica; Roden, Dan M.; Denny, Joshua C.; Aldrich, Melinda C.; Xu, Hua; Zhao, Zhongming

2015-01-01

A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin’s antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets. PMID:26083494

Optimality principles in the regulation of metabolic networks.

PubMed

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

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.

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.

Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

PubMed Central

Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.

2014-01-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology. PMID:24921649

Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

PubMed

Chen, Guocai; Cairelli, Michael J; Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C

2014-06-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.

Functional Network Disruption in the Degenerative Dementias

PubMed Central

Pievani, Michela; de Haan, Willem; Wu, Tao; Seeley, William W; Frisoni, Giovanni B

2011-01-01

Despite considerable advances toward understanding the molecular pathophysiology of the neurodegenerative dementias, the mechanisms linking molecular changes to neuropathology and the latter to clinical symptoms remain largely obscure. Connectivity is a distinctive feature of the brain and the integrity of functional network dynamics is critical for normal functioning. A better understanding of network disruption in the neurodegenerative dementias may help bridge the gap between molecular changes, pathology and symptoms. Recent findings on functional network disruption as assessed with “resting-state” or intrinsic connectivity fMRI and EEG/MEG have shown distinct patterns of network disruption across the major neurodegenerative diseases. These network abnormalities are relatively specific to the clinical syndromes, and in Alzheimer's disease and frontotemporal dementia network disruption tracks the pattern of pathological changes. These findings may have a practical impact on diagnostic accuracy, allowing earlier detection of neurodegenerative diseases even at the pre-symptomatic stage, and tracking of disease progression. PMID:21778116

Inferring causal molecular networks: empirical assessment through a community-based effort.

PubMed

Hill, Steven M; Heiser, Laura M; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K; Carlin, Daniel E; Zhang, Yang; Sokolov, Artem; Paull, Evan O; Wong, Chris K; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V; Favorov, Alexander V; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W; Long, Byron L; Noren, David P; Bisberg, Alexander J; Mills, Gordon B; Gray, Joe W; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A; Fertig, Elana J; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M; Spellman, Paul T; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach

2016-04-01

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.

Molecular ecological network analyses.

PubMed

Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong

2012-05-30

Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.

Emerging trends in the functional genomics of the abiotic stress response in crop plants.

PubMed

Vij, Shubha; Tyagi, Akhilesh K

2007-05-01

Plants are exposed to different abiotic stresses, such as water deficit, high temperature, salinity, cold, heavy metals and mechanical wounding, under field conditions. It is estimated that such stress conditions can potentially reduce the yield of crop plants by more than 50%. Investigations of the physiological, biochemical and molecular aspects of stress tolerance have been conducted to unravel the intrinsic mechanisms developed during evolution to mitigate against stress by plants. Before the advent of the genomics era, researchers primarily used a gene-by-gene approach to decipher the function of the genes involved in the abiotic stress response. However, abiotic stress tolerance is a complex trait and, although large numbers of genes have been identified to be involved in the abiotic stress response, there remain large gaps in our understanding of the trait. The availability of the genome sequences of certain important plant species has enabled the use of strategies, such as genome-wide expression profiling, to identify the genes associated with the stress response, followed by the verification of gene function by the analysis of mutants and transgenics. Certain components of both abscisic acid-dependent and -independent cascades involved in the stress response have already been identified. Information originating from the genome-wide analysis of abiotic stress tolerance will help to provide an insight into the stress-responsive network(s), and may allow the modification of this network to reduce the loss caused by stress and to increase agricultural productivity.

Systems Biomedicine of Rabies Delineates the Affected Signaling Pathways

PubMed Central

Azimzadeh Jamalkandi, Sadegh; Mozhgani, Sayed-Hamidreza; Gholami Pourbadie, Hamid; Mirzaie, Mehdi; Noorbakhsh, Farshid; Vaziri, Behrouz; Gholami, Alireza; Ansari-Pour, Naser; Jafari, Mohieddin

2016-01-01

The prototypical neurotropic virus, rabies, is a member of the Rhabdoviridae family that causes lethal encephalomyelitis. Although there have been a plethora of studies investigating the etiological mechanism of the rabies virus and many precautionary methods have been implemented to avert the disease outbreak over the last century, the disease has surprisingly no definite remedy at its late stages. The psychological symptoms and the underlying etiology, as well as the rare survival rate from rabies encephalitis, has still remained a mystery. We, therefore, undertook a systems biomedicine approach to identify the network of gene products implicated in rabies. This was done by meta-analyzing whole-transcriptome microarray datasets of the CNS infected by strain CVS-11, and integrating them with interactome data using computational and statistical methods. We first determined the differentially expressed genes (DEGs) in each study and horizontally integrated the results at the mRNA and microRNA levels separately. A total of 61 seed genes involved in signal propagation system were obtained by means of unifying mRNA and microRNA detected integrated DEGs. We then reconstructed a refined protein–protein interaction network (PPIN) of infected cells to elucidate the rabies-implicated signal transduction network (RISN). To validate our findings, we confirmed differential expression of randomly selected genes in the network using Real-time PCR. In conclusion, the identification of seed genes and their network neighborhood within the refined PPIN can be useful for demonstrating signaling pathways including interferon circumvent, toward proliferation and survival, and neuropathological clue, explaining the intricate underlying molecular neuropathology of rabies infection and thus rendered a molecular framework for predicting potential drug targets. PMID:27872612

Integrative Analyses of miRNA-mRNA Interactions Reveal let-7b, miR-128 and MAPK Pathway Involvement in Muscle Mass Loss in Sex-Linked Dwarf Chickens

PubMed Central

Luo, Wen; Lin, Shumao; Li, Guihuan; Nie, Qinghua; Zhang, Xiquan

2016-01-01

The sex-linked dwarf (SLD) chicken is an ideal model system for understanding growth hormone (GH)-action and growth hormone receptor (GHR) function because of its recessive mutation in the GHR gene. Skeletal muscle mass is reduced in the SLD chicken with a smaller muscle fiber diameter. Our previous study has presented the mRNA and miRNA expression profiles of the SLD chicken and normal chicken between embryo day 14 and seven weeks of age. However, the molecular mechanism of GHR-deficient induced muscle mass loss is still unclear, and the key molecules and pathways underlying the GHR-deficient induced muscle mass loss also remain to be illustrated. Here, by functional network analysis of the differentially expressed miRNAs and mRNAs between the SLD and normal chickens, we revealed that let-7b, miR-128 and the MAPK pathway might play key roles in the GHR-deficient induced muscle mass loss, and that the reduced cell division and growth are potential cellular processes during the SLD chicken skeletal muscle development. Additionally, we also found some genes and miRNAs involved in chicken skeletal muscle development, through the MAPK, PI3K-Akt, Wnt and Insulin signaling pathways. This study provides new insights into the molecular mechanism underlying muscle mass loss in the SLD chickens, and some regulatory networks that are crucial for chicken skeletal muscle development. PMID:26927061

Optimality Principles in the Regulation of Metabolic Networks

PubMed Central

Berkhout, Jan; Bruggeman, Frank J.; Teusink, Bas

2012-01-01

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide. PMID:24957646

Molecular clock on a neutral network.

PubMed

Raval, Alpan

2007-09-28

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

Molecular Clock on a Neutral Network

NASA Astrophysics Data System (ADS)

Raval, Alpan

2007-09-01

The number of fixed mutations accumulated in an evolving population often displays a variance that is significantly larger than the mean (the overdispersed molecular clock). By examining a generic evolutionary process on a neutral network of high-fitness genotypes, we establish a formalism for computing all cumulants of the full probability distribution of accumulated mutations in terms of graph properties of the neutral network, and use the formalism to prove overdispersion of the molecular clock. We further show that significant overdispersion arises naturally in evolution when the neutral network is highly sparse, exhibits large global fluctuations in neutrality, and small local fluctuations in neutrality. The results are also relevant for elucidating aspects of neutral network topology from empirical measurements of the substitution process.

Primary Respiratory Chain Disease Causes Tissue-Specific Dysregulation of the Global Transcriptome and Nutrient-Sensing Signaling Network

PubMed Central

Zhang, Zhe; Tsukikawa, Mai; Peng, Min; Polyak, Erzsebet; Nakamaru-Ogiso, Eiko; Ostrovsky, Julian; McCormack, Shana; Place, Emily; Clarke, Colleen; Reiner, Gail; McCormick, Elizabeth; Rappaport, Eric; Haas, Richard; Baur, Joseph A.; Falk, Marni J.

2013-01-01

Primary mitochondrial respiratory chain (RC) diseases are heterogeneous in etiology and manifestations but collectively impair cellular energy metabolism. Mechanism(s) by which RC dysfunction causes global cellular sequelae are poorly understood. To identify a common cellular response to RC disease, integrated gene, pathway, and systems biology analyses were performed in human primary RC disease skeletal muscle and fibroblast transcriptomes. Significant changes were evident in muscle across diverse RC complex and genetic etiologies that were consistent with prior reports in other primary RC disease models and involved dysregulation of genes involved in RNA processing, protein translation, transport, and degradation, and muscle structure. Global transcriptional and post-transcriptional dysregulation was also found to occur in a highly tissue-specific fashion. In particular, RC disease muscle had decreased transcription of cytosolic ribosomal proteins suggestive of reduced anabolic processes, increased transcription of mitochondrial ribosomal proteins, shorter 5′-UTRs that likely improve translational efficiency, and stabilization of 3′-UTRs containing AU-rich elements. RC disease fibroblasts showed a strikingly similar pattern of global transcriptome dysregulation in a reverse direction. In parallel with these transcriptional effects, RC disease dysregulated the integrated nutrient-sensing signaling network involving FOXO, PPAR, sirtuins, AMPK, and mTORC1, which collectively sense nutrient availability and regulate cellular growth. Altered activities of central nodes in the nutrient-sensing signaling network were validated by phosphokinase immunoblot analysis in RC inhibited cells. Remarkably, treating RC mutant fibroblasts with nicotinic acid to enhance sirtuin and PPAR activity also normalized mTORC1 and AMPK signaling, restored NADH/NAD+ redox balance, and improved cellular respiratory capacity. These data specifically highlight a common pathogenesis extending across different molecular and biochemical etiologies of individual RC disorders that involves global transcriptome modifications. We further identify the integrated nutrient-sensing signaling network as a common cellular response that mediates, and may be amenable to targeted therapies for, tissue-specific sequelae of primary mitochondrial RC disease. PMID:23894440

Communication: Molecular-level insights into asymmetric triblock copolymers: Network and phase development

NASA Astrophysics Data System (ADS)

Tallury, Syamal S.; Mineart, Kenneth P.; Woloszczuk, Sebastian; Williams, David N.; Thompson, Russell B.; Pasquinelli, Melissa A.; Banaszak, Michal; Spontak, Richard J.

2014-09-01

Molecularly asymmetric triblock copolymers progressively grown from a parent diblock copolymer can be used to elucidate the phase and property transformation from diblock to network-forming triblock copolymer. In this study, we use several theoretical formalisms and simulation methods to examine the molecular-level characteristics accompanying this transformation, and show that reported macroscopic-level transitions correspond to the onset of an equilibrium network. Midblock conformational fractions and copolymer morphologies are provided as functions of copolymer composition and temperature.

Molecular networks implicated in speech-related disorders: FOXP2 regulates the SRPX2/uPAR complex.

PubMed

Roll, Patrice; Vernes, Sonja C; Bruneau, Nadine; Cillario, Jennifer; Ponsole-Lenfant, Magali; Massacrier, Annick; Rudolf, Gabrielle; Khalife, Manal; Hirsch, Edouard; Fisher, Simon E; Szepetowski, Pierre

2010-12-15

It is a challenge to identify the molecular networks contributing to the neural basis of human speech. Mutations in transcription factor FOXP2 cause difficulties mastering fluent speech (developmental verbal dyspraxia, DVD), whereas mutations of sushi-repeat protein SRPX2 lead to epilepsy of the rolandic (sylvian) speech areas, with DVD or with bilateral perisylvian polymicrogyria. Pathophysiological mechanisms driven by SRPX2 involve modified interaction with the plasminogen activator receptor (uPAR). Independent chromatin-immunoprecipitation microarray screening has identified the uPAR gene promoter as a potential target site bound by FOXP2. Here, we directly tested for the existence of a transcriptional regulatory network between human FOXP2 and the SRPX2/uPAR complex. In silico searches followed by gel retardation assays identified specific efficient FOXP2-binding sites in each of the promoter regions of SRPX2 and uPAR. In FOXP2-transfected cells, significant decreases were observed in the amounts of both SRPX2 (43.6%) and uPAR (38.6%) native transcripts. Luciferase reporter assays demonstrated that FOXP2 expression yielded a marked inhibition of SRPX2 (80.2%) and uPAR (77.5%) promoter activity. A mutant FOXP2 that causes DVD (p.R553H) failed to bind to SRPX2 and uPAR target sites and showed impaired down-regulation of SRPX2 and uPAR promoter activity. In a patient with polymicrogyria of the left rolandic operculum, a novel FOXP2 mutation (p.M406T) was found in the leucine-zipper (dimerization) domain. p.M406T partially impaired the FOXP2 regulation of SRPX2 promoter activity, whereas that of the uPAR promoter remained unchanged. Together with recently described FOXP2-CNTNAP2 and SRPX2/uPAR links, the FOXP2-SRPX2/uPAR network provides exciting insights into molecular pathways underlying speech-related disorders.

Elastic and thermal expansion asymmetry in dense molecular materials.

PubMed

Burg, Joseph A; Dauskardt, Reinhold H

2016-09-01

The elastic modulus and coefficient of thermal expansion are fundamental properties of elastically stiff molecular materials and are assumed to be the same (symmetric) under both tension and compression loading. We show that molecular materials can have a marked asymmetric elastic modulus and coefficient of thermal expansion that are inherently related to terminal chemical groups that limit molecular network connectivity. In compression, terminal groups sterically interact to stiffen the network, whereas in tension they interact less and disconnect the network. The existence of asymmetric elastic and thermal expansion behaviour has fundamental implications for computational approaches to molecular materials modelling and practical implications on the thermomechanical strains and associated elastic stresses. We develop a design space to control the degree of elastic asymmetry in molecular materials, a vital step towards understanding their integration into device technologies.

Gene expression in bovine rumen epithelium during weaning identifies molecular regulators of rumen development and growth.

PubMed

Connor, Erin E; Baldwin, Ransom L; Li, Cong-jun; Li, Robert W; Chung, Hoyoung

2013-03-01

During weaning, epithelial cell function in the rumen transitions in response to conversion from a pre-ruminant to a true ruminant environment to ensure efficient nutrient absorption and metabolism. To identify gene networks affected by weaning in bovine rumen, Holstein bull calves were fed commercial milk replacer only (MRO) until 42 days of age, then were provided diets of either milk + orchardgrass hay (MH) or milk + grain-based calf starter (MG). Rumen epithelial RNA was extracted from calves sacrificed at four time points: day 14 (n = 3) and day 42 (n = 3) of age while fed the MRO diet and day 56 (n = 3/diet) and day 70 (n = 3/diet) while fed the MH and MG diets for transcript profiling by microarray hybridization. Five two-group comparisons were made using Permutation Analysis of Differential Expression® to identify differentially expressed genes over time and developmental stage between days 14 and 42 within the MRO diet, between day 42 on the MRO diet and day 56 on the MG or MH diets, and between the MG and MH diets at days 56 and 70. Ingenuity Pathway Analysis (IPA) of differentially expressed genes during weaning indicated the top 5 gene networks involving molecules participating in lipid metabolism, cell morphology and death, cellular growth and proliferation, molecular transport, and the cell cycle. Putative genes functioning in the establishment of the rumen microbial population and associated rumen epithelial inflammation during weaning were identified. Activation of transcription factor PPAR-α was identified by IPA software as an important regulator of molecular changes in rumen epithelium that function in papillary development and fatty acid oxidation during the transition from pre-rumination to rumination. Thus, molecular markers of rumen development and gene networks regulating differentiation and growth of rumen epithelium were identified for selecting targets and methods for improving and assessing rumen development and function, particularly in the growing calf.

Hyperexpandable, self-healing macromolecular crystals with integrated polymer networks.

PubMed

Zhang, Ling; Bailey, Jake B; Subramanian, Rohit H; Tezcan, F Akif

2018-05-01

The formation of condensed matter typically involves a trade-off between structural order and flexibility. As the extent and directionality of interactions between atomic or molecular components increase, materials generally become more ordered but less compliant, and vice versa. Nevertheless, high levels of structural order and flexibility are not necessarily mutually exclusive; there are many biological (such as microtubules 1,2 , flagella 3 , viruses 4,5 ) and synthetic assemblies (for example, dynamic molecular crystals 6-9 and frameworks 10-13 ) that can undergo considerable structural transformations without losing their crystalline order and that have remarkable mechanical properties 8,14,15 that are useful in diverse applications, such as selective sorption 16 , separation 17 , sensing 18 and mechanoactuation 19 . However, the extent of structural changes and the elasticity of such flexible crystals are constrained by the necessity to maintain a continuous network of bonding interactions between the constituents of the lattice. Consequently, even the most dynamic porous materials tend to be brittle and isolated as microcrystalline powders 14 , whereas flexible organic or inorganic molecular crystals cannot expand without fracturing. Owing to their rigidity, crystalline materials rarely display self-healing behaviour 20 . Here we report that macromolecular ferritin crystals with integrated hydrogel polymers can isotropically expand to 180 per cent of their original dimensions and more than 500 per cent of their original volume while retaining periodic order and faceted Wulff morphologies. Even after the separation of neighbouring ferritin molecules by 50 ångströms upon lattice expansion, specific molecular contacts between them can be reformed upon lattice contraction, resulting in the recovery of atomic-level periodicity and the highest-resolution ferritin structure reported so far. Dynamic bonding interactions between the hydrogel network and the ferritin molecules endow the crystals with the ability to resist fragmentation and self-heal efficiently, whereas the chemical tailorability of the ferritin molecules enables the creation of chemically and mechanically differentiated domains within single crystals.

Computer-Based Semantic Network in Molecular Biology: A Demonstration.

ERIC Educational Resources Information Center

Callman, Joshua L.; And Others

This paper analyzes the hardware and software features that would be desirable in a computer-based semantic network system for representing biology knowledge. It then describes in detail a prototype network of molecular biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…

Investigation of candidate genes for osteoarthritis based on gene expression profiles.

PubMed

Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei

2016-12-01

To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Network Topologies and Dynamics Leading to Endotoxin Tolerance and Priming in Innate Immune Cells

NASA Astrophysics Data System (ADS)

Fu, Yan; Glaros, Trevor; Zhu, Meng; Wang, Ping; Wu, Zhanghan; Tyson, John; Li, Liwu; Xing, Jianhua

2012-01-01

The innate immune system, acting as the first line of host defense, senses and adapts to foreign challenges through complex intracellular and intercellular signaling networks. Endotoxin tolerance and priming elicited by macrophages are classic examples of the complex adaptation of innate immune cells. Upon repetitive exposures to different doses of bacterial endotoxin (lipopolysaccharide) or other stimulants, macrophages show either suppressed or augmented inflammatory responses compared to a single exposure to the stimulant. Endotoxin tolerance and priming are critically involved in both immune homeostasis and the pathogenesis of diverse inflammatory diseases. However, the underlying molecular mechanisms are not well understood. By means of a computational search through the parameter space of a coarse-grained three-node network with a two-stage Metropolis sampling approach, we enumerated all the network topologies that can generate priming or tolerance. We discovered three major mechanisms for priming (pathway synergy, suppressor deactivation, activator induction) and one for tolerance (inhibitor persistence). These results not only explain existing experimental observations, but also reveal intriguing test scenarios for future experimental studies to clarify mechanisms of endotoxin priming and tolerance.

Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

PubMed

Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

2018-04-01

Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

PubMed

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Effects of Nerve Injury and Segmental Regeneration on the Cellular Correlates of Neural Morphallaxis

PubMed Central

Martinez, Veronica G.; Manson, Josiah M.B.; Zoran, Mark J.

2009-01-01

Functional recovery of neural networks after injury requires a series of signaling events similar to the embryonic processes that governed initial network construction. Neural morphallaxis, a form of nervous system regeneration, involves reorganization of adult neural connectivity patterns. Neural morphallaxis in the worm, Lumbriculus variegatus, occurs during asexual reproduction and segmental regeneration, as body fragments acquire new positional identities along the anterior–posterior axis. Ectopic head (EH) formation, induced by ventral nerve cord lesion, generated morphallactic plasticity including the reorganization of interneuronal sensory fields and the induction of a molecular marker of neural morphallaxis. Morphallactic changes occurred only in segments posterior to an EH. Neither EH formation, nor neural morphallaxis was observed after dorsal body lesions, indicating a role for nerve cord injury in morphallaxis induction. Furthermore, a hierarchical system of neurobehavioral control was observed, where anterior heads were dominant and an EH controlled body movements only in the absence of the anterior head. Both suppression of segmental regeneration and blockade of asexual fission, after treatment with boric acid, disrupted the maintenance of neural morphallaxis, but did not block its induction. Therefore, segmental regeneration (i.e., epimorphosis) may not be required for the induction of morphallactic remodeling of neural networks. However, on-going epimorphosis appears necessary for the long-term consolidation of cellular and molecular mechanisms underlying the morphallaxis of neural circuitry. PMID:18561185

Reducing uncertainties in energy dissipation measurements in atomic force spectroscopy of molecular networks and cell-adhesion studies.

PubMed

Biswas, Soma; Leitao, Samuel; Theillaud, Quentin; Erickson, Blake W; Fantner, Georg E

2018-06-20

Atomic force microscope (AFM) based single molecule force spectroscopy (SMFS) is a valuable tool in biophysics to investigate the ligand-receptor interactions, cell adhesion and cell mechanics. However, the force spectroscopy data analysis needs to be done carefully to extract the required quantitative parameters correctly. Especially the large number of molecules, commonly involved in complex networks formation; leads to very complicated force spectroscopy curves. One therefore, generally characterizes the total dissipated energy over a whole pulling cycle, as it is difficult to decompose the complex force curves into individual single molecule events. However, calculating the energy dissipation directly from the transformed force spectroscopy curves can lead to a significant over-estimation of the dissipated energy during a pulling experiment. The over-estimation of dissipated energy arises from the finite stiffness of the cantilever used for AFM based SMFS. Although this error can be significant, it is generally not compensated for. This can lead to significant misinterpretation of the energy dissipation (up to the order of 30%). In this paper, we show how in complex SMFS the excess dissipated energy caused by the stiffness of the cantilever can be identified and corrected using a high throughput algorithm. This algorithm is then applied to experimental results from molecular networks and cell-adhesion measurements to quantify the improvement in the estimation of the total energy dissipation.

SynBioSS designer: a web-based tool for the automated generation of kinetic models for synthetic biological constructs

PubMed Central

Weeding, Emma; Houle, Jason

2010-01-01

Modeling tools can play an important role in synthetic biology the same way modeling helps in other engineering disciplines: simulations can quickly probe mechanisms and provide a clear picture of how different components influence the behavior of the whole. We present a brief review of available tools and present SynBioSS Designer. The Synthetic Biology Software Suite (SynBioSS) is used for the generation, storing, retrieval and quantitative simulation of synthetic biological networks. SynBioSS consists of three distinct components: the Desktop Simulator, the Wiki, and the Designer. SynBioSS Designer takes as input molecular parts involved in gene expression and regulation (e.g. promoters, transcription factors, ribosome binding sites, etc.), and automatically generates complete networks of reactions that represent transcription, translation, regulation, induction and degradation of those parts. Effectively, Designer uses DNA sequences as input and generates networks of biomolecular reactions as output. In this paper we describe how Designer uses universal principles of molecular biology to generate models of any arbitrary synthetic biological system. These models are useful as they explain biological phenotypic complexity in mechanistic terms. In turn, such mechanistic explanations can assist in designing synthetic biological systems. We also discuss, giving practical guidance to users, how Designer interfaces with the Registry of Standard Biological Parts, the de facto compendium of parts used in synthetic biology applications. PMID:20639523

Molecular cross-talk of IL-6 in tumors and new progress in combined therapy.

PubMed

Song, Zuoqing; Ren, Dian; Xu, Xiaohong; Wang, Yuxin

2018-06-01

IL-6, a cytokine activated by type I interferons (IFNs), is encoded by the IL-6 gene, and secreted by T cells and macrophages. It serves many purposes in the human body and is significant to pathological and physiological activities, such as acute inflammatory responses, autoimmune diseases, and tumor formation. The wide range of IL-6 actions on tumors rely on more than one specific pathway. Advances in modern research have determined that to fulfill its complex physiological functions, IL-6 must be involved in cross-talk with a number of other molecular pathways. Therefore, it is important to clarify the comprehensive pathway network associated with IL-6 activity and to explore the mechanisms to inhibit its pathological activity in order to develop corresponding treatment plans. This study is a simple review of the pathological and physiological actions of IL-6 on the human body. It explains in detail the molecular pathways involved in cross-talk between IL-6 and tumors, summarizing and discussing the latest progress made in IL-6-related internal medicine treatments in recent years, including chemotherapies, targeted therapies, and immunotherapies. Our results provide new insight into the treatment of tumors. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

Main regulatory pathways, key genes and microRNAs involved in flower formation and development of moso bamboo (Phyllostachys edulis).

PubMed

Ge, Wei; Zhang, Ying; Cheng, Zhanchao; Hou, Dan; Li, Xueping; Gao, Jian

2017-01-01

Moso bamboo is characterized by infrequent sexual reproduction and erratic flowering habit; however, the molecular biology of flower formation and development is not well studied in this species. We studied the molecular regulation mechanisms of moso bamboo development and flowering by selecting three key regulatory pathways: plant-pathogen interaction, plant hormone signal transduction and protein processing in endoplasmic reticulum at different stages of flowering in moso bamboo. We selected PheDof1, PheMADS14 and six microRNAs involved in the three pathways through KEGG pathway and cluster analysis. Subcellular localization, transcriptional activation, Western blotting, in situ hybridization and qRT-PCR were used to further investigate the expression patterns and regulatory roles of pivotal genes at different flower development stages. Differential expression patterns showed that PheDof1, PheMADS14 and six miRNAs may play vital regulatory roles in flower development and floral transition in moso bamboo. Our research paves way for further studies on metabolic regulatory networks and provides insight into the molecular regulation mechanisms of moso bamboo flowering and senescence. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

An equal force theory for network models of soft materials with arbitrary molecular weight distribution

NASA Astrophysics Data System (ADS)

Verron, E.; Gros, A.

2017-09-01

Most network models for soft materials, e.g. elastomers and gels, are dedicated to idealized materials: all chains admit the same number of Kuhn segments. Nevertheless, such standard models are not appropriate for materials involving multiple networks, and some specific constitutive equations devoted to these materials have been derived in the last few years. In nearly all cases, idealized networks of different chain lengths are assembled following an equal strain assumption; only few papers adopt an equal stress assumption, although some authors argue that such hypothesis would reflect the equilibrium of the different networks in contact. In this work, a full-network model with an arbitrary chain length distribution is derived by considering that chains of different lengths satisfy the equal force assumption in each direction of the unit sphere. The derivation is restricted to non-Gaussian freely jointed chains and to affine deformation of the sphere. Firstly, after a proper definition of the undeformed configuration of the network, we demonstrate that the equal force assumption leads to the equality of a normalized stretch in chains of different lengths. Secondly, we establish that the network with chain length distribution behaves as an idealized full-network of which both chain length and density of are provided by the chain length distribution. This approach is finally illustrated with two examples: the derivation of a new expression for the Young modulus of bimodal interpenetrated polymer networks, and the prediction of the change in fluorescence during deformation of mechanochemically responsive elastomers.

Multilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.

PubMed

Davidsen, Peter K; Turan, Nil; Egginton, Stuart; Falciani, Francesco

2016-02-01

The overall aim of physiological research is to understand how living systems function in an integrative manner. Consequently, the discipline of physiology has since its infancy attempted to link multiple levels of biological organization. Increasingly this has involved mathematical and computational approaches, typically to model a small number of components spanning several levels of biological organization. With the advent of "omics" technologies, which can characterize the molecular state of a cell or tissue (intended as the level of expression and/or activity of its molecular components), the number of molecular components we can quantify has increased exponentially. Paradoxically, the unprecedented amount of experimental data has made it more difficult to derive conceptual models underlying essential mechanisms regulating mammalian physiology. We present an overview of state-of-the-art methods currently used to identifying biological networks underlying genomewide responses. These are based on a data-driven approach that relies on advanced computational methods designed to "learn" biology from observational data. In this review, we illustrate an application of these computational methodologies using a case study integrating an in vivo model representing the transcriptional state of hypoxic skeletal muscle with a clinical study representing muscle wasting in chronic obstructive pulmonary disease patients. The broader application of these approaches to modeling multiple levels of biological data in the context of modern physiology is discussed. Copyright © 2016 the American Physiological Society.

Thermal properties of the gel made by low molecular weight gelator 1,2-O-(1-ethylpropylidene)-alpha-D-glucofuranose with toluene and molecular dynamics of solvent.

PubMed

Tritt-Goc, Jadwiga; Bielejewski, Michał; Luboradzki, Roman; Lapiński, Andrzej

2008-01-15

The studies of the gel-to-sol phase transition by the Raman, FT-IR, and 1H NMR methods of the gel made by low molecular weight organogelator 1,2-O-(1-ethylpropylidene)-alpha-D-glucofuranose with toluene as the solvent are reported. The FT-IR spectra revealed the existence of a hydrogen bond network formed by gelator molecules in the crystalline and gel phase. In both phases, the network formation is dominated by the gelator self-interaction. Upon gelation, only one stretching band of infrared absorption modes nualpha, assigned to the O(6)H hydroxyl protons of gelator, is shifted by Deltaupsilonalpha = 25 cm-1, which indicates the involvement of this proton in the interaction with the solvent molecules. The phase transition measurements performed as a function of gelator concentration allowed the calculation of the energy correlated with the transition from gel to solution phase. The obtained value of 72 kJ/mol is the largest one reported up until now for monosaccharide-based gels. The analysis of the temperature measurements of the toluene 1H NMR spectra provides evidence for a different chemical environment of toluene molecules in the gel. The toluene spin-lattice relaxation in bulk and gel indicate that the viscosity is most likely the main factor that influences the dynamics of toluene.

Artificial neural networks for efficient clustering of conformational ensembles and their potential for medicinal chemistry.

PubMed

Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura

2013-01-01

The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.

Hydrogen bonded binary molecular adducts derived from exobidentate N-donor ligand with dicarboxylic acids: Acid⋯imidazole hydrogen-bonding interactions in neutral and ionic heterosynthons

NASA Astrophysics Data System (ADS)

Kathalikkattil, Amal Cherian; Damodaran, Subin; Bisht, Kamal Kumar; Suresh, Eringathodi

2011-01-01

Four new binary molecular compounds between a flexible exobidentate N-heterocycle and a series of dicarboxylic acids have been synthesized. The N-donor 1,4-bis(imidazol-1-ylmethyl)benzene (bix) was reacted with flexible and rigid dicarboxylic acids viz., cyclohexane-1,4-dicarboxylic acid (H 2chdc), naphthalene-1,4-dicarboxylic acid (H 2npdc) and 1H-pyrazole-3,5-dicarboxylic acid (H 2pzdc), generating four binary molecular complexes. X-ray crystallographic investigation of the molecular adducts revealed the primary intermolecular interactions carboxylic acid⋯amine (via O-H⋯N) as well as carboxylate⋯protonated amine (via N-H +⋯O -) within the binary compounds, generating layered and two-dimensional sheet type H-bonded networks involving secondary weak interactions (C-H⋯O) including the solvent of crystallization. Depending on the differences in p Ka values of the selected base/acid (Δp Ka), diverse H-bonded supramolecular assemblies could be premeditated. This study demonstrates the H-bonding interactions between imidazole/imidazolium cation and carboxylic acid/carboxylate anion in providing sufficient driving force for the directed assembly of binary molecular complexes. In the two-component solid form of hetero synthons involving bix and dicarboxylic acid, only H 2chdc exist as cocrystal with bix, while all the other three compounds crystallized exclusively as salt, in agreement with the Δp Ka values predicted for the formation of salts/cocrystals from the base and acid used in the synthesis of supramolecular solids.

The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology.

PubMed

Agnati, L F; Guidolin, D; Fuxe, K

2007-01-01

A new model of the brain organization is proposed. The model is based on the assumption that a global molecular network enmeshes the entire central nervous system. Thus, brain extra-cellular and intra-cellular molecular networks are proposed to communicate at the level of special plasma membrane regions (e.g., the lipid rafts) where horizontal molecular networks can represent input/output regions allowing the cell to have informational exchanges with the extracellular environment. Furthermore, some "pervasive signals" such as field potentials, pressure waves and thermal gradients that affect large parts of the brain cellular and molecular networks are discussed. Finally, at least two learning paradigms are analyzed taking into account the possible role of Volume Transmission: the so-called model of "temporal difference learning" and the "Turing B-unorganised machine". The relevance of this new view of brain organization for a deeper understanding of some neurophysiological and neuropathological aspects of its function is briefly discussed.

Deciphering the pharmacological mechanism of the Chinese formula Huanglian-Jie-Du decoction in the treatment of ischemic stroke using a systems biology-based strategy

PubMed Central

Zhang, Yan-qiong; Wang, Song-song; Zhu, Wei-liang; Ma, Yan; Zhang, Fang-bo; Liang, Ri-xin; Xu, Hai-yu; Yang, Hong-jun

2015-01-01

Aim: Huanglian-Jie-Du decoction (HLJDD) is an important multiherb remedy in TCM, which is recently demonstrated to be effective to treat ischemic stroke. Here, we aimed to investigate the pharmacological mechanisms of HLJDD in the treatment of ischemic stroke using systems biology approaches. Methods: Putative targets of HLJDD were predicted using MetaDrug. An interaction network of putative HLJDD targets and known therapeutic targets for the treatment of ischemic stroke was then constructed, and candidate HLJDD targets were identified by calculating topological features, including 'Degree', 'Node-betweenness', 'Closeness', and 'K-coreness'. The binding efficiencies of the candidate HLJDD targets with the corresponding compositive compounds were further validated by a molecular docking simulation. Results: A total of 809 putative targets were obtained for 168 compositive compounds in HLJDD. Additionally, 39 putative targets were common to all four herbs of HLJDD. Next, 49 major nodes were identified as candidate HLJDD targets due to their network topological importance. The enrichment analysis based on the Gene Ontology (GO) annotation system and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway demonstrated that candidate HLJDD targets were more frequently involved in G-protein-coupled receptor signaling pathways, neuroactive ligand-receptor interactions and gap junctions, which all played important roles in the progression of ischemic stroke. Finally, the molecular docking simulation showed that 170 pairs of chemical components and candidate HLJDD targets had strong binding efficiencies. Conclusion: This study has developed for the first time a comprehensive systems approach integrating drug target prediction, network analysis and molecular docking simulation to reveal the relationships between the herbs contained in HLJDD and their putative targets and ischemic stroke-related pathways. PMID:25937634

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

PubMed Central

Yang, Jin; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.

2009-01-01

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena. PMID:18851068

Dynamic Transcription Factor Networks in Epithelial-Mesenchymal Transition in Breast Cancer Models

PubMed Central

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J.; Shin, Seungjin; Jeruss, Jacqueline S.; Shea, Lonnie D.

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy. PMID:23593114

Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

PubMed

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J; Shin, Seungjin; Jeruss, Jacqueline S; Shea, Lonnie D

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network1[OPEN

PubMed Central

Herman, Dorota; Slabbinck, Bram; Pè, Mario Enrico

2016-01-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. PMID:26754667

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network.

PubMed

Baute, Joke; Herman, Dorota; Coppens, Frederik; De Block, Jolien; Slabbinck, Bram; Dell'Acqua, Matteo; Pè, Mario Enrico; Maere, Steven; Nelissen, Hilde; Inzé, Dirk

2016-03-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. © 2016 American Society of Plant Biologists. All Rights Reserved.

Neurobiological Mechanisms for the Regulation of Mammalian Sleep-Wake Behavior: Reinterpretation of Historical Evidence and Inclusion of Contemporary Cellular and Molecular Evidence

PubMed Central

Datta, Subimal; MacLean, Robert Ross

2007-01-01

At its most basic level, the function of mammalian sleep can be described as a restorative process of the brain and body; recently, however, progressive research has revealed a host of vital functions to which sleep is essential. Although many excellent reviews on sleep behavior have been published, none have incorporated contemporary studies examining the molecular mechanisms that govern the various stages of sleep. Utilizing a holistic approach, this review is focused on the basic mechanisms involved in the transition from wakefulness, initiation of sleep and the subsequent generation of slow-wave sleep and rapid eye movement (REM) sleep. Additionally, using recent molecular studies and experimental evidence that provides a direct link to sleep as a behavior, we have developed a new model, the Cellular-Molecular-Network model, explaining the mechanisms responsible for regulating REM sleep. By analyzing the fundamental neurobiological mechanisms responsible for the generation and maintenance of sleep-wake behavior in mammals, we intend to provide a broader understanding of our present knowledge in the field of sleep research. PMID:17445891

Surveillance at the molecular level: Developing an integrated network for detecting variation in avian influenza viruses in Indonesia.

PubMed

Hartaningsih, Nining; Wibawa, Hendra; Pudjiatmoko; Rasa, Fadjar Sumping Tjatur; Irianingsih, Sri Handayani; Dharmawan, Rama; Azhar, Muhammad; Siregar, Elly Sawitri; McGrane, James; Wong, Frank; Selleck, Paul; Allen, John; Broz, Ivano; Torchetti, Mia Kim; Dauphin, Gwenaelle; Claes, Filip; Sastraningrat, Wiryadi; Durr, Peter A

2015-06-01

Since 2006, Indonesia has used vaccination as the principal means of control of H5N1-HPAI. During this time, the virus has undergone gradual antigenic drift, which has necessitated changes in seed strains for vaccine production and associated modifications to diagnostic antigens. In order to improve the system of monitoring such viral evolution, the Government of Indonesia, with the assistance of FAO/OFFLU, has developed an innovative network whereby H5N1 isolates are antigenically and genetically characterised. This molecular surveillance network ("Influenza Virus Monitoring" or "IVM") is based on the regional network of veterinary diagnostic laboratories, and is supported by a web-based data management system ("IVM Online"). The example of the Indonesian IVM network has relevance for other countries seeking to establish laboratory networks for the molecular surveillance of avian influenza and other pathogens. Copyright © 2015 Elsevier B.V. All rights reserved.

Scale dependence of the mechanics of active gels with increasing motor concentration.

PubMed

Sonn-Segev, Adar; Bernheim-Groswasser, Anne; Roichman, Yael

2017-10-18

Actin is a protein that plays an essential role in maintaining the mechanical integrity of cells. In response to strong external stresses, it can assemble into large bundles, but it grows into a fine branched network to induce cell motion. In some cases, the self-organization of actin fibers and networks involves the action of bipolar filaments of the molecular motor myosin. Such self-organization processes mediated by large myosin bipolar filaments have been studied extensively in vitro. Here we create active gels, composed of single actin filaments and small myosin bipolar filaments. The active steady state in these gels persists long enough to enable the characterization of their mechanical properties using one and two point microrheology. We study the effect of myosin concentration on the mechanical properties of this model system for active matter, for two different motor assembly sizes. In contrast to previous studies of networks with large motor assemblies, we find that the fluctuations of tracer particles embedded in the network decrease in amplitude as motor concentration increases. Nonetheless, we show that myosin motors stiffen the actin networks, in accordance with bulk rheology measurements of networks containing larger motor assemblies. This implies that such stiffening is of universal nature and may be relevant to a wider range of cytoskeleton-based structures.

Understanding large multiprotein complexes: applying a multiple allosteric networks model to explain the function of the Mediator transcription complex.

PubMed

Lewis, Brian A

2010-01-15

The regulation of transcription and of many other cellular processes involves large multi-subunit protein complexes. In the context of transcription, it is known that these complexes serve as regulatory platforms that connect activator DNA-binding proteins to a target promoter. However, there is still a lack of understanding regarding the function of these complexes. Why do multi-subunit complexes exist? What is the molecular basis of the function of their constituent subunits, and how are these subunits organized within a complex? What is the reason for physical connections between certain subunits and not others? In this article, I address these issues through a model of network allostery and its application to the eukaryotic RNA polymerase II Mediator transcription complex. The multiple allosteric networks model (MANM) suggests that protein complexes such as Mediator exist not only as physical but also as functional networks of interconnected proteins through which information is transferred from subunit to subunit by the propagation of an allosteric state known as conformational spread. Additionally, there are multiple distinct sub-networks within the Mediator complex that can be defined by their connections to different subunits; these sub-networks have discrete functions that are activated when specific subunits interact with other activator proteins.

Molecular Correlates of Cortical Network Modulation by Long-Term Sensory Experience in the Adult Rat Barrel Cortex

ERIC Educational Resources Information Center

Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J. M.

2014-01-01

Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment…

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer’s Disease

PubMed Central

Dulla, Chris G.; Coulter, Douglas A.; Ziburkus, Jokubas

2015-01-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer’s disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. PMID:25948650

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer's Disease.

PubMed

Dulla, Chris G; Coulter, Douglas A; Ziburkus, Jokubas

2016-06-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer's disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. © The Author(s) 2015.

Quantitative proteomics analysis highlights the role of redox hemostasis and energy metabolism in human embryonic stem cell differentiation to neural cells.

PubMed

Fathi, Ali; Hatami, Maryam; Vakilian, Haghighat; Han, Chia-Li; Chen, Yu-Ju; Baharvand, Hossein; Salekdeh, Ghasem Hosseini

2014-04-14

Neural differentiation of human embryonic stem cells (hESCs) is a unique opportunity for in vitro analyses of neurogenesis in humans. Extrinsic cues through neural plate formation are well described in the hESCs although intracellular mechanisms underlying neural development are largely unknown. Proteome analysis of hESC differentiation to neural cells will help to further define molecular mechanisms involved in neurogenesis in humans. Using a two-dimensional differential gel electrophoresis (2D-DIGE) system, we analyzed the proteome of hESC differentiation to neurons at three stages, early neural differentiation, neural ectoderm and mature neurons. Out of 137 differentially accumulated protein spots, 118 spots were identified using MALDI-TOF/TOF and LC MS/MS. We observed that proteins involved in redox hemostasis, vitamin and energy metabolism and ubiquitin dependent proteolysis were more abundant in differentiated cells, whereas the abundance of proteins associated with RNA processing and protein folding was higher in hESCs. Higher abundance of proteins involved in maintaining cellular redox state suggests the importance of redox hemostasis in neural differentiation. Furthermore, our results support the concept of a coupling mechanism between neuronal activity and glucose utilization. The protein network analysis showed that the majority of the interacting proteins were associated with the cell cycle and cellular proliferation. These results enhanced our understanding of the molecular dynamics that underlie neural commitment and differentiation. In highlighting the role of redox and unique metabolic properties of neuronal cells, the present findings add insight to our understanding of hESC differentiation to neurons. The abundance of fourteen proteins involved in maintaining cellular redox state, including 10 members of peroxiredoxin (Prdx) family, mainly increased during differentiation, thus highlighting a link of neural differentiation to redox. Our results revealed markedly higher expression of genes encoding enzymes involved in the glycolysis and amino acid synthesis during differentiation. Protein network analysis predicted a number of critical mediators in hESC differentiation. These proteins included TP53, CTNNB1, SMARCA4, TNF, TERT, E2F1, MYC, RB1, and AR. Copyright © 2014 Elsevier B.V. All rights reserved.

MATI, a Novel Protein Involved in the Regulation of Herbivore-Associated Signaling Pathways

PubMed Central

Santamaría, M. Estrella; Martinez, Manuel; Arnaiz, Ana; Ortego, Félix; Grbic, Vojislava; Diaz, Isabel

2017-01-01

The defense response of the plants against herbivores relies on a complex network of interconnected signaling pathways. In this work, we characterized a new key player in the response of Arabidopsis against the two-spotted spider mite Tetranychus urticae, the MATI (Mite Attack Triggered Immunity) gene. This gene was differentially induced in resistant Bla-2 strain relative to susceptible Kon Arabidopsis accessions after mite attack, suggesting a potential role in the control of spider mites. To study the MATI gene function, it has been performed a deep molecular characterization of the gene combined with feeding bioassays using modified Arabidopsis lines and phytophagous arthropods. The MATI gene belongs to a new gene family that had not been previously characterized. Biotic assays showed that it confers a high tolerance not only to T. urticae, but also to the chewing lepidopteran Spodoptera exigua. Biochemical analyses suggest that MATI encodes a protein involved in the accumulation of reducing agents upon herbivore attack to control plant redox homeostasis avoiding oxidative damage and cell death. Besides, molecular analyses demonstrated that MATI is involved in the modulation of different hormonal signaling pathways, affecting the expression of genes involved in biosynthesis and signaling of the jasmonic acid and salicylic acid hormones. The fact that MATI is also involved in defense through the modulation of the levels of photosynthetic pigments highlights the potential of MATI proteins to be exploited as biotechnological tools for pest control. PMID:28649257

Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross.

PubMed

Brand, Bodo; Scheinhardt, Markus O; Friedrich, Juliane; Zimmer, Daisy; Reinsch, Norbert; Ponsuksili, Siriluck; Schwerin, Manfred; Ziegler, Andreas

2016-10-06

The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing insight into the molecular and genetic background of complex traits in cattle and will help to understand molecular networks involved.

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

PubMed Central

2011-01-01

Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs), microRNAs (miRNAs) and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs). Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL). In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT), an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http://mironton.uni.lu which will be updated on a regular basis. PMID:21375730

[Hypogonadotropic hypogonadism: new aspects in the regulation of hypothalamic-pituitary-gonadal axis].

PubMed

Brioude, F; Bouvattier, C-E; Lombès, M

2010-09-01

Hypogonadotropic hypogonadism (HH) is defined by the absence of sex steroid synthesis associated with the lack of appropriate gonadotrophin secretion. This leads to a variable degree of impuberism, often diagnosed during childhood or adolescence. Genetics of HH involve many genes. However, molecular defects have been identified in only 30 % of patients. Kallmann syndrome (KS) is defined by the association of HH and anosmia. Six genes are involved in KS (KAL1, FGFR1, FGF8, PROK2, PROKR2 and CHD7). However, genetics of KS is complex, because of the variability of the phenotype for a similar molecular defect. Otherwise, heterozygous anomalies are frequently described. Identification in the same patient of several mutations in some of these genes (digenism) could account for this variability. Autosomal recessive transmission is frequently observed in familial cases of HH without anosmia. Molecular alterations have been identified for several neuropeptides or their corresponding receptors, which are involved in the physiology of the gonadotropic axis : GNRHR, KISS1R/GPR54, neurokinin B (TAC3), TACR3 and GNRH1 (and PROK2, PROKR2 and CHD7). Anomalies of leptin or its receptor are also involved in HH cases. A new negative regulating element has been recently identified in humans : RFRP3, which is ortholog of the avian GnIH (gonadotrophin inhibitory hormone). Recent progress about these neuropeptides leads to a new model of comprehension of the gonadotropic axis physiology, from a linear model to a network model, which regulates the central element of regulation of the gonadotropic axis, represented by the GnRH neurons. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Auxin-BR Interaction Regulates Plant Growth and Development

PubMed Central

Tian, Huiyu; Lv, Bingsheng; Ding, Tingting; Bai, Mingyi; Ding, Zhaojun

2018-01-01

Plants develop a high flexibility to alter growth, development, and metabolism to adapt to the ever-changing environments. Multiple signaling pathways are involved in these processes and the molecular pathways to transduce various developmental signals are not linear but are interconnected by a complex network and even feedback mutually to achieve the final outcome. This review will focus on two important plant hormones, auxin and brassinosteroid (BR), based on the most recent progresses about these two hormone regulated plant growth and development in Arabidopsis, and highlight the cross-talks between these two phytohormones. PMID:29403511

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917

Targeting Metastasis with Snake Toxins: Molecular Mechanisms

PubMed Central

Urra, Félix A.

2017-01-01

Metastasis involves the migration of cancer cells from a primary tumor to invade and establish secondary tumors in distant organs, and it is the main cause for cancer-related deaths. Currently, the conventional cytostatic drugs target the proliferation of malignant cells, being ineffective in metastatic disease. This highlights the need to find new anti-metastatic drugs. Toxins isolated from snake venoms are a natural source of potentially useful molecular scaffolds to obtain agents with anti-migratory and anti-invasive effects in cancer cells. While there is greater evidence concerning the mechanisms of cell death induction of several snake toxin classes on cancer cells; only a reduced number of toxin classes have been reported (i.e., disintegrins/disintegrin-like proteins, C-type lectin-like proteins, C-type lectins, serinproteases, cardiotoxins, snake venom cystatins) as inhibitors of adhesion, migration, and invasion of cancer cells. Here, we discuss the anti-metastatic mechanisms of snake toxins, distinguishing three targets, which involve (1) inhibition of extracellular matrix components-dependent adhesion and migration, (2) inhibition of epithelial-mesenchymal transition, and (3) inhibition of migration by alterations in the actin/cytoskeleton network. PMID:29189742

Molecular and Epigenetic Mechanisms for the Complex Effects of Stress on Synaptic Physiology and Cognitive Functions

PubMed Central

Yuen, Eunice Y.; Wei, Jing

2017-01-01

Abstract Evidence over the past decades has found that stress, particularly through the corticosterone stress hormones, produces complex changes in glutamatergic signaling in prefrontal cortex, which leads to the alteration of cognitive processes medicated by this brain region. Interestingly, the effects of stress on glutamatergic transmission appear to be “U-shaped,” depending upon the duration and severity of the stressor. These biphasic effects of acute vs chronic stress represent the adaptive vs maladaptive responses to stressful stimuli. Animal studies suggest that the stress-induced modulation of excitatory synaptic transmission involves changes in presynaptic glutamate release, postsynaptic glutamate receptor membrane trafficking and degradation, spine structure and cytoskeleton network, and epigenetic control of gene expression. This review will discuss current findings on the key molecules involved in the stress-induced regulation of prefrontal cortex synaptic physiology and prefrontal cortex-mediated functions. Understanding the molecular and epigenetic mechanisms that underlie the complex effects of stress will help to develop novel strategies to cope with stress-related mental disorders. PMID:29016816

Molecular and Epigenetic Mechanisms for the Complex Effects of Stress on Synaptic Physiology and Cognitive Functions.

PubMed

Yuen, Eunice Y; Wei, Jing; Yan, Zhen

2017-11-01

Evidence over the past decades has found that stress, particularly through the corticosterone stress hormones, produces complex changes in glutamatergic signaling in prefrontal cortex, which leads to the alteration of cognitive processes medicated by this brain region. Interestingly, the effects of stress on glutamatergic transmission appear to be "U-shaped," depending upon the duration and severity of the stressor. These biphasic effects of acute vs chronic stress represent the adaptive vs maladaptive responses to stressful stimuli. Animal studies suggest that the stress-induced modulation of excitatory synaptic transmission involves changes in presynaptic glutamate release, postsynaptic glutamate receptor membrane trafficking and degradation, spine structure and cytoskeleton network, and epigenetic control of gene expression. This review will discuss current findings on the key molecules involved in the stress-induced regulation of prefrontal cortex synaptic physiology and prefrontal cortex-mediated functions. Understanding the molecular and epigenetic mechanisms that underlie the complex effects of stress will help to develop novel strategies to cope with stress-related mental disorders. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Robustness trade-offs and host–microbial symbiosis in the immune system

PubMed Central

Kitano, Hiroaki; Oda, Kanae

2006-01-01

The immune system provides organisms with robustness against pathogen threats, yet it also often adversely affects the organism as in autoimmune diseases. Recently, the molecular interactions involved in the immune system have been uncovered. At the same time, the role of the bacterial flora and its interactions with the host immune system have been identified. In this article, we try to reconcile these findings to draw a consistent picture of the host defense system. Specifically, we first argue that the network of molecular interactions involved in immune functions has a bow-tie architecture that entails inherent trade-offs among robustness, fragility, resource limitation, and performance. Second, we discuss the possibility that commensal bacteria and the host immune system constitute an integrated defense system. This symbiotic association has evolved to optimize its robustness against pathogen attacks and nutrient perturbations by harboring a broad range of microorganisms. Owing to the inherent propensity of a host immune system toward hyperactivity, maintenance of bacterial flora homeostasis might be particularly important in the development of preventive strategies against immune disorders such as autoimmune diseases. PMID:16738567

Telomere sequence content can be used to determine ALT activity in tumours

PubMed Central

Lee, Michael; Teber, Erdahl T; Holmes, Oliver; Nones, Katia; Patch, Ann-Marie; Dagg, Rebecca A; Lau, Loretta M S; Lee, Joyce H; Napier, Christine E; Arthur, Jonathan W; Grimmond, Sean M; Hayward, Nicholas K; Johansson, Peter A; Mann, Graham J; Scolyer, Richard A; Wilmott, James S; Reddel, Roger R; Pearson, John V; Waddell, Nicola; Pickett, Hilda A

2018-01-01

Abstract The replicative immortality of human cancer cells is achieved by activation of a telomere maintenance mechanism (TMM). To achieve this, cancer cells utilise either the enzyme telomerase, or the Alternative Lengthening of Telomeres (ALT) pathway. These distinct molecular pathways are incompletely understood with respect to activation and propagation, as well as their associations with clinical outcomes. We have identified significant differences in the telomere repeat composition of tumours that use ALT compared to tumours that do not. We then employed a machine learning approach to stratify tumours according to telomere repeat content with an accuracy of 91.6%. Importantly, this classification approach is applicable across all tumour types. Analysis of pathway mutations that were under-represented in ALT tumours, across 1,075 tumour samples, revealed that the autophagy, cell cycle control of chromosomal replication, and transcriptional regulatory network in embryonic stem cells pathways are involved in the survival of ALT tumours. Overall, our approach demonstrates that telomere sequence content can be used to stratify ALT activity in cancers, and begin to define the molecular pathways involved in ALT activation. PMID:29718321

Personalized anticancer therapy selection using molecular landscape topology and thermodynamics.

PubMed

Rietman, Edward A; Scott, Jacob G; Tuszynski, Jack A; Klement, Giannoula Lakka

2017-03-21

Personalized anticancer therapy requires continuous consolidation of emerging bioinformatics data into meaningful and accurate information streams. The use of novel mathematical and physical approaches, namely topology and thermodynamics can enable merging differing data types for improved accuracy in selecting therapeutic targets. We describe a method that uses chemical thermodynamics and two topology measures to link RNA-seq data from individual patients with academically curated protein-protein interaction networks to select clinically relevant targets for treatment of low-grade glioma (LGG). We show that while these three histologically distinct tumor types (astrocytoma, oligoastrocytoma, and oligodendroglioma) may share potential therapeutic targets, the majority of patients would benefit from more individualized therapies. The method involves computing Gibbs free energy of the protein-protein interaction network and applying a topological filtration on the energy landscape to produce a subnetwork known as persistent homology. We then determine the most likely best target for therapeutic intervention using a topological measure of the network known as Betti number. We describe the algorithm and discuss its application to several patients.

Molecular characterization and analysis of the acrB gene of Aspergillus nidulans: a gene identified by genetic interaction as a component of the regulatory network that includes the CreB deubiquitination enzyme.

PubMed Central

Boase, Natasha A; Lockington, Robin A; Adams, Julian R J; Rodbourn, Louise; Kelly, Joan M

2003-01-01

Mutations in the acrB gene, which were originally selected through their resistance to acriflavine, also result in reduced growth on a range of sole carbon sources, including fructose, cellobiose, raffinose, and starch, and reduced utilization of omega-amino acids, including GABA and beta-alanine, as sole carbon and nitrogen sources. The acrB2 mutation suppresses the phenotypic effects of mutations in the creB gene that encodes a regulatory deubiquitinating enzyme, and in the creC gene that encodes a WD40-repeat-containing protein. Thus AcrB interacts with a regulatory network controlling carbon source utilization that involves ubiquitination and deubiquitination. The acrB gene was cloned and physically analyzed, and it encodes a novel protein that contains three putative transmembrane domains and a coiled-coil region. AcrB may play a role in the ubiquitination aspect of this regulatory network. PMID:12750323

Thermal fluctuations and elastic relaxation in the compressed exponential dynamics of colloidal gels

NASA Astrophysics Data System (ADS)

Bouzid, Mehdi; Colombo, Jader; Del Gado, Emanuela

Colloidal gels belong to the class of amorphous systems, they are disordered elastic solids that can form at very low volume fraction, via aggregation into a rich variety of networks. They exhibit a slow relaxation process in the aging regime similar to the glassy dynamics. A wide range of experiments on colloidal gels show unusual compressed exponential of the relaxation dynamical properties. We use molecular dynamics simulation to investigate how the dynamic change with the age of the system. Upon breaking and reorganization of the network structure, the system may display stretched or compressed exponential relaxation. We show that the transition between these two regimes is associated to the interplay between thermally activated rearrangements and the elastic relaxation of internal stresses. In particular, ballistic-like displacements emerge from the non local relaxation of internal stresses mediated by a series of ''micro-collapses''. When thermal fluctuations dominate, the gel restructuring involves instead more homogeneous displacements across the heterogeneous gel network, leading to a stretched exponential type of relaxation.

Dopamine homeostasis: brain functional connectivity in reward deficiency syndrome.

PubMed

Febo, Marcelo; Blum, Kenneth; Badgaiyan, Rajendra D; Baron, David; Thanos, Panayotis K; Colon-Perez, Luis M; Demortrovics, Zsolt; Gold, Mark S

2017-01-01

Reward deficiency syndrome (RDS) was first proposed by Kenneth Blum in 1995 to provide a clinically relevant and predictive term for conditions involving deficits in mesocorticolimbic dopamine function. Genetic, molecular, and neuronal alterations in key components of this circuitry contribute to a reward deficit state that can drive drug-seeking, consumption, and relapse. Among the dysfunctions observed in RDS are dysregulated resting state networks, which recently have been assessed in detail in chronic drug users by, positron emission tomography, functional magnetic resonance imaging, and functional connectivity analysis. A growing number of studies are helping to determine the putative roles of dopamine and glutamatergic neurotransmission in the regulation of activity in resting state networks, particularly in brain reward circuitry affected in drug use disorders. Indeed, we hypothesize in the present review that loss of homeostasis of these systems may lead to 'unbalanced' functional networks that might be both cause and outcome of disrupted synaptic communication between cortical and subcortical systems essential for controlling reward, emotional control, sensation seeking, and chronic drug use.

Network Medicine: A Network-based Approach to Human Disease

PubMed Central

Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph

2011-01-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525

Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

PubMed Central

Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

2012-01-01

Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led us to suggest that DR commonly suppresses translation, while stimulating an ancient reproduction-related process. PMID:22912585

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication

PubMed Central

Stetz, Gabrielle; Verkhivker, Gennady M.

2017-01-01

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms. PMID:28095400

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication.

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2017-01-01

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.

Programmed proteome response for drought avoidance/tolerance in the root of a C(3) xerophyte (wild watermelon) under water deficits.

PubMed

Yoshimura, Kazuya; Masuda, Akiko; Kuwano, Masayoshi; Yokota, Akiho; Akashi, Kinya

2008-02-01

Water availability is a critical determinant for the growth and ecological distribution of terrestrial plants. Although some xerophytes are unique regarding their highly developed root architecture and the successful adaptation to arid environments, virtually nothing is known about the molecular mechanisms underlying this adaptation. Here, we report physiological and molecular responses of wild watermelon (Citrullus lanatus sp.), which exhibits extraordinarily high drought resistance. At the early stage of drought stress, root development of wild watermelon was significantly enhanced compared with that of the irrigated plants, indicating the activation of a drought avoidance mechanism for absorbing water from deep soil layers. Consistent with this observation, comparative proteome analysis revealed that many proteins induced in the early stage of drought stress are involved in root morphogenesis and carbon/nitrogen metabolism, which may contribute to the drought avoidance via the enhancement of root growth. On the other hand, lignin synthesis-related proteins and molecular chaperones, which may function in the enhancement of physical desiccation tolerance and maintenance of protein integrity, respectively, were induced mostly at the later stage of drought stress. Our findings suggest that this xerophyte switches survival strategies from drought avoidance to drought tolerance during the progression of drought stress, by regulating its root proteome in a temporally programmed manner. This study provides new insights into the complex molecular networks within plant roots involved in the adaptation to adverse environments.

System Model Network for Adipose Tissue Signatures Related to Weight Changes in Response to Calorie Restriction and Subsequent Weight Maintenance

PubMed Central

Montastier, Emilie; Villa-Vialaneix, Nathalie; Caspar-Bauguil, Sylvie; Hlavaty, Petr; Tvrzicka, Eva; Gonzalez, Ignacio; Saris, Wim H. M.; Langin, Dominique; Kunesova, Marie; Viguerie, Nathalie

2015-01-01

Nutrigenomics investigates relationships between nutrients and all genome-encoded molecular entities. This holistic approach requires systems biology to scrutinize the effects of diet on tissue biology. To decipher the adipose tissue (AT) response to diet induced weight changes we focused on key molecular (lipids and transcripts) AT species during a longitudinal dietary intervention. To obtain a systems model, a network approach was used to combine all sets of variables (bio-clinical, fatty acids and mRNA levels) and get an overview of their interactions. AT fatty acids and mRNA levels were quantified in 135 obese women at baseline, after an 8-week low calorie diet (LCD) and after 6 months of ad libitum weight maintenance diet (WMD). After LCD, individuals were stratified a posteriori according to weight change during WMD. A 3 steps approach was used to infer a global model involving the 3 sets of variables. It consisted in inferring intra-omic networks with sparse partial correlations and inter-omic networks with regularized canonical correlation analysis and finally combining the obtained omic-specific network in a single global model. The resulting networks were analyzed using node clustering, systematic important node extraction and cluster comparisons. Overall, AT showed both constant and phase-specific biological signatures in response to dietary intervention. AT from women regaining weight displayed growth factors, angiogenesis and proliferation signaling signatures, suggesting unfavorable tissue hyperplasia. By contrast, after LCD a strong positive relationship between AT myristoleic acid (a fatty acid with low AT level) content and de novo lipogenesis mRNAs was found. This relationship was also observed, after WMD, in the group of women that continued to lose weight. This original system biology approach provides novel insight in the AT response to weight control by highlighting the central role of myristoleic acid that may account for the beneficial effects of weight loss. PMID:25590576

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso; Elena, Santiago F

2009-01-01

Background Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes. Results We show that the A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feed-forward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures. Conclusions These data suggest that A. thaliana has evolved high connectivity in terms of transcriptional regulation among cellular functions involved in response and adaptation to changing environments, while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this eukaryote. PMID:19754933

Identification and functional analysis of long non-coding RNAs in human and mouse early embryos based on single-cell transcriptome data

PubMed Central

Qiu, Jia-jun; Ren, Zhao-rui; Yan, Jing-bin

2016-01-01

Epigenetics regulations have an important role in fertilization and proper embryonic development, and several human diseases are associated with epigenetic modification disorders, such as Rett syndrome, Beckwith-Wiedemann syndrome and Angelman syndrome. However, the dynamics and functions of long non-coding RNAs (lncRNAs), one type of epigenetic regulators, in human pre-implantation development have not yet been demonstrated. In this study, a comprehensive analysis of human and mouse early-stage embryonic lncRNAs was performed based on public single-cell RNA sequencing data. Expression profile analysis revealed that lncRNAs are expressed in a developmental stage–specific manner during human early-stage embryonic development, whereas a more temporal-specific expression pattern was identified in mouse embryos. Weighted gene co-expression network analysis suggested that lncRNAs involved in human early-stage embryonic development are associated with several important functions and processes, such as oocyte maturation, zygotic genome activation and mitochondrial functions. We also found that the network of lncRNAs involved in zygotic genome activation was highly preservative between human and mouse embryos, whereas in other stages no strong correlation between human and mouse embryo was observed. This study provides insight into the molecular mechanism underlying lncRNA involvement in human pre-implantation embryonic development. PMID:27542205

Mechanisms and strategies of plant defense against Botrytis cinerea.

PubMed

AbuQamar, Synan; Moustafa, Khaled; Tran, Lam Son

2017-03-01

Biotic factors affect plant immune responses and plant resistance to pathogen infections. Despite the considerable progress made over the past two decades in manipulating genes, proteins and their levels from diverse sources, no complete genetic tolerance to environmental stresses has been developed so far in any crops. Plant defense response to pathogens, including Botrytis cinerea, is a complex biological process involving various changes at the biochemical, molecular (i.e. transcriptional) and physiological levels. Once a pathogen is detected, effective plant resistance activates signaling networks through the generation of small signaling molecules and the balance of hormonal signaling pathways to initiate defense mechanisms to the particular pathogen. Recently, studies using Arabidopsis thaliana and crop plants have shown that many genes are involved in plant responses to B. cinerea infection. In this article, we will review our current understanding of mechanisms regulating plant responses to B. cinerea with a particular interest on hormonal regulatory networks involving phytohormones salicylic acid (SA), jasmonic acid (JA), ethylene (ET) and abscisic acid (ABA). We will also highlight some potential gene targets that are promising for improving crop resistance to B. cinerea through genetic engineering and breeding programs. Finally, the role of biological control as a complementary and alternative disease management will be overviewed.

Propagating annotations of molecular networks using in silico fragmentation

PubMed Central

da Silva, Ricardo R.; Wang, Mingxun; Fox, Evan; Balunas, Marcy J.; Klassen, Jonathan L.; Dorrestein, Pieter C.

2018-01-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp. PMID:29668671

Propagating annotations of molecular networks using in silico fragmentation.

PubMed

da Silva, Ricardo R; Wang, Mingxun; Nothias, Louis-Félix; van der Hooft, Justin J J; Caraballo-Rodríguez, Andrés Mauricio; Fox, Evan; Balunas, Marcy J; Klassen, Jonathan L; Lopes, Norberto Peporine; Dorrestein, Pieter C

2018-04-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

Inferring causal molecular networks: empirical assessment through a community-based effort

PubMed Central

Hill, Steven M.; Heiser, Laura M.; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K.; Carlin, Daniel E.; Zhang, Yang; Sokolov, Artem; Paull, Evan O.; Wong, Chris K.; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V.; Favorov, Alexander V.; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W.; Long, Byron L.; Noren, David P.; Bisberg, Alexander J.; Mills, Gordon B.; Gray, Joe W.; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A.; Fertig, Elana J.; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M.; Spellman, Paul T.; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach

2016-01-01

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks. PMID:26901648

EMQN/CMGS best practice guidelines for the molecular genetic testing of Huntington disease.

PubMed

Losekoot, Monique; van Belzen, Martine J; Seneca, Sara; Bauer, Peter; Stenhouse, Susan A R; Barton, David E

2013-05-01

Huntington disease (HD) is caused by the expansion of an unstable polymorphic trinucleotide (CAG)n repeat in exon 1 of the HTT gene, which translates into an extended polyglutamine tract in the protein. Laboratory diagnosis of HD involves estimation of the number of CAG repeats. Molecular genetic testing for HD is offered in a wide range of laboratories both within and outside the European community. In order to measure the quality and raise the standard of molecular genetic testing in these laboratories, the European Molecular Genetics Quality Network has organized a yearly external quality assessment (EQA) scheme for molecular genetic testing of HD for over 10 years. EQA compares a laboratory's output with a fixed standard both for genotyping and reporting of the results to the referring physicians. In general, the standard of genotyping is very high but the clarity of interpretation and reporting of the test result varies more widely. This emphasizes the need for best practice guidelines for this disorder. We have therefore developed these best practice guidelines for genetic testing for HD to assist in testing and reporting of results. The analytical methods and the potential pitfalls of molecular genetic testing are highlighted and the implications of the different test outcomes for the consultand and his or her family members are discussed.

Quantitative implementation of the endogenous molecular-cellular network hypothesis in hepatocellular carcinoma.

PubMed

Wang, Gaowei; Zhu, Xiaomei; Gu, Jianren; Ao, Ping

2014-06-06

A quantitative hypothesis for cancer genesis and progression-the endogenous molecular-cellular network hypothesis, intended to include both genetic and epigenetic causes of cancer-has been proposed recently. Using this hypothesis, here we address the molecular basis for maintaining normal liver and hepatocellular carcinoma (HCC), and the potential strategy to cure or relieve HCC. First, we elaborate the basic assumptions of the hypothesis and establish a core working network of HCC according to the hypothesis. Second, we quantify the working network by a nonlinear dynamical system. We show that the working network reproduces the main known features of normal liver and HCC at both the modular and molecular levels. Lastly, the validated working network reveals that (i) specific positive feedback loops are responsible for the maintenance of normal liver and HCC; (ii) inhibiting proliferation and inflammation-related positive feedback loops and simultaneously inducing a liver-specific positive feedback loop is predicated as a potential strategy to cure or relieve HCC; and (iii) the genesis and regression of HCC are asymmetric. In light of the characteristic properties of the nonlinear dynamical system, we demonstrate that positive feedback loops must exist as a simple and general molecular basis for the maintenance of heritable phenotypes, such as normal liver and HCC, and regulating the positive feedback loops directly or indirectly provides potential strategies to cure or relieve HCC.

Molecular regulation of plant cell wall extensibility

NASA Technical Reports Server (NTRS)

Cosgrove, D. J.

1998-01-01

Gravity responses in plants often involve spatial and temporal changes in cell growth, which is regulated primarily by controlling the ability of the cell wall to extend. The wall is thought to be a cellulose-hemicellulose network embedded in a hydrated matrix of complex polysaccharides and a small amount of structural protein. The wall extends by a form of polymer creep, which is mediated by expansins, a novel group of wall-loosening proteins. Expansins were discovered during a molecular dissection of the "acid growth" behavior of cell walls. Expansin alters the rheology of plant walls in profound ways, yet its molecular mechanism of action is still uncertain. It lacks detectable hydrolytic activity against the major components of the wall, but it is able to disrupt noncovalent adhesion between wall polysaccharides. The discovery of a second family of expansins (beta-expansins) sheds light on the biological role of a major group of pollen allergens and implies that expansins have evolved for diverse developmental functions. Finally, the contribution of other processes to wall extensibility is briefly summarized.

Molecular genetics of dyslexia: an overview.

PubMed

Carrion-Castillo, Amaia; Franke, Barbara; Fisher, Simon E

2013-11-01

Dyslexia is a highly heritable learning disorder with a complex underlying genetic architecture. Over the past decade, researchers have pinpointed a number of candidate genes that may contribute to dyslexia susceptibility. Here, we provide an overview of the state of the art, describing how studies have moved from mapping potential risk loci, through identification of associated gene variants, to characterization of gene function in cellular and animal model systems. Work thus far has highlighted some intriguing mechanistic pathways, such as neuronal migration, axon guidance, and ciliary biology, but it is clear that we still have much to learn about the molecular networks that are involved. We end the review by highlighting the past, present, and future contributions of the Dutch Dyslexia Programme to studies of genetic factors. In particular, we emphasize the importance of relating genetic information to intermediate neurobiological measures, as well as the value of incorporating longitudinal and developmental data into molecular designs. Copyright © 2013 John Wiley & Sons, Ltd.

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

The meaning of PIWI proteins in cancer development.

PubMed

Litwin, Monika; Szczepańska-Buda, Anna; Piotrowska, Aleksandra; Dzięgiel, Piotr; Witkiewicz, Wojciech

2017-05-01

Cancer is a histologically and genetically heterogeneous population of tumor cells that exhibits distinct molecular profiles determined by epigenetic alterations. P-element-induced wimpy testis (PIWI) proteins in complex with PIWI-interacting RNA (piRNA) have been previously demonstrated to be involved in epigenetic regulation in germline cells. Recently, reactivation of PIWI expression, primarily PIWI-like protein 1 and 2, through aberrant DNA methylation resulting in genomic silencing has been identified in various types of tumors. It has been suggested that the PIWI-piRNA complex contributes to cancer development and progression by promoting a stem-like state of cancer cells, or cancer stem cells (CSCs). It has been identified that CSCs represent the cells that have undergone epithelial-mesenchymal transition (EMT) and acquired metastatic capacities. However, the molecular association between the EMT process and the stem-cell state remains unclear. Further extensive characterization of CSCs in individual types of tumors is required to identify specific markers for the heterogeneous population of CSCs and therefore selectively target CSCs. Previous studies indicate a reciprocal regulation between PIWI proteins and a complex signaling network linking markers characterized for CSCs and transcription factors involved in EMT. In the present review, studies of PIWI function are summarized, and the potential involvement of PIWI proteins in cancer development and progression is discussed.

The meaning of PIWI proteins in cancer development

PubMed Central

Litwin, Monika; Szczepańska-Buda, Anna; Piotrowska, Aleksandra; Dzięgiel, Piotr; Witkiewicz, Wojciech

2017-01-01

Cancer is a histologically and genetically heterogeneous population of tumor cells that exhibits distinct molecular profiles determined by epigenetic alterations. P-element-induced wimpy testis (PIWI) proteins in complex with PIWI-interacting RNA (piRNA) have been previously demonstrated to be involved in epigenetic regulation in germline cells. Recently, reactivation of PIWI expression, primarily PIWI-like protein 1 and 2, through aberrant DNA methylation resulting in genomic silencing has been identified in various types of tumors. It has been suggested that the PIWI-piRNA complex contributes to cancer development and progression by promoting a stem-like state of cancer cells, or cancer stem cells (CSCs). It has been identified that CSCs represent the cells that have undergone epithelial-mesenchymal transition (EMT) and acquired metastatic capacities. However, the molecular association between the EMT process and the stem-cell state remains unclear. Further extensive characterization of CSCs in individual types of tumors is required to identify specific markers for the heterogeneous population of CSCs and therefore selectively target CSCs. Previous studies indicate a reciprocal regulation between PIWI proteins and a complex signaling network linking markers characterized for CSCs and transcription factors involved in EMT. In the present review, studies of PIWI function are summarized, and the potential involvement of PIWI proteins in cancer development and progression is discussed. PMID:28529570

Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis)

PubMed Central

Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang

2015-01-01

Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology. PMID:25901577

Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis).

PubMed

Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang

2015-01-01

Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants' growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., 'Photosynthesis'), GO terms (e.g., 'response to karrikin') and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology.

Molecular characterization of the acquisition of longevity during seed maturation in soybean

PubMed Central

Lalanne, David; Rossi, Rubiana Falopa; Pelletier, Sandra; da Silva, Edvaldo Aparecido Amaral

2017-01-01

Seed longevity, defined as the ability to remain alive during storage, is an important agronomic factor. Poor longevity negatively impacts seedling establishment and consequently crop yield. This is particularly problematic for soybean as seeds have a short lifespan. While the economic importance of soybean has fueled a large number of transcriptome studies during embryogenesis and seed filling, the mechanisms regulating seed longevity during late maturation remain poorly understood. Here, a detailed physiological and molecular characterization of late seed maturation was performed in soybean to obtain a comprehensive overview of the regulatory genes that are potentially involved in longevity. Longevity appeared at physiological maturity at the end of seed filling before maturation drying and progressively doubled until the seeds reached the dry state. The increase in longevity was associated with the expression of genes encoding protective chaperones such as heat shock proteins and the repression of nuclear and chloroplast genes involved in a range of chloroplast activities, including photosynthesis. An increase in the raffinose family oligosaccharides (RFO)/sucrose ratio together with changes in RFO metabolism genes was also associated with longevity. A gene co-expression network analysis revealed 27 transcription factors whose expression profiles were highly correlated with longevity. Eight of them were previously identified in the longevity network of Medicago truncatula, including homologues of ERF110, HSF6AB, NFXL1 and members of the DREB2 family. The network also contained several transcription factors associated with auxin and developmental cell fate during flowering, organ growth and differentiation. A transcriptional transition occurred concomitant with seed chlorophyll loss and detachment from the mother plant, suggesting the activation of a post-abscission program. This transition was enriched with AP2/EREBP and WRKY transcription factors and genes associated with growth, germination and post-transcriptional processes, suggesting that this program prepares the seed for the dry quiescent state and germination. PMID:28700604

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.

Network pharmacology-based identification of key pharmacological pathways of Yin-Huang-Qing-Fei capsule acting on chronic bronchitis.

PubMed

Yu, Guohua; Zhang, Yanqiong; Ren, Weiqiong; Dong, Ling; Li, Junfang; Geng, Ya; Zhang, Yi; Li, Defeng; Xu, Haiyu; Yang, Hongjun

2017-01-01

For decades in China, the Yin-Huang-Qing-Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness) of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL-5, IL-10, IL-13, FCER1G, CCL11, and EPX) were demonstrated to be associated with the inflammatory process that occurs during the progression of asthma. Finally, a molecular docking simulation was performed and the results exhibited that 17 pairs of chemical components and candidate YHQFC targets involved in asthma pathway had strong binding efficiencies. In conclusion, this network pharmacology-based investigation revealed that YHQFC may attenuate the inflammatory reaction of chronic bronchitis by regulating its candidate targets, which may be implicated in the major pathological processes of the asthma pathway.

Network pharmacology-based identification of key pharmacological pathways of Yin–Huang–Qing–Fei capsule acting on chronic bronchitis

PubMed Central

Yu, Guohua; Zhang, Yanqiong; Ren, Weiqiong; Dong, Ling; Li, Junfang; Geng, Ya; Zhang, Yi; Li, Defeng; Xu, Haiyu; Yang, Hongjun

2017-01-01

For decades in China, the Yin–Huang–Qing–Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness) of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL-5, IL-10, IL-13, FCER1G, CCL11, and EPX) were demonstrated to be associated with the inflammatory process that occurs during the progression of asthma. Finally, a molecular docking simulation was performed and the results exhibited that 17 pairs of chemical components and candidate YHQFC targets involved in asthma pathway had strong binding efficiencies. In conclusion, this network pharmacology-based investigation revealed that YHQFC may attenuate the inflammatory reaction of chronic bronchitis by regulating its candidate targets, which may be implicated in the major pathological processes of the asthma pathway. PMID:28053519

TFmiR: a web server for constructing and analyzing disease-specific transcription factor and miRNA co-regulatory networks.

PubMed

Hamed, Mohamed; Spaniol, Christian; Nazarieh, Maryam; Helms, Volkhard

2015-07-01

TFmiR is a freely available web server for deep and integrative analysis of combinatorial regulatory interactions between transcription factors, microRNAs and target genes that are involved in disease pathogenesis. Since the inner workings of cells rely on the correct functioning of an enormously complex system of activating and repressing interactions that can be perturbed in many ways, TFmiR helps to better elucidate cellular mechanisms at the molecular level from a network perspective. The provided topological and functional analyses promote TFmiR as a reliable systems biology tool for researchers across the life science communities. TFmiR web server is accessible through the following URL: http://service.bioinformatik.uni-saarland.de/tfmir. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Network Medicine: From Cellular Networks to the Human Diseasome

NASA Astrophysics Data System (ADS)

Barabasi, Albert-Laszlo

2014-03-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

Exploring molecular networks using MONET ontology.

PubMed

Silva, João Paulo Müller da; Lemke, Ney; Mombach, José Carlos; Souza, José Guilherme Camargo de; Sinigaglia, Marialva; Vieira, Renata

2006-03-31

The description of the complex molecular network responsible for cell behavior requires new tools to integrate large quantities of experimental data in the design of biological information systems. These tools could be used in the characterization of these networks and in the formulation of relevant biological hypotheses. The building of an ontology is a crucial step because it integrates in a coherent framework the concepts necessary to accomplish such a task. We present MONET (molecular network), an extensible ontology and an architecture designed to facilitate the integration of data originating from different public databases in a single- and well-documented relational database, that is compatible with MONET formal definition. We also present an example of an application that can easily be implemented using these tools.

Improved actuation strain of PDMS-based DEA materials chemically modified with softening agents

NASA Astrophysics Data System (ADS)

Biedermann, Miriam; Blümke, Martin; Wegener, Michael; Krüger, Hartmut

2015-04-01

Dielectric elastomer actuators (DEAs) are smart materials that gained much in interest particularly in recent years. One active field of research is the improvement of their properties by modification of their structural framework. The object of this work is to improve the actuation properties of polydimethylsiloxane (PDMS)-based DEAs by covalent incorporation of mono-vinyl-terminated low-molecular PDMS chains into the PDMS network. These low-molecular units act as a kind of softener within the PDMS network. The loose chain ends interfere with the network formation and lower the network's density. PDMS films with up to 50wt% of low-molecular PDMS additives were manufactured and the chemical, mechanical, electrical, and electromechanical properties of these novel materials were investigated.

Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

PubMed Central

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

2013-01-01

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

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.

Transcriptomic dissection reveals wide spread differential expression in chickpea during early time points of Fusarium oxysporum f. sp. ciceri Race 1 attack

PubMed Central

Ghosh, Amartya

2017-01-01

Plants’ reaction to underground microorganisms is complex as sessile nature of plants compels them to prioritize their responses to diverse microorganisms both pathogenic and symbiotic. Roots of important crops are directly exposed to diverse microorganisms, but investigations involving root pathogens are significantly less. Thus, more studies involving root pathogens and their target crops are necessitated to enrich the understanding of underground interactions. Present study reported the molecular complexities in chickpea during Fusarium oxysporum f. sp. ciceri Race 1 (Foc1) infection. Transcriptomic dissections using RNA-seq showed significantly differential expression of molecular transcripts between infected and control plants of both susceptible and resistant genotypes. Radar plot analyses showed maximum expressional undulations after infection in both susceptible and resistant plants. Gene ontology and functional clustering showed large number of transcripts controlling basic metabolism of plants. Network analyses demonstrated defense components like peptidyl cis/trans isomerase, MAP kinase, beta 1,3 glucanase, serine threonine kinase, patatin like protein, lactolylglutathione lyase, coproporphyrinogen III oxidase, sulfotransferases; reactive oxygen species regulating components like respiratory burst oxidase, superoxide dismutases, cytochrome b5 reductase, glutathione reductase, thioredoxin reductase, ATPase; metabolism regulating components, myo inositol phosphate, carboxylate synthase; transport related gamma tonoplast intrinsic protein, and structural component, ubiquitins to serve as important nodals of defense signaling network. These nodal molecules probably served as hub controllers of defense signaling. Functional characterization of these hub molecules would not only help in developing better understanding of chickpea-Foc1 interaction but also place them as promising candidates for resistance management programs against vascular wilt of legumes. PMID:28542579

A census of P. longum’s phytochemicals and their network pharmacological evaluation for identifying novel drug-like molecules against various diseases, with a special focus on neurological disorders

PubMed Central

Choudhary, Neha

2018-01-01

Piper longum (P. longum, also called as long pepper) is one of the common culinary herbs that has been extensively used as a crucial constituent in various indigenous medicines, specifically in traditional Indian medicinal system known as Ayurveda. For exploring the comprehensive effect of its constituents in humans at proteomic and metabolic levels, we have reviewed all of its known phytochemicals and enquired about their regulatory potential against various protein targets by developing high-confidence tripartite networks consisting of phytochemical—protein target—disease association. We have also (i) studied immunomodulatory potency of this herb; (ii) developed subnetwork of human PPI regulated by its phytochemicals and could successfully associate its specific modules playing important role in diseases, and (iii) reported several novel drug targets. P10636 (microtubule-associated protein tau, that is involved in diseases like dementia etc.) was found to be the commonly screened target by about seventy percent of these phytochemicals. We report 20 drug-like phytochemicals in this herb, out of which 7 are found to be the potential regulators of 5 FDA approved drug targets. Multi-targeting capacity of 3 phytochemicals involved in neuroactive ligand receptor interaction pathway was further explored via molecular docking experiments. To investigate the molecular mechanism of P. longum’s action against neurological disorders, we have developed a computational framework that can be easily extended to explore its healing potential against other diseases and can also be applied to scrutinize other indigenous herbs for drug-design studies. PMID:29320554

A census of P. longum's phytochemicals and their network pharmacological evaluation for identifying novel drug-like molecules against various diseases, with a special focus on neurological disorders.

PubMed

Choudhary, Neha; Singh, Vikram

2018-01-01

Piper longum (P. longum, also called as long pepper) is one of the common culinary herbs that has been extensively used as a crucial constituent in various indigenous medicines, specifically in traditional Indian medicinal system known as Ayurveda. For exploring the comprehensive effect of its constituents in humans at proteomic and metabolic levels, we have reviewed all of its known phytochemicals and enquired about their regulatory potential against various protein targets by developing high-confidence tripartite networks consisting of phytochemical-protein target-disease association. We have also (i) studied immunomodulatory potency of this herb; (ii) developed subnetwork of human PPI regulated by its phytochemicals and could successfully associate its specific modules playing important role in diseases, and (iii) reported several novel drug targets. P10636 (microtubule-associated protein tau, that is involved in diseases like dementia etc.) was found to be the commonly screened target by about seventy percent of these phytochemicals. We report 20 drug-like phytochemicals in this herb, out of which 7 are found to be the potential regulators of 5 FDA approved drug targets. Multi-targeting capacity of 3 phytochemicals involved in neuroactive ligand receptor interaction pathway was further explored via molecular docking experiments. To investigate the molecular mechanism of P. longum's action against neurological disorders, we have developed a computational framework that can be easily extended to explore its healing potential against other diseases and can also be applied to scrutinize other indigenous herbs for drug-design studies.

Analyzing the Coordinated Gene Network Underlying Temperature-Dependent Sex Determination in Reptiles

PubMed Central

Shoemaker, Christina M.; Crews, David

2009-01-01

Although gonadogenesis has been extensively studied in vertebrates with genetic sex determination, investigations at the molecular level in nontraditional model organisms with temperature-dependent sex determination are a relatively new area of research. Results show that while the key players of the molecular network underlying gonad development appear to be retained, their functions range from conserved to novel roles. In this review, we summarize experiments investigating candidate molecular players underlying temperature-dependent sex determination. We discuss some of the problems encountered unraveling this network, pose potential solutions, and suggest rewarding future directions of research. PMID:19022389

Solvation of excess electrons trapped in charge pockets on molecular surfaces

NASA Astrophysics Data System (ADS)

Jalbout, Abraham F.

This work considers the ability of hydrogen fluoride (HF) to solvate excess electrons located on cyclic hydrocarbon surfaces. The principle applied involves the formation of systems in which excess electrons can be stabilized not only on concentrated molecular surface charge pockets but also by HF. Recent studies have shown that OH groups can form stable hydrogen-bonded networks on one side of a hydrocarbon surface (i.e. cyclohexane sheets), at the same time, the hydrogen atoms on the opposite side of this surface form a pocket of positive charge can attract the excess electron. This density can be further stabilized by the addition of an HF molecule that can form an 'anion with an internally solvated electron' (AISE) state. These systems are shown to be stable with respect to vertical electron detachment (VDE).

Aryl hydrocarbon receptor

PubMed Central

Kiss, Elina A.; Vonarbourg, Cedric

2012-01-01

Intestinal homeostasis results from a complex mutualism between gut microbiota and host cells. Defining the molecular network regulating such mutualism is currently of increasing interest, as its deregulation is reported to lead to increased susceptibility to infections, chronic inflammatory bowel diseases and cancer. Until now, the focus has been on the mechanism, by which the composition of indigenous microbiota shapes the immune system. In a recent study, we have shown that dietary compounds have also the ability to affect innate immune system. This regulation involves aryl hydrocarbon receptor (AhR), a sensor of plant-derived phytochemicals, which mediates the maintenance of Retinoic acid related orphan receptor γ t-expressing innate lymphoid cells (RORγt+ ILC) in the gut and consequently formation of postnatal lymphoid follicles. Thus, AhR represents the first evidence of a molecular link between diet and immunity at intestinal mucosal surfaces. PMID:22909905

Molecular inspired models for prediction and control of directional FSO/RF wireless networks

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Milner, Stuart D.; Davis, Christopher C.

2010-08-01

Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a framework based on the definition of a potential energy function to characterize robustness in communication networks and the study of first and second order variations of the potential energy to provide prediction and control strategies for network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in the eigenvalues of the Hessian of the network potential and network degradation.

Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

Meta-review of protein network regulating obesity between validated obesity candidate genes in the white adipose tissue of high-fat diet-induced obese C57BL/6J mice.

PubMed

Kim, Eunjung; Kim, Eun Jung; Seo, Seung-Won; Hur, Cheol-Goo; McGregor, Robin A; Choi, Myung-Sook

2014-01-01

Worldwide obesity and related comorbidities are increasing, but identifying new therapeutic targets remains a challenge. A plethora of microarray studies in diet-induced obesity models has provided large datasets of obesity associated genes. In this review, we describe an approach to examine the underlying molecular network regulating obesity, and we discuss interactions between obesity candidate genes. We conducted network analysis on functional protein-protein interactions associated with 25 obesity candidate genes identified in a literature-driven approach based on published microarray studies of diet-induced obesity. The obesity candidate genes were closely associated with lipid metabolism and inflammation. Peroxisome proliferator activated receptor gamma (Pparg) appeared to be a core obesity gene, and obesity candidate genes were highly interconnected, suggesting a coordinately regulated molecular network in adipose tissue. In conclusion, the current network analysis approach may help elucidate the underlying molecular network regulating obesity and identify anti-obesity targets for therapeutic intervention.

A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer's disease.

PubMed

Mostafavi, Sara; Gaiteri, Chris; Sullivan, Sarah E; White, Charles C; Tasaki, Shinya; Xu, Jishu; Taga, Mariko; Klein, Hans-Ulrich; Patrick, Ellis; Komashko, Vitalina; McCabe, Cristin; Smith, Robert; Bradshaw, Elizabeth M; Root, David E; Regev, Aviv; Yu, Lei; Chibnik, Lori B; Schneider, Julie A; Young-Pearse, Tracy L; Bennett, David A; De Jager, Philip L

2018-06-01

There is a need for new therapeutic targets with which to prevent Alzheimer's disease (AD), a major contributor to aging-related cognitive decline. Here we report the construction and validation of a molecular network of the aging human frontal cortex. Using RNA sequence data from 478 individuals, we first build a molecular network using modules of coexpressed genes and then relate these modules to AD and its neuropathologic and cognitive endophenotypes. We confirm these associations in two independent AD datasets. We also illustrate the use of the network in prioritizing amyloid- and cognition-associated genes for in vitro validation in human neurons and astrocytes. These analyses based on unique cohorts enable us to resolve the role of distinct cortical modules that have a direct effect on the accumulation of AD pathology from those that have a direct effect on cognitive decline, exemplifying a network approach to complex diseases.

The Drosophila Clock Neuron Network Features Diverse Coupling Modes and Requires Network-wide Coherence for Robust Circadian Rhythms.

PubMed

Yao, Zepeng; Bennett, Amelia J; Clem, Jenna L; Shafer, Orie T

2016-12-13

In animals, networks of clock neurons containing molecular clocks orchestrate daily rhythms in physiology and behavior. However, how various types of clock neurons communicate and coordinate with one another to produce coherent circadian rhythms is not well understood. Here, we investigate clock neuron coupling in the brain of Drosophila and demonstrate that the fly's various groups of clock neurons display unique and complex coupling relationships to core pacemaker neurons. Furthermore, we find that coordinated free-running rhythms require molecular clock synchrony not only within the well-characterized lateral clock neuron classes but also between lateral clock neurons and dorsal clock neurons. These results uncover unexpected patterns of coupling in the clock neuron network and reveal that robust free-running behavioral rhythms require a coherence of molecular oscillations across most of the fly's clock neuron network. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Ascl1 as a Novel Player in the Ptf1a Transcriptional Network for GABAergic Cell Specification in the Retina

PubMed Central

Parlier, Damien; Pretto, Silvia; Hamdache, Johanna; Vernier, Philippe; Locker, Morgane; Bellefroid, Eric; Perron, Muriel

2014-01-01

In contrast with the wealth of data involving bHLH and homeodomain transcription factors in retinal cell type determination, the molecular bases underlying neurotransmitter subtype specification is far less understood. Using both gain and loss of function analyses in Xenopus, we investigated the putative implication of the bHLH factor Ascl1 in this process. We found that in addition to its previously characterized proneural function, Ascl1 also contributes to the specification of the GABAergic phenotype. We showed that it is necessary for retinal GABAergic cell genesis and sufficient in overexpression experiments to bias a subset of retinal precursor cells towards a GABAergic fate. We also analysed the relationships between Ascl1 and a set of other bHLH factors using an in vivo ectopic neurogenic assay. We demonstrated that Ascl1 has unique features as a GABAergic inducer and is epistatic over factors endowed with glutamatergic potentialities such as Neurog2, NeuroD1 or Atoh7. This functional specificity is conferred by the basic DNA binding domain of Ascl1 and involves a specific genetic network, distinct from that underlying its previously demonstrated effects on catecholaminergic differentiation. Our data show that GABAergic inducing activity of Ascl1 requires the direct transcriptional regulation of Ptf1a, providing therefore a new piece of the network governing neurotransmitter subtype specification during retinogenesis. PMID:24643195

Uncovering a Predictive Molecular Signature for the Onset of NASH-Related Fibrosis in a Translational NASH Mouse Model.

PubMed

van Koppen, Arianne; Verschuren, Lars; van den Hoek, Anita M; Verheij, Joanne; Morrison, Martine C; Li, Kelvin; Nagabukuro, Hiroshi; Costessi, Adalberto; Caspers, Martien P M; van den Broek, Tim J; Sagartz, John; Kluft, Cornelis; Beysen, Carine; Emson, Claire; van Gool, Alain J; Goldschmeding, Roel; Stoop, Reinout; Bobeldijk-Pastorova, Ivana; Turner, Scott M; Hanauer, Guido; Hanemaaijer, Roeland

2018-01-01

The incidence of nonalcoholic steatohepatitis (NASH) is increasing. The pathophysiological mechanisms of NASH and the sequence of events leading to hepatic fibrosis are incompletely understood. The aim of this study was to gain insight into the dynamics of key molecular processes involved in NASH and to rank early markers for hepatic fibrosis. A time-course study in low-density lipoprotein-receptor knockout. Leiden mice on a high-fat diet was performed to identify the temporal dynamics of key processes contributing to NASH and fibrosis. An integrative systems biology approach was used to elucidate candidate markers linked to the active fibrosis process by combining transcriptomics, dynamic proteomics, and histopathology. The translational value of these findings were confirmed using human NASH data sets. High-fat-diet feeding resulted in obesity, hyperlipidemia, insulin resistance, and NASH with fibrosis in a time-dependent manner. Temporal dynamics of key molecular processes involved in the development of NASH were identified, including lipid metabolism, inflammation, oxidative stress, and fibrosis. A data-integrative approach enabled identification of the active fibrotic process preceding histopathologic detection using a novel molecular fibrosis signature. Human studies were used to identify overlap of genes and processes and to perform a network biology-based prioritization to rank top candidate markers representing the early manifestation of fibrosis. An early predictive molecular signature was identified that marked the active profibrotic process before histopathologic fibrosis becomes manifest. Early detection of the onset of NASH and fibrosis enables identification of novel blood-based biomarkers to stratify patients at risk, development of new therapeutics, and help shorten (pre)clinical experimental time frames.

The Effect of Crosslinking on the Microscale Stress Response and Molecular Deformations in Actin Networks

NASA Astrophysics Data System (ADS)

Gurmessa, Bekele; Fitzpatrick, Robert; Valdivia, Jonathon; Anderson, Rae M. R.

Actin, the most abundant protein in eukaryotic cells, is a semi-flexible biopolymer in the cytoskeleton that plays a crucial structural and mechanical role in cell stability, motion and replication, as well as muscle contraction. Most of these mechanically driven structural changes in cells stem from the complex viscoelastic nature of entangled actin networks and the presence of a myriad of proteins that cross-link actin filaments. Despite their importance, the mechanical response of actin networks is not yet well understood, particularly at the molecular level. Here, we use optical trapping - coupled with fluorescence microscopy - to characterize the microscale stress response and induced filament deformations in entangled and cross-linked actin networks subject to localized mechanical perturbations. In particular, we actively drive a microsphere 10 microns through an entangled or cross- linked actin network at a constant speed and measure the resistive force that the deformed actin filaments exert on the bead during and following strain. We simultaneously visualize and track individual sparsely-labeled actin filaments to directly link force response to molecular deformations, and map the propagation of the initially localized perturbation field throughout the rest of the network (~100 um). By varying the concentration of actin and cross-linkers we directly determine the role of crosslinking and entanglements on the length and time scales of stress propagation, molecular deformation and relaxation mechanisms in actin networks.

Charge transport network dynamics in molecular aggregates

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

Jackson, Nicholas E.; Chen, Lin X.; Ratner, Mark A.

2016-07-20

Due to the nonperiodic nature of charge transport in disordered systems, generating insight into static charge transport networks, as well as analyzing the network dynamics, can be challenging. Here, we apply time-dependent network analysis to scrutinize the charge transport networks of two representative molecular semiconductors: a rigid n-type molecule, perylenediimide, and a flexible p-type molecule, bBDT(TDPP)2. Simulations reveal the relevant timescale for local transfer integral decorrelation to be ~100 fs, which is shown to be faster than that of a crystalline morphology of the same molecule. Using a simple graph metric, global network changes are observed over timescales competitive withmore » charge carrier lifetimes. These insights demonstrate that static charge transport networks are qualitatively inadequate, whereas average networks often overestimate network connectivity. Finally, a simple methodology for tracking dynamic charge transport properties is proposed.« less

A new paradigm for the molecular basis of rubber elasticity

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

Hanson, David E.; Barber, John L.

The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less

A new paradigm for the molecular basis of rubber elasticity

DOE PAGES

Hanson, David E.; Barber, John L.

2015-02-19

The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less

[Exploiture and application of an internet-based Computation Platform for Integrative Pharmacology of Traditional Chinese Medicine].

PubMed

Xu, Hai-Yu; Liu, Zhen-Ming; Fu, Yan; Zhang, Yan-Qiong; Yu, Jian-Jun; Guo, Fei-Fei; Tang, Shi-Huan; Lv, Chuan-Yu; Su, Jin; Cui, Ru-Yi; Yang, Hong-Jun

2017-09-01

Recently, integrative pharmacology(IP) has become a pivotal paradigm for the modernization of traditional Chinese medicines(TCM) and combinatorial drugs discovery, which is an interdisciplinary science for establishing the in vitro and in vivo correlation between absorption, distribution, metabolism, and excretion/pharmacokinetic(ADME/PK) profiles of TCM and the molecular networks of disease by the integration of the knowledge of multi-disciplinary and multi-stages. In the present study, an internet-based Computation Platform for IP of TCM(TCM-IP, www.tcmip.cn) is established to promote the development of the emerging discipline. Among them, a big data of TCM is an important resource for TCM-IP including Chinese Medicine Formula Database, Chinese Medical Herbs Database, Chemical Database of Chinese Medicine, Target Database for Disease and Symptoms, et al. Meanwhile, some data mining and bioinformatics approaches are critical technology for TCM-IP including the identification of the TCM constituents, ADME prediction, target prediction for the TCM constituents, network construction and analysis, et al. Furthermore, network beautification and individuation design are employed to meet the consumer's requirement. We firmly believe that TCM-IP is a very useful tool for the identification of active constituents of TCM and their involving potential molecular mechanism for therapeutics, which would wildly applied in quality evaluation, clinical repositioning, scientific discovery based on original thinking, prescription compatibility and new drug of TCM, et al. Copyright© by the Chinese Pharmaceutical Association.

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis.

PubMed

Song, Zhenhua; Zhang, Chi; He, Lingxiao; Sui, Yanfang; Lin, Xiafei; Pan, Jingjing

2018-06-12

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes. Copyright © 2018 Elsevier Inc. All rights reserved.

System analysis identifies distinct and common functional networks governed by transcription factor ASCL1, in glioma and small cell lung cancer.

PubMed

Donakonda, Sainitin; Sinha, Swati; Dighe, Shrinivas Nivrutti; Rao, Manchanahalli R Satyanarayana

2017-07-25

ASCL1 is a basic Helix-Loop-Helix transcription factor (TF), which is involved in various cellular processes like neuronal development and signaling pathways. Transcriptome profiling has shown that ASCL1 overexpression plays an important role in the development of glioma and Small Cell Lung Carcinoma (SCLC), but distinct and common molecular mechanisms regulated by ASCL1 in these cancers are unknown. In order to understand how it drives the cellular functional network in these two tumors, we generated a gene expression profile in a glioma cell line (U87MG) to identify ASCL1 gene targets by an si RNA silencing approach and then compared this with a publicly available dataset of similarly silenced SCLC (NCI-H1618 cells). We constructed TF-TF and gene-gene interactions, as well as protein interaction networks of ASCL1 regulated genes in glioma and SCLC cells. Detailed network analysis uncovered various biological processes governed by ASCL1 target genes in these two tumor cell lines. We find that novel ASCL1 functions related to mitosis and signaling pathways influencing development and tumor growth are affected in both glioma and SCLC cells. In addition, we also observed ASCL1 governed functional networks that are distinct to glioma and SCLC.

Systems biology impact on antiepileptic drug discovery.

PubMed

Margineanu, Doru Georg

2012-02-01

Systems biology (SB), a recent trend in bioscience research to consider the complex interactions in biological systems from a holistic perspective, sees the disease as a disturbed network of interactions, rather than alteration of single molecular component(s). SB-relying network pharmacology replaces the prevailing focus on specific drug-receptor interaction and the corollary of rational drug design of "magic bullets", by the search for multi-target drugs that would act on biological networks as "magic shotguns". Epilepsy being a multi-factorial, polygenic and dynamic pathology, SB approach appears particularly fit and promising for antiepileptic drug (AED) discovery. In fact, long before the advent of SB, AED discovery already involved some SB-like elements. A reported SB project aimed to find out new drug targets in epilepsy relies on a relational database that integrates clinical information, recordings from deep electrodes and 3D-brain imagery with histology and molecular biology data on modified expression of specific genes in the brain regions displaying spontaneous epileptic activity. Since hitting a single target does not treat complex diseases, a proper pharmacological promiscuity might impart on an AED the merit of being multi-potent. However, multi-target drug discovery entails the complicated task of optimizing multiple activities of compounds, while having to balance drug-like properties and to control unwanted effects. Specific design tools for this new approach in drug discovery barely emerge, but computational methods making reliable in silico predictions of poly-pharmacology did appear, and their progress might be quite rapid. The current move away from reductionism into network pharmacology allows expecting that a proper integration of the intrinsic complexity of epileptic pathology in AED discovery might result in literally anti-epileptic drugs. Copyright © 2011 Elsevier B.V. All rights reserved.

HOXB7 and Hsa-miR-222 as the Potential Therapeutic Candidates for Metastatic Colorectal Cancer.

PubMed

Iman, Maryam; Mostafavi, Seyede Samaneh; Arab, Seyed Shahriar; Azimzadeh, Sadegh; Poorebrahim, Mansour

2016-01-01

Recent studies have shown that the high mortality of patients with colorectal cancer (CRC) is related to its ability to spread the surrounding tissues, thus there is a need for designing and developing new drugs. Here, we proposed a combinational therapy strategy, an inhibitory peptide in combination with miRNA targeting, for modulating CRC metastasis. In this study, some of the recent patents were also reviewed. After data analysis with GEO2R and gene annotation using DAVID server, regulatory interactions of differentially expressed genes (DEGs) were obtained from STRING, GeneMANIA, KEGG and TRED databases. In parallel, the corresponding validated microRNAs (miRNAs) were obtained from mirDIP web server and a miRNA-DEG regulatory network was also reconstructed. Clustering and topological analyses of the regulatory networks were performed using Cytoscape plug-ins. We found the HOXB family as the most important functional complex in DEG-derived regulatory network. Accordingly, an anti-HOXB7 peptide was designed based on the binding interface of its coactivator, PBX1. Topological analysis of miRNA-DEG network indicated that hsa-miR-222 is one of the most important oncomirs involved in regulation of DEGs activities. Thus, this miRNA, along with HOXB7, was also considered as the potential target for inhibiting CRC metastasis. Molecular docking studies exhibited that the designed peptide can bind to desired binding pocket of HOXB7 in a highaffinity manner. Further confirmations were also observed in Molecular dynamics (MD) simulations carried out by GROMACS v5.0.2 simulation package. In conclusion, our findings suggest that simultaneous targeting of key regulatory genes and miRNAs may be a useful strategy for prevention of CRC metastasis.

Role of a Water Network around the Mn4CaO5 Cluster in Photosynthetic Water Oxidation: A Fourier Transform Infrared Spectroscopy and Quantum Mechanics/Molecular Mechanics Calculation Study.

PubMed

Nakamura, Shin; Ota, Kai; Shibuya, Yuichi; Noguchi, Takumi

2016-01-26

Photosynthetic water oxidation takes place at the Mn4CaO5 cluster in photosystem II. Around the Mn4CaO5 cluster, a hydrogen bond network is formed by several water molecules, including four water ligands. To clarify the role of this water network in the mechanism of water oxidation, we investigated the effects of the removal of Ca(2+) and substitution with metal ions on the vibrations of water molecules coupled to the Mn4CaO5 cluster by means of Fourier transform infrared (FTIR) difference spectroscopy and quantum mechanics/molecular mechanics (QM/MM) calculations. The OH stretching vibrations of nine water molecules forming a network between D1-D61 and YZ were calculated using the QM/MM method. On the the calculated normal modes, a broad positive feature at 3200-2500 cm(-1) in an S2-minus-S1 FTIR spectrum was attributed to the vibrations of strongly hydrogen-bonded OH bonds of water involving the vibrations of water ligands to a Mn ion and the in-phase coupled vibration of a water network connected to YZ, while bands in the 3700-3500 cm(-1) region were assigned to the coupled vibrations of weakly hydrogen-bonded OH bonds of water. All the water bands were lost upon Ca(2+) depletion and Ba(2+) substitution, which inhibit the S2 → S3 transition, indicating that a solid water network was broken by these treatments. By contrast, Sr(2+) substitution slightly altered the water bands around 3600 cm(-1), reflecting minor modification in water interactions, consistent with the retention of water oxidation activity with a decreased efficiency. These results suggest that the water network around the Mn4CaO5 cluster plays an essential role in the water oxidation mechanism particularly in a concerted process of proton transfer and water insertion during the S2 → S3 transition.

Modeling of cell signaling pathways in macrophages by semantic networks

PubMed Central

Hsing, Michael; Bellenson, Joel L; Shankey, Conor; Cherkasov, Artem

2004-01-01

Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed investigation of connections among various essential molecules and reflected the cause-effect relationships among signaling events. The simulation demonstrated the dynamics of the semantic network, where a change of states on a molecule can alter its function and potentially cause a chain-reaction effect in the system. PMID:15494071

Transcript Analysis and Regulative Events during Flower Development in Olive (Olea europaea L.).

PubMed

Alagna, Fiammetta; Cirilli, Marco; Galla, Giulio; Carbone, Fabrizio; Daddiego, Loretta; Facella, Paolo; Lopez, Loredana; Colao, Chiara; Mariotti, Roberto; Cultrera, Nicolò; Rossi, Martina; Barcaccia, Gianni; Baldoni, Luciana; Muleo, Rosario; Perrotta, Gaetano

2016-01-01

The identification and characterization of transcripts involved in flower organ development, plant reproduction and metabolism represent key steps in plant phenotypic and physiological pathways, and may generate high-quality transcript variants useful for the development of functional markers. This study was aimed at obtaining an extensive characterization of the olive flower transcripts, by providing sound information on the candidate MADS-box genes related to the ABC model of flower development and on the putative genetic and molecular determinants of ovary abortion and pollen-pistil interaction. The overall sequence data, obtained by pyrosequencing of four cDNA libraries from flowers at different developmental stages of three olive varieties with distinct reproductive features (Leccino, Frantoio and Dolce Agogia), included approximately 465,000 ESTs, which gave rise to more than 14,600 contigs and approximately 92,000 singletons. As many as 56,700 unigenes were successfully annotated and provided gene ontology insights into the structural organization and putative molecular function of sequenced transcripts and deduced proteins in the context of their corresponding biological processes. Differentially expressed genes with potential regulatory roles in biosynthetic pathways and metabolic networks during flower development were identified. The gene expression studies allowed us to select the candidate genes that play well-known molecular functions in a number of biosynthetic pathways and specific biological processes that affect olive reproduction. A sound understanding of gene functions and regulatory networks that characterize the olive flower is provided.

Strategies for Advancing Disease Definition Using Biomarkers and Genetics: The Bipolar and Schizophrenia Network for Intermediate Phenotypes.

PubMed

Tamminga, Carol A; Pearlson, Godfrey D; Stan, Ana D; Gibbons, Robert D; Padmanabhan, Jaya; Keshavan, Matcheri; Clementz, Brett A

2017-01-01

It is critical for psychiatry as a field to develop approaches to define the molecular, cellular, and circuit basis of its brain diseases, especially for serious mental illnesses, and then to use these definitions to generate biologically based disease categories, as well as to explore disease mechanisms and illness etiologies. Our current reliance on phenomenology is inadequate to support exploration of molecular treatment targets and disease formulations, and the leap directly from phenomenology to disease biology has been limiting because of broad heterogeneity within conventional diagnoses. The questions addressed in this review are formulated around how we can use brain biomarkers to achieve disease categories that are biologically based. We have grouped together a series of vignettes as examples of early approaches, all using the Bipolar and Schizophrenia Network on Intermediate Phenotypes (BSNIP) biomarker database and collaborators, starting off with describing the foundational statistical methods for these goals. We use primarily criterion-free statistics to identify pertinent groups of involved genes related to psychosis as well as symptoms, and finally, to create new biologically based disease cohorts within the psychopathological dimension of psychosis. Although we do not put these results forward as final formulations, they represent a novel effort to rely minimally on phenomenology as a diagnostic tool and to fully embrace brain characteristics of structure, as well as molecular and cellular characteristics and function, to support disease definition in psychosis. Copyright © 2016. Published by Elsevier Inc.

Transcript Analysis and Regulative Events during Flower Development in Olive (Olea europaea L.)

PubMed Central

Alagna, Fiammetta; Cirilli, Marco; Galla, Giulio; Carbone, Fabrizio; Daddiego, Loretta; Facella, Paolo; Lopez, Loredana; Colao, Chiara; Mariotti, Roberto; Cultrera, Nicolò; Rossi, Martina; Barcaccia, Gianni; Baldoni, Luciana; Muleo, Rosario; Perrotta, Gaetano

2016-01-01

The identification and characterization of transcripts involved in flower organ development, plant reproduction and metabolism represent key steps in plant phenotypic and physiological pathways, and may generate high-quality transcript variants useful for the development of functional markers. This study was aimed at obtaining an extensive characterization of the olive flower transcripts, by providing sound information on the candidate MADS-box genes related to the ABC model of flower development and on the putative genetic and molecular determinants of ovary abortion and pollen-pistil interaction. The overall sequence data, obtained by pyrosequencing of four cDNA libraries from flowers at different developmental stages of three olive varieties with distinct reproductive features (Leccino, Frantoio and Dolce Agogia), included approximately 465,000 ESTs, which gave rise to more than 14,600 contigs and approximately 92,000 singletons. As many as 56,700 unigenes were successfully annotated and provided gene ontology insights into the structural organization and putative molecular function of sequenced transcripts and deduced proteins in the context of their corresponding biological processes. Differentially expressed genes with potential regulatory roles in biosynthetic pathways and metabolic networks during flower development were identified. The gene expression studies allowed us to select the candidate genes that play well-known molecular functions in a number of biosynthetic pathways and specific biological processes that affect olive reproduction. A sound understanding of gene functions and regulatory networks that characterize the olive flower is provided. PMID:27077738

Identification of common coexpression modules based on quantitative network comparison.

PubMed

Jo, Yousang; Kim, Sanghyeon; Lee, Doheon

2018-06-13

Finding common molecular interactions from different samples is essential work to understanding diseases and other biological processes. Coexpression networks and their modules directly reflect sample-specific interactions among genes. Therefore, identification of common coexpression network or modules may reveal the molecular mechanism of complex disease or the relationship between biological processes. However, there has been no quantitative network comparison method for coexpression networks and we examined previous methods for other networks that cannot be applied to coexpression network. Therefore, we aimed to propose quantitative comparison methods for coexpression networks and to find common biological mechanisms between Huntington's disease and brain aging by the new method. We proposed two similarity measures for quantitative comparison of coexpression networks. Then, we performed experiments using known coexpression networks. We showed the validity of two measures and evaluated threshold values for similar coexpression network pairs from experiments. Using these similarity measures and thresholds, we quantitatively measured the similarity between disease-specific and aging-related coexpression modules and found similar Huntington's disease-aging coexpression module pairs. We identified similar Huntington's disease-aging coexpression module pairs and found that these modules are related to brain development, cell death, and immune response. It suggests that up-regulated cell signalling related cell death and immune/ inflammation response may be the common molecular mechanisms in the pathophysiology of HD and normal brain aging in the frontal cortex.

MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model.

PubMed

Lawless, Nathan; Reinhardt, Timothy A; Bryan, Kenneth; Baker, Mike; Pesch, Bruce; Zimmerman, Duane; Zuelke, Kurt; Sonstegard, Tad; O'Farrelly, Cliona; Lippolis, John D; Lynn, David J

2014-01-27

Bovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per year. Because disease susceptibility is a multifactorial complex phenotype, an integrative biology approach is required to dissect the molecular networks involved. Here, we report such an approach using next-generation sequencing combined with advanced network and pathway biology methods to simultaneously profile mRNA and miRNA expression at multiple time points (0, 12, 24, 36 and 48 hr) in milk and blood FACS-isolated CD14(+) monocytes from animals infected in vivo with Streptococcus uberis. More than 3700 differentially expressed (DE) genes were identified in milk-isolated monocytes (MIMs), a key immune cell recruited to the site of infection during mastitis. Upregulated genes were significantly enriched for inflammatory pathways, whereas downregulated genes were enriched for nonglycolytic metabolic pathways. Monocyte transcriptional changes in the blood, however, were more subtle but highlighted the impact of this infection systemically. Genes upregulated in blood-isolated monocytes (BIMs) showed a significant association with interferon and chemokine signaling. Furthermore, 26 miRNAs were DE in MIMs and three were DE in BIMs. Pathway analysis revealed that predicted targets of downregulated miRNAs were highly enriched for roles in innate immunity (FDR < 3.4E-8), particularly TLR signaling, whereas upregulated miRNAs preferentially targeted genes involved in metabolism. We conclude that during S. uberis infection miRNAs are key amplifiers of monocyte inflammatory response networks and repressors of several metabolic pathways. Copyright © 2014 Lawless et al.

Implications of Circadian Rhythm in Dopamine and Mood Regulation.

PubMed

Kim, Jeongah; Jang, Sangwon; Choe, Han Kyoung; Chung, Sooyoung; Son, Gi Hoon; Kim, Kyungjin

2017-07-31

Mammalian physiology and behavior are regulated by an internal time-keeping system, referred to as circadian rhythm. The circadian timing system has a hierarchical organization composed of the master clock in the suprachiasmatic nucleus (SCN) and local clocks in extra-SCN brain regions and peripheral organs. The circadian clock molecular mechanism involves a network of transcription-translation feedback loops. In addition to the clinical association between circadian rhythm disruption and mood disorders, recent studies have suggested a molecular link between mood regulation and circadian rhythm. Specifically, genetic deletion of the circadian nuclear receptor Rev-erbα induces mania-like behavior caused by increased midbrain dopaminergic (DAergic) tone at dusk. The association between circadian rhythm and emotion-related behaviors can be applied to pathological conditions, including neurodegenerative diseases. In Parkinson's disease (PD), DAergic neurons in the substantia nigra pars compacta progressively degenerate leading to motor dysfunction. Patients with PD also exhibit non-motor symptoms, including sleep disorder and neuropsychiatric disorders. Thus, it is important to understand the mechanisms that link the molecular circadian clock and brain machinery in the regulation of emotional behaviors and related midbrain DAergic neuronal circuits in healthy and pathological states. This review summarizes the current literature regarding the association between circadian rhythm and mood regulation from a chronobiological perspective, and may provide insight into therapeutic approaches to target psychiatric symptoms in neurodegenerative diseases involving circadian rhythm dysfunction.

TNF-α Gene Knockout in Triple Negative Breast Cancer Cell Line Induces Apoptosis

PubMed Central

Pileczki, Valentina; Braicu, Cornelia; Gherman, Claudia D.; Berindan-Neagoe, Ioana

2013-01-01

Tumor necrosis factor alpha (TNF-α) is a pro-inflammatory cytokine involved in the promotion and progression of cancer, including triple negative breast cancer cells. Thus, there is significant interest in understanding the molecular signaling pathways that connect TNF-α with the survival of tumor cells. In our experiments, we used as an in vitro model for triple negative breast cancer the cell line Hs578T. The purpose of this study is to determine the gene expression profiling of apoptotic signaling networks after blocking TNF-α formation by using specially designed siRNA molecules to target TNF-α messenger RNA. Knockdown of TNF-α gene was associated with cell proliferation inhibition and apoptosis, as observed by monitoring the cell index using the xCELLigence RTCA System and flow cytometry. PCR array technology was used to examine the transcript levels of 84 genes involved in apoptosis. 15 genes were found to be relevant after comparing the treated group with the untreated one of which 3 were down-regulated and 12 up-regulated. The down-regulated genes are all involved in cell survival, whereas the up-regulated ones are involved in and interact with pro-apoptotic pathways. The results described here indicate that the direct target of TNF-α in the Hs578T breast cancer cell line increases the level of certain pro-apoptotic factors that modulate different cellular networks that direct the cells towards death. PMID:23263670

Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.

Application of the artificial neural network in quantitative structure-gradient elution retention relationship of phenylthiocarbamyl amino acids derivatives.

PubMed

Tham, S Y; Agatonovic-Kustrin, S

2002-05-15

Quantitative structure-retention relationship(QSRR) method was used to model reversed-phase high-performance liquid chromatography (RP-HPLC) separation of 18 selected amino acids. Retention data for phenylthiocarbamyl (PTC) amino acids derivatives were obtained using gradient elution on ODS column with mobile phase of varying acetonitrile, acetate buffer and containing 0.5 ml/l of triethylamine (TEA). Molecular structure of each amino acid was encoded with 36 calculated molecular descriptors. The correlation between the molecular descriptors and the retention time of the compounds in the calibration set was established using the genetic neural network method. A genetic algorithm (GA) was used to select important molecular descriptors and supervised artificial neural network (ANN) was used to correlate mobile phase composition and selected descriptors with the experimentally derived retention times. Retention time values were used as the network's output and calculated molecular descriptors and mobile phase composition as the inputs. The best model with five input descriptors was chosen, and the significance of the selected descriptors for amino acid separation was examined. Results confirmed the dominant role of the organic modifier in such chromatographic systems in addition to lipophilicity (log P) and molecular size and shape (topological indices) of investigated solutes.

Learning surface molecular structures via machine vision

NASA Astrophysics Data System (ADS)

Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

2017-08-01

Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

Gene expression profiling of breast cancer cell lines treated with proton and electron radiations.

PubMed

Bravatà, Valentina; Minafra, Luigi; Cammarata, Francesco Paolo; Pisciotta, Pietro; Lamia, Debora; Marchese, Valentina; Manti, Lorenzo; Cirrone, Giuseppe Ap; Gilardi, Maria Carla; Cuttone, Giacomo; Forte, Giusi Irma; Russo, Giorgio

2018-06-11

Technological advances in radiation therapy are evolving with the use of hadrons, such as protons, indicated for tumors where conventional radiotherapy does not give significant advantages or for tumors located in sensitive regions, which need the maximum of dose-saving of the surrounding healthy tissues. The genomic response to conventional and non conventional Linear Energy Transfer exposure is a poor investigated topic and became an issue of radiobiological interest. The aim of this work was to analyze and compare molecular responses in term of gene expression profiles, induced by electron and proton irradiation in breast cancer cell lines. We studied the gene expression profiling differences by cDNA microarray activated in response to electron and proton irradiation with different Linear Energy Transfer values, among three breast cell lines (the tumorigenic MCF7 and MDA-MB-231 and the non tumorigenic MCF10A), exposed to the same sub-lethal dose of 9 Gy. Gene expression profiling pathway analyses showed the activation of different signaling and molecular networks in a cell line and radiation type-dependent manner. MCF10A and MDA-MB-231 cell lines were found to induce factors and pathways involved in the immunological process control. Here we describe in a detailed way the gene expression profiling and pathways activated after electron and proton irradiation in breast cancer cells. Summarizing, although specific pathways are activated in a radiation type-dependent manner, each cell line activates overall similar molecular networks in response to both these two types of ionizing radiation. Advances in knowledge: In the era of personalized medicine and breast cancer target-directed intervention, we trust that this study could drive radiation therapy towards personalized treatments, evaluating possible combined treatments, based on the molecular characterization.

Genetic control of root growth: from genes to networks

PubMed Central

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B.; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Background Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. Scope This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. Conclusions While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. PMID:26558398

Comparison of gene co-networks reveals the molecular mechanisms of the rice (Oryza sativa L.) response to Rhizoctonia solani AG1 IA infection.

PubMed

Zhang, Jinfeng; Zhao, Wenjuan; Fu, Rong; Fu, Chenglin; Wang, Lingxia; Liu, Huainian; Li, Shuangcheng; Deng, Qiming; Wang, Shiquan; Zhu, Jun; Liang, Yueyang; Li, Ping; Zheng, Aiping

2018-05-05

Rhizoctonia solani causes rice sheath blight, an important disease affecting the growth of rice (Oryza sativa L.). Attempts to control the disease have met with little success. Based on transcriptional profiling, we previously identified more than 11,947 common differentially expressed genes (TPM > 10) between the rice genotypes TeQing and Lemont. In the current study, we extended these findings by focusing on an analysis of gene co-expression in response to R. solani AG1 IA and identified gene modules within the networks through weighted gene co-expression network analysis (WGCNA). We compared the different genes assigned to each module and the biological interpretations of gene co-expression networks at early and later modules in the two rice genotypes to reveal differential responses to AG1 IA. Our results show that different changes occurred in the two rice genotypes and that the modules in the two groups contain a number of candidate genes possibly involved in pathogenesis, such as the VQ protein. Furthermore, these gene co-expression networks provide comprehensive transcriptional information regarding gene expression in rice in response to AG1 IA. The co-expression networks derived from our data offer ideas for follow-up experimentation that will help advance our understanding of the translational regulation of rice gene expression changes in response to AG1 IA.

The shortest path is not the one you know: application of biological network resources in precision oncology research.

PubMed

Kuperstein, Inna; Grieco, Luca; Cohen, David P A; Thieffry, Denis; Zinovyev, Andrei; Barillot, Emmanuel

2015-03-01

Several decades of molecular biology research have delivered a wealth of detailed descriptions of molecular interactions in normal and tumour cells. This knowledge has been functionally organised and assembled into dedicated biological pathway resources that serve as an invaluable tool, not only for structuring the information about molecular interactions but also for making it available for biological, clinical and computational studies. With the advent of high-throughput molecular profiling of tumours, close to complete molecular catalogues of mutations, gene expression and epigenetic modifications are available and require adequate interpretation. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular profiles of tumours. Making sense out of these descriptions requires biological pathway resources for functional interpretation of the data. In this review, we describe the available biological pathway resources, their characteristics in terms of construction mode, focus, aims and paradigms of biological knowledge representation. We present a new resource that is focused on cancer-related signalling, the Atlas of Cancer Signalling Networks. We briefly discuss current approaches for data integration, visualisation and analysis, using biological networks, such as pathway scoring, guilt-by-association and network propagation. Finally, we illustrate with several examples the added value of data interpretation in the context of biological networks and demonstrate that it may help in analysis of high-throughput data like mutation, gene expression or small interfering RNA screening and can guide in patients stratification. Finally, we discuss perspectives for improving precision medicine using biological network resources and tools. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular patterns of tumours and enable to put precision oncology into general clinical practice. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Bioinformatics Analysis Reveals Genes Involved in the Pathogenesis of Ameloblastoma and Keratocystic Odontogenic Tumor.

PubMed

Santos, Eliane Macedo Sobrinho; Santos, Hércules Otacílio; Dos Santos Dias, Ivoneth; Santos, Sérgio Henrique; Batista de Paula, Alfredo Maurício; Feltenberger, John David; Sena Guimarães, André Luiz; Farias, Lucyana Conceição

2016-01-01

Pathogenesis of odontogenic tumors is not well known. It is important to identify genetic deregulations and molecular alterations. This study aimed to investigate, through bioinformatic analysis, the possible genes involved in the pathogenesis of ameloblastoma (AM) and keratocystic odontogenic tumor (KCOT). Genes involved in the pathogenesis of AM and KCOT were identified in GeneCards. Gene list was expanded, and the gene interactions network was mapped using the STRING software. "Weighted number of links" (WNL) was calculated to identify "leader genes" (highest WNL). Genes were ranked by K-means method and Kruskal-Wallis test was used (P<0.001). Total interactions score (TIS) was also calculated using all interaction data generated by the STRING database, in order to achieve global connectivity for each gene. The topological and ontological analyses were performed using Cytoscape software and BinGO plugin. Literature review data was used to corroborate the bioinformatics data. CDK1 was identified as leader gene for AM. In KCOT group, results show PCNA and TP53 . Both tumors exhibit a power law behavior. Our topological analysis suggested leader genes possibly important in the pathogenesis of AM and KCOT, by clustering coefficient calculated for both odontogenic tumors (0.028 for AM, zero for KCOT). The results obtained in the scatter diagram suggest an important relationship of these genes with the molecular processes involved in AM and KCOT. Ontological analysis for both AM and KCOT demonstrated different mechanisms. Bioinformatics analyzes were confirmed through literature review. These results may suggest the involvement of promising genes for a better understanding of the pathogenesis of AM and KCOT.

System Design for Nano-Network Communications

NASA Astrophysics Data System (ADS)

ShahMohammadian, Hoda

The potential applications of nanotechnology in a wide range of areas necessities nano-networking research. Nano-networking is a new type of networking which has emerged by applying nanotechnology to communication theory. Therefore, this dissertation presents a framework for physical layer communications in a nano-network and addresses some of the pressing unsolved challenges in designing a molecular communication system. The contribution of this dissertation is proposing well-justified models for signal propagation, noise sources, optimum receiver design and synchronization in molecular communication channels. The design of any communication system is primarily based on the signal propagation channel and noise models. Using the Brownian motion and advection molecular statistics, separate signal propagation and noise models are presented for diffusion-based and flow-based molecular communication channels. It is shown that the corrupting noise of molecular channels is uncorrelated and non-stationary with a signal dependent magnitude. The next key component of any communication system is the reception and detection process. This dissertation provides a detailed analysis of the effect of the ligand-receptor binding mechanism on the received signal, and develops the first optimal receiver design for molecular communications. The bit error rate performance of the proposed receiver is evaluated and the impact of medium motion on the receiver performance is investigated. Another important feature of any communication system is synchronization. In this dissertation, the first blind synchronization algorithm is presented for the molecular communication channels. The proposed algorithm uses a non-decision directed maximum likelihood criterion for estimating the channel delay. The Cramer-Rao lower bound is also derived and the performance of the proposed synchronization algorithm is evaluated by investigating its mean square error.

Advancing Risk Assessment through the Application of Systems Toxicology

PubMed Central

Sauer, John Michael; Kleensang, André; Peitsch, Manuel C.; Hayes, A. Wallace

2016-01-01

Risk assessment is the process of quantifying the probability of a harmful effect to individuals or populations from human activities. Mechanistic approaches to risk assessment have been generally referred to as systems toxicology. Systems toxicology makes use of advanced analytical and computational tools to integrate classical toxicology and quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Three presentations including two case studies involving both in vitro and in vivo approaches described the current state of systems toxicology and the potential for its future application in chemical risk assessment. PMID:26977253

5-Chloro-2-nitro-phenol.

PubMed

Ren, Dong-Mei

2012-05-01

The asymmetric unit of the title compound, C(6)H(4)ClNO(3), contains two independent mol-ecules in which the dihedral angles between the benzene ring and the nitro groups are 2.5 (1) and 8.5 (1)°. Intra-molecular O-H⋯O hydrogen bonds involving the hy-droxy and nitro substituents result in the formation of S(6) six-membered rings. In the crystal, O-H⋯O, O-H⋯Cl and C-H⋯O hydrogen bonds together with Cl⋯O contacts [3.238 (3) and 3.207 (3) Å] generate a three-dimensional network.

Identification of activated enhancers and linked transcription factors in breast, prostate, and kidney tumors by tracing enhancer networks using epigenetic traits.

PubMed

Rhie, Suhn Kyong; Guo, Yu; Tak, Yu Gyoung; Yao, Lijing; Shen, Hui; Coetzee, Gerhard A; Laird, Peter W; Farnham, Peggy J

2016-01-01

Although technological advances now allow increased tumor profiling, a detailed understanding of the mechanisms leading to the development of different cancers remains elusive. Our approach toward understanding the molecular events that lead to cancer is to characterize changes in transcriptional regulatory networks between normal and tumor tissue. Because enhancer activity is thought to be critical in regulating cell fate decisions, we have focused our studies on distal regulatory elements and transcription factors that bind to these elements. Using DNA methylation data, we identified more than 25,000 enhancers that are differentially activated in breast, prostate, and kidney tumor tissues, as compared to normal tissues. We then developed an analytical approach called Tracing Enhancer Networks using Epigenetic Traits that correlates DNA methylation levels at enhancers with gene expression to identify more than 800,000 genome-wide links from enhancers to genes and from genes to enhancers. We found more than 1200 transcription factors to be involved in these tumor-specific enhancer networks. We further characterized several transcription factors linked to a large number of enhancers in each tumor type, including GATA3 in non-basal breast tumors, HOXC6 and DLX1 in prostate tumors, and ZNF395 in kidney tumors. We showed that HOXC6 and DLX1 are associated with different clusters of prostate tumor-specific enhancers and confer distinct transcriptomic changes upon knockdown in C42B prostate cancer cells. We also discovered de novo motifs enriched in enhancers linked to ZNF395 in kidney tumors. Our studies characterized tumor-specific enhancers and revealed key transcription factors involved in enhancer networks for specific tumor types and subgroups. Our findings, which include a large set of identified enhancers and transcription factors linked to those enhancers in breast, prostate, and kidney cancers, will facilitate understanding of enhancer networks and mechanisms leading to the development of these cancers.

Direct Nanoscale Characterization of Submolecular Mobility in Complex Organic Non-linear Optical Systems

NASA Astrophysics Data System (ADS)

Knorr, Daniel; Gray, Tomoko; Kim, Tae-Dong; Luo, Jingdong; Jen, Alex; Overney, Rene

2008-03-01

For organic non-linear optical (NLO) materials composed of intricate molecular building blocks, the challenge is to deduce meaningful molecular scale mobility information to understand complex relaxation and phase behavior. This is crucial, as the process of achieving a robust acentric alignment strongly depends on the availability of inter- and intra-molecular mobilities outside the temperature range of the device operation window. Here, we introduce a nanoscale methodology based on scanning probe microscopy that provides direct insight into structural relaxations and shows great potential to direct material design of sophisticated macromolecules. It also offers a means by which mesoscale dynamics and cooperativity involved in relaxation processes can be quantified in terms of dynamic entropy and enthalpy. This study demonstrates this methodology to describe the mesocale dynamics of two systems (1) organic networking dendronized NLO molecular glasses that self-assemble into physically linked polymers due to quadrupolar phenyl-perfluorophenyl interactions and (2) dendronized side-chain electro-optic (EO) polymers. For the self assembling glasses, the degree of intermolecular cooperativity can be deduced using this methodology, while for the dendronized side-chain polymers, specific side chain mobilities are exploited to improve EO properties.

Network analysis of genes involved in the enhancement of hyperthermia sensitivity by the knockdown of BAG3 in human oral squamous cell carcinoma cells.

PubMed

Yunoki, Tatsuya; Tabuchi, Yoshiaki; Hayashi, Atsushi; Kondo, Takashi

2016-07-01

BCL2-associated athanogene 3 (BAG3), a co-chaperone of the heat shock 70 kDa protein (HSPA) family of proteins, is a cytoprotective protein that acts against various stresses, including heat stress. The aim of the present study was to identify gene networks involved in the enhancement of hyperthermia (HT) sensitivity by the knockdown (KD) of BAG3 in human oral squamous cell carcinoma (OSCC) cells. Although a marked elevation in the protein expression of BAG3 was detected in human the OSCC HSC-3 cells exposed to HT at 44˚C for 90 min, its expression was almost completely suppressed in the cells transfected with small interfering RNA against BAG3 (siBAG) under normal and HT conditions. The silencing of BAG3 also enhanced the cell death that was increased in the HSC-3 cells by exposure to HT. Global gene expression analysis revealed many genes that were differentially expressed by >2-fold in the cells exposed to HT and transfected with siBAG. Moreover, Ingenuity® pathways analysis demonstrated two unique gene networks, designated as Pro-cell death and Anti-cell death, which were obtained from upregulated genes and were mainly associated with the biological functions of induction and the prevention of cell death, respectively. Of note, the expression levels of genes in the Pro-cell death and Anti-cell death gene networks were significantly elevated and reduced in the HT + BAG3-KD group compared to those in the HT control group, respectively. These results provide further insight into the molecular mechanisms involved in the enhancement of HT sensitivity by the silencing of BAG3 in human OSCC cells.

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. Conclusions The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes. PMID:23418942

Disease gene classification with metagraph representations.

PubMed

Kircali Ata, Sezin; Fang, Yuan; Wu, Min; Li, Xiao-Li; Xiao, Xiaokui

2017-12-01

Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes. As disease proteins tend to have a similar topological characteristics on the PPIK network, we further propose to represent proteins with metagraphs. Different from a traditional network motif or subgraph, a metagraph can capture a particular topological arrangement involving the interactions/associations between both proteins and keywords. Based on the novel metagraph representations for proteins, we further build classifiers for disease protein classification through supervised learning. Our experiments on three different PPI databases demonstrate that the proposed method consistently improves disease protein prediction across various classifiers, by 15.3% in AUC on average. It outperforms the baselines including the diffusion-based methods (e.g., RWR) and the module-based methods by 13.8-32.9% for overall disease protein prediction. For predicting breast cancer genes, it outperforms RWR, PRINCE and the module-based baselines by 6.6-14.2%. Finally, our predictions also turn out to have better correlations with literature findings from PubMed. Copyright © 2017 Elsevier Inc. All rights reserved.

Molecular Dynamics Study of Twister Ribozyme: Role of Mg(2+) Ions and the Hydrogen-Bonding Network in the Active Site.

PubMed

Ucisik, Melek N; Bevilacqua, Philip C; Hammes-Schiffer, Sharon

2016-07-12

The recently discovered twister ribozyme is thought to utilize general acid-base catalysis in its self-cleavage mechanism, but the roles of nucleobases and metal ions in the mechanism are unclear. Herein, molecular dynamics simulations of the env22 twister ribozyme are performed to elucidate the structural and equilibrium dynamical properties, as well as to examine the role of Mg(2+) ions and possible candidates for the general base and acid in the self-cleavage mechanism. The active site region and the ends of the pseudoknots were found to be less mobile than other regions of the ribozyme, most likely providing structural stability and possibly facilitating catalysis. A purported catalytic Mg(2+) ion and the closest neighboring Mg(2+) ion remained chelated and relatively immobile throughout the microsecond trajectories, although removal of these Mg(2+) ions did not lead to any significant changes in the structure or equilibrium motions of the ribozyme on the microsecond time scale. In addition, a third metal ion, a Na(+) ion remained close to A1(O5'), the leaving group atom, during the majority of the microsecond trajectories, suggesting that it might stabilize the negative charge on A1(O5') during self-cleavage. The locations of these cations and their interactions with key nucleotides in the active site suggest that they may be catalytically relevant. The P1 stem is partially melted at its top and bottom in the crystal structure and further unwinds in the trajectories. The simulations also revealed an interconnected network comprised of hydrogen-bonding and π-stacking interactions that create a relatively rigid network around the self-cleavage site. The nucleotides involved in this network are among the highly conserved nucleotides in twister ribozymes, suggesting that this interaction network may be important to structure and function.

Transcriptome analysis of mRNA and microRNAs in intramuscular fat tissues of castrated and intact male Chinese Qinchuan cattle

PubMed Central

Wang, Ya-Ning; Wang, Hong-Cheng; Zhang, Song; Hong, Jie-Yun; Guo, Hong-Fang; Chen, Dai; Yang, Yang; Zan, Lin-Sen

2017-01-01

Intramuscular fat (IMF) is known to enhance beef palatability and can be markedly increased by castration. However, there is little understanding of the molecular mechanism underlying the IMF deposition after castration of beef cattle. We hypothesize that genetic regulators function differently in IMF from bulls and steers. Therefore, after detecting serum testosterone and lipid parameter, as well as the contents of IMF at 6, 12, 18 and 24 months, we have investigated differentially expressed (DE) microRNAs (miRNAs) and mRNAs in IMF of bulls and steers at 24 months of age in Qinchuan cattle using next-generation sequencing, and then explored the possible biopathways regulating IMF deposition. Serum testosterone levels were significantly decreased in steers, whereas IMF content, serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TGs) were markedly increased in steers. Comparing the results of steers and bulls, 580 upregulated genes and 1,120 downregulated genes in IMF tissues were identified as DE genes correlated with IMF deposition. The upregulated genes were mainly associated with lipid metabolism, lipogenesis and fatty acid transportation signalling pathways, and the downregulated genes were correlated with immune response and intracellular signal transduction. Concurrently, the DE miRNAs—important players in adipose tissue accumulation induced by castration—were also examined in IMF tissues; 52 DE miRNAs were identified. The expression profiles of selected genes and miRNAs were also confirmed by quantitative real-time PCR (qRT-PCR) assays. Using integrated analysis, we constructed the microRNA-target regulatory network which was supported by target validation using the dual luciferase reporter system. Moreover, Ingenuity Pathway Analysis (IPA) software was used to construct a molecular interaction network that could be involved in regulating IMF after castration. The detected molecular network is closely associated with lipid metabolism and adipocyte differentiation, which is supported by functional identification results of bta-let-7i on bovine preadipocytes. These results provided valuable insights into the molecular mechanisms of the IMF phenotype differences between steers and bulls. PMID:29073274

Memory loss in Alzheimer's disease

PubMed Central

Jahn, Holger

2013-01-01

Loss of memory is among the first symptoms reported by patients suffering from Alzheimer's disease (AD) and by their caretakers. Working memory and long-term declarative memory are affected early during the course of the disease. The individual pattern of impaired memory functions correlates with parameters of structural or functional brain integrity. AD pathology interferes with the formation of memories from the molecular level to the framework of neural networks. The investigation of AD memory loss helps to identify the involved neural structures, such as the default mode network, the influence of epigenetic and genetic factors, such as ApoE4 status, and evolutionary aspects of human cognition. Clinically, the analysis of memory assists the definition of AD subtypes, disease grading, and prognostic predictions. Despite new AD criteria that allow the earlier diagnosis of the disease by inclusion of biomarkers derived from cerebrospinal fluid or hippocampal volume analysis, neuropsychological testing remains at the core of AD diagnosis. PMID:24459411

Viral Disease Networks?

NASA Astrophysics Data System (ADS)

Gulbahce, Natali; Yan, Han; Vidal, Marc; Barabasi, Albert-Laszlo

2010-03-01

Viral infections induce multiple perturbations that spread along the links of the biological networks of the host cells. Understanding the impact of these cascading perturbations requires an exhaustive knowledge of the cellular machinery as well as a systems biology approach that reveals how individual components of the cellular system function together. Here we describe an integrative method that provides a new approach to studying virus-human interactions and its correlations with diseases. Our method involves the combined utilization of protein - protein interactions, protein -- DNA interactions, metabolomics and gene - disease associations to build a ``viraldiseasome''. By solely using high-throughput data, we map well-known viral associated diseases and predict new candidate viral diseases. We use microarray data of virus-infected tissues and patient medical history data to further test the implications of the viral diseasome. We apply this method to Epstein-Barr virus and Human Papillomavirus and shed light into molecular development of viral diseases and disease pathways.

diffuStats: an R package to compute diffusion-based scores on biological networks.

PubMed

Picart-Armada, Sergio; Thompson, Wesley K; Buil, Alfonso; Perera-Lluna, Alexandre

2018-02-01

Label propagation and diffusion over biological networks are a common mathematical formalism in computational biology for giving context to molecular entities and prioritizing novel candidates in the area of study. There are several choices in conceiving the diffusion process-involving the graph kernel, the score definitions and the presence of a posterior statistical normalization-which have an impact on the results. This manuscript describes diffuStats, an R package that provides a collection of graph kernels and diffusion scores, as well as a parallel permutation analysis for the normalized scores, that eases the computation of the scores and their benchmarking for an optimal choice. The R package diffuStats is publicly available in Bioconductor, https://bioconductor.org, under the GPL-3 license. sergi.picart@upc.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The power and promise of "rewiring" the mitogen-activated protein kinase network in prostate cancer therapeutics.

PubMed

Papatsoris, Athanasios G; Karamouzis, Michalis V; Papavassiliou, Athanasios G

2007-03-01

Prostate cancer is the most frequently diagnosed cancer among men and the second leading cause of male cancer deaths. Initially, tumor growth is androgen dependent and thus responsive to pharmacologic androgen deprivation, but there is a high rate of treatment failure because the disease evolves in an androgen-independent state. Growing evidence suggests that the Ras/mitogen-activated protein kinase (MAPK) signaling cascade represents a pivotal molecular circuitry participating directly or indirectly in prostate cancer evolution. The crucial role of the protein elements comprising this complex signal transduction network makes them potential targets for pharmacologic interference. Here, we will delineate the current knowledge regarding the involvement of the Ras/MAPK pathway in prostate carcinogenesis, spotlight ongoing research concerning the development of novel targeted agents such as the Ras/MAPK inhibitors in prostate cancer, and discuss the future perspectives of their therapeutic efficacy.

The National Clinical Trials Network: Conducting Successful Clinical Trials of New Therapies for Rare Cancers

PubMed Central

Schott, Anne F.; Welch, John J.; Verschraegen, Claire F.; Kurzrock, Razelle

2015-01-01

Rare cancers account for 27% of neoplasms diagnosed each year, and 25% of cancer-related deaths in the United States. However, rare cancers show some of the highest response rates to targeted therapies, probably due to identification of oncogenic drivers with little inter-patient variability. Although the low incidence of rare cancers make large scale randomized trials involving single histologies difficult to perform, drugs have been successfully developed in rare cancers utilizing clinical trial designs that combine microscopic anatomies. Such trials are being pursued within the National Clinical Trials Network (NCTN), which possesses unique qualifications to perform widespread molecular screening of tumors for patient enrollment onto therapeutic clinical trials. When larger clinical trials are needed to determine optimum treatment strategies in rare cancers, the NCTN's broad reach in North America and internationally, and ability to partner with both US-based and international research organizations, can make these challenging studies feasible. PMID:26433554

Informed walks: whispering hints to gene hunters inside networks' jungle.

PubMed

Bourdakou, Marilena M; Spyrou, George M

2017-10-11

Systemic approaches offer a different point of view on the analysis of several types of molecular associations as well as on the identification of specific gene communities in several cancer types. However, due to lack of sufficient data needed to construct networks based on experimental evidence, statistical gene co-expression networks are widely used instead. Many efforts have been made to exploit the information hidden in these networks. However, these approaches still need to capitalize comprehensively the prior knowledge encrypted into molecular pathway associations and improve their efficiency regarding the discovery of both exclusive subnetworks as candidate biomarkers and conserved subnetworks that may uncover common origins of several cancer types. In this study we present the development of the Informed Walks model based on random walks that incorporate information from molecular pathways to mine candidate genes and gene-gene links. The proposed model has been applied to TCGA (The Cancer Genome Atlas) datasets from seven different cancer types, exploring the reconstructed co-expression networks of the whole set of genes and driving to highlighted sub-networks for each cancer type. In the sequel, we elucidated the impact of each subnetwork on the indication of underlying exclusive and common molecular mechanisms as well as on the short-listing of drugs that have the potential to suppress the corresponding cancer type through a drug-repurposing pipeline. We have developed a method of gene subnetwork highlighting based on prior knowledge, capable to give fruitful insights regarding the underlying molecular mechanisms and valuable input to drug-repurposing pipelines for a variety of cancer types.

Gel Permeation Chromatography Characterization of the Chain Length Distributions in Thiol-Acrylate Photopolymer Networks

PubMed Central

Rydholm, Amber E.; Held, Nicole L.; Bowman, Christopher N.; Anseth, Kristi S.

2008-01-01

Crosslinked, degradable networks formed from the photopolymerization of thiol and acrylate monomers are explored as potential biomaterials. The degradation behavior and material properties of these networks are influenced by the molecular weight of the nondegradable thiol-polyacrylate backbone chains that form during photopolymerization. Here, gel permeation chromatography was used to characterize the thiol-polyacrylate backbone chain lengths in degraded thiol-acrylate networks. Increasing thiol functionality from 1 to 4 increased the backbone molecular weight (M̄w = 2.3 ± 0.07 × 104 Da for monothiol and 3.6 ± 0.1 × 104 Da for tetrathiol networks). Decreasing thiol functional group concentration from 30 to 10 mol% also increased the backbone lengths (M̄w = 7.3 ± 1.1 × 104 Da for the networks containing 10 mol% thiol groups as compared to 3.6 ± 0.1 × 104 Da for 30 mol% thiol). Finally, the backbone chain lengths were probed at various stages of degradation and an increase in backbone molecular weight was observed as mass loss progressed from 10 to 70%. PMID:19079733

Drug target identification using network analysis: Taking active components in Sini decoction as an example

NASA Astrophysics Data System (ADS)

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-04-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

PubMed Central

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-01-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound. PMID:27095146

Transcriptome Sequencing Reveals Wide Expression Reprogramming of Basal and Unknown Genes in Leptospira biflexa Biofilms

PubMed Central

Spangenberg, Lucía; Lopes Bastos, Bruno; Graña, Martín; Vasconcelos, Larissa; Almeida, Áurea; Greif, Gonzalo; Robello, Carlos; Ristow, Paula

2016-01-01

ABSTRACT The genus Leptospira is composed of pathogenic and saprophytic spirochetes. Pathogenic Leptospira is the etiological agent of leptospirosis, a globally spread neglected disease. A key ecological feature of some pathogenic species is their ability to survive both within and outside the host. For most leptospires, the ability to persist outside the host is associated with biofilm formation, a most important bacterial strategy to face and overcome hostile environmental conditions. The architecture and biochemistry of leptospiral biofilms are rather well understood; however, the genetic program underpinning biofilm formation remains mostly unknown. In this work, we used the saprophyte Leptospira biflexa as a model organism to assess over- and underrepresented transcripts during the biofilm state, using transcriptome sequencing (RNA-seq) technology. Our results showed that some basal biological processes like DNA replication and cell division are downregulated in the mature biofilm. Additionally, we identified significant expression reprogramming for genes involved in motility, sugar/lipid metabolism, and iron scavenging, as well as for outer membrane-encoding genes. A careful manual annotation process allowed us to assign molecular functions to many previously uncharacterized genes that are probably involved in biofilm metabolism. We also provided evidence for the presence of small regulatory RNAs in this species. Finally, coexpression networks were reconstructed to pinpoint functionally related gene clusters that may explain how biofilm maintenance is regulated. Beyond elucidating some genetic aspects of biofilm formation, this work reveals a number of pathways whose functional dissection may impact our understanding of leptospiral biology, in particular how these organisms adapt to environmental changes. IMPORTANCE In this work, we describe the first transcriptome based on RNA-seq technology focused on studying transcriptional changes associated with biofilm growth in a member of the genus Leptospira. As many pathogenic species of this genus can survive inside the host but also persist in environmental water, mostly forming biofilms, identifying the molecular basis of this capacity can impact the understanding of how leptospires are able to fulfill a complete life cycle that alternates between adaptation to the host and adaptation to hostile external environmental conditions. We identified several genes and regulatory networks that can be the kickoff for deepening understanding of the molecular mechanisms involving bacterial persistence via biofilm formation; understanding this is important for the future development of tools for controlling leptospirosis. PMID:27303713

Transcriptome Sequencing Reveals Wide Expression Reprogramming of Basal and Unknown Genes in Leptospira biflexa Biofilms.

PubMed

Iraola, Gregorio; Spangenberg, Lucía; Lopes Bastos, Bruno; Graña, Martín; Vasconcelos, Larissa; Almeida, Áurea; Greif, Gonzalo; Robello, Carlos; Ristow, Paula; Naya, Hugo

2016-01-01

The genus Leptospira is composed of pathogenic and saprophytic spirochetes. Pathogenic Leptospira is the etiological agent of leptospirosis, a globally spread neglected disease. A key ecological feature of some pathogenic species is their ability to survive both within and outside the host. For most leptospires, the ability to persist outside the host is associated with biofilm formation, a most important bacterial strategy to face and overcome hostile environmental conditions. The architecture and biochemistry of leptospiral biofilms are rather well understood; however, the genetic program underpinning biofilm formation remains mostly unknown. In this work, we used the saprophyte Leptospira biflexa as a model organism to assess over- and underrepresented transcripts during the biofilm state, using transcriptome sequencing (RNA-seq) technology. Our results showed that some basal biological processes like DNA replication and cell division are downregulated in the mature biofilm. Additionally, we identified significant expression reprogramming for genes involved in motility, sugar/lipid metabolism, and iron scavenging, as well as for outer membrane-encoding genes. A careful manual annotation process allowed us to assign molecular functions to many previously uncharacterized genes that are probably involved in biofilm metabolism. We also provided evidence for the presence of small regulatory RNAs in this species. Finally, coexpression networks were reconstructed to pinpoint functionally related gene clusters that may explain how biofilm maintenance is regulated. Beyond elucidating some genetic aspects of biofilm formation, this work reveals a number of pathways whose functional dissection may impact our understanding of leptospiral biology, in particular how these organisms adapt to environmental changes. IMPORTANCE In this work, we describe the first transcriptome based on RNA-seq technology focused on studying transcriptional changes associated with biofilm growth in a member of the genus Leptospira. As many pathogenic species of this genus can survive inside the host but also persist in environmental water, mostly forming biofilms, identifying the molecular basis of this capacity can impact the understanding of how leptospires are able to fulfill a complete life cycle that alternates between adaptation to the host and adaptation to hostile external environmental conditions. We identified several genes and regulatory networks that can be the kickoff for deepening understanding of the molecular mechanisms involving bacterial persistence via biofilm formation; understanding this is important for the future development of tools for controlling leptospirosis.

Association genetics in Solanum tuberosum provides new insights into potato tuber bruising and enzymatic tissue discoloration

PubMed Central

2011-01-01

Background Most agronomic plant traits result from complex molecular networks involving multiple genes and from environmental factors. One such trait is the enzymatic discoloration of fruit and tuber tissues initiated by mechanical impact (bruising). Tuber susceptibility to bruising is a complex trait of the cultivated potato (Solanum tuberosum) that is crucial for crop quality. As phenotypic evaluation of bruising is cumbersome, the application of diagnostic molecular markers would empower the selection of low bruising potato varieties. The genetic factors and molecular networks underlying enzymatic tissue discoloration are sparsely known. Hitherto there is no association study dealing with tuber bruising and diagnostic markers for enzymatic discoloration are rare. Results The natural genetic diversity for bruising susceptibility was evaluated in elite middle European potato germplasm in order to elucidate its molecular basis. Association genetics using a candidate gene approach identified allelic variants in genes that function in tuber bruising and enzymatic browning. Two hundred and five tetraploid potato varieties and breeding clones related by descent were evaluated for two years in six environments for tuber bruising susceptibility, specific gravity, yield, shape and plant maturity. Correlations were found between different traits. In total 362 polymorphic DNA fragments, derived from 33 candidate genes and 29 SSR loci, were scored in the population and tested for association with the traits using a mixed model approach, which takes into account population structure and kinship. Twenty one highly significant (p < 0.001) and robust marker-trait associations were identified. Conclusions The observed trait correlations and associated marker fragments provide new insight in the molecular basis of bruising susceptibility and its natural variation. The markers diagnostic for increased or decreased bruising susceptibility will facilitate the combination of superior alleles in breeding programs. In addition, this study presents novel candidates that might control enzymatic tissue discoloration and tuber bruising. Their validation and characterization will increase the knowledge about the underlying biological processes. PMID:21208436

High-Throughput Sequencing and Linkage Mapping of a Clownfish Genome Provide Insights on the Distribution of Molecular Players Involved in Sex Change.

PubMed

Casas, Laura; Saenz-Agudelo, Pablo; Irigoien, Xabier

2018-03-06

Clownfishes are an excellent model system for investigating the genetic mechanism governing hermaphroditism and socially-controlled sex change in their natural environment because they are broadly distributed and strongly site-attached. Genomic tools, such as genetic linkage maps, allow fine-mapping of loci involved in molecular pathways underlying these reproductive processes. In this study, a high-density genetic map of Amphiprion bicinctus was constructed with 3146 RAD markers in a full-sib family organized in 24 robust linkage groups which correspond to the haploid chromosome number of the species. The length of the map was 4294.71 cM, with an average marker interval of 1.38 cM. The clownfish linkage map showed various levels of conserved synteny and collinearity with the genomes of Asian and European seabass, Nile tilapia and stickleback. The map provided a platform to investigate the genomic position of genes with differential expression during sex change in A. bicinctus. This study aims to bridge the gap of genome-scale information for this iconic group of species to facilitate the study of the main gene regulatory networks governing social sex change and gonadal restructuring in protandrous hermaphrodites.

Metabolic control of female puberty: potential therapeutic targets.

PubMed

Castellano, Juan M; Tena-Sempere, Manuel

2016-10-01

The onset of puberty in females is highly sensitive to the nutritional status and the amount of energy reserves of the organism. This metabolic information is sensed and transmitted to hypothalamic GnRH neurons, considered to be ultimately responsible for triggering puberty through the coordinated action of different peripheral hormones, central neurotransmitters, and molecular mediators. This article will review and discuss (i) the relevant actions of the adipose hormone leptin, as a stimulatory/permissive signal, and the gut hormone ghrelin, as an inhibitory factor, in the metabolic control of female puberty; (ii) the crucial role of the hypothalamic kisspeptin neurons, recently emerged as essential gatekeepers of puberty, in transmitting this metabolic information to GnRH neurons; and (iii) the potential involvement of key cellular energy sensors, such as mTOR, as molecular mediators in this setting. The thorough characterization of the physiological roles of the above elements in the metabolic control of female puberty, along with the discovery of novel factors, pathways, and mechanisms involved, will promote our understanding of the complex networks connecting metabolism and puberty and, ultimately, will aid in the design of target-specific treatments for female pubertal disorders linked to conditions of metabolic stress.

The Arabidopsis phytohormone crosstalk network involves a consecutive metabolic route and circular control units of transcription factors that regulate enzyme-encoding genes.

PubMed

Yue, Xun; Li, Xing Guo; Gao, Xin-Qi; Zhao, Xiang Yu; Dong, Yu Xiu; Zhou, Chao

2016-09-02

Phytohormone synergies and signaling interdependency are important topics in plant developmental biology. Physiological and genetic experimental evidence for phytohormone crosstalk has been accumulating and a genome-scale enzyme correlation model representing the Arabidopsis metabolic pathway has been published. However, an integrated molecular characterization of phytohormone crosstalk is still not available. A novel modeling methodology and advanced computational approaches were used to construct an enzyme-based Arabidopsis phytohormone crosstalk network (EAPCN) at the biosynthesis level. The EAPCN provided the structural connectivity architecture of phytohormone biosynthesis pathways and revealed a surprising result; that enzymes localized at the highly connected nodes formed a consecutive metabolic route. Furthermore, our analysis revealed that the transcription factors (TFs) that regulate enzyme-encoding genes in the consecutive metabolic route formed structures, which we describe as circular control units operating at the transcriptional level. Furthermore, the downstream TFs in phytohormone signal transduction pathways were found to be involved in the circular control units that included the TFs regulating enzyme-encoding genes. In addition, multiple functional enzymes in the EAPCN were found to be involved in ion and pH homeostasis, environmental signal perception, cellular redox homeostasis, and circadian clocks. Last, publicly available transcriptional profiles and a protein expression map of the Arabidopsis root apical meristem were used as a case study to validate the proposed framework. Our results revealed multiple scales of coupled mechanisms in that hormonal crosstalk networks that play a central role in coordinating internal developmental processes with environmental signals, and give a broader view of Arabidopsis phytohormone crosstalk. We also uncovered potential key regulators that can be further analyzed in future studies.

Back to the biology in systems biology: what can we learn from biomolecular networks?

PubMed

Huang, Sui

2004-02-01

Genome-scale molecular networks, including protein interaction and gene regulatory networks, have taken centre stage in the investigation of the burgeoning disciplines of systems biology and biocomplexity. What do networks tell us? Some see in networks simply the comprehensive, detailed description of all cellular pathways, others seek in networks simple, higher-order qualities that emerge from the collective action of the individual pathways. This paper discusses networks from an encompassing category of thinking that will hopefully help readers to bridge the gap between these polarised viewpoints. Systems biology so far has emphasised the characterisation of large pathway maps. Now one has to ask: where is the actual biology in 'systems biology'? As structures midway between genome and phenome, and by serving as an 'extended genotype' or an 'elementary phenotype', molecular networks open a new window to the study of evolution and gene function in complex living systems. For the study of evolution, features in network topology offer a novel starting point for addressing the old debate on the relative contributions of natural selection versus intrinsic constraints to a particular trait. To study the function of genes, it is necessary not only to see them in the context of gene networks, but also to reach beyond describing network topology and to embrace the global dynamics of networks that will reveal higher-order, collective behaviour of the interacting genes. This will pave the way to understanding how the complexity of genome-wide molecular networks collapses to produce a robust whole-cell behaviour that manifests as tightly-regulated switching between distinct cell fates - the basis for multicellular life.

Emerging Plasmodium vivax resistance to chloroquine in South America: an overview

PubMed Central

Gonçalves, Lígia Antunes; Cravo, Pedro; Ferreira, Marcelo Urbano

2014-01-01

The global emergence of Plasmodium vivax strains resistant to chloroquine (CQ) since the late 1980s is complicating the current international efforts for malaria control and elimination. Furthermore, CQ-resistant vivax malaria has already reached an alarming prevalence in Indonesia, East Timor and Papua New Guinea. More recently, in vivo studies have documented CQ-resistant P. vivax infections in Guyana, Peru and Brazil. Here, we summarise the available data on CQ resistance across P. vivax-endemic areas of Latin America by combining published in vivo and in vitro studies. We also review the current knowledge regarding the molecular mechanisms of CQ resistance in P. vivax and the prospects for developing and standardising reliable molecular markers of drug resistance. Finally, we discuss how the Worldwide Antimalarial Resistance Network, an international collaborative effort involving malaria experts from all continents, might contribute to the current regional efforts to map CQ-resistant vivax malaria in South America. PMID:25184999

Stress responses during ageing: molecular pathways regulating protein homeostasis.

PubMed

Kyriakakis, Emmanouil; Princz, Andrea; Tavernarakis, Nektarios

2015-01-01

The ageing process is characterized by deterioration of physiological function accompanied by frailty and ageing-associated diseases. The most broadly and well-studied pathways influencing ageing are the insulin/insulin-like growth factor 1 signaling pathway and the dietary restriction pathway. Recent studies in diverse organisms have also delineated emerging pathways, which collectively or independently contribute to ageing. Among them the proteostatic-stress-response networks, inextricably affect normal ageing by maintaining or restoring protein homeostasis to preserve proper cellular and organismal function. In this chapter, we survey the involvement of heat stress and endoplasmic reticulum stress responses in the regulation of longevity, placing emphasis on the cross talk between different response mechanisms and their systemic effects. We further discuss novel insights relevant to the molecular pathways mediating these stress responses that may facilitate the development of innovative interventions targeting age-related pathologies such as diabetes, cancer, cardiovascular and neurodegenerative diseases.

Characterization of molecular associations involving L-ornithine and α-ketoglutaric acid: crystal structure of L-ornithinium α-ketoglutarate.

PubMed

Allouchi, H; Céolin, R; Berthon, L; Tombret, F; Rietveld, I B

2014-07-01

The crystal structure of L-ornithinium α-ketoglutarate (C5H13N2O2, C5H5O5) has been solved by direct methods using single crystal X-ray diffraction data. It crystallizes in the monoclinic system, space group P21, unit cell parameters a=15.4326(3), b=5.2015(1), c=16.2067(3) Å and β=91.986(1)°, containing two independent pairs of molecular ions in the asymmetric unit. An extensive hydrogen-bond network and electrostatic charges due to proton transfer provide an important part of the cohesive energy of the crystal. The conformational versatility of L-ornithine and α-ketoglutaric acid is illustrated by the present results and crystal structures available from the Cambridge Structural Database. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Dynamic Coupling and Allosteric Networks in the α Subunit of Heterotrimeric G Proteins.

PubMed

Yao, Xin-Qiu; Malik, Rabia U; Griggs, Nicholas W; Skjærven, Lars; Traynor, John R; Sivaramakrishnan, Sivaraj; Grant, Barry J

2016-02-26

G protein α subunits cycle between active and inactive conformations to regulate a multitude of intracellular signaling cascades. Important structural transitions occurring during this cycle have been characterized from extensive crystallographic studies. However, the link between observed conformations and the allosteric regulation of binding events at distal sites critical for signaling through G proteins remain unclear. Here we describe molecular dynamics simulations, bioinformatics analysis, and experimental mutagenesis that identifies residues involved in mediating the allosteric coupling of receptor, nucleotide, and helical domain interfaces of Gαi. Most notably, we predict and characterize novel allosteric decoupling mutants, which display enhanced helical domain opening, increased rates of nucleotide exchange, and constitutive activity in the absence of receptor activation. Collectively, our results provide a framework for explaining how binding events and mutations can alter internal dynamic couplings critical for G protein function. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Competitive inhibition can linearize dose-response and generate a linear rectifier

PubMed Central

Savir, Yonatan; Tu, Benjamin P.; Springer, Michael

2015-01-01

Summary Many biological responses require a dynamic range that is larger than standard bi-molecular interactions allow, yet the also ability to remain off at low input. Here we mathematically show that an enzyme reaction system involving a combination of competitive inhibition, conservation of the total level of substrate and inhibitor, and positive feedback can behave like a linear rectifier—that is, a network motif with an input-output relationship that is linearly sensitive to substrate above a threshold but unresponsive below the threshold. We propose that the evolutionarily conserved yeast SAGA histone acetylation complex may possess the proper physiological response characteristics and molecular interactions needed to perform as a linear rectifier, and we suggest potential experiments to test this hypothesis. One implication of this work is that linear responses and linear rectifiers might be easier to evolve or synthetically construct than is currently appreciated. PMID:26495436

Competitive inhibition can linearize dose-response and generate a linear rectifier.

PubMed

Savir, Yonatan; Tu, Benjamin P; Springer, Michael

2015-09-23

Many biological responses require a dynamic range that is larger than standard bi-molecular interactions allow, yet the also ability to remain off at low input. Here we mathematically show that an enzyme reaction system involving a combination of competitive inhibition, conservation of the total level of substrate and inhibitor, and positive feedback can behave like a linear rectifier-that is, a network motif with an input-output relationship that is linearly sensitive to substrate above a threshold but unresponsive below the threshold. We propose that the evolutionarily conserved yeast SAGA histone acetylation complex may possess the proper physiological response characteristics and molecular interactions needed to perform as a linear rectifier, and we suggest potential experiments to test this hypothesis. One implication of this work is that linear responses and linear rectifiers might be easier to evolve or synthetically construct than is currently appreciated.

Dietary selenium disrupts hepatic triglyceride stores and transcriptional networks associated with growth and Notch signaling in juvenile rainbow trout.

PubMed

Knight, Rosalinda; Marlatt, Vicki L; Baker, Josh A; Lo, Bonnie P; deBruyn, Adrian M H; Elphick, James R; Martyniuk, Christopher J

2016-11-01

Dietary Se has been shown to adversely affect adult fish by altering growth rates and metabolism. To determine the underlying mechanisms associated with these observations, we measured biochemical and transcriptomic endpoints in rainbow trout following dietary Se exposures. Treatment groups of juvenile rainbow trout were fed either control Lumbriculus variegatus worms or worms cultured on selenized yeast. Selenized yeast was cultured at four nominal doses of 5, 10, 20 or 40mg/kg Se dry weight (measured dose in the worms of 7.1, 10.7, 19.5, and 31.8mg/kgSedw respectively) and fish were fed for 60days. At 60 d, hepatic triglycerides, glycogen, total glutathione, 8-isoprostane and the transcriptome response in the liver (n=8/group) were measured. Fish fed the nominal dose of 20 and 40mg/kg Se dry weight had lower body weight and a shorter length, as well as lower triglyceride in the liver compared to controls. Evidence was lacking for an oxidative stress response and there was no change in total glutathione, 8-isoprostane levels, nor relative mRNA levels for glutathione peroxidase isoforms among groups. Microarray analysis revealed that molecular networks for long-chain fatty acid transport, lipid transport, and low density lipid oxidation were increased in the liver of fish fed 40mg/kg, and this is hypothesized to be associated with the lower triglyceride levels in these fish. In addition, up-regulated gene networks in the liver of 40mg/kg Se treated fish included epidermal growth factor receptor signaling, growth hormone receptor, and insulin growth factor receptor 1 signaling pathways. These molecular changes are hypothesized to be compensatory and related to impaired growth. A gene network related to Notch signaling, which is involved in cell-cell communication and gene transcription regulation, was also increased in the liver following dietary treatments with both 20 and 40mg/kg Se. Transcriptomic data support the hypothesis that dietary Se increases the expression of networks for growth-related signaling cascades in addition to those related to fatty acid synthesis and metabolism. We propose that the disruption of metabolites related to triglyceride processing and storage, as well as gene networks for epidermal growth factor and Notch signaling in the liver, represent key molecular initiating events for adverse outcomes related to growth and Se toxicity in fish. Copyright © 2016 Elsevier B.V. All rights reserved.

Transcriptional Network Analysis in Muscle Reveals AP-1 as a Partner of PGC-1α in the Regulation of the Hypoxic Gene Program

PubMed Central

Baresic, Mario; Salatino, Silvia; Kupr, Barbara

2014-01-01

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here, we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α overexpression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto-underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein 1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of the hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α. PMID:24912679

Quality control methodology for high-throughput protein-protein interaction screening.

PubMed

Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

RhoA regulates actin network dynamics during apical surface emergence in multiciliated epithelial cells

PubMed Central

Sedzinski, Jakub; Hannezo, Edouard; Tu, Fan; Biro, Maté

2017-01-01

ABSTRACT Homeostatic replacement of epithelial cells from basal precursors is a multistep process involving progenitor cell specification, radial intercalation and, finally, apical surface emergence. Recent data demonstrate that actin-based pushing under the control of the formin protein Fmn1 drives apical emergence in nascent multiciliated epithelial cells (MCCs), but little else is known about this actin network or the control of Fmn1. Here, we explore the role of the small GTPase RhoA in MCC apical emergence. Disruption of RhoA function reduced the rate of apical surface expansion and decreased the final size of the apical domain. Analysis of cell shapes suggests that RhoA alters the balance of forces exerted on the MCC apical surface. Finally, quantitative time-lapse imaging and fluorescence recovery after photobleaching studies argue that RhoA works in concert with Fmn1 to control assembly of the specialized apical actin network in MCCs. These data provide new molecular insights into epithelial apical surface assembly and could also shed light on mechanisms of apical lumen formation. PMID:28089989

RhoA regulates actin network dynamics during apical surface emergence in multiciliated epithelial cells.

PubMed

Sedzinski, Jakub; Hannezo, Edouard; Tu, Fan; Biro, Maté; Wallingford, John B

2017-01-15

Homeostatic replacement of epithelial cells from basal precursors is a multistep process involving progenitor cell specification, radial intercalation and, finally, apical surface emergence. Recent data demonstrate that actin-based pushing under the control of the formin protein Fmn1 drives apical emergence in nascent multiciliated epithelial cells (MCCs), but little else is known about this actin network or the control of Fmn1. Here, we explore the role of the small GTPase RhoA in MCC apical emergence. Disruption of RhoA function reduced the rate of apical surface expansion and decreased the final size of the apical domain. Analysis of cell shapes suggests that RhoA alters the balance of forces exerted on the MCC apical surface. Finally, quantitative time-lapse imaging and fluorescence recovery after photobleaching studies argue that RhoA works in concert with Fmn1 to control assembly of the specialized apical actin network in MCCs. These data provide new molecular insights into epithelial apical surface assembly and could also shed light on mechanisms of apical lumen formation. © 2017. Published by The Company of Biologists Ltd.

The paradox of caffeine-zolpidem interaction: a network analysis.

PubMed

Myslobodsky, Michael

2009-10-01

A widely prescribed and potent short-acting hypnotic, zolpidem has become the mainstay for the treatment of middle-of-the-night sleeplessness. It is expected to be antagonized by caffeine. Paradoxically, in some cases caffeine appears to slightly enhance zolpidem sedation. The pharmacokinetic and pharmacodynamic nature of this odd effect remains unexplored. The purpose of this study is to reproduce a hypothetical molecular network recruited by caffeine when co-administered with zolpidem using Ingenuity Pathway Analysis. Thus generated, network drew attention to several possible contributors to caffeine sedation, such as tachykinin precursor 1, cannabinoid, and GABA receptors. The present overview is centered on the possibility that caffeine potentiation of zolpidem sedation does not involve a centralized interaction of specific neurotransmitters, but rather is contributed by its antioxidant capacity. It is proposed that by modifying the cellular redox state, caffeine ultimately reduces the pool of reactive oxygen species, thereby increasing the bioavailability of endogenous melatonin for interaction with zolpidem. This side effect of caffeine encourages further studies of multiple antioxidants as an attractive way to potentially increasing somnolence.

Functional modules of sigma factor regulons guarantee adaptability and evolvability

PubMed Central

Binder, Sebastian C.; Eckweiler, Denitsa; Schulz, Sebastian; Bielecka, Agata; Nicolai, Tanja; Franke, Raimo; Häussler, Susanne; Meyer-Hermann, Michael

2016-01-01

The focus of modern molecular biology turns from assigning functions to individual genes towards understanding the expression and regulation of complex sets of molecules. Here, we provide evidence that alternative sigma factor regulons in the pathogen Pseudomonas aeruginosa largely represent insulated functional modules which provide a critical level of biological organization involved in general adaptation and survival processes. Analysis of the operational state of the sigma factor network revealed that transcription factors functionally couple the sigma factor regulons and significantly modulate the transcription levels in the face of challenging environments. The threshold quality of newly evolved transcription factors was reached faster and more robustly in in silico testing when the structural organization of sigma factor networks was taken into account. These results indicate that the modular structures of alternative sigma factor regulons provide P. aeruginosa with a robust framework to function adequately in its environment and at the same time facilitate evolutionary change. Our data support the view that widespread modularity guarantees robustness of biological networks and is a key driver of evolvability. PMID:26915971

Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer.

PubMed

Gao, Xue-Xin; Gao, Lei; Wang, Jiu-Qiang; Qu, Su-Su; Qu, Yue; Sun, Hong-Lei; Liu, Si-Dang; Shang, Ying-Li

2016-07-12

Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce.In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis.Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC.Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC.

Diverse ways of perturbing the human arachidonic acid metabolic network to control inflammation.

PubMed

Meng, Hu; Liu, Ying; Lai, Luhua

2015-08-18

Inflammation and other common disorders including diabetes, cardiovascular disease, and cancer are often the result of several molecular abnormalities and are not likely to be resolved by a traditional single-target drug discovery approach. Though inflammation is a normal bodily reaction, uncontrolled and misdirected inflammation can cause inflammatory diseases such as rheumatoid arthritis and asthma. Nonsteroidal anti-inflammatory drugs including aspirin, ibuprofen, naproxen, or celecoxib are commonly used to relieve aches and pains, but often these drugs have undesirable and sometimes even fatal side effects. To facilitate safer and more effective anti-inflammatory drug discovery, a balanced treatment strategy should be developed at the biological network level. In this Account, we focus on our recent progress in modeling the inflammation-related arachidonic acid (AA) metabolic network and subsequent multiple drug design. We first constructed a mathematical model of inflammation based on experimental data and then applied the model to simulate the effects of commonly used anti-inflammatory drugs. Our results indicated that the model correctly reproduced the established bleeding and cardiovascular side effects. Multitarget optimal intervention (MTOI), a Monte Carlo simulated annealing based computational scheme, was then developed to identify key targets and optimal solutions for controlling inflammation. A number of optimal multitarget strategies were discovered that were both effective and safe and had minimal associated side effects. Experimental studies were performed to evaluate these multitarget control solutions further using different combinations of inhibitors to perturb the network. Consequently, simultaneous control of cyclooxygenase-1 and -2 and leukotriene A4 hydrolase, as well as 5-lipoxygenase and prostaglandin E2 synthase were found to be among the best solutions. A single compound that can bind multiple targets presents advantages including low risk of drug-drug interactions and robustness regarding concentration fluctuations. Thus, we developed strategies for multiple-target drug design and successfully discovered several series of multiple-target inhibitors. Optimal solutions for a disease network often involve mild but simultaneous interventions of multiple targets, which is in accord with the philosophy of traditional Chinese medicine (TCM). To this end, our AA network model can aptly explain TCM anti-inflammatory herbs and formulas at the molecular level. We also aimed to identify activators for several enzymes that appeared to have increased activity based on MTOI outcomes. Strategies were then developed to predict potential allosteric sites and to discover enzyme activators based on our hypothesis that combined treatment with the projected activators and inhibitors could balance different AA network pathways, control inflammation, and reduce associated adverse effects. Our work demonstrates that the integration of network modeling and drug discovery can provide novel solutions for disease control, which also calls for new developments in drug design concepts and methodologies. With the rapid accumulation of quantitative data and knowledge of the molecular networks of disease, we can expect an increase in the development and use of quantitative disease models to facilitate efficient and safe drug discovery.

System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks

PubMed Central

Miao, Yingbo; Zhang, Liangcai; Wang, Yang; Feng, Rennan; Yang, Lei; Zhang, Shihua; Jiang, Yongshuai; Liu, Guiyou

2014-01-01

Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM. PMID:25243143

Genome-Wide siRNA Screen Identifies Complementary Signaling Pathways Involved in Listeria Infection and Reveals Different Actin Nucleation Mechanisms during Listeria Cell Invasion and Actin Comet Tail Formation

PubMed Central

Kühbacher, Andreas; Emmenlauer, Mario; Rämo, Pauli; Kafai, Natasha; Dehio, Christoph

2015-01-01

ABSTRACT Listeria monocytogenes enters nonphagocytic cells by a receptor-mediated mechanism that is dependent on a clathrin-based molecular machinery and actin rearrangements. Bacterial intra- and intercellular movements are also actin dependent and rely on the actin nucleating Arp2/3 complex, which is activated by host-derived nucleation-promoting factors downstream of the cell receptor Met during entry and by the bacterial nucleation-promoting factor ActA during comet tail formation. By genome-wide small interfering RNA (siRNA) screening for host factors involved in bacterial infection, we identified diverse cellular signaling networks and protein complexes that support or limit these processes. In addition, we could precise previously described molecular pathways involved in Listeria invasion. In particular our results show that the requirements for actin nucleators during Listeria entry and actin comet tail formation are different. Knockdown of several actin nucleators, including SPIRE2, reduced bacterial invasion while not affecting the generation of comet tails. Most interestingly, we observed that in contrast to our expectations, not all of the seven subunits of the Arp2/3 complex are required for Listeria entry into cells or actin tail formation and that the subunit requirements for each of these processes differ, highlighting a previously unsuspected versatility in Arp2/3 complex composition and function. PMID:25991686

Comprehensive proteomic analysis of bovine spermatozoa of varying fertility rates and identification of biomarkers associated with fertility.

PubMed

Peddinti, Divyaswetha; Nanduri, Bindu; Kaya, Abdullah; Feugang, Jean M; Burgess, Shane C; Memili, Erdogan

2008-02-22

Male infertility is a major problem for mammalian reproduction. However, molecular details including the underlying mechanisms of male fertility are still not known. A thorough understanding of these mechanisms is essential for obtaining consistently high reproductive efficiency and to ensure lower cost and time-loss by breeder. Using high and low fertility bull spermatozoa, here we employed differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT) and identified 125 putative biomarkers of fertility. We next used quantitative Systems Biology modeling and canonical protein interaction pathways and networks to show that high fertility spermatozoa differ from low fertility spermatozoa in four main ways. Compared to sperm from low fertility bulls, sperm from high fertility bulls have higher expression of proteins involved in: energy metabolism, cell communication, spermatogenesis, and cell motility. Our data also suggests a hypothesis that low fertility sperm DNA integrity may be compromised because cell cycle: G2/M DNA damage checkpoint regulation was most significant signaling pathway identified in low fertility spermatozoa. This is the first comprehensive description of the bovine spermatozoa proteome. Comparative proteomic analysis of high fertility and low fertility bulls, in the context of protein interaction networks identified putative molecular markers associated with high fertility phenotype.

Crosstalk among Jasmonate, Salicylate and Ethylene Signaling Pathways in Plant Disease and Immune Responses.

PubMed

Yang, You-Xin; Ahammed, Golam J; Wu, Caijun; Fan, Shu-ying; Zhou, Yan-Hong

2015-01-01

Phytohormone crosstalk is crucial for plant defenses against pathogens and insects in which salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) play key roles. These low molecular mass signals critically trigger and modulate plant resistance against biotrophic as well as necrotrophic pathogens through a complex signaling network that even involves participation of other hormones. Crosstalk among SA, JA and ET is mediated by different molecular players, considered as integral part of these crosscommunicating signal transduction pathways. Recent progress has revealed that the positive versus negative interactions among those pathways ultimately enable a plant to fine-tune its defense against specific aggressors. On the other hand, pathogens have evolved strategies to manipulate the signaling network to their favour in order to intensify virulence on host plant. Here we review recent advances and current knowledge on the role of classical primary defense hormones SA, JA and ET as well as their synergistic and antagonistic interaction in plant disease and immune responses. Crosstalk with other hormones such as abscisic acid, auxin, brassinosteroids, cytokinins and melatonin is also discussed mainly in plant disease resistance. In addition to our keen focus on hormonal crosstalk, this review also highlights potential implication of positive and negative regulatory interactions for developing an efficient disease management strategy through manipulation of hormone signaling in plant.

Metabolomics and transcriptomics profiles reveal the dysregulation of the tricarboxylic acid cycle and related mechanisms in prostate cancer.

PubMed

Shao, Yaping; Ye, Guozhu; Ren, Shancheng; Piao, Hai-Long; Zhao, Xinjie; Lu, Xin; Wang, Fubo; Ma, Wang; Li, Jia; Yin, Peiyuan; Xia, Tian; Xu, Chuanliang; Yu, Jane J; Sun, Yinghao; Xu, Guowang

2018-07-15

Genetic alterations drive metabolic reprograming to meet increased biosynthetic precursor and energy demands for cancer cell proliferation and survival in unfavorable environments. A systematic study of gene-metabolite regulatory networks and metabolic dysregulation should reveal the molecular mechanisms underlying prostate cancer (PCa) pathogenesis. Herein, we performed gas chromatography-mass spectrometry (GC-MS)-based metabolomics and RNA-seq analyses in prostate tumors and matched adjacent normal tissues (ANTs) to elucidate the molecular alterations and potential underlying regulatory mechanisms in PCa. Significant accumulation of metabolic intermediates and enrichment of genes in the tricarboxylic acid (TCA) cycle were observed in tumor tissues, indicating TCA cycle hyperactivation in PCa tissues. In addition, the levels of fumarate and malate were highly correlated with the Gleason score, tumor stage and expression of genes encoding related enzymes and were significantly related to the expression of genes involved in branched chain amino acid degradation. Using an integrated omics approach, we further revealed the potential anaplerotic routes from pyruvate, glutamine catabolism and branched chain amino acid (BCAA) degradation contributing to replenishing metabolites for TCA cycle. Integrated omics techniques enable the performance of network-based analyses to gain a comprehensive and in-depth understanding of PCa pathophysiology and may facilitate the development of new and effective therapeutic strategies. © 2018 UICC.

The mature anther-preferentially expressed genes are associated with pollen fertility, pollen germination and anther dehiscence in rice.

PubMed

Ling, Sheng; Chen, Caisheng; Wang, Yang; Sun, Xiaocong; Lu, Zhanhua; Ouyang, Yidan; Yao, Jialing

2015-02-19

The anthers and pollen grains are critical for male fertility and hybrid rice breeding. The development of rice mature anther and pollen consists of multiple continuous stages. However, molecular mechanisms regulating mature anther development were poorly understood. In this study, we have identified 291 mature anther-preferentially expressed genes (OsSTA) in rice based on Affymetrix microarray data. Gene Ontology (GO) analysis indicated that OsSTA genes mainly participated in metabolic and cellular processes that are likely important for rice anther and pollen development. The expression patterns of OsSTA genes were validated using real-time PCR and mRNA in situ hybridizations. Cis-element identification showed that most of the OsSTA genes had the cis-elements responsive to phytohormone regulation. Co-expression analysis of OsSTA genes showed that genes annotated with pectinesterase and calcium ion binding activities were rich in the network, suggesting that OsSTA genes could be involved in pollen germination and anther dehiscence. Furthermore, OsSTA RNAi transgenic lines showed male-sterility and pollen germination defects. The results suggested that OsSTA genes function in rice male fertility, pollen germination and anther dehiscence and established molecular regulating networks that lay the foundation for further functional studies.

Inference of Low and High-Grade Glioma Gene Regulatory Networks Delineates the Role of Rnd3 in Establishing Multiple Hallmarks of Cancer

PubMed Central

Turan, Nil; Soulet, Fabienne; Mohd Zahari, Maihafizah; Ryan, Katie R.; Durant, Sarah; He, Shan; Herbert, John; Ankers, John; Heath, John K.; Bjerkvig, Rolf; Bicknell, Roy; Hotchin, Neil A.; Bikfalvi, Andreas; Falciani, Francesco

2015-01-01

Gliomas are a highly heterogeneous group of brain tumours that are refractory to treatment, highly invasive and pro-angiogenic. Glioblastoma patients have an average survival time of less than 15 months. Understanding the molecular basis of different grades of glioma, from well differentiated, low-grade tumours to high-grade tumours, is a key step in defining new therapeutic targets. Here we use a data-driven approach to learn the structure of gene regulatory networks from observational data and use the resulting models to formulate hypothesis on the molecular determinants of glioma stage. Remarkably, integration of available knowledge with functional genomics datasets representing clinical and pre-clinical studies reveals important properties within the regulatory circuits controlling low and high-grade glioma. Our analyses first show that low and high-grade gliomas are characterised by a switch in activity of two subsets of Rho GTPases. The first one is involved in maintaining normal glial cell function, while the second is linked to the establishment of multiple hallmarks of cancer. Next, the development and application of a novel data integration methodology reveals novel functions of RND3 in controlling glioma cell migration, invasion, proliferation, angiogenesis and clinical outcome. PMID:26132659

Comprehensive proteomic analysis of bovine spermatozoa of varying fertility rates and identification of biomarkers associated with fertility

PubMed Central

Peddinti, Divyaswetha; Nanduri, Bindu; Kaya, Abdullah; Feugang, Jean M; Burgess, Shane C; Memili, Erdogan

2008-01-01

Background Male infertility is a major problem for mammalian reproduction. However, molecular details including the underlying mechanisms of male fertility are still not known. A thorough understanding of these mechanisms is essential for obtaining consistently high reproductive efficiency and to ensure lower cost and time-loss by breeder. Results Using high and low fertility bull spermatozoa, here we employed differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT) and identified 125 putative biomarkers of fertility. We next used quantitative Systems Biology modeling and canonical protein interaction pathways and networks to show that high fertility spermatozoa differ from low fertility spermatozoa in four main ways. Compared to sperm from low fertility bulls, sperm from high fertility bulls have higher expression of proteins involved in: energy metabolism, cell communication, spermatogenesis, and cell motility. Our data also suggests a hypothesis that low fertility sperm DNA integrity may be compromised because cell cycle: G2/M DNA damage checkpoint regulation was most significant signaling pathway identified in low fertility spermatozoa. Conclusion This is the first comprehensive description of the bovine spermatozoa proteome. Comparative proteomic analysis of high fertility and low fertility bulls, in the context of protein interaction networks identified putative molecular markers associated with high fertility phenotype. PMID:18294385

The Crosstalk of Pathways Involved in Immune Response Maybe the Shared Molecular Basis of Rheumatoid Arthritis and Type 2 Diabetes

PubMed Central

Ge, Na; Jiang, Miao; Li, Li; Bian, Yanqin; Xu, Gang; Bian, Zhaoxiang; Zhang, Ge; Lu, Aiping

2015-01-01

Rheumatoid arthritis (RA) and Type 2 diabetes (T2D) are both systemic diseases linked with altered immune response, moderate mortality when present together. The treatment for both RA and T2D are not satisfied, partly because of the linkage between them has not yet been appreciated. A comprehensive study for the potential associations between the two disorders is needed. In this study, we used RNA sequencing to explore the differently expressed genes (DEGs) in peripheral blood mononuclear cells (PBMC) of 10 RA and 10 T2D patients comparing with 10 healthy volunteers (control). We used bioinformatics analysis and the Ingenuity Pathways Analysis (IPA) to predict the commonalities on signaling pathways and molecular networks between those two diseases. 212 DEGs in RA and 114 DEGs in T2D patients were identified compared with healthy controls, respectively. 32 DEGs were shared between the two comparisons. The top 10 shared pathways interacted in cross-talking networks, regulated by 5 shared predicted upstream regulators, leading to the activated immune response were explored, which was considered as partly of the association mechanism of this two disorders. These discoveries would be considered as new understanding on the associations between RA and T2D, and provide novel treatment or prevention strategy. PMID:26252209

Evo-devo, deep homology and FoxP2: implications for the evolution of speech and language

PubMed Central

Scharff, Constance; Petri, Jana

2011-01-01

The evolution of novel morphological features, such as feathers, involves the modification of developmental processes regulated by gene networks. The fact that genetic novelty operates within developmental constraints is the central tenet of the ‘evo-devo’ conceptual framework. It is supported by findings that certain molecular regulatory pathways act in a similar manner in the development of morphological adaptations, which are not directly related by common ancestry but evolved convergently. The Pax6 gene, important for vision in molluscs, insects and vertebrates, and Hox genes, important for tetrapod limbs and fish fins, exemplify this ‘deep homology’. Recently, ‘evo-devo’ has expanded to the molecular analysis of behavioural traits, including social behaviour, learning and memory. Here, we apply this approach to the evolution of human language. Human speech is a form of auditory-guided, learned vocal motor behaviour that also evolved in certain species of birds, bats and ocean mammals. Genes relevant for language, including the transcription factor FOXP2, have been identified. We review evidence that FoxP2 and its regulatory gene network shapes neural plasticity in cortico-basal ganglia circuits underlying the sensory-guided motor learning in animal models. The emerging picture can help us understand how complex cognitive traits can ‘descend with modification’. PMID:21690130

Evo-devo, deep homology and FoxP2: implications for the evolution of speech and language.

PubMed

Scharff, Constance; Petri, Jana

2011-07-27

The evolution of novel morphological features, such as feathers, involves the modification of developmental processes regulated by gene networks. The fact that genetic novelty operates within developmental constraints is the central tenet of the 'evo-devo' conceptual framework. It is supported by findings that certain molecular regulatory pathways act in a similar manner in the development of morphological adaptations, which are not directly related by common ancestry but evolved convergently. The Pax6 gene, important for vision in molluscs, insects and vertebrates, and Hox genes, important for tetrapod limbs and fish fins, exemplify this 'deep homology'. Recently, 'evo-devo' has expanded to the molecular analysis of behavioural traits, including social behaviour, learning and memory. Here, we apply this approach to the evolution of human language. Human speech is a form of auditory-guided, learned vocal motor behaviour that also evolved in certain species of birds, bats and ocean mammals. Genes relevant for language, including the transcription factor FOXP2, have been identified. We review evidence that FoxP2 and its regulatory gene network shapes neural plasticity in cortico-basal ganglia circuits underlying the sensory-guided motor learning in animal models. The emerging picture can help us understand how complex cognitive traits can 'descend with modification'.

Mechanisms of fibrin polymerization and clinical implications

PubMed Central

Litvinov, Rustem I.

2013-01-01

Research on all stages of fibrin polymerization, using a variety of approaches including naturally occurring and recombinant variants of fibrinogen, x-ray crystallography, electron and light microscopy, and other biophysical approaches, has revealed aspects of the molecular mechanisms involved. The ordered sequence of fibrinopeptide release is essential for the knob-hole interactions that initiate oligomer formation and the subsequent formation of 2-stranded protofibrils. Calcium ions bound both strongly and weakly to fibrin(ogen) have been localized, and some aspects of their roles are beginning to be discovered. Much less is known about the mechanisms of the lateral aggregation of protofibrils and the subsequent branching to yield a 3-dimensional network, although the αC region and B:b knob-hole binding seem to enhance lateral aggregation. Much information now exists about variations in clot structure and properties because of genetic and acquired molecular variants, environmental factors, effects of various intravascular and extravascular cells, hydrodynamic flow, and some functional consequences. The mechanical and chemical stability of clots and thrombi are affected by both the structure of the fibrin network and cross-linking by plasma transglutaminase. There are important clinical consequences to all of these new findings that are relevant for the pathogenesis of diseases, prophylaxis, diagnosis, and treatment. PMID:23305734

Molecular chaperones in Parkinson's disease--present and future.

PubMed

Ebrahimi-Fakhari, Darius; Wahlster, Lara; McLean, Pamela J

2011-01-01

Parkinson's disease, like many other neurodegenerative disorders, is characterized by the progressive accumulation of pathogenic protein species and the formation of intracellular inclusion bodies. The cascade by which the small synaptic protein α-synuclein misfolds to form distinctive protein aggregates, termed Lewy bodies and Lewy neurites, has been the subject of intensive research for more than a decade. Genetic and pathological studies in Parkinson's disease patients as well as experimental studies in disease models have clearly established altered protein metabolism as a key element in the pathogenesis of Parkinson's disease. Alterations in protein metabolism include misfolding and aggregation, post-translational modification and dysfunctional degradation of cytotoxic protein species. Protein folding and re-folding are both mediated by a highly conserved network of molecules, called molecular chaperones and co-chaperones. In addition to the regulatory role in protein folding, molecular chaperone function is intimately associated with pathways of protein degradation, such as the ubiquitin-proteasome system and the autophagy-lysosomal pathway, to effectively remove irreversibly misfolded proteins. Because of the central role of molecular chaperones in maintaining protein homeostasis, we herein review our current knowledge on the involvement of molecular chaperones and co-chaperones in Parkinson's disease. We further discuss the capacity of molecular chaperones to prevent or modulate neurodegeneration, an important concept for future neuroprotective strategies and summarize the current progress in preclinical studies in models of Parkinson's disease and other neurodegenerative disorders. Finally we include a discussion on the future potential of using molecular chaperones as a disease modifying therapy.

Reticular synthesis of porous molecular 1D nanotubes and 3D networks.

PubMed

Slater, A G; Little, M A; Pulido, A; Chong, S Y; Holden, D; Chen, L; Morgan, C; Wu, X; Cheng, G; Clowes, R; Briggs, M E; Hasell, T; Jelfs, K E; Day, G M; Cooper, A I

2017-01-01

Synthetic control over pore size and pore connectivity is the crowning achievement for porous metal-organic frameworks (MOFs). The same level of control has not been achieved for molecular crystals, which are not defined by strong, directional intermolecular coordination bonds. Hence, molecular crystallization is inherently less controllable than framework crystallization, and there are fewer examples of 'reticular synthesis', in which multiple building blocks can be assembled according to a common assembly motif. Here we apply a chiral recognition strategy to a new family of tubular covalent cages to create both 1D porous nanotubes and 3D diamondoid pillared porous networks. The diamondoid networks are analogous to MOFs prepared from tetrahedral metal nodes and linear ditopic organic linkers. The crystal structures can be rationalized by computational lattice-energy searches, which provide an in silico screening method to evaluate candidate molecular building blocks. These results are a blueprint for applying the 'node and strut' principles of reticular synthesis to molecular crystals.

Reticular synthesis of porous molecular 1D nanotubes and 3D networks

NASA Astrophysics Data System (ADS)

Slater, A. G.; Little, M. A.; Pulido, A.; Chong, S. Y.; Holden, D.; Chen, L.; Morgan, C.; Wu, X.; Cheng, G.; Clowes, R.; Briggs, M. E.; Hasell, T.; Jelfs, K. E.; Day, G. M.; Cooper, A. I.

2017-01-01

Synthetic control over pore size and pore connectivity is the crowning achievement for porous metal-organic frameworks (MOFs). The same level of control has not been achieved for molecular crystals, which are not defined by strong, directional intermolecular coordination bonds. Hence, molecular crystallization is inherently less controllable than framework crystallization, and there are fewer examples of 'reticular synthesis', in which multiple building blocks can be assembled according to a common assembly motif. Here we apply a chiral recognition strategy to a new family of tubular covalent cages to create both 1D porous nanotubes and 3D diamondoid pillared porous networks. The diamondoid networks are analogous to MOFs prepared from tetrahedral metal nodes and linear ditopic organic linkers. The crystal structures can be rationalized by computational lattice-energy searches, which provide an in silico screening method to evaluate candidate molecular building blocks. These results are a blueprint for applying the 'node and strut' principles of reticular synthesis to molecular crystals.

GenCLiP 2.0: a web server for functional clustering of genes and construction of molecular networks based on free terms.

PubMed

Wang, Jia-Hong; Zhao, Ling-Feng; Lin, Pei; Su, Xiao-Rong; Chen, Shi-Jun; Huang, Li-Qiang; Wang, Hua-Feng; Zhang, Hai; Hu, Zhen-Fu; Yao, Kai-Tai; Huang, Zhong-Xi

2014-09-01

Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms. http://ci.smu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

NASA Astrophysics Data System (ADS)

Zhang, Linfeng; Han, Jiequn; Wang, Han; Car, Roberto; E, Weinan

2018-04-01

We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

C. elegans network biology: a beginning.

PubMed Central

Piano, Fabio; Gunsalus, Kristin C; Hill, David E; Vidal, Marc

2006-01-01

The architecture and dynamics of molecular networks can provide an understanding of complex biological processes complementary to that obtained from the in-depth study of single genes and proteins. With a completely sequenced and well-annotated genome, a fully characterized cell lineage, and powerful tools available to dissect development, Caenorhabditis elegans, among metazoans, provides an optimal system to bridge cellular and organismal biology with the global properties of macromolecular networks. This chapter considers omic technologies available for C. elegans to describe molecular networks--encompassing transcriptional and phenotypic profiling as well as physical interaction mapping--and discusses how their individual and integrated applications are paving the way for a network-level understanding of C. elegans biology. PMID:18050437

Systematic Evaluation of Molecular Networks for Discovery of Disease Genes.

PubMed

Huang, Justin K; Carlin, Daniel E; Yu, Michael Ku; Zhang, Wei; Kreisberg, Jason F; Tamayo, Pablo; Ideker, Trey

2018-04-25

Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation, gene expression profiling, or genome-wide association studies. While all networks have some ability to recover disease genes, we observe a wide range of performance with STRING, ConsensusPathDB, and GIANT networks having the best performance overall. A general tendency is that performance scales with network size, suggesting that new interaction discovery currently outweighs the detrimental effects of false positives. Correcting for size, we find that the DIP network provides the highest efficiency (value per interaction). Based on these results, we create a parsimonious composite network with both high efficiency and performance. This work provides a benchmark for selection of molecular networks in human disease research. Copyright © 2018 Elsevier Inc. All rights reserved.

A simple transferable adaptive potential to study phase separation in large-scale xMgO-(1-x)SiO2 binary glasses.

PubMed

Bidault, Xavier; Chaussedent, Stéphane; Blanc, Wilfried

2015-10-21

A simple transferable adaptive model is developed and it allows for the first time to simulate by molecular dynamics the separation of large phases in the MgO-SiO2 binary system, as experimentally observed and as predicted by the phase diagram, meaning that separated phases have various compositions. This is a real improvement over fixed-charge models, which are often limited to an interpretation involving the formation of pure clusters, or involving the modified random network model. Our adaptive model, efficient to reproduce known crystalline and glassy structures, allows us to track the formation of large amorphous Mg-rich Si-poor nanoparticles in an Mg-poor Si-rich matrix from a 0.1MgO-0.9SiO2 melt.

Antimicrobial inflammasomes: unified signalling against diverse bacterial pathogens.

PubMed

Eldridge, Matthew J G; Shenoy, Avinash R

2015-02-01

Inflammasomes - molecular platforms for caspase-1 activation - have emerged as common hubs for a number of pathways that detect and respond to bacterial pathogens. Caspase-1 activation results in the secretion of bioactive IL-1β and IL-18 and pyroptosis, and thus launches a systemic immune and inflammatory response. In this review we discuss signal transduction leading to 'canonical' and 'non-canonical' activation of caspase-1 through the involvement of upstream caspases. Recent studies have identified a growing number of regulatory networks involving guanylate binding proteins, protein kinases, ubiquitylation and necroptosis related pathways that modulate inflammasome responses and immunity to bacterial infection. By being able to respond to extracellular, vacuolar and cytosolic bacteria, their cytosolic toxins or ligands for cell surface receptors, inflammasomes have emerged as important sentinels of infection. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of raphe serotonin neurons from specification to guidance.

PubMed

Kiyasova, Vera; Gaspar, Patricia

2011-11-01

The main features of the development of the serotonin (5-HT) raphe neurons have been known for many years but more recent molecular studies, using mouse genetics, have since unveiled several intriguing aspects of the specification of the raphe serotonergic system. These studies indicated that, although all 5-HT neurons in the raphe follow the same general program for their specification, there are also clear regional differences in the way that these neurons are specified and are guided towards different brain targets. Here we overview recent progress made in the understanding of the developmental programming of serotonergic neurons in the mouse raphe, emphasizing data showing how heterogeneous subsets of 5-HT neurons may be generated. Serotonergic progenitors are produced in the brainstem in different rhombomeres under the influence of a set of secreted factors, sonic hedgehog and fibroblast growth factors, which determine their position in the neural tube. Two main transcriptional gene networks are involved in the specification of 5-HT identity, with Lmx1b and Pet1 transcription factors as main players. A differential requirement for Pet1 was, however, revealed, which underlies an anatomical and functional diversity. Transcriptional programs controlling 5-HT identity could also impact axon guidance mechanisms directing 5-HT neurons to their targets. Although no direct links have yet been established, a large set of molecular determinants have already been shown to be involved in the growth, axon guidance and targeting of 5-HT raphe neurons, particularly within the forebrain. Alterations in the molecular mechanisms involved in 5-HT development are likely to have significant roles in mood disease predisposition. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Molecular dynamics simulation studies of novel β-lactamase inhibitor.

PubMed

Ul Haq, Farhan; Abro, Asma; Raza, Saad; Liedl, Klaus R; Azam, Syed Sikander

2017-06-01

New Delhi Metallo-β-Lactamase-1 (NDM-1) has drawn great attention due to its diverse antibiotic resistant activity. It can hydrolyze almost all clinically available β-lactam antibiotics. To inhibit the activity of NDM-1 a new strategy is proposed using computational methods. Molecular dynamics (MD) simulations are used to analyze the molecular interactions between selected inhibitor candidates and NDM-1 structure. The enzyme-ligand complex is subject to binding free energy calculations using MM(PB/GB)SA methods. The role of each residue of the active site contributing in ligand binding affinity is explored using energy decomposition analysis. Furthermore, a hydrogen bonding network between ligand and enzyme active site is observed and key residues are identified ensuring that the ligand stays inside the active site and maintains its movement towards the active site pocket. A production run of 150ns is carried out and results are analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) to explain the stability of enzyme ligand complex. Important active site residue e.g. PHE70, VAL73, TRP93, HIS122, GLN123, ASP124, HIS189, LYS216, CYS208, LYS211, ALA215, HIS250, and SER251 were observed to be involved in ligand attachemet inside the active site pocket, hence depicting its inhibitor potential. Hydrogen bonds involved in structural stability are analyzed through radial distribution function (RDF) and contribution of important residues involved in ligand movement is explained using a novel analytical tool, axial frequency distribution (AFD) to observe the role of important hydrogen bonding partners between ligand atoms and active site residues. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of transcriptional regulatory nodes in soybean defense networks using transient co-transactivation assays

PubMed Central

Wang, Yongli; Wang, Hui; Ma, Yujie; Du, Haiping; Yang, Qing; Yu, Deyue

2015-01-01

Plant responses to major environmental stressors, such as insect feeding, not only occur via the functions of defense genes but also involve a series of regulatory factors. Our previous transcriptome studies proposed that, in addition to two defense-related genes, GmVSPβ and GmN:IFR, a high proportion of transcription factors (TFs) participate in the incompatible soybean-common cutworm interaction networks. However, the regulatory mechanisms and effects of these TFs on those induced defense-related genes remain unknown. In the present work, we isolated and identified 12 genes encoding MYB, WRKY, NAC, bZIP, and DREB TFs from a common cutworm-induced cDNA library of a resistant soybean line. Sequence analysis of the promoters of three co-expressed genes, including GmVSPα, GmVSPβ, and GmN:IFR, revealed the enrichment of various TF-binding sites for defense and stress responses. To further identify the regulatory nodes composed of these TFs and defense gene promoters, we performed extensive transient co-transactivation assays to directly test the transcriptional activity of the 12 TFs binding at different levels to the three co-expressed gene promoters. The results showed that all 12 TFs were able to transactivate the GmVSPβ and GmN:IFR promoters. GmbZIP110 and GmMYB75 functioned as distinct regulators of GmVSPα/β and GmN:IFR expression, respectively, while GmWRKY39 acted as a common central regulator of GmVSPα/β and GmN:IFR expression. These corresponding TFs play crucial roles in coordinated plant defense regulation, which provides valuable information for understanding the molecular mechanisms involved in insect-induced transcriptional regulation in soybean. More importantly, the identified TFs and suitable promoters can be used to engineer insect-resistant plants in molecular breeding studies. PMID:26579162

The Phosphoinositide 3-Kinase p110α Isoform Regulates Leukemia Inhibitory Factor Receptor Expression via c-Myc and miR-125b to Promote Cell Proliferation in Medulloblastoma

PubMed Central

von Bueren, André O.; Ćwiek, Paulina; Rehrauer, Hubert; Djonov, Valentin; Anderle, Pascale; Arcaro, Alexandre

2015-01-01

Medulloblastoma (MB) is the most common malignant brain tumor in childhood and represents the main cause of cancer-related death in this age group. The phosphoinositide 3-kinase (PI3K) pathway has been shown to play an important role in the regulation of medulloblastoma cell survival and proliferation, but the molecular mechanisms and downstream effectors underlying PI3K signaling still remain elusive. The impact of RNA interference (RNAi)-mediated silencing of PI3K isoforms p110α and p110δ on global gene expression was investigated by DNA microarray analysis in medulloblastoma cell lines. A subset of genes with selectively altered expression upon p110α silencing in comparison to silencing of the closely related p110δ isoform was revealed. Among these genes, the leukemia inhibitory factor receptor α (LIFR α) was validated as a novel p110α target in medulloblastoma. A network involving c-Myc and miR-125b was shown to be involved in the control of LIFRα expression downstream of p110α. Targeting the LIFRα by RNAi, or by using neutralizing reagents impaired medulloblastoma cell proliferation in vitro and induced a tumor volume reduction in vivo. An analysis of primary tumors revealed that LIFRα and p110α expression were elevated in the sonic hedgehog (SHH) subgroup of medulloblastoma, indicating its clinical relevance. Together, these data reveal a novel molecular signaling network, in which PI3K isoform p110α controls the expression of LIFRα via c-Myc and miR-125b to promote MB cell proliferation. PMID:25915540

CH(+) Destruction by Reaction with H: Computing Quantum Rates To Model Different Molecular Regions in the Interstellar Medium.

PubMed

Bovino, S; Grassi, T; Gianturco, F A

2015-12-17

A detailed analysis of an ionic reaction that plays a crucial role in the carbon chemistry of the interstellar medium (ISM) is carried out by computing ab initio reactive cross sections with a quantum method and by further obtaining the corresponding CH(+) destruction rates over a range of temperatures that shows good overall agreement with existing experiments. The differences found between all existing calculations and the very-low-T experiments are discussed and explored via a simple numerical model that links these cross section reductions to collinear approaches where nonadiabatic crossing is expected to dominate. The new rates are further linked to a complex chemical network that models the evolution of the CH(+) abundance in the photodissociation region (PDR) and molecular cloud (MC) environments of the ISM. The abundances of CH(+) are given by numerical solutions of a large set of coupled, first-order kinetics equations that employs our new chemical package krome. The analysis that we carry out reveals that the important region for CH(+) destruction is that above 100 K, hence showing that, at least for this reaction, the differences with the existing laboratory low-T experiments are of essentially no importance within the astrochemical environments discussed here because, at those temperatures, other chemical processes involving the title molecule are taking over. A detailed analysis of the chemical network involving CH(+) also shows that a slight decrease in the initial oxygen abundance might lead to higher CH(+) abundances because the main chemical carbon ion destruction channel is reduced in efficiency. This might provide an alternative chemical route to understand the reason why general astrochemical models fail when the observed CH(+) abundances are matched with the outcomes of their calculations.

Building a foundation for structure-based cellulosome design for cellulosic ethanol: Insight into cohesin-dockerin complexation from computer simulation

PubMed Central

Xu, Jiancong; Crowley, Michael F; Smith, Jeremy C

2009-01-01

The organization and assembly of the cellulosome, an extracellular multienzyme complex produced by anaerobic bacteria, is mediated by the high-affinity interaction of cohesin domains from scaffolding proteins with dockerins of cellulosomal enzymes. We have performed molecular dynamics simulations and free energy calculations on both the wild type (WT) and D39N mutant of the C. thermocellum Type I cohesin-dockerin complex in aqueous solution. The D39N mutation has been experimentally demonstrated to disrupt cohesin-dockerin binding. The present MD simulations indicate that the substitution triggers significant protein flexibility and causes a major change of the hydrogen-bonding network in the recognition strips—the conserved loop regions previously proposed to be involved in binding—through electrostatic and salt-bridge interactions between β-strands 3 and 5 of the cohesin and α-helix 3 of the dockerin. The mutation-induced subtle disturbance in the local hydrogen-bond network is accompanied by conformational rearrangements of the protein side chains and bound water molecules. Additional free energy perturbation calculations of the D39N mutation provide differences in the cohesin-dockerin binding energy, thus offering a direct, quantitative comparison with experiments. The underlying molecular mechanism of cohesin-dockerin complexation is further investigated through the free energy profile, that is, potential of mean force (PMF) calculations of WT cohesin-dockerin complex. The PMF shows a high-free energy barrier against the dissociation and reveals a stepwise pattern involving both the central β-sheet interface and its adjacent solvent-exposed loop/turn regions clustered at both ends of the β-barrel structure. PMID:19384997

Individualised cancer therapeutics: dream or reality? Therapeutics construction.

PubMed

Shen, Yuqiao; Senzer, Neil; Nemunaitis, John

2005-11-01

The analysis of DNA microarray and proteomic data, and the subsequent integration into functional expression sets, provides a circuit map of the hierarchical cellular networks responsible for sustaining the viability and environmental competitiveness of cancer cells, that is, their robust systematics. These technologies can be used to 'snapshot' the unique patterns of molecular derangements and modified interactions in cancer, and allow for strategic selection of therapeutics that best match the individual profile of the tumour. This review highlights technology that can be used to selectively disrupt critical molecular targets and describes possible vehicles to deliver the synthesised molecular therapeutics to the relevant cellular compartments of the malignant cells. RNA interference (RNAi) involves a group of evolutionarily conserved gene silencing mechanisms in which small sequences of double-stranded RNA or intrinsic antisense RNA trigger mRNA cleavage or translational repression, respectively. Although RNAi molecules can be synthesised to 'silence' virtually any gene, even if upregulated, a mechanism for selective delivery of RNAi effectors to sites of malignant disease remains challenging. The authors will discuss gene-modified conditionally replicating viruses as candidate vehicles for the delivery of RNAi.